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Università degli Studi di Trieste
PhD program in MOLECULAR MEDICINE
PhD Thesis
siRNAs targeted against cell cycle related genes as tools to down regulate cell-proliferation
in hepatocellular carcinoma and vascular smooth muscle cells
Rossella Farra
Anno Accademico 2005-2007 (XX ciclo)
SUPERVISOR:
Prof. Gabriele Grassi, Università degli Studi di Trieste, Dipartimento di Scienze Cliniche,
Morfologiche e Tecnologiche
Prof. Gianni Biolo, Università degli Studi di Trieste, Dipartimento di Scienze Cliniche,
Morfologiche e Tecnologiche
TUTOR:
Dott. Barbara Dapas, Università degli Studi di Trieste, Dipartimento di Scienze Cliniche,
Morfologiche e Tecnologiche
EXTERNAL SUPERVISOR:
Prof. Olaf Heidenreich, Newcastle University; Northern Institute for Cancer Research
THESIS COMMETTEE:
Prof. Francesco Tedesco (Presidente effettivo), Università degli Studi di Trieste, Dipartimento di
Fisiologia e Patologia
Prof. Stefano Gustincich (Componente effettivo), Università degli Studi di Trieste, Scuola
Internazionale Superiore di Studi Avanzati di Trieste
Prof. Massimo Levrero (Componente effettivo), Università degli Studi di Roma “La Sapienza”,
Dipartimento Medicina Interna
Prof. Giannino Del Sal (Coordinatore del Corso di Dottorato), Università degli Studi di Trieste,
Dipartimento di Biochimica, Biofisica e Chimica delle Macromolecole
Prof. Renato Gennaro (Direttore del Dipartimento di Riferimento), Università degli Studi di
Trieste, Dipartimento di Biochimica, Biofisica e Chimica delle Macromolecole
TABLE OF CONTENTS
ABSTRACT pag. 1
LIST OF PAPERS pag. 2
LIST OF ABBREVIATIONS pag. 4
INTRODUCTION
1. HEPATOCELLULAR CARCINOMA pag. 5
1.1 Sequential morphological changes in the liver leading to HCC pag. 5
1.2 Genomic alterations during the preneoplastic phase pag. 6
1.3 Genomic changes in HCC pag. 7
1.3.1 Promoters of cell proliferation pag. 8
1.3.2 Tumor suppressor genes pag. 9
1.3.3 DNA mismatch repair genes pag. 10
1.3.4 Telomerase activation pag. 10
1.3.5 Growth factors pag. 10
1.3.6 Other factors pag. 11
2. IN-STENT RESTENOSIS pag. 12
2.1 Arterial anatomy pag. 12
2.2 Atherosclerosis pag. 13
2.3 Artery reocclusion pag. 14
2.3.1 Percutaneous transluminal angioplasty (PTA) pag. 14
2.3.2 Bare metal stents pag. 16
2.3.3 Drug eluting stents pag. 17
2.4 ISR patho-physiology pag. 19
2.4.1 Intimal thickening pag. 20
3. CELL CYCLE AND PROLIFERATION pag. 23
3.1 Cell cycle regulators pag. 24
3.1.1 Cyclin E family pag. 24
3.1.2 The transcription factor E2F1 pag. 26
3.1.3 The Serum Response Factor pag. 2
4. RNA INTERFERENCE pag. 29
4.1 RNA interference mechanism pag. 30
4.2 SiRNA delivery in vitro pag. 31
4.2.1 Lipid-mediated transfection pag. 32
AIMS OF THE STUDY pag. 34
MATERIALS AND METHODS
1. Cell cultures pag. 35
2. Selection of siRNAs targeted against SRF, Cyclin E1, Cyclin E2 and E2F1 pag. 35
3. Uptake studies pag. 36
3.1 Experimental set up pag. 37
4. Cell count and viability assay pag. 38
5. Evaluation of cell colony number and area pag. 39
6. Quantitative real time RT-PCR pag. 39
7. Protein extraction pag. 42
8. Immunoblotting pag. 43
9. Cytotoxicity assay pag. 44
10. Apoptosis evaluation pag. 44
11. Proliferation assays pag. 45
12. Statistical analysis pag. 46
RESULTS
Selection of siRNAs and uptake studies
1. Selection of siRNAs targeted against SRF, Cyclin E1,Cyclin E2 and E2F1 pag. 47
2. Uptake studies pag. 48
3. INF Response pag. 52
Depletion of SRF in HCC cell lines
4. siSRF797 effects on SRF mRNA and protein levels pag. 54
5. Effects of SRF depletion on cell morphology and cell-counting pag. 56
6. Effects of SRF depletion on cell cycle phase distribution pag. 61
7. Effects of SRF depletion on cell death pag. 67
8. Effects of SRF depletion on other cell cycle regulators pag. 70
Depletion of CyE1, CyE2 and E2F1 in HCC cell lines
9. siRNAs effects on CyE1, CyE2 and E2F1 mRNA and protein levels pag. 76
10. Effects of CyE1, CyE2 and E2F1 depletion on cell morphology
and cell-counting pag. 79
11. Effects of CyE1, CyE2 and E2F1 depletion on cell cycle phase distribution pag. 85
12. Effects of CyE1, CyE2 and E2F1 depletion on cell death pag. 88
13. Effects of CyE1, CyE2 and E2F1 depletion on other cell cycle regulators pag. 91
Depletion of SRF in VSMC
14. siSRF797 effects on SRF mRNA and protein levels pag.102
15. Effects of SRF depletion on cell morphology and cell-counting pag.104
16. Effects of SRF depletion on cell cycle phase distribution pag.106
17. Effects of SRF depletion on cell death pag.110
18. Effects of SRF depletion on other cell cycle regulators pag.111
DISCUSSION
1. Hepatocellular carcinoma data pag.114
1.1 Effects of SRF depletion on HCC cell lines pag.114
1.2 Effects of CyE1, CyE2 and E2F1 depletion on HCC cell lines pag.119
2. In-stent Restenosis data pag.124
2.1 Effects of SRF depletion on VSMC pag.124
CONCLUSION pag.128
AKNOWLEDGMENTS pag.129
REFERENCES pag.131
1
ABSTRACT
Exuberant and non-controlled cellular proliferation underlines the ethio-pathogenesis of many
human pathological conditions, including tumour and non-tumour diseases. Thus, the possibility
to control this complex process can be extremely useful in terms of prevention/control of disease
progression, especially in the light of the limited efficacy of current therapeutic approaches. In
this project we draw our attention on the down regulation of cell proliferation in the context of
two human diseases, namely hepatocellular carcinoma (HCC), as an example of tumour
pathology and in stent- restenosis, example of non-tumour pathology. To explore the possibility
to down regulate cell growth, we targeted the transcription factor E2F1 and the serum response
factor (SRF) and cyclins E1/E2, all genes implicated in cell cycle progression. As tools to down
regulate the expression of the target genes, we used small interfering RNAs, short double
stranded RNA molecules able to induce the specific degradation of a homologue mRNA.
The presented results indicate that SRF depletion impairs cell proliferation, in primary VSMC
and in the most differentiated HCC cell line HepG2, but not in the less differentiated HuH7 and
JHH6. Additionally, the depletion of CyE1, CyE2 and E2F1 is effective in preventing all HCC
cell expansion, regardless of the differentiation status. However, whereas in HepG2 the major
mechanism is the induction of apoptosis, in HuH7 and JHH6 it is the down modulation of cell
growth.
In conclusion, our project based on the inhibition of cell growth in tumour and non tumour cells
by means of siRNAs, can contribute to better understand the complex mechanisms regulating
cell proliferation in HCC and in vascular smooth muscle cells. Moreover, these data support the
rationale to continue the studies for the development of future novel anti HCC and in-stent
restenosis approaches based on the use of siRNAs.
2
LIST OF PAPERS INCLUDED IN THE THESIS
1) D. Werth, G. Grassi, B. Dapas, N. Konjer, R. Farra, C. Giansante, R. Kandolf, G. Guarnieri,
A. Nordheim and O. Heidenreich Suppression of Serum Response Factor Inhibits Proliferation
of Primary Human Vascular Smooth Muscle Cells and Induces Senescence. Submitted.
2) F. Agostini, B. Dapas, R. Farra, M. Grassi, G. Racchi, K. Klingel, R. Kandolf, O.
Heindenreich, A. Mercatanti, G. Rainaldi, N. Altamura, G. Guarnieri, and G. Grassi. Potential
applications of small interfering RNA in the cardiovascular field. Drug of the future, 31(6):
513-525, 2006.
LIST OF PAPERS NOT DIRECTLY RELEVANT TO THE THESIS
1) N. Fiotti, F. Tubaro, G. Grassi, M. Moretti, B. Dapas, R. Farra, N. Altamura, S. Buratti, C.
Giansante. Alcohol reduces mmp-2 in humans and isolated smooth muscle cells. Alcohol, 2008
in press.
2) G. Grassi G, R. Farra, E. Noro, D. Voinovich, R. Lapasin, B. Dapas, O. Alpar, C. Zennaro,
M. Carraro, C. Giansante, G. Guarnieri, A. Pascotto, B. Rehimers, M. Grassi. Charactherization
of nucleid acid molecule/liposome complexes and rheological effects on pluronic/alginate
matrices. Journal of Drug Delivery Science and Technology, 17,5: 325-331, 2007.
3) M. Zanetti, A. Stocca, B. Dapas, R. Farra, A. Bosutti, R. Barazzoni, C. Giansante, F.
Tedesco, L. Cattin, G. Guarnieri and G. Grassi. Inhibitory Effects Of Fenofibrate On Apoptosis
And Cell Proliferation In Human Endothelial Cells In High Glucose. Journal of Molecular
Medicine, 86 (2) 185-95, 2007.
4) G. Grassi, B. Scaggiante, R. Farra, B. Dapas , F. Agostini, D. Baiz, N. Rosso, and C.
Tiribelli . The expression levels of the translational factors eEF1A 1/2 correlate with cell growth
but not apoptosis in hepatocellular carcinoma cell lines with different differentiation grade.
Biochemie, 89, 1522-1544, 2007.
3
5) J. Platz, M. Grassi, A. Kuhn, R. Kandolf, G. Racchi, R. Farra, B. Dapas, A. Pascotto, C.
Giansante N. Fiotti, G. Guarnierei and and G. Grassi. Effects of various promoter derived
sequences on the cleavage kinetic of an hammerhead ribozyme directed against cyclin E1
mRNA. Drug Metabolism letter 1, 218-225, 2007.
6) G. Grassi, N. Coceani, R. Farra, B. Dapas, G. Racchi, N. Fiotti, A. Pascotto, B. Rehimers, G.
Guarnieri, M. Grassi. Propaedeutic study for the delivery of nucleic acid based molecules from
PLGA microparticles and Stearic acid nanoparticles. International Journal of Nanomedicine,
1 (4): 523-533, 2006.
7) G. Grassi; A. Crevatin; R. Farra; G. Guarnieri, A. Pancotto, B. Rehimers; R. Lapasin and M.
Grassi. Rheological properties of aqueous pluronic-alginate systems containing liposomes.
Journal of Colloid and Interface Science, 301 (1) 282-90, 2006
8) G. Grassi, H. Köhn, B. Dapas, R. Farra, J. Platz, S. Engel, S. Cjsareck, R. Kandolf C.
Teutsch, R. Klima, G. Triolo, and A. Kuhn. Comparison between recombinant baculo and
adenoviral-vectors as transfer system in cardiovascular cells. Archives of Virology, 2006
151:255-271.
9) G. Grassi, R. Farra, P. Caliceti, M. Grassi. Temperature-Sensitive Hydrogels: Potential
Therapeutic Applications. American Journal of Drug Delivery. 2005; 3 (4):239-251
4
LIST OF ABBREVIATIONS
HCC: Hepatocellularcarcinoma
VSMC: Vascular Smooth Muscle Cells
siRNAs: small interfering RNA
SRF: Serum Response Factor
CyE1: Cyclin E1
CyE2: Cyclin E2
E2F1: transcription factor E2F1
GL2: Luciferase gene
CyA: Cyclin A
CyD1: Cyclin D1
GAPDH: Glyceraldehyde 3-phosphate dehydrogenase
pRb: phosphorylated form of the Retinoblastoma protein
P-pRb: hyperphosphorylated form of the Retinoblastoma protein
INF: Interferon
PDGF: Platelet-Derived Growth Factor
NG: Normal glucose
HG: High glucose
Introduction
5
INTRODUCTION
1. Hepatocellular carcinoma.
Hepatocellular carcinoma (HCC), the major type of primary liver cancer, is one of the
commonest cancers worldwide and a leading cause of death in many countries (Murray and
Lopez, 1997; Bosch et al., 1999), with an estimated 564,000 new cases and almost as many
deaths in 2000 (Thorgeirsson and Grisham, 2002). There is no clinically tested useful therapy for
the advanced stage of the disease and any effective treatment has not been assessed in large
controlled randomized trials for this kind of hyper-vascular and chemotherapy-resistant tumour.
Chronic hepatitis B and C and associated liver cirrhosis represent major risk factors for HCC
development, being implicated in more than 70% of HCC cases worldwide. Additional
etiological factors, which often represent co-factors of an underlying HBV- or HCV-related
chronic liver disease, include toxins and drugs (e.g., alcohol, aflatoxins, microcystin, anabolic
steroids), metabolic liver diseases (e.g., hereditary hemochromatosis, α-1-antitrypsin deficiency),
steatosis, non-alcoholic fatty liver diseases and diabetes.
Hepatocarcinogenesis is a multistep process that can last for decades and involves the
progressive accumulation of different genetic alterations ultimately leading to malignant
transformation. Regardless of the etiological agent, malignant transformation of hepatocytes is
believed to occur through an increased liver cell turnover, induced by chronic liver injury and
regeneration, in a context of inflammation and oxidative DNA damage.
The detailed analysis of HCC development in experimental animals and the comparison of the
results with HCC in humans has identified a variety of genomic and molecular alterations in
fully developed HCC and, to a lesser extent, in morphologically defined pre-neoplastic precursor
lesions. At least five pathways that regulate either cell proliferation or cell death (i.e., the
phospho-retinoblastoma protein (pRb), cyclin E, p53, transforming growth factor-β (TGF-β) and
β-catenin pathways) can be affected in HCCs. These changes drastically alter the matrix and
microenvironment of the liver (Grisham J.W., 2001; Buendia, 2000).
1.1 Sequential morphological changes in the liver leading to HCC.
Hepatocarcinogenesis in humans unfolds during a process that may take more than 30 years after
chronic infection with HBV or HCV is first diagnosed (Buendia, 2000; Tong et al., 1995)
(Fig.1). Cirrhosis and HCC occur routinely in a fraction of patients who develop chronic
Introduction
6
infection with HBV or HCV. HCC arises with increasing frequency in livers that are the site of
chronic hepatitis and cirrhosis, particularly from dysplastic hepatocytes.
The tissue lesions that commonly precede HCC ( chronic hepatitis and cirrhosis containing foci
of phenotypically altered and dysplastic hepatocytes ) provide a framework for identifying the
temporal order of genomic alterations development during hepatocarcinogenesis (Thorgeirsson
and Grisham, 2002).
Fig.1 Chronologic sequence of cellular lesions culminating
in the development of hepatocellular carcinoma in human.
1.2 Genomic alterations during the preneoplastic phase.
Althought HCC development is a multistep process and its appearance in children suggest also
the contribution of a genetic predisposition (Chang et al., 1989) , it is difficult to identify most of
the predisposing genes for hepatocarcinogenesis. During most of the long preneoplastic stage
leading to HCC, alterations in gene expression are almost entirely quantitative, occurring by
epigenetic mechanisms in the absence of detected changes in the structures of genes and
chromosomes. Elevated expression of transforming growth factor-α (TGF-α) (Grisham J.W.,
2001; Kawakita et al., 1992) and insulin-like growth factor-2 (IGF-2) (Grisham J.W., 2001) is
responsible for accelerated hepatocyte proliferation. Upregulation of these two genes results
Introduction
7
from the combined actions of cytokines produced by chronic inflammatory cells that infiltrate
the carcinogen-damaged liver (Grisham J.W., 2001), viral transactivation (Grisham J.W., 2001;
Brechot, 1998; Diao et al., 2001; Smela et al., 2001) and the regenerative response of the liver to
cell loss (Grisham J.W., 2001).
It should be emphasized that in addition to TGF-α and IGF-2 upregulation, tumor and non-
tumor liver contain multiple other changes. Moreover, there is variability in the profile of
genomic alterations among different patients even within single studies (Feitelson et al., 2002).
Variability in the number and types of genetic changes has also been observed geographically
and depends upon the etiology of the tumor (viral, chemical or both) (Wong et al., 2000).
1.3 Genomic changes in HCC.
The early epigenetic changes and some of the early structural alterations of genes or loci are not
sufficient to induce malignant phenotypes in hepatocytes, as HCCs ultimately develop in only a
fraction of the livers with chronic hepatitis or cirrhosis. Epigenetic changes in gene expression
that occur in HCCs appear to act indirectly by creating conditions that increase the chance of
generating hepatocyte populations containing critical combinations of structurally and
functionally aberrant genes.
Central to the concept of molecular carcinogenesis are mutations of oncogenes and tumor
suppressor genes as well as genetic instability of cellular DNA, including mismatch repair
efficiency and impaired chromosomal segregation. Overall, there are a variety of molecular and
immunological mechanisms by which endogenous, environmental and viral factors may play an
interactive role in HCC development (Bergsland, 2001; Blum, 2002; blum HE and Moradpour
D, 2002; Hassan et al., 2002; Chen and Chen, 2002).
New technologies should allow to identify genes critical in early stages of tumorigenesis (Chen
and Chen, 2002)
Introduction
8
Fig.2 Hcc development.
1.3.1 Promoters of cell proliferation.
Genetic analyses have revealed that one of the most commonly altered gene in HCC is the cell-
cycle regulator cyclin E (Li et al., 2003). Cyclin E is believed to control G1-S phase progression
by associating with cyclin-dependent kinase Cdk2 and activating its kinase activity shortly
before entry of cells into the S phase (see also paragraphs 3.1.1) (Sauer and Lehner, 1995; Reed,
1997). Its expression near the G1-S phase transition is thought to be critical for the initiation of
DNA replication and duplication of the centrosomes. The timely appearance of cyclin E is
crucial as excessive activity of the cyclin E-Cdk2 complex drives cells to duplicate the DNA
prematurely, resulting in genome instability (Spruck et al., 1999) and carcinogenesis (Bortner
and Rosenberg, 1997). Notably, overexpression of cyclin E was found in 70% of HCC patients
and was correlated with poor prognosis (Jung et al., 2001).
Other studies reveal that over-expression of the transcription factor E2F1 promotes
hepatocarcinogenesis and that accelerates liver cancer development (Conner et al., 2000). E2F1
is involved in regulating key cellular activities including growth and death (DeGregori et al.,
1997; Nevins et al., 1997). When over-expressed, E2F1 is capable of driving quiescent cells into
S phase in the absence of other mitogenic stimuli (Johnson et al., 1993). In addition to providing
Introduction
9
a continuous proliferative signal, E2F1 is also a potent inducers of apoptosis and operate at least
through one common pathway involving p53 (Kowalik et al., 1998). Thus, oncogenic activity of
E2F1 is associated with a persistent increase in hepatocyte proliferation, above all in the pre-
neoplastic phases of liver growth (Conner et al., 2003).
1.3.2 Tumor suppressor genes.
HCCs have recurrent allelic alterations (Grisham J.W., 2001; Buendia, 2000; Kondo et al., 2000;
Kawai et al., 2000; Chen et al., 2000a; Okabe et al., 2000) and regional losses and gains
(Grisham J.W., 2001; Buendia, 2000; Chen et al., 2000b; Guan et al., 2000; Marchio et al., 2000;
Tornillo et al., 2000; Wong et al., 2000; Zondervan et al., 2000; Balsara et al., 2001; Rao et al.,
2001; Wilkens et al., 2001) on several chromosomes. In general, these genetic alterations appear
to occur at later stages of HCC development.
p53 gene is probably the most common molecular target involved in human carcinogenesis
(Levine et al., 1991). A G to T mutation at the third base position of codon 249 of the p53 gene,
leading to a substitution of arginine to serine, was found in a significant number of HCC patients
(Blum, 2003). Moreover, frequent allelic deletions at chromosome 13q have been associated in
human cancer with the inactivation of the tumor suppressor Rb, which is located on 13q14
(Friend et al., 1986) and which represents a pivotal cell-cycle control gene (see also paragraph
3.1.1). Notably, the disruption of the pRb pathway renders cells insensitive to antiproliferative
signals that induce growth arrest at the G1 phase. In HCC, pRb chromosomal allelic losses have
been found in 25-48% of cases (Murakami et al., 1991; Fujimoto et al., 1994; Zhang et al., 1994;
Kuroki et al., 1995), and pRb expression down regulation was found in 30-50% of HCC tumors
(Zhang et al., 1994; Hsia et al., 1994).
While mutations of the pRb gene itself have not been documented so far in HCC, there are many
different ways to inactivate pRb, including the inactivation of p16INK4A. The protein product of
p16INK4A tumor suppressor gene binds to cyclin-dependent kinase 4 and 6 and inhibits their
interaction with cyclin D1 (Serrano et al., 1993). As the progression through the G1 phase of cell
cycle is also mediated by cyclin D1 phosphorylation of pRb, defects of p16INK4A can result in an
increased proliferation reate for the cell. The genetic changes of the p16 INK4A gene include
homozygous deletion and intragenic mutation (Gonzalgo and Jones, 1997). Moreover, recently,
epigenetic changes in p16 INK4A gene have been recognized as importans events leading to the
occurrence of HCC. In particular, p16INK4A promoter methylation has been associated with
reduced expression (Grisham J.W., 2001; Buendia, 2000; Kondo et al., 2000; Kawai et al., 2000;
Chen et al., 2000a; Okabe et al., 2000).
Introduction
10
Finally, a novel pathway leading to pRb inactivation has recently been discovered by the finding
of a new oncogene termed gankirin (Higashitsuji et al., 2000), an ankirin-repeat protein
homologous to the p28 subunit of the 26S proteasome. Gankyrin, over expressed in all HCCs,
binds to pRb and promotes its degradation by the ubiquitin-proteasome pathway (Buendia,
2000).
1.3.3 DNA mismatch repair genes.
In addition to oncogenes and tumor suppressor genes, DNA mismatch repair genes have recently
been identified as a class of susceptibility genes involved in the pathogenesis of human tumors.
Defective DNA mismatch repair can lead to the accumulation of mutations and microsatellite
instability in the cellular genome and thus increase the chance of malignant transformation
(Blum, 2003). The role of DNA mismatch repair defects in HCC development is currently
unknown.
1.3.4 Telomerase activation.
Telomeres correspond to the ends of eukaryotic chromosomes and are specialized structures
containing unique (TTAGGG)n repeats (Blackburn, 1991). Telomeres protect the chromosomes
from DNA degradation, end to end fusions, rearrangements, and chromosome loss (de Lange,
1994). Because cellular DNA polymerase cannot replicate the 5’ end of the linear DNA
molecule, the number of telomere repeats decreases during aging of normal somatic cells. The
progressive shortening of telomeres may control the proliferative capacity of normal cells
(Harley et al., 1990) and serves as control mechanism against unregulated cellular proliferation.
Telomerase, a ribonucleicacid-protein complex, adds hexameric repeats of 5’-TTAGGG-3’ to
the end of telomeres to compensate for the progressive loss (Greider and Blackburn, 1985).
Althought normal somatic cells do not express telomerase, its expression has been found in most
tumor cells. The activation of telomerase activity may play a significant role in
hepatocarcinogenesis (Liu et al., 2003).
1.3.5 Growth factors.
As in most other forms of cancer, the downregulated expression of growth factors and of
components of their signalling pathways may play an important role in hepatic oncogenesis.
Indeed, overexpression of certain growth factors was found in HCC, including insulin-like
growth factor II (IGF-II), transforming growth factor (TGF), and hepatovyte growth factor
(HGF) (Blum, 2003). The role of growth factors in promoting HCC is still incomplete and
Introduction
11
additional factors are likely to emerge as potentially important candidates involved in
hepatocarcinogenesis. Among these, it is worthy of mentioning Serum response factor (SRF).
SRF is a transcription factor, which binds to a serum response element (SRE) associated with a
variety of genes including immediate early genes such as c-fos, fosB, junB, egr-1 and -2,
neuronal genes such as nurr1 and nur77 and muscle genes such as actins and myosins. By
regulating the expression of these genes, SRF controls cell growth and differentiation. Recently,
it has been proposed that SRF is implicated in HCC cell growth (Shao et al., 2005).
1.3.6 Other factors.
Other host factors beyond those addressed above may be genetic polymorphisms of enzymes
metabolising environmental xenobiotics, such as alcohol and the hydrocarbons in tobacco smoke
(Hassan et al., 2002).
Fig.3 Model of stepwise hepatocarcinogenesis (LOH:loss of heterozygosity).
Introduction
12
2. In-stent Restenosis.
In-stent restenosis (ISR) is a relevant clinical problem which often follows therapeutic
interventions aimed at the revascularization of coronary arteries partially/totally obstructed by
atherosclerotic plaques.
2.1 Arterial anatomy.
The normal artery wall consists of three layers which, from the inner to the outmost part of the
artery are represented by: the intima, the media, and the adventitia (Fig. 4).
Fig.4 Artery anatomy
The intima is constituted by a continuous layer of endothelial cells (ECs) connected each other
by a series of junctional complexes (Miyoshi and Takai, 2005) and adherent to a layer of loose
connective tissue named “basal lamina”. Endothelial cells form a barrier that controls the entry
of substances from the blood into the arterial wall. Under physiological conditions, they control
the passage of circulating molecules by active transport (endocytosis and exocytosis) and
elaborate the connective tissue components which form their own substrate. Additionally, ECs
prevent clotting partly by elaboration of prostaglandin (such as PGI2) that inhibit platelet
function. In case of EC layer damage, platelets adhere to the inner vessel surface and form a clot.
Damaged ECs favour clot formation by synthesising a variety of molecules among which factor
VIII represents a key player. In addition to produce molecules which can affect clot formation,
ECs can secrete substances that influence the contraction-relaxation of the subjacent vascular
smooth muscle cells (VSMCs).
The intima is delimited from the outer layer called “media” by the internal elastic lamina, an
anatomical structure particular prominent in large and medium calibre arteries and absent in
capillaries. The media consists of only one cell type, the VSMCs organised in either a single
Adventitia
Media
Intima
Lumen
Introduction
13
layer (as in small muscular arteries) or in multiple lamellae (as in elastic arteries). The cells of
the inner part of the media receive the nutrients from the vessel lumen while the cells of the outer
part are nourished by small vessel termed “vasa-vasorum” which originate in the adventitia, the
outer layer of arteries.
In the media, VSMC are surrounded by small amounts of collagen and elastic fibers which they
produce together with other extra-cellular molecules such as proteoglycans. VSMCs are highly
specialized cells whose principal function consists of the contraction and regulation of blood
vessel tone-diameter, blood pressure, and blood flow distribution (reviewed in (Owens et al.,
2004)). VSMCs within adult blood vessels proliferate at an extremely low rate, exhibit very low
synthetic activity, and express a unique repertoire of contractile proteins, ion channels, and
signalling molecules required for the cell’s contractile function (Owens, 1995). Thus, under
physiological conditions they display a so called “contractile phenotype”, indicating that their
activities are mainly devoted to regulated vessel tone (Adachi et al., 1998). However, unlike
skeletal and cardiac muscle that are terminally differentiated, VSMCs retain remarkable
plasticity and can undergo rather profound and reversible changes in phenotype in response to
changes in local environment (Owens, 1995). In this regard, a classical example is represented
by vascular injury, where the VSMCs dramatically increases their rate of proliferation,
migration, and the capacity to produce different extra-cellular matrix molecules (synthetic
phenotype), in order to repair the vessel damage. The possibility to switch from the contractile to
the synthetic or proliferating phenotype is defined as “phenotypic modulation”. This ability,
however, predisposes the cell to abnormal environmental signals that can lead to adverse
phenotypic switching and acquisition of characteristics that can contribute to the development
and/or progression of vascular disease.
The outermost layer of the artery, delimited from the media by a non continuous sheet of elastic
tissue (external elastic lamina), is named adventitia. This external coat consists of a loose
mixture of collagen, elastic fibres, VSMCs, fibroblasts and contains vasa vasorum and nerves.
2.2 Atherosclerosis.
Arteriosclerosis represents a generic term indicating the thickening and hardening of the arterial
wall, which is responsible for the majority of deaths in most westernised societies (Bierman,
1995). One type of arteriosclerosis, defined atherosclerosis, is a disorder which involves larger
arteries and which underlies most coronary artery disease, aortic aneurism, arterial diseases of
the lower extremities and cerebrovascular diseases.
Introduction
14
Atherosclerosis can be considered a form of chronic inflammation resulting from the interaction
between modified lipoproteins, monocyte-derived macrophages, T cells and the normal cellular
elements of the arterial wall, i.e. ECs and VSMCs (Ross, 1999). This inflammatory process can
ultimately lead to the development of complex lesions, also defined plaques, that protrude into
the arterial lumen.
Atherosclerotic lesions begin as “fatty streaks” underlying the endothelium of large arteries
(Navab et al., 1996). The transition from the relatively simple fatty streak to the more complex
lesion is characterized by the immigration of VSMCs from the medial layer of the artery wall
through the internal elastic lamina to reach the intimal, or subendothelial, space. Intimal VSMCs
take up modified lipoproteins, contributing to foam cell formation. Additionally, they show
increased growth rate and are subjected to a number of other variations collectively referred to as
“phenotypic modulation” (Owens et al., 2004).
Although advanced atherosclerotic lesions can lead to ischemic symptoms as a result of
progressive narrowing of the vessel lumen, acute cardiovascular events can also result from
plaque rupture (Lee and Libby, 1997). Plaque rupture exposes plaque lipids and tissue factor to
blood components, initiating the coagulation cascade, platelet adherence thus leading to
thrombosis and to a sudden vascular occlusion with the related ischemic symptoms (Fiotti et al.,
2006).
2.3 Artery reocclusion.
In order to restore blood flow in artery totally/partially occluded by atherosclerotic plaques,
different approaches have been developed. The first to be established was the coronary artery
bypass grafting (CABG) followed by percutaneous transluminal coronary angioplasty (PTA)
(late 1970s). Subsequently, PTA has been combined with the implantation of either intra-
vascular bare metal stents (late 1980s) or drug eluting stents (beginning 2000s).
2.3.1 Percutaneous transluminal angioplasty (PTA).
In order to revascularize stenotic coronary arteries, since 1979 (Gruntzig et al., 1979) it has been
introduced the so called percutaneous transluminal coronary angioplasty (PTCA). This is a non-
surgical method that has been shown to be safe and effective in comparisons to CABG (Pocock
et al., 1995), a surgical approach used to circumvent artery stenosis.
PTCA (Fig 5) involves:
• advancing a balloon catheter to an area of coronary narrowing
• inflating the balloon
Introduction
15
• retrieving the catheter following balloon deflation.
Fig.5 PTCA procedure.
Angioplasty can be applied to broad groups of patients, reducing the severity of coronary
stenosis and diminishing or eliminating ischemia. More than 500,000 percutaneous coronary
intervention procedures are performed yearly in the USA, and about 1 million procedures
worldwide (American Heart Association, 2001). However, PTCA has been shown to induce
(Fig. 6) the development of symptomatic re-occlusion (restenosis) caused by early elastic recoil,
intimal thickening, late constricting remodelling of the vessel (Ruygrok et al., 2003) and
formation of mural thrombus in about 30-50% of treated patients (Califf, 1995).
Introduction
16
Fig.6 Possible complications of PTCA (from (Bult, 2000)).
2.3.2 Bare metal stents.
To try to overcome the PTCA related problems, the expansion of the balloon during angioplasty
has been associated with the deployment of a stent. This is an expandable metal tubular mesh
usually made of stainless steel or titanium/nickel (nitinol) alloys (Fig. 7), firstly developed in
1987 (Sigwart et al., 1987). The deployment of the stents has significantly reduced the rates of
early elastic recoil and late constructive remodelling of the vessel reducing restenosis rate down
to 20-30% (Serruys et al., 1994; Fischman et al., 1994). The partial success of the stents is due to
the induction of the intimal thickening (in-stent restenosis, ISR), a phenomenon particularly
evident in small calibre vessels (Ruygrok et al., 2003; Moreno et al., 2004) and charaterized by
an exuberant proliferation of VSMCs. Clinical ISR produces recurrent angina or evidence of
myocardial ischemia. By angiography, a vessel is considered affected by ISR when its lumen at
the dilated segment is occluded for more than 50%.
media
intima
Atheroscleroticplaque
PTCA
Elastic recoil
Intimal thickening
Constrictive remodelling
Incorporation of mural thrombus
media
intima
Atheroscleroticplaque
PTCA
Elastic recoil
Intimal thickening
Constrictive remodelling
Incorporation of mural thrombus
Introduction
17
Fig.7 Endo-arterial implantation of a bare metal stent (B).
2.3.3 Drug eluting stents.
With the aim to overcome the excessive VSMC proliferation observed after bare metal stent
implantation, devices able to locally deliver anti-proliferative drugs (drug-eluting stent (DES))
have been developd (Fig.8). Currently, more than 85% of all coronary interventions in the
United States are performed with drug-eluting stents (Kandzari et al., 2005). Two pivotal trials,
Sirolimus-Eluting Balloon Expandable Stent in the Treatment of Patients With De Novo Native
Coronary Artery Lesions (SIRIUS) (Moses et al., 2003) and Treatment of De Novo Coronary
Disease Using a Single Paclitaxel Eluting Stent (TAXUS)-IV (Stone et al., 2004), demonstrated
striking reductions in angiographic restenosis and revascularization rates with sirolimus- and
paclitaxel-eluting stents, respectively, compared to bare metal stents (9% ISR rate in sirolimus-
stent compared to 21% in bare metal stents; 8% ISR rate in paclitaxel-stent compared to 26% in
bare metal stents). Sirolimus (Rapamycin®) is an immunosuppressor of T-lymphocytes also
capable of reducing the inflammatory response and the proliferation of VSMCs. Moreover,
sirolimus promotes apoptosis in VSMC (Giordano et al., 2006). Paclitaxel (Taxol®) is a
microtuble stabilizing agent which reduces the concentration of free tubulin required for new
tubulin formation. This in turn down regulates biological processes such as proliferation and
Introduction
18
migration of VSMC (reviewed in (Liuzzo et al., 2005)). In addition, Paclitaxel induces apoptosis
and cell death.
Fig.8 Drug eluting stent
The current U.S. Food and Drug Administration approved indication for drug-eluting stents is for
low risk patients with discrete, de novo lesions in native vessels with reference vessel diameters
of 2.5 mm to 3.5 mm (Rockville, 2007). Nevertheless, the unrestricted implementation of drug-
eluting stents seems to be widely accepted in contemporary interventional clinical practice. This
widespread adoption has largely been driven by non-randomized registry experience and has
been fuelled by enthusiastic dissemination and acceptance of data and aggressive marketing.
However, some concerns are now emerging (reviewed in (Tung et al., 2006; Serruys and
Daemen, 2007)). First of all, the impressive results on ISR in the pivotal drug-eluting stent trials
may have been overestimated. Careful examination reveals inordinately high ISR rates in the
bare metal stent control group, nearly 50% higher than that observed in contemporary
randomized trials and in real world clinical experience. The inferior performance of bare metal
stents may be explained by the use, in the above cited trials, of thick-strut stents which are
known to have higher ISR compared to thinner-strut stents (Pache et al., 2003). Thus, the
impressive ISR reduction rate observed using DES may be exaggerated because of the use of
sub-optimal control bare metal stents. Not only over-estimation of the beneficial effects of DES
may have occurred, also under-estimation of adverse events, such as thrombosis, may have
occurred. Stent thrombosis usually occurs before re-endothelialization of the treated artery
(healing) has been completed. Stent thrombosis rarely occurs beyond 2 to 4 weeks for bare metal
stents. In contrast, in a large observational study of DES use in real-world settings, the incidence
of stent thrombosis was 1.3% (29 of 2229 cases) at 9 months (Iakovou et al., 2005). This implies
v e s s e l
s t e n t
D e l i v e r y o f t h e t h e r a p e u t i c m o le c u le t o t h e v e s s e l w a l l
v e s s e l
s t e n t
D e l i v e r y o f t h e t h e r a p e u t i c m o le c u le t o t h e v e s s e l w a l l
Introduction
19
a prolonged antiplatelet therapy with aspirin and clopidogrel for at least 6 months or, in some
cases, for longer or perhaps indefinitely.
Finally, it should be also pointed out that the re-vascularization benefit with DES is attenuated in
high-risk patients (diabetes; the acute coronary syndromes, including ST-segment elevation
myocardial infarction; smaller-diameter lesions and longer lesions; several stents or overlapping
stents), compared to low risk patients displaying, for example, 26% ISR rate in coronary
bifurcation lesions (Colombo et al., 2004).
2.4 ISR patho-physiology
According to Mehran et al. (Mehran et al., 1999) four classes of ISR patients can be
distinguished:
• Class I Focal in-stent restenosis group: lesions are ≤10 mm in length and are positioned
at the unscaffolded segment, the body of the stent, the proximal or distal margin (but not
both), or a combination of these sites (multifocal in-stent restenosis).
• Class II “Diffuse intrastent” in-stent restenosis: lesions are >10 mm in length and are
confined to the stent(s), without extending outside the margins of the stent(s).
• Class III “Diffuse proliferative” in-stent restenosis: lesions are >10 mm in length and
extend beyond the margin(s) of the stent(s).
• Class IV In-stent restenosis with “total occlusion”.
Many predictors of ISR have been identified so far. Several studies (reviewed in (Scott, 2006))
have demonstrated an association between ISR and stent length, multiple stents, smaller final
minimal lumen diameter, lack of use of intravascular ultrasound, the female gender, the
presence of diabetes, and polymorphism in the angiotensin converting enzyme gene. Beside
these factors, it is now accepted that stent implantation following PTCA represents a traumatic
event which is the primary cause of ISR, both in the presence of bare metal stent and DES
(Karthikeyan and Bhargava, 2004).
The first traumatic event takes place during the balloon-driven expansion of the stent (Fig. 4).
The trauma of this procedure is often exacerbated by the inability of the balloon to expand the
stent fully to its nominal size. This requires a second dilation of the balloon called post-dilation,
which leads to the over-expansion of the blood vessel wall (Brodie et al., 2003; Vernhet et al.,
2002). Second, inadequate stent deployment is likely to alter the blood flow conditions
increasing the risk of reduced laminary flow and increased pressure gradients. These flow
disturbances and pressure gradients have been advocated as possible factors predisposing to the
Introduction
20
formation of a neointimal thickening (Muller-Hulsbeck et al., 2001). Third, an over-expansion of
the vessel wall is induced by the presence of the device. Indeed, some types of stents seems to
enlarge progressively after implantation (Yu et al., 2002). Additionally, endo-vascular stenting
produces a significant decrease in arterial wall compliance and extendibility (Vernhet et al.,
2003). In physiologic conditions the arterial wall constantly undergoes physical deformation due
to the pulsatile change in aortic pressure and consequent coronary perfusion pressure. These
mechanical stimuli cause changes in the coronary vessel size, generating cyclic mechanical strain
and cyclic flexion. Conversely, in patients with implanted stents, the vessel wall compliance to
these stimuli is decreased as the local artery extendibility is impaired and regional stresses are
augmented by the stent. These non-physiologic cyclical strains have been shown to induce the
proliferation of the VSMCs, heavily contributing to thickening of the intima (Sudhir et al.,
2001).
Above all, the damage caused by the expansion of the stent to the vessel wall is considered the
most important event leading to ISR. The destruction of the tissue integrity, paralleled by the
presence of a foreign body (i.e., the stent), is likely to impair the normal wound healing, which
instead develops into hyperplasia (Virmani and Farb, 1999), mainly charaterized by an exuberant
proliferation of VSMCs which leads to the thickening of the intima. Although reduced in the
frequency, these problem also plagues DES, especially in high risk patients.
2.4.1 Intimal thickening.
The neointima thickening, directly related to the degree of penetration of the stent within the
vessel wall media (Farb et al., 2002), follows a temporal evolution (Fig.9). Within ten days from
stent implantation the constant presence of platelet-rich thrombi surrounding the stent struts is
evidenced. This fibrin clot is almost completely resorbed after 12 days. A gradual formation of
VSMC-rich tissue, is observed between 12 and 30 days after implantation. These cells are
typically associated to a proteoglycan-rich extracellular matrix (ECM). Inflammatory cells are
always present. Among them, neutrophils are prevalent during the early phases of implantation,
but their number tend to decrease between 12 and 30 days of implantation. Conversely,
macrophages are constantly present. Notably, the score of the inflammatory cells contacting the
strut is higher in those cases where the damage of the media is more pronounced. From 3–18-
months after implantation (Farb et al., 2004; Skowasch et al., 2004), the restenotic tissue is
characterized by a proteoglycan-rich (versican and hyaluronan) ECM. This ECM is constantly
infiltrated by α-actin-positive VSMCs, thus pointing towards the relevance of VSMC
hypercellularity which is considered to be relevant in the pathogenesis of ISR. The
Introduction
21
hypercellularity mainly results from the previously occurred VSMC switch from the contractile
to the synthetic phenotype. Hypercellularity also depends on the mobilization of progenitor cells
from the bone marrow to the injured vessel area (Shoji et al., 2004). Additionally, macrophages,
which can differentiate into myofibroblasts, also contribute to the hypercellularity (Bayes-Genis
et al., 2002). Notably, VSMC proliferation, although reduced in extent, persists for months after
stent implantation.
Fig.9 Events leading to instent restenosis (Modified from:(Edelman and Rogers, 1998))
The hypercellular ECM mostly contains collagen Type III during the first 9 months, and is
progressively substituted by collagen Type I at later stages. After 18 months of implantation,
decorin-positive staining and collagen Type I prevail. VSMCs and inflammatory cells density are
significantly reduced after 18 months (Skowasch et al., 2004; Sakai et al., 2004). Such an ECM
is typical of a tissue not fully healed (Farb et al., 2004). Notably it has also been observed that
the neointimal tissue can undergo a “contraction” comparable to that occurring in a wound
healing process. The contraction seems to be induced by the colonization of the ECM by
myofibroblasts which interact with the ECM components (Turley, 2001). Finally, it has to be
pointed out that in ISR the endothelium in the stented region is dysfunctional. This has been
proved observing the altered endothelium reactivity to acetylcholine (Caramori et al., 1999).
Morever, in the presence of DES, re-endothelization is considerably delayed due to the anti-
Days after the procedure
0 5 10 15 20 25
Inflammation
Monocyteadherence Monocyte
infiltration
0 5 10 15 20 25
VSMC and Monocytesproliferation
Remodelling
0 5 10 15 20 25
Thrombus deposition
PTCA/stent
Days after the procedure
Days after the procedure
Days after the procedure
0 5 10 15 20 25
Inflammation
Monocyteadherence Monocyte
infiltration
0 5 10 15 20 25
VSMC and Monocytesproliferation
Remodelling
0 5 10 15 20 25
Thrombus deposition
PTCA/stent
0 5 10 15 20 25
Thrombus deposition
PTCA/stent
Days after the procedure
Days after the procedure
Introduction
22
proliferative/apoptotic effects exerted by the released drugs (Tung et al., 2006). This
phenomenon is probably responsible for the increased thrombosisi rate observed for DES
compared to bare metal stents (Tung et al., 2006).
Taken together, these data indicate that the process of ISR can be divided in two main phases:
• The wound healing process, where the activation of the clotting system is followed by an
inflammatory response, and by the proliferation and migration of VSMCs;
• The neiointima organization, where VSMCs reduce their proliferation rate to enter a
synthetic phenotype and secrete a hyaluronan-rich ECM.
Neointimal thickening can be observed within any discreet location of the stented segment or can
appear in a diffuse pattern. Although certain systemic characteristics (e.g., the presence of
diabetes) or anatomical variables (small vessel diameter, long lesion length) increase the
probability of ISR, the presence or absence of these factors does not completely explain the
specific location of neointimal formation. In this regard, it has been shown that alterations in
shear stress could cause important compensatory changes in both luminal and vessel diameter
(Glagov et al., 1987).
Introduction
23
3. Cell cycle and proliferation.
The relevance of VSMC and HCC cell proliferation in the pathogenesis of ISR and HCC,
requires a description of the major events ruling this process. Moreover, these informations are
useful to properly understand the strategy here adopted to explore possible novel therapeutic
approaches.
Somatic cells proliferate to support tissue and organism growth and to replace damaged cells.
Proliferation is also a fundamental response that underlies cellular mechanisms involved in
immunity, inflammation, hematopoiesis, neoplasia, and other biological responses. Cell growth,
replication and division in eukaryotic cells occur according to a highly controlled series of events
called the cell cycle.
The cell cycle can be subdivided into two major stages: interphase ( a phase between mitotic
events) and mitosis (Fig.12)
Fig.12 Cell cycle phases
There are three distinct, successive stages within interphase, called G1, S and G2 phases. During
G1, cells “monitor” their environment and upon receipt of specific signals, induce the synthesis
of protein required in the next phases. If proper conditions occur, cells “commit” to DNA
synthesis (S phase) and replicate their chromosomal DNA. A G2 phase follows in which cells
continue to prepare themselves for mitosis. In mitosis (M), there are four successive phases
called prophase, metaphase, anaphase and telophase that are accompanied by cytoplasmic
division (cytokinesis) giving rise to two daughter cells. For the most part, upon completion of the
process, each daughter cell contains the same genetic material as the original parent cell.
In addition to these specific stages, the G0 phase has been described for cells that exit from the
cell cycle and enter a quiescent, non-dividing state. In response to external stimuli, some
quiescent cells may undergo reactivation and express early response genes. The G0-G1 transition
Introduction
24
is marked by measurable increases in newly-synthesized RNAs and proteins and by the
expression of the Ki67 antigen (Gerdes et al., 1983).
3.1 Cell cycle regulators.
Many regulators of the different cell cycle phases have been described so far (Donjerkovic and
Scott, 2000). Among them, cyclin E, the transcription factor E2F1 and the transcription factor
SRF represent relevant mediators.
3.1.1 Cyclin E family.
Cyclin E1 (formerly called cyclin E) and the recently described cyclin E2 belong to the family of
E-type cyclins that operate during the G1/S phase progression in mammalian cells. The two E-
cyclins share a catalytic partner, cyclin-dependent kinase 2 (CDK2), which they activate at
similar times during cell cycle progression. Despite these similarities, it is unknown whether the
two proteins perform distinct functions, or, alternatively, they control S-phase entry of different
cell types in a tissue-specific fashion.
Cyclin E1 is a nuclear protein (Hwang and Clurman, 2005; Moroy and Geisen, 2004) first
identified through its ability to complement the proliferative defects in cyclin-deficient yeast
cells (Koff et al., 1991). The gene for the human cyclin E protein encodes several polypeptides
with molecular weights ranging from 39 to 52 kDa. The “regular” cyclin E1 protein contains a
domain spanning from amino acid position 129–215, which is called “cyclin box”. Its sequence
is to a certain degree conserved among cyclins (Fig. 13).
Fig.13 Cyclin E1 protein structure
A conserved stretch of hydrophobic amino acids within the cyclin box is responsible for the
recognition of the RXL-motif substrates or inhibitors (Adams et al., 1996). Further towards the
C-terminal end, cyclin E1 protein bears another “substrate recognition motif” which binds the
retinoblastoma protein, pRb (Kelly et al., 1998). Finally, a PEST box sequence also known as
“destruction box” present at the very C-terminal end of cyclin E1 at a position 370–385, is at
least partially responsible for targeting the protein to degradation (Lew et al., 1991). In addition
to the regular form of cyclin E1, different splice variants have been described (Ohtsubo et al.,
Rb binding domain PEST box Cyclin box
Introduction
25
1995) (Keyomarsi et al., 1995). It is unclear to date, whether the presence of a particular splice
variant of cyclin E1 correlates with a specific cell cycle phenotype or a particular cellular state.
Expression of cyclin E1 varies during the cell cycle, peaking at the G1–S-phase boundary.
Expression is regulated by proteins of the E2F-transcription factor family (Duronio and
O'Farrell, 1995). More in detail, the transcriptional activation of the cyclin E1 gene depends on
the activity of D-type cyclins which, coniugated with the respective cyclin dependent kinase –
cdk2/4-, phosphorylate the retinoblastoma protein (pRb) family leading to the release of E2F/DP
heterodimer from pRB complexes thus allowing E2F transactivation function. Since cyclin E1,
coniugated with its cyclin dependent kinase- cdk2-, also phosphorylate pRb family protein, the
concentration of free E2F progressively rises and leads to a further amplification of cyclin E
transcription (Geng et al., 1996) (Fig. 14). This constitutes a classical feedback mechanism,
conferring cyclin E1 the ability to stimulate its own transcription.
Fig.14 Cyclin E/D regulation of the pRB/E2F1 complex.
Repression of the cyclin E1 gene during G2-M and the early G1 phases of the cell cycle is
mediated through the assembly of a multiprotein complex containing hypophosphorylated pRb,
histone deacetylase (HDAC), and SWI/SNF which binds the E2F transcription factors bound to
the cyclin E1 promoter, thus silencing cyclin E1 transcription. Another important factor in
regulating cyclin E1 levels is represented by its degradation at the protein level which occurs via
two distinct pathways involving the ubiquitin-proteasome system (Hwang and Clurman, 2005)
and is regulated, at least in part, by autophosphorylation on Thr-380.
Cyclin E
Cyclin E gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE
DPE2F/DPinactive
E2F1pRb
PpRb
pre-E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
Cyclin E1
Cyclin E1 gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE1
DPE2F/DPinactive
E2F1pRb
PpRb
-initiationcomplex
E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
E2F1/DPactive
E2F1/DPactive
DPDP
E2F1
Cyclin E
Cyclin E gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE
DPE2F/DPinactive
E2F1pRb
PpRb
pre-E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
Cyclin E1
Cyclin E1 gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE1
DPE2F/DPinactive
E2F1pRb
PpRb
-initiationcomplex
E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
E2F1/DPactive
E2F1/DPactive
E2F1/DPactive
E2F1/DPactive
DPDPDPDP
E2F1E2F1
Introduction
26
A second member of the cyclin E family, emerging as a novel potential cell cycle regulator, is
called cyclin E2. This protein shares at the protein level 47% overall similarity to cyclin E1 and
contains a cyclin box motif that is characteristic of all cyclins (Lauper et al., 1998). The human
cyclin E2 gene encodes a 404-amino-acid protein that is most closely related to cyclin E (Payton
and Coats, 2002). Cyclin E2 mRNA levels peaks at the G1/S transition. As cyclin E1, cyclin E2
controls the initiation of DNA synthesis by activating CDK2. Cyclin E2 associates with CDK2 in
a functional, catalytically active kinase complex, which phosphorilates pRb leading to the release
of E2F. Abnormally high levels of cyclin E expression have frequently been observed in human
cancers; unlike cyclin E1, which is expressed in great majority of proliferating normal and
neoplastically transformed cells, cyclin E2 levels are low in non-transformed cells and increase
significantly in neoplasm-derived cells (Gudas et al., 1999).
In addition to the E2F1-mediated regulation of cyclin E1 expression, recently, the liver receptor
homolog 1 (LRH-1, NR5A2) has been shown to be able to regulate cyclin E1 expression. Indeed
in cyclin E1 promoter, one perfect consensus LRH-1-RE was identified (Botrugno et al., 2004).
LRH-1 is a nuclear orphan receptor that binds as a monomer to the DNA sequence 5’-
YCAAGGYCR-3’, the recognition motif for the fushi tarazu factor 1 (Ftz-F1) subfamily of
nuclear receptors. It is predominantly expressed in tissues of endodermal origin including liver,
exocrine pancreas, and intestinal (Fayard et al., 2004). The ligand binding domain of this
receptor has been shown to adopt an active conformation in the absence of a bound ligand,
providing an explanation for its constitutive transcriptional activity (Sablin et al., 2003). It has
been shown recently that LRH-1 induces cell proliferation through the concomitant induction of
cyclin D1 and E1, an effect that is potentiated by its interaction with β-catenin. Whereas β-
catenin caoactivates LRH-1 on the cyclin E1 promoter, LRH-1 acts as a potent tissue-restricted
coactivator of β-catenin on the cyclin D1 promoter (Wang et al., 2005). This observation
highlights on an additional function of this orphan nuclear receptor, which controls cell
proliferation via crosstalk with the β-catenin signaling pathway.
3.1.2 The transcription factor E2F1.
E2F1 belongs to the E2Fs family (reviewed in (Bracken et al., 2004; DeGregori and Johnson,
2006) which all contain a DNA-binding domain (DB) (Fig. 15).
Fig.15 E2F1 protein structure.
Cyclin A binding domain
DNA binding domain
Dimerization domain
Transcriptional activation
Rb binding domain
Introduction
27
Except E2F7 and 8, they also contain a dimerization domain (DIM) to form heterodimer with DP
proteins. Sequences for transcriptional activation (TA) and pRB family protein binding (PB) are
present in E2F1-5 only. Moreover, E2F1-3 share a cyclin-A-binding domain (cA), absent in the
other members. DPs protein are distantly related to the E2F family, sharing homology in the DB
and DIM domains.
The E2F transcription factors can be divided into four subgroups based on their main function.
E2Fs 1–3a, the ‘activating’ E2Fs, are required for the transactivation of target genes involved in
the G1/S transition and, hence, for correct progression through the cell cycle. E2Fs 3b, 4 and 5
are considered to possess predominantly repressive activity, because they are mainly nuclear in
G0/G1 cells where they are bound to members of the retinoblastoma protein (pRB) family
(Muller et al., 1997). E2Fs 6, 7 and 8 are the founding members of the last two subgroups and
are also considered to be transcriptional repressors (Morkel et al., 1997). Six of the E2Fs protein,
including E2F1, require, for proper activity, to form heterodimers with the DP proteins (Dp1 2/3
and 4), also considered to be part of E2Fs family (Bandara et al., 1993) (Fig.15).
The transcriptional activity of E2F1 through E2F5 is regulated through their association with
pRB or the related pocket proteins, p107 and p130. Pocket protein binding blocks the
transcriptional activity of E2F-DP heterodimers by masking the transcriptional activation
domains located in the carboxy terminus of E2F1-5. This association prevents the E2F-DP
heterodimer from recruiting the basal transcription factor TFIID, as well as transcriptional co-
activators, such as p300/CBP, GCN5, TRAPP, Tip60 and ACTR/AIB1 (Louie et al., 2004).
The expression pattern for E2F1-3 members is cell cycle dependent and mainly dependent of
E2F1-3 itself as, for example, E2F1-3 contain E2F binding sites on their promoter (Bracken et
al., 2004). Upon growth factor stimulation, E2F1-3 and DP1 mRNA levels progressively
increase with a pick at the G1/S boundary, approximately reaching a 4 folds increase, compared
to the basal expression (reviewed in (Slansky and Farnham, 1996). With the progression of the S
phase and till the next G1 phase, their mRNA levels drops considerably. The same patter is
followed by their protein levels which are mainly regulated, as describe for cyclin E, by
ubiquitin-directed degradation (reviewed in Dyson (Dyson, 1998)). In contrast to E2F1-3, E2F4
and 5 are constitutively expressed (DeGregori and Johnson, 2006).
3.1.3 The Serum Response Factor.
Serum Rsponse Factor (SRF) is a phylogenetically conserved protein of 67Kda that belongs to
MADS box family of transcription factors (Norman et al., 1988). SRF protein contains 508
amino acids ; it contains three major domains: a Serum Response Element (SRE) DNA binding
domain, a transactivation domain and several phosphorylation sites.
Introduction
28
Fig.16 SRF protein structure.
SRF is a widely expressed transcription factor essential for murine embryogenesis (Arsenian et
al., 1998). SRF not only controls the expression of immediate early genes (IEGs), such as c-fos
or egr1, which are involved in proliferation of many cell types, but it also regulates selectively
the expression of Ssmooth muscle cells marker genes, such as smooth muscle α-actin, calponin-
1, or transgelin (SM22α) (Dalton and Treisman, 1992; Hipskind et al., 1991; Manabe and
Owens, 2001). Thereby, both the type of protein interaction partner and the kind of signal
transduction determine SRF activity, including its cell-type- or target gene-specificity.
In contrast to the well-established function of SRF in cellular development, a possible role of
SRF in cellular proliferation has not yet directly been addressed. Suggestive evidence exists,
however, implicating SRF in cell proliferation. For instance, sphingosine 1-phosphate mediated
VSMC proliferation has been shown to correlate with Erk-mediated phosphorylation of the SRF
cofactor Elk-1 (Lockman et al., 2004). Also, ectopic overexpression of SRF in the A7R5 cell line
established from rat thoracic aorta SMCs was associated with a twofold increased proliferation
(Chai et al., 2004). Moreover, it seems possible that SRF plays an important role also in the HCC
cell growth (Shao et al., 2005).
SRF is a stable protein with an half life of about 12hours, that is not actively synthetized in
serum-starved cells, but only upon serum stimulation, with kinetics that are delayed relative to
Fos induction (Misra et al., 1991). Mature SRF protein results from a series of successive
posttranslational modifications that retard its migration on SDS-polyacrylamide gels compared
to the newly synthetized form. Newly synthetized SRF migrates as a 63- to 65-Kda species,
which upon modifications is converted to a 67-Kda mature form (Misra et al., 1991). Recent
studies have shown that the newly synthetized SRF is converted to mature SRF by
phosphorilation and glycosylation events (Schroter et al., 1990).
SRE-DNA binding domain
Transcription activation domain
Phosphorilation sites
Introduction
29
4. RNA interference.
RNA interference (RNAi), firstly discovered in Nematodes (Fire et al., 1998) derives from an
evolutionarily conserved mechanism, involved in cellular defense against viral invasion,
transposon invasion and post-transcriptional regulation (Zamore, 2001; Tuschl, 2001; Sharp,
2001; McManus and Sharp, 2002; Hannon, 2002; Hutvagner and Zamore, 2002).
As a novel biological pathway, RNAi has quickly distinguished itself as a valuable reverse
genetic tool. The functional intermediates in the RNAi pathway, small interfering RNAs
(siRNAs), may be synthesized by a variety of means and also introduced intracellularly for
research purposes to induce changes in gene expression. The potency and specificity of siRNA-
mediated gene silecing exploits a naturally occurring pathway, thus distinguishing it from other
nucleic acid-based silencing technologies such as antisense oligonucleotides (Scanlon et al.,
1995) and ribozymes (Grassi et al., 2004) (Fig.10).
Fig.10 Silencing pathways. (A: Protein activity may be silenced by an inhibitor that binds the protein directly; B: An
antisense oligonucletides may bind complementary target mRNA and thereby block translation; C: A ribozymes
may promote degradation of target MRNA molecules; D:siRNAs may incorporate into the RISC and catalyze
cleavage of complementary mRNAs.
A. B. C./D.
protein
A. B. C./D.
protein
Introduction
30
4.1 RNA interference mechanism.
The original phenotypic observations of RNAi were made over a decade ago by researchers
working in plant and fungal genetics (Jorgensen, 1990). In the late 1990’s, major strides in
understanding the mechanics underlying RNAi were made, most notably by Andrew Fire, Craig
Mello and their colleagues. Working with C. Elegans, the founders of this emerging field in
RNA biology observed that injection of double-stranded RNA (dsRNA) induced sequence-
specific reduction of the target mRNA. Moreover, the authors documented that only a few
molecules were required to reduce the population of the target mRNA, thus suggesting an
extremely potent mechanism of action (Fire, 1999).
RNAi pathways are guided by small RNAs that include small interfering RNA (siRNA) and
microRNAs (miRNAs). The siRNA pathway begins with the cleavage of long double-stranded
RNA (dsRNA) by the Dicer enzyme complex into siRNA. These siRNAs are incorporated into
Argonaute 2 (AGO2) and the RNAi-induced silencing complex (RISC).
The sense strand of the duplex siRNA is then cleaved by AGO2 so that the antisense strand can
direct the cleavage of the target RNA by RISC.
The microRNA pathway begins with endogenously encoded primary microRNA transcripts (pri-
miRNAs) that are transcribed by RNA polymerase II (Pol II) and are processed by the Drosha
enzyme complex to yield precursor miRNAs (pre-miRNAs). These precursors are then exported
to the cytoplasm by exportin 5 and subsequently bound to the Dicer enzyme complex, which
processes the pre-miRNA for loading onto the AGO2–RISC complex. When the RNA duplex
loaded onto RISC has imperfect sequence complementarity, the passenger (sense) strand is
unwound leaving a mature miRNA bound to active RISC. The mature miRNA recognizes target
sites (typically in the 3'-UTR) in the mRNA, leading to direct translational inhibition (Fig.11).
Introduction
31
Fig.11 siRNA and microRNA pathways
4.2 SiRNA delivery in vitro.
Due to their ability to specifically induce the destruction of a given targe RNA, siRNAs have
been used to down modulate the expression of deleterious genes in cellular and animal models.
However, due to their chemical nature, siRNAs cannot be delivered to the target cells as naked
molecules. Two main categories of siRNAs delivery systems exist: viral and non viral. Viral
constructs have the advantage of being able to guarantee a long lasting expression of the siRNA
of interest. However, they can induce serious deleterious effects (Chen et al., 2003). Non-viral
approaches are considered to have far less draw backs, althought multiple administrations are
required for a long lasting presence of the siRNA within the cells (Luo and Saltzman, 2000). To
Introduction
32
overcome this limitation, a number of innovative approaches are intensively pursued (Agostini et
al., 2006).
Among the non-viral approaches, those most commonly used include lipid-mediated
transfection, electroporation, calcium phosphate-mediated delivery and microinjection.
Successful introduction of siRNA into cells using any of these methods depends on a number of
factors including delivery reagent chemical composition and charge, siRNA amounts and cell
membrane characteristics. For this reason, delivery methods demand comprehensive
optimization to achieve effective silencing while minimizing toxicity.
4.2.1 Lipid-mediated transfection.
Lipid-mediated transfection is currently the most popular method for introducing siRNA into cell
cultures (Billy et al., 2001; Caplen et al., 2000; Elbashir et al., 2001; Elbashir et al., 2002;
Brummelkamp et al., 2002; Weil et al., 2002; Hutvagner et al., 2001). For lipid-mediated
delivery to be successful, multiple dynamic categories must be taken into consideration,
including lipid concentrations, total siRNA concentrations and cell type charachteristics (i.e.,
adherent or non-adherent, differentiated or undifferentiated, primary cell or transformed cell
line). Transfection protocols are often unique for each cell type. In most cases, cells should be in
an exponential growth phase and actively dividing at the time of transfection. The growth rate
will determine optimal cell densities for plating and transfection. Cell densities that are too high
should be avoided as overgrown cell populations limit access to siRNA:lipid complexes and
have a greater sensitivity to the toxic effects associated with transfection. Similarly, cell densities
that are too low may also lead to toxicity due to excessive exposure and uptake of siRNA:lipid
complexes. Moreover, the composition and concentration of lipid plays a significant role in lipid-
mediated transfection. Different cell types may exhibit greater or lesser levels of viability and
transfection efficiencies with different transfection reagents. Lastly, the presence or absence of
serum should be rigidly controlled during transfection procedures. Some reagents are
incompatible with the presence of serum and require serum-free conditions to prevent potential
binding to serum proteins and to ensure efficient transfer of siRNA:lipid complexes. Finally,
total siRNA amount, the siRNA:lipid ratio and the duration of the transfection are important
parameters to be considered when optimizing transfection procedures. Optimizing the interplay
between the important transfection factors is critical for each cell line.
In contrast to in vitro studies, siRNAs for in vivo use must also have additional attributes that
permit appropriate biodistribution and that result in the desired pharmacokinetic properties
(absorption, distribution, metabolism, excretion) to achieve silencing. Rapid infusion or
Introduction
33
hydrodynamic injection of siRNA achieves the greatest overall delivery efficiency to a limited
set of vascularized tissues, with the primary recipient tissue being the liver.
Recently, macromoleculeshave been proposed to ferry the siRNAs through the bloodstream into
target tissues. These include conjugation of a cholesterol moiety to one of the strands of the
siRNA duplex (Soutschek et al., 2004) (Wolfrum et al., 2007). It has been demonstrated that
cholesterol-conjugated siRNAs can silence gene expression in vivo. Efficient uptake of these
siRNA conjugates depends on interactions with lipoprotein particles, lipoprotein receptors and
transmembrane proteins.But not only cholesterol is able to bind siRNAs to lipoprotein particles.
There are other possible lipophilic conjugates, such as long.chain fatty acids and bile acids, that
are also effective in binding to lipoproteins like LDL or HDL and which lead to siRNA uptake
into cells. The role of LDL and HDL binding of lipophilic siRNA conjugates is very important,
because the cellular uptake is mediated by their corresponding uptake receptors. HDL directs
siRNA delivery into liver, gut, kidney and steroidogenic organs, whereas low-density lipoprotein
(LDL) targets siRNA primarily to the liver (Wolfrum et al., 2007).
Aims of the study
34
AIMS OF THE STUDY
The aim of this thesis is to provide the rational for the development of novel therapeutic
approaches for the treatment of Hepatocellular carcinoma (HCC) and In-stent Restenosis (ISR).
HCC is the third leading cause of cancer death worldwide, with an estimated 564,000 new cases
and almost as many deaths in 2000. Despite current therapies, local recurrences are the rule and
life expectancy is short. ISR still represents a major non completely solved problem which often
follows the revascularization of coronary arteries partially/totally obstructed by atherosclerotic
plaques. To restore blood flow, plaques are first mechanically destroyed by percutaneous
transluminal angioplasty (PTA) and subsequently a stent is placed at the site of intervention.
Althought stent can prevent early artery elastic recoil and late remodeling, it induces a
particularly pronounced intimal hyperplasia characterized by exuberant proliferation of vascular
smooth muscle cells (VSMC). The use of stents releasing anti-proliferative drugs substantially
contributed to reduce ISR rate in arteries bearing single primary lesions by down regulating
VSMC growth.. However, the limited efficacy of conventional therapies for complex coronary
lesions suggests the development of alternative approaches.
Here we plan to inhibit HCC derived cells and VSMC growth by targeting the transcription
factor SRF. SRF has been implicated in the control of the expression of genes involved in the
proliferation of many primary cell types, but direct evidence of its involvment in VSMC and
HCC derived cells are lacking. Furthermore, SRF has been recently shown to be implicated in
the proliferation of HCC cells in vivo. As an additional strategy to target HCC proliferation we
plan to knock down two pivotal cell cycle promoting genes, cyclin E1 and the transcription
factor E2F1. The choice of these genes as targets is particularly attractive because of the
existence of a feed-forward loop between them which amplifies cell proliferation promoting
signals. Moreover, they both have been implicated in the development of HCC. Finally, as it is
becoming evident the role of the second member of the cyclin E family, i.e. cyclin E2, in the
E2F1-cyclin E1 pathway, also cyclin E2 was considered as target in our research.
As tools to inhibit target gene expressions, we plan to use small interfering RNAs (siRNAs)
whose potential application in many different human disease has been recently reported.
Meterials and Methods
35
MATERIALS AND METHODS
1. Cell cultures.
In the case of HCC, three different cell lines were evaluated: HepG2, HuH7 and JHH6. These
three cell lines have been chosen as they reflect different phenotypes: HepG2, HuH7 and JHH6
were assigned to high, medium and low hepatocytic differentiation grade on the base of the
capacity to synthesize albumin, a known marker of hepatic differentiation (Rothschild et al.,
1972). HepG2 exhibit a relatively normal hepatocyte phenotype, including many hepatic
inducible enzymes and an aromatic hydrocarbon receptor (Darlington et al., 1987; Ellsworth et
al., 1986). HuH7 and JHH6 cell lines derives from a differentiated and undifferentiated
hepatoma respectively (Fujise et al., 1990). Despite the almost undetectable albumin production,
JHH6 were able to synthesize ferritin, thus showing a residual hepatic phenotype (Grassi et al.,
2007).
HepG2 and HUH7 cell lines were cultured in DMEM High Glucose medium (Celbio); JHH6 cell
line was cultured in William’s medium (Sigma). All media contained 10% of heat inactivated
foetal bovine serum (Euroclone, Celbio), 100 U/mL penicillin, 100 μg/mL streptomycin and
2mM L-glutamine (Euroclone, Celbio). HCC cell lines were grown at 37°C in a humidified
atmosphere at 5% CO2.
With regard to in-stent restenosis, primary cultures of human vascular smooth muscle cells
(VSMC) (Promocell), isolated from three different donors, were purchased from Promocell. For
all experiments, cells in the third passage were used. VSMC were cultured in a medium
containing one third Smooth Muscle Cell Basal Medium (Promocell), one third Nutrient Misture
F-12 (Euroclone, Celbio) and one third Waymouth Medium (Invitrogen) supplemented with 15%
of heat inactivated foetal bovine serum and 100 U/mL penicillin and 100 μg/mL streptomycin
(Euroclone, Celbio) at 37°C in a humidified atmosphere containing 5% CO2.
2. Selection of siRNAs targeted agains SRF, Cyciln E1, Cyclin E2 and E2F1.
A preliminary selection of siRNAs was conducted according to the previously reported guide
lines based on a mathematical algorithm (Poliseno et al., 2004a; Poliseno et al., 2004b). In the
case of siRNAs targeted against SRF, a previously selected molecule was used (werth et al.,
2007).
Meterials and Methods
36
3. Uptake studies.
For each cell type considered, uptake studies were performed in the presence of variable amounts
of transfection reagent and siRNAs conjugated with a fluorescein-isothiocynate (FITC) molecule
in order to optimize the weight ratio siRNAs/transfection reagent. Transfection time was also
optimised for each cell type considered (1-6 hours); uptake efficiencies were studied soon after
transfection by evaluating the amount of FITC positive cells using a fluorescence microscope
(Leica Mycrosystem); a more quantitative evaluation was carried out counting FITC positive
cells by flow citometry (FACScanto, Becton Dickinson, DIVA software) after cell
trypsinization.
Optimized HCC cell transfection conditions: 7.65, 2.55 or 2.55 μg of liposome
(Lipofectamin2000 -1mg/ml, Invitrogen) for HepG2, HuH7 and JHH6, respectively, were mixed
in 125 μl of appropiate medium (Optimem, Invitrogen) for 15 minutes at room temperature. 2.55
μg of the selected siRNAs were dissolved in 125 μl of Optimem for 15 minutes at room
temperature and subsequently mixed with the liposome solution prepared as above. After 20
minutes, necessary to allow complexes formation, the mixture was added to 800 μl of
decomplemented DMEM High Glucose medium to reach a final siRNA concentration of 220 nM
and administered to the cells seeded in 6-well plate at density of 3.8x103 cells/cm2. After three
hours, the supernatant was replaced by 3 ml of complete medium (Fig.1).
Fig.1: Transfection protocol.
SiRNA Transfection reagent
Incubate 20min RT
Addition of siRNA
complexes to plated cells (t=2h or 3h )
SiRNA Transfection reagent
Incubate 20min RT
Addition of siRNA
complexes to plated cells (t=2h or 3h )
Meterials and Methods
37
Optimized VSMC transfection conditions: 12.0 μg of liposome (CellFectin -1mg/ml,
Invitrogen), were mixed in 125 μl of appropiate medium (Smooth Muscle Cell Basal Medium,
Promocell) for 15 minutes at room temperature. 4.8 μg of the selected siRNAs were dissolved in
125 μl of Smooth Muscle Cell Basal Medium for 10 minutes at room temperature and
subsequently mixed with the liposome solution prepared as above. After 20 minutes, the mixture
was added in 1500 μl decomplemented Smooth Muscle Cell Basal Medium to reach a final
concentration of 220 nM and administered to the cells cultured in 6 cm plastic dishes at density
of 3.3x103 cells/cm2. After two hours, the supernatant was replaced by 4 ml of VSMC complete
medium (Fig.1).
3.1 Experimental set up.
HCC cell lines were seeded in complete medium at a density of 3.8x103 cells/cm2 in 6-well plate
and allowed to attach overnight. The experiments were performed with actively growing cells
(proliferating cells) and transfections were conducted the day after seeding (see protocol 1)
(Fig.2). In a variation of protocol 1, cells were re-transfected at day three and then collected at
day six.
As regard with VSMC, 3.3x103 cells/cm2 (Grassi et al., 2005b) were seeded into 6 cm plastic
dishes in the presence of complete medium. In the experiments performed with actively growing
cells (proliferating cells), transfections were conducted the day after seeding (Protocol 1). In the
case of Protocol 2, one day after seeding, cells were kept under starving conditions for 48 hours
and then transfected (re-proliferating cells) (Fig.2).
Fig. 2: Transfection scheme.
Cell
seed
ing
siRN
Astra
nsfe
ctio
n
day1 day2 day3
Cell harvest and analysis
PROTOCOL 1
Cell
seed
ing
siRN
Astra
nsfe
ctio
n
day1 day2 day3day1 day2 day3
Cell harvest and analysis
PROTOCOL 1
Meterials and Methods
38
Fig. 3: Transfection scheme.
In a variation of Protocol 2, after transfection, VSMC were cultured in the presence of platelet-
derived growth factor-ββ (PDGF-ββ) (Sigma) in place of serum. In another variation of Protocol
2, cells were cultured in the presence of 22mmol/l glucose (high glucose HG) to simulate the
high glucose concentration found in diabetic patients.
Different commercially available transfection reagents, i.e. Oligofectamin, Cellfectin, Lipofectin
and Lipofectamin2000 (Invitrogen) were tested.
Under final optimized conditions, non treated cells, cells treated with selected siRNAs, cells
treated with the transfection system only and cells treated by a control siRNA directed against
the luciferase gene (siGL2), were analysed in parallel.
4. Cell count and viability assay.
The evaluation of cell morphology and number were performed by direct microscopic
observation (Nikon Eclipse TS100) and by Thoma’s haemocytometer chamber. Cell viability
was evaluated by 0.05% Trypan Blue dye staining (w/v in PBS) (1:1,v/v). Total viable cell
number was calculated by the formula:
Xn = N° x 2 x 104
where Xn is the number of cells in 1 ml of sample, N° is the number of viable cells, 2 is the
dilution’s factor with Trypan Blue dye and 104 is the convertion’s factor of Thoma’s
haemocytometer.
Cell
seed
ing
siRNA
stra
nsfe
ctio
n an
d se
rum
ad
ditio
n
Cell
starv
atio
n
day1 day2 day3
Cell harvest and analysis
PROTOCOL 2
Cell
seed
ing
siRNA
stra
nsfe
ctio
n an
d se
rum
ad
ditio
n
Cell
starv
atio
n
day1 day2 day3day1 day2 day3
Cell harvest and analysis
PROTOCOL 2
Meterials and Methods
39
5. Evaluation of cell colony number and area.
After siRNA treatment (Protocol 1), cells were gently washed by PBS and then added with fresh
medium. Analysis were performed with living cells in order not to alterate the morphological
characteristics of cells and evaluated by an inverted microscope (Leica Mycrosystem). Colony
morphometrical analysis and amount were calculated using the Sigma Scan Pro program. Five
fields for each treatment, each containing at least 20 events (magnification = 5x), were
considered.
6. Quantitative real time RT-PCR.
Total RNAs were extracted from siRNA treated and control cells (siGL2 and non treated cells)
by using the RNeasy Mini kit (Qiagen). The quantification of total RNA was evaluated by
spectrophotometric determination using NanoDrop ND-1000 (CelBio). The RNA quality was
controlled by a Lab-on-Chip-System Bioanalyser 2100 (Agilent).
Reverse transcription reactions were performed using 500ng of each RNA sample; the master
mix for reverse transcription was prepared by adding the reagents in the order and in the
proportions shown in table 1:
Component
(Applied Biosystems-Applera Corporation).
Final
concentration
25mM MgCl2 Solution 5mM
10x PCR Buffer II 1x
dGTP 1mM
dATP 1mM
dCTP 1mM
dTTP 1mM
Rnase Inhibitor 1U/μl
MuLV Reverse Transcriptase 2.5U/μl
Random Hexamers 2.5μM
Table 1: Reverse Trancription Master Mix
Using Random Hexamers as reverse transcriptase primer, allow samples to incubate at room
temperature for 10 minutes: the room temperature incubation allows for the extension of the
Meterials and Methods
40
exameric primers by reverse transcriptase. The extended primers will then remain annealed to
the RNA template upon raising the reaction temperature of 42°C.
Real-Time polymerase chain reaction was performed using the SYBRGreen Master Mix
(Applied Biosystems) on a 7900/HT Sequence Detection System (Applied Biosystems). The
primers (MWG Biotech, GA) and the Tm used are reported in Table 1.
Amplifications, conducted in triplicate, were performed in a final volume of 35μl of SYBRGreen
Master Mix buffer, containing primers (300nM each) and 1μl cDNA. 28s rRNA and all the other
target genes were submitted to 40 cycles of amplification, preceded by pre-denaturation at 95°C
for 10 minutes, denaturation at 95°C for 15 seconds, annealing at proper temperature for 60
seconds and extension at 72°C for 30 seconds. A final extension at 72°C for 10 minutes and a
dissociation stage (95°C/60°C/95°C for 15 seconds each) was then added. The relative amounts
of the mRNA of target genes were normalized by 28s rRNA content according to Pfaffl (Michael
W.Pfaffl, 2004).
Meterials and Methods
41
Table 1. Primers and annealing temperature.
Gene Primer pair Tm Length (bp)
Amplification Region
28S
(M11167)
Fw 5’–TGG GAA TGC AGC CCA AAG- 3’
Rev 5’–CCT TAC GGT ACT TGT TGA CTA TGC–3’
60°C
84
282-365
SRF
(J03161)
Fw 5’- AGT GCA GGC CAT TCA AGT G-3’
Rev 5’-ACG GAT GAC GTC ATG ATG GTG-3’
60°C
128
1426-1554
Cyclin E1
(NM 001238)
Fw 5’-TGC CTG TAC TGA GCT GGG CA-3’
Rev 5’-GGC TGC AGA AGA GGG TGT TG-3’
60°C
112
497-608
Cyclin E2
(NM 057749)
Fw 5’-CTT CCA AAC TTG AGG AAA TC-3’
Rev 5’-TCC ATC CTT AAG ATA TCC TC-3’
62°C
94
696-789
E2F1
( NM 005225)
Fw 5’-CCA GGA AAA GGT GTG AAA TC-3’
Rev 5’-AAG CGC TTG GTG GTC AGA TT-3’
62°C
74
466-539
Cyclin D1
(NM 053056)
Fw 5’-CCG TCC ATG CGG AAG ATC-3’
Rev 5’-CCT CCT CCT CGC ACT TCT GT-3’
62°C
70
369-438
Cyclin A1
(NM 003914)
Fw 5’-GTC AGA GAG GGG ATG GCA T- 3’
Revf 5’- CCA GTC CAC CAG AAT CGT G -3’
58°C
90
804-894
LRH-1
(NM 205860)
Fw 5’-CCG ACA AGT GGT ACA TGG AA-3’
Rev 5’-ACT CAT GAG GTT GTT GAG GG-3’
60°C
112
1382-1493
p21waf1/cip1
(NM 000389)
Fw 5’-AGT GGA CAG CGA GCA GCT GA-3’
Rev 5’-CGA AGT TCC ATC GCT CAC GG-3’
62°C
83
166-248
p27kip1
(NM 004064)
Fw 5’-CGG TGG ACC ACG AAG AGT TAA-3’
Rev 5’-GGC TCG CCT CTT CCA TGT C-3’
60°C
66
569-634
OAS1
(NM016816)
Fw 5’-TCC AAG GTG GTA AAG GGT GG-3’
Rev 5’-AGG TCA GCG TCA GAT CGG C-3’
60°C
68
272-339
Meterials and Methods
42
7. Protein extraction.
After siRNA treatment (Protocol 1 or Protocol 2), cells were collected by centrifugation at 1000
rpm for 5 min and rinsed with PBS. The cells were lysed with an extraction buffer containing
45mM Tris-HCl (pH 6.8) (Sigma), 0.2% N-Lauroylsarcosine (Fluka), 0.2 mM of
phenylmethanesulfonyl fluoride (PMSF) (Sigma), proteases and phosphatases inhibitors .
Because of the instability of PMSF in aqueous solution, this component was added to the buffer
shortly before use. Twenty μl of buffer/105 cells were added and incubation performed at room
temperature for 5 minutes. Protein extracts were then stored at –80°C (Wu W. et al., 2004).
The protein content was determined by the bicinchoninic (BCA) protein assay. The BCA method
is based on the reduction of Cu+2 to Cu+1 by protein in alkaline medium (the biuret reaction) and
their subsequent reaction with BCA to form a water-soluble complex that exhibits a strong
absorbance at 570nm, proportional to the protein concentration.
Fig.18 BCA reaction.
Standards solutions of BSA were prepared to have a calibration curve in order to determine the
concentration of protein extracts. 20 μl of each standards and of protein sample were pipetted
into a 96 well flat-bottomed microplate in duplicate. 200 μl of the freshly prepared working
reagent (mixture of BCA and CuSO4 at a ratio of 50:1) were added and put in the microplate at
37°C for 30 minutes. The samples are then cooled at room temperature and the absorbance
measured at 570 nm using a spectrophotometer (Spectra Max plus 384, Molecular Devices). The
concentration of each protein sample was determined from a plot of concentration against the
absorbance obtained for the standard solutions (calibration curve).
Meterials and Methods
43
8. Immunoblotting.
30 μg of protein extract were loaded on 12% SDS-PAGE (29:1, acrylamide:bis-acrylamide) gel
according to LaemmLi’s procedure (Laemmli, 1970) and then transferred onto a 0.22 μm
nitrocellulose membrane (Schleicher & Schuell) using a transblot semi-dry apparatus system
(Biorad) with 60 mM Tris-HCl, 40 mM glycine containing 0.05 % SDS and 10% methanol. The
membranes were then stained by Ponceau S (Sigma Chemicals) to verify the efficiency of the
transfer. The membrane was blocked with non-fat dried milk. The IgG and the hybridisation
conditions used are reported in the table 2:
Table 2: IgG and hybridisation conditions.
Primary antibody Dilution Non-fat Milk Incubation time Secondary antibody
1:2000 Incubation time
E2F1 (Santa Cruz) 1:100
5%
o/n a 4°C Anti-Mouse HRP
(Santa Cruz) 1 h
Ciclina E1 (BD Pharmigen) 1:1000 3%
+ Tween 1 h a RT Anti-Mouse
HRP (Santa Cruz)
1 h
Cyclin A1 (Santa Cruz) 1: 500 5%
+ Tween o/n a 4°C Anti-Rabbit
HRP (Santa Cruz)
1 h
pRb (BD Pharmigen) 1:400 5%
+Tween 1 h a RT Anti-Mouse
HRP (Santa Cruz)
1 h
PARP (BD Pharmigen) 1 :1000 5%
+Tween o/n a 4°C Anti-Mouse
HRP (Santa Cruz)
1 h
Cyclin E2 (Santa Cruz) 1 :100 5% o/n a 4°C
Anti-rabbit HRP
(Santa Cruz) 1 h
Cyclin D1 (Santa Cruz) 1 :500 5%
+Tween o/n a 4°C Anti-Mouse
HRP (Santa Cruz)
1 h
P27 (Santa Cruz) 1 :100
3%
o/n a 4°C
Anti-Mouse HRP
(Santa Cruz) 1 h
p-Cyclin E1 (Santa Cruz)
1 :100 5%
+Tween 1 h a RT Anti-goat
HRP (Santa Cruz)
1 h
GAPDH (Santa Cruz)
1 :800 5%
+Tween 1 h a RT Anti-Rabbit
HRP
1 h
Meterials and Methods
44
The membranes were washed twice by PBS containing 0.05% Tween 20 and then develop by
enhanced chemiluminescence’s detection kit (Pierce). Band intensities were quantified by
densitometry (Model GS-700 Imaging Densitometer, Biorad and Molecular Analyst software,
Biorad). GAPDH was used as internal loading control.
9. Cytotoxicity assay.
Cytotoxicity was evaluated by lactate dehydrogenase (LDH) assay kit (BioVision Prod.,
Mountain View CA). LDH activity is determined by a coupled enzymatic reaction: LDH
oxidizes lactate to pyruvate which then reacts with tetrazolium salt to form formazan. The
formazan dye is water soluble and can be detected by spectrophotometer at 500nm.
100 μl of supernatant were transferred to corresponding wells in an optically clear 96-well plate.
100 μl of Reaction Mixture (containing Catalyst Solution: Dye Solution = 1 : 45) were then
added to each well and incubated for 30 minutes at room temperature protecting the plate from
light. Absorbance of sample was performed at 500nm using a spectrophotometer (Spectra Max
plus 384, Molecular Devices). As positive control, triton X-100 (1% final concentration) treated
cells were considered; as negative control, free medium was used.
The percentage of cytotoxicity was determined according to the formula:
(Test sample – Negative control)
Cytotoxicity (%) = --------------------------------------------- x 100
(Positive control – Negative control)
10. Apoptosis evaluation.
Apoptosis was evaluated by the Annexin V test (Bender – Med System, Burlingame, CA) and
Propidium Iodide (PI) staining (BD PharmigenTM). Annexin V binds to phosphatidylserine
when it is translocated from the inner to the outer part of the membrane, an early event in
apoptosis. As annexin V is conjugated to a fluorochrome (FITC) it is possible to identify
annexin V positive cells (apoptotic) by flow-cytometric identification. PI, which stains the DNA
of cells with damaged cytoplasmic membrane, allow to identify apoptotic and necrotic cells.
HepG2 were collected two days after siRNA transfection, HuH7 and JHH6 three days after
siRNA transfection; then cells were resuspended in binding buffer at the concentration of 2–
5 × 105 cell/ml and incubated with annexin V Ig for 15 min. Cells were then sedimented,
Meterials and Methods
45
resuspended in the binding buffer and incubated with propidium iodide PI for 20 min at room
temperature. After a final washing step, cells were re-suspended in 0.5 ml of 1x PBS/0.5% BSA
(bovine serum albumin) and analyzed by flow cytometry (FACS Canto, BD) using the DIVA
software. As positive control a sample of cells kept in complete medium was incubated with
1 μM staurosporin (Sigma Chem. Co, St. Louis) 3 h prior harvesting.
11. Proliferation assays.
The distribution of cell cycle phases can be performed by the measurement of
bromodeoxyuridine (BrdU) incorporation into newly synthesized cellular DNA and DNA
staining by Propidium Iodide. Moreover, KI67 staining can be used to descriminate the G0-phase
of cell cycle. Ki67 is a nuclear cell proliferation-associated antigen expressed in all stages of the
cell cycle, except of G0.
Fig.19 Schematic view of cells in different phases of cell cycle
BrdU pulse and DNA staining: twelve hours before harvesting, cells were pulsed with
bromodeoxyuridine (BrdU) at a concentration of 10 μM. Then cells were trypsinized and
resuspend in ice cold 70% EtOH over night. These fixed samples can be storeded in EtOH at 4°C
up to 3 days. Afterwards, a washing step with PBS containing 0.5% BSA was performed; then
cells were traeated with 1 M HCl/0.5% BSA for 1 hour (only 20 minutes in the case of VSMC).
After a further washing step, cells were resuspended in 0.1 M sodium borate, pH 8.5, for 2
minutes and washed again. Each sample was incubated with fluorescein-isothiocyanate (FITC) –
conjugated mouse monoclonal antibody (BD PharMigenTM) anti BrdU or with FITC-conjugated
mouse IgG1 Isotype Control (as background control) for 60 minutes (only 20 minutes in the case
G1/G0
S
G2/M
Meterials and Methods
46
of VSMC). Another washing step preceded incubation with 4 μl PI Staining Solution (BD
PharmigenTM) and 100 μl Ribonuclease A 100 μg/ml (Sigma) for 1-2 hours. After a final
washing step, cells were resuspended in PBS containing 0.5% BSA and analyzed by flow
cytometry (FACScanto, Becton Dickinson) using the DIVA software.
Detection of KI67: cells were harvested, counted and pelleted as above. Then cells were
resuspend in 200 μl ice cold 70% EtOH over night. Fixed cells can be stored at -20°C for up to
60 days prior to staining. After washing with PBS containing 1% BSA and 0.09% NaN3 cells
were incubated with 7 μl of FITC-conjigated Anti-Human Ki67 (BD PharMigenTM) or with 7 μl
of FITC-conjugated mouse IgG1 Isotype Control (as background control) for 60 minutes (only 20
minutes in the case of VSMC). After a further washing step, 4 μl PI Staining Solution (BD
PharmigenTM) and 100 μl Ribonuclease A 100 μg/ml (Sigma) were added and the incubation
allowed for 30 minutes. After a final washing step, cells were resuspended in PBS containing
0.5% BSA and analysed by flow cytometry.
12. Statistical analysis.
If not otherwise indicated, data are expressed as the mean ± SEM, and statistical significance (P
value) was calculated using the ANOVA one way test led by MS Excel. P values ≤ 0.05 were
considered to be statistically significant.
Results
47
RESULTS
Selection of siRNAs and uptake studies
1. Selection of siRNAs targeted against SRF, Cyclin E1,Cyclin E2 and E2F1.
Guide lines for the identification of active siRNAs against the mRNA targets chosen (SRF,
CyE1,CyE2 and E2F1), were as described (Poliseno et al., 2004a; Poliseno et al., 2004b).
To interfere with SRF expression, we selected two different SRF-specific siRNAs, siSRF820 and
siSRF797, thereby specifically targeting sequences encoding the SRF MADS-box. Targeted
region showed no significant homology to any other transcript including MEF2 (myocyte
enhancer factor-2) transcripts, which possess a very homologous MADS-box to SRF, nor did
they significantly affect transcript levels of MEF2 genes as judged by gene expression profiling
(werth et al., 2007). Also in the case of siRNAs targeted against Cyclin E1,Cyclin E2 and E2F1,
two different specific siRNAs were selected. After some preliminary investigations, only the
more effective siRNAs, in terms of the effects on the specific protein levels (data not shown),
were chosen for our experiments and are reported in the table 1. A luciferase siRNA (siGL2), as
sequence unrelated control, was used.
Table 1: siRNAs sequences.
siRNAs sense antisense
SiSRF797 GAUGGAGUUCAUCGACAACAA GUUGUCGAUGAACUCCAUCUU
siCyclin E1-1415 GAGCGGUAAGAAGCAGAGC GCUCUGCUUCUUACCGCUC
siCyclin E2-647 GCUUGCAGUGAAGAGGAUA UAUCCUCUUCACUGCAAGC
SiE2F1-1324 GAGGAGUUCAUCAGCCUUU AAAGGCUGAUGAACUCCUC
siGl2 CGUACGCGGAAUACUUCGA UCGAAGUAUUCCGCGUACG
Results
48
2. Uptake studies.
To evaluate uptake efficiencies, a siRNA, siGL2, conjugated with a fluorescein-isothiocynate
(FITC) molecule, was transfected to the target cells. The following transfection parameters were
considered:
a. percent of cell transfected;
b. cellular distribution of the molecules;
c. persistence of the molecules in the cell.
The percentage of cell transfected (a) and the persistence of the molecules in the cell (c) were
evaluated by flow cytometry. Cellular distribution (b), which was evaluated by fluorescence
microscopy, is an important parameter for our studies. Our experience in the field of HHRzs
(Grassi et al., 2005a; Grassi et al., 2001) and data showed by other groups (Bramlage et al.,
1999) indicate that different cellular localization of RNA molecules dramatically affect their
activities. This variable was investigated by fluorescence microscopy.
a. percent of cell transfected: as it is not possible to predict a priori the optimal transfection
conditions for each cell type considered, transfections were performed in the presence of
different commercially available transfectant, variable ratios of transfection reagent/FITC-
labeled siRNAs and variable transfection times (see Materials and Methods).
Lipofectamin 2000, at a siGL2-FITC/Lipofectamin 2000 weight ratio of 1:3 and afer a
transfection time of three hours gave the highest transfection rates in HepG2 cell line (Fig. 1).
Fig.1: transfection efficiency in HepG2 cell line evaluated by flowcitometry
(siRNAs conc=220nM, density of 1*104cells/cm2 in 6well plate).
Transfection efficiencies in HepG2 cell line
0% 20% 40% 60%
lipofectamin2000 1:3
lipofectamin2000 1:2
lipofectamin2000 1:1
cellfectin 1:3
cellfectin 1:2
cellfectin 1:1
lipofectin 1:3
lipofectin 1:2
lipofectin 1:1
oligofecatmin 1:3
oligofecatmin 1:2
oligofecatmin 1:1
Percentage of FITC positive cells
Transfection efficiencies in HepG2 cell line
0% 20% 40% 60%
lipofectamin2000 1:3
lipofectamin2000 1:2
lipofectamin2000 1:1
cellfectin 1:3
cellfectin 1:2
cellfectin 1:1
lipofectin 1:3
lipofectin 1:2
lipofectin 1:1
oligofecatmin 1:3
oligofecatmin 1:2
oligofecatmin 1:1
Percentage of FITC positive cells
Results
49
Similar results were obtained for HuH7 and JHH6 (data not shown) but using a siGL2-
FITC/Lipofectamin2000 weight ratio of 1:1. Vascular smooth muscle cells (VSMC) were better
transfected by cellfectin at a weight ratio siGL2-FITC/Cellfectin of 1:2.5 with a transfection time
of two hours (Fig. 2). Similar experiments as described above were conducted prolonging cell-
liposomes interaction to six hours, with no significant increase of transfection rate (data not
shown).
Fig. 2: transfection efficiency in VSMC evaluated by flowcitometry
(siRNAs conc=220nM, density of 3.3*103cells/cm2 in 6 cm dishes).
In all these experiments, the concentration of siRNAs was of 220nM for all cell types used. At
higher siRNAs concentrations, the pronounced increase in cell death, as visualized
microscopically (data not shown), suggested us not to overcame in our experiments this
concentration.
In VSMC an excellent transfection rate was achieved under the conditions reported in Fig.2 and
using a cell seeding density of 3.3x103 cells/cm2. In all HCC cell lines seeded at 1*104cells/cm2,
the amount of positive cells never exceed 60%, suggesting that further optimisation was
required. For this purpose the best conditions selected in Fig.1 were tested in the presence of
different cell seeding density (Fig.3):
Transfection efficiency in VSMC
0% 20% 40% 60% 80% 100%
cellfectin 1:3
cellfectin 1:2.5
cellfectin 1:2
cellfectin 1:1
lipofectin 1:3
lipofectin 1:2
lipofectin 1:1
lipofectamin2000 1:3
lipofectamin2000 1:2
lipofectamin2000 1:1
Percentage of FITC positive cells
Transfection efficiency in VSMC
0% 20% 40% 60% 80% 100%
cellfectin 1:3
cellfectin 1:2.5
cellfectin 1:2
cellfectin 1:1
lipofectin 1:3
lipofectin 1:2
lipofectin 1:1
lipofectamin2000 1:3
lipofectamin2000 1:2
lipofectamin2000 1:1
Percentage of FITC positive cells
Results
50
Fig. 3: transfection efficiency in HepG2 cell line evaluated by flowcitometry
(siRNAs conc=220nM in 6well plate)
Reducing cell density, transfection efficiency increased from about 60% to more than 80% in
HepG2 cell line (Fig.3) and in JHH6 and HuH7 cell lines (siGL2-FITC/Lipofectamin2000
weight ratio of 1:1) (data not shown).
In conclusion, the final optimised transfection conditions for each cell type were as reported in
the table 2:
Table 2: Optimised transfection conditions for each cell type.
Cell type
Seeding density
SiRNAs concentration
weight ratio siRNAs:liposome
HepG2
3.8*103/cm2
220nM
1:3
HuH7
3.8*103/cm2
220nM
1:1
JHH6
3.8*103/cm2
220nM
1:1
VSMC
3.3*103/cm2
220nM
1:2.5
siGL2-FITC:Lipofectamin 2000 = 1:3 in HepG2 cell line
0% 20% 40% 60% 80% 100%
d=3.8*103/cm2
d=1.0*104/cm2
d=7.6*103/cm2
Percentage of FITC positive cells
siGL2-FITC:Lipofectamin 2000 = 1:3 in HepG2 cell line
0% 20% 40% 60% 80% 100%
d=3.8*103/cm2
d=1.0*104/cm2
d=7.6*103/cm2
Percentage of FITC positive cells
Results
51
b. cellular distribution of the FITC-siGL2: the intracellular localization of siGL2-FITC
following the above reported transfection conditions was documented with living cells to avoid
artifacts introduced by fixation. As reported in Fig.4, in VSMC an even distribution of green
fluorescence in the cells was observed. Similar results were observed for the HCC cell lines.
Fig.4: VSMC transfected cell with siGL2-FITC
(siRNAs conc=220nM, density of 3.3*103cells/cm2 , weight ratio siGL2-FITC:Cellfectin = 1:2.5).
Results
52
3. INF Response.
SiRNAs are believed to be too short to activate the non-specific antiviral response against
dsRNA molecules. However, a recent report showed that short hairpin RNAs (shRNAs) can
activate an antiviral response (Bridge et al., 2003). Thus, before proceeding with the siRNAs
experiments, it was necessary to exclude an INF- triggered response by our molecules. This fact
would have profoundly altered the siRNA specificity of action abrogating the relevance of the
investigation planned.
By quantitative RT-PCR analysis, we measured the expression of 2’-5’-oligoadenylate
synthetase 1 (OAS1) gene, a classical INF target gene that is induced >50-fold upon activation of
an INF-response. The mRNA levels of OAS-1 in siRNA-transfected cells varied between 0.5 and
3 fold of controls, thus being far below the reported activation observed in an INF-response
(Fig.5).
Fig. 5: Quantitative RT-PCR analysis of OAS1.
OAS1 induction by all siRNAs is within 3-fold, which is far less than
that reported on activation of an IFN response.
OAS1 RNA levels
0
0.5
1.0
1.5
2.0
2.5
3.0
NT siCyE1 1415 siE2F1 1324 siSrf 797 siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
JHH6HUH7HepG2VSMC
OAS1 RNA levels
0
0.5
1.0
1.5
2.0
2.5
3.0
NT siCyE1 1415 siE2F1 1324 siSrf 797 siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
JHH6HUH7HepG2VSMC
Results
53
Depletion of SRF in HCC cell lines
For HCC, a leading cause of cancer death world-wide, there is no clinically tested useful therapy.
Thus, the development of novel effective therapeutic approaches are of utmost relevance. As a
strategy to down modulate HCC cell expansion, we have considered the targeting of the
transcription factor SRF by means of siRNAs. SRF has been considered as target in this work
because of its implication in the proliferation of the HCC cell line HepG2 (Shao et al., 2005).
Moreover, it has been observed that SRF is expressed in HCC tissue but not in normal/cirrhotic
liver and that its over-expression is particularly evident in high grade, poorly differentiated, HCC
forms(Park et al., 2007). These observation together with the absolute lack of any published data
about the investigation of a direct depletion of SRF in HCC cell lines, prompted us to generate a
specific siRNA anti SRF and test its effect in three HCC cell lines, i.e. HepG2, HuH7 and JHH6.
Suitable transfection systems were undertaken to test siSRF797 effects in HepG2, HuH7 and
JHH6 cell lines. Non treated cells, and cells treated by a control siRNA directed against the
luciferase gene (siGL2), were analysed in parallel. Optimized analysis times were two and three
days after transfection for HepG2 and HuH7-JHH6, respectively. In all reported histogram the
data belonging to the three different cell lines and they are normalized to the respective siGL2
control: this implies that it is not possible to compare the reported values among the three
different cell lines.
Results
54
4. siSRF797 effects on SRF mRNA and protein levels.
To investigate the specificity and the efficacy of siSRF797-mediated RNAi, siSRF797 was
transfected into all HCC cell lines and the mRNA and protein levels of SRF evaluated.
Between two and three days after transfection, siSRF797 induced an evident decrease in the
specific target mRNA levels in all HCC cell lines (* p < 0.001) (Fig. 6).
Fig. 6: siRNA-mediated reduction of SRF transcript levels evaluated by quantitative RT- PCR
(data were normalized to 28S). Data are expressed as means ± SEM, n=6.
* p < 0.001 compared to siGL2 treated cells. NT=not treated cells.
In the reported histogram, as well as in the following, the data belonging to the three different cell lines are
normalized to the respective siGL2 control: this implies that it is not possible to compare the reported values
among the three different cell lines.
In all HCC cell lines, total SRF protein levels correlated with the mRNA levels: the decrease in
SRF mRNA upon transfection with siSRF797 was paralleled by a clear decrease in SRF protein
levels as reported in a representative experiment in Fig. 7a and summarized in Fig 7b.
Fig. 7a: Reduction of endogenous SRF protein by siSRF797 was detected by immunoblotting.
GAPDH protein served as a loading control.
0
50
NT siSrf 797
HepG2
HuH7JHH6
SRF mRNA levels
150
* * *
100
norm
aliz
edto
GL2
tr
eate
d ce
lls
0
50
NT siSrf 797
HepG2
HuH7JHH6
HepG2
HuH7JHH6
SRF mRNA levels
150
* * *
100
norm
aliz
edto
GL2
tr
eate
d ce
lls
s iGL2
siSRF7
97
NT
GapdH
siGL2
siSRF7
97
NT siGL2
siSRF7
97
NT
HepG2 day2
HuH7 day3
JHH6 day3
SRF mature form
SRF neo-synthesized form
siGL2
siSRF7
97
NT
GapdH
siGL2
siSRF7
97
NT siGL2
siSRF7
97
NT
HepG2 day2
HuH7 day3
JHH6 day3
SRF mature form
SRF neo-synthesized form
Results
55
Fig. 7b: SRF protein levels;
data are expressed as means ± SEM, n=3. NT=not treated cells.
As indicated in Fig.7a, two bands were detected for SRF. The upper one corresponds to the
mature SRF form while the lower one to the immature neo-synthesized form (REF). It should be
noted that in general the upper band (mature form) remained visible while the lower one (neo-
synthesized) disappeared in the blot in siSRF797 treated cells. This effect was somewhat
variable among the three cell lines as in HepG2 the upper band is clearly decreased (similarly to
VSMC, as reported in the next chapter) while in HuH7 and in JHH6 it is comparable to the
controls. Despite this variability, in all cell lines tested the disappearance of the neo-synthesized
SRF form was evident and thus the global protein levels of SRF were reduced.
SRF total protein levels
0
50
100
150
200
250
NT siSrf 797
norm
aliz
edto
GL2
tr
eate
d ce
lls
HepG2HuH7JHH6
SRF total protein levels
0
50
100
150
200
250
NT siSrf 797
norm
aliz
edto
GL2
tr
eate
d ce
lls
HepG2HuH7JHH6
Results
56
5. Effects of SRF depletion on cell morphology and cell-counting.
The morphology of HepG2, HUH7 and JHH6 cell lines are reported in figures 8, 9 and 10.
HepG2
Fig. 8: Effect of SRF depletion by siSRF797 on HepG2 morphology, two days after transfection.
Cell morphology was analysed by phase contrast microscopy
at 5x and 20x magnification. NT = not-treated cells.
In HepG2 treated cells we observed a clear reduction in cell number compared to controls.
Morevorer, part of the attached cells started to round up and detach from plates.
NT
100 μm 100 μm
siGL2
100 μm100 μm
siSRF797
100 μm 100 μm
5x 20x
NT
100 μm 100 μm100 μm
siGL2
100 μm100 μm
siSRF797
100 μm 100 μm
5x 20x
Results
57
HuH7 JHH6
Fig. 9 and 10: Effect of SRF depletion by siSRF797 on HuH7 and JHH6 morphology, three days after transfection.
With regard to HuH7 and JHH6, no evident variations were detected in cell morphology upon
siSRF797 treatment compared to controls.
NT
100 μm 100 μm
siGL2
100 μm 100 μm
100 μm
siSRF797
100 μm
5x 20x
NT
100 μm 100 μm
siGL2
100 μm 100 μm
100 μm
siSRF797
100 μm
5x 20x
NT
100 μm 100 μm
100 μm
100 μm
siGL2
siSRF797
5x 20x
100 μm
100 μm
NT
100 μm 100 μm
100 μm
100 μm
siGL2
siSRF797
5x 20x
100 μm
100 μm
Results
58
Thus, SRF depletion resulted in a microscopically appreciable reduction in the amount of HepG2
but not of HuH7 and JHH6 cells.
With regard to HepG2, this observation was confirmed by cell counting (41.1% ± 15.0 of
reduction compared to siGL2 treated cells) (Fig.11a). The reduction in cell number compared to
controls indicate a specific effect of the siSRF797 (*p<0.05). As HepG2 grow in colonies (Fig
8), amount and areas were also measured. As reported in Fig.11b and 11c, the reduction in cell
number was paralleled by a decrease in colonies area (*p<0.05) but not in number, suggesting a
cytostatic effect of SRF depletion.
Fig. 11: siSRF797 effects on HepG2 cell line.
a. The amount of cell number was evaluated two days after transfection; (*p<0.05 compared to
siGL2 treated cells); data are expressed as means ± SEM, n=4. NT=not treated cells.
b. Colonies area was evaluated two days after transfection (*p<0.05 compared to siGL2
treated cells); data are expressed as means ± SEM, n=100. NT=not treated cells.
c. Colonies number was evaluated two days after transfection;
data are expressed as means ± SEM, n=100. NT=not treated cells.
a. HepG2 cell counting
0
20
40
60
80
100
120
140
160
day1 day2 day3
% c
ell n
umbe
r no
rmal
ized
to
GL2
trea
ted
cells
siSRF797siGL2NT* *
a. HepG2 cell counting
0
20
40
60
80
100
120
140
160
day1 day2 day3
% c
ell n
umbe
r no
rmal
ized
to
GL2
trea
ted
cells
siSRF797siGL2NT* *
Um
squa
re
b. HepG2 colony areas, day2
0
5000
10000
15000
20000
25000
30000
35000
siSrf797 siGL2 NT
*
μm
squ
are
Um
squa
re
b. HepG2 colony areas, day2
0
5000
10000
15000
20000
25000
30000
35000
siSrf797 siGL2 NT
*
μm
squ
are
c. HepG2 number of colonies, day2
0
10
2030
4050
6070
80
siSrf797 siGL2 NT
Num
ber
of c
olon
ies
c. HepG2 number of colonies, day2
0
10
2030
4050
6070
80
siSrf797 siGL2 NT
Num
ber
of c
olon
ies
Results
59
In the case of HUH7, no significant reduction in the cell number as well as in colonies area and
amount were observed in siSRF797 treated cells compared to siGL2 treated cells; a clear
reduction was in contrast observed compared to not-treated cells (Fig.12 a, b, c). This suggest an
aspecific reduction in cell number in this cell line upon siRNA treatment.
Fig. 12: siSRF797 effects on HuH7 cell line.
a. The cell number was evaluated three days after transfection;
data are expressed as means ± SEM, n=4. NT=not treated cells.
b. Colonies area was evaluated three days after transfection
data are expressed as means ± SEM, n=100. NT=not treated cells.
c. Colonies number was evaluated three days after transfection;
data are expressed as means ± SEM, n=100. NT=not treated cells.
a. HuH7 cell counting
day2 day3
siSRF797siGL2NT
0
50
100
150
200
250
300
% c
ell n
umbe
r no
rmal
ized
to
GL2
trea
ted
cells
a. HuH7 cell counting
day2 day3
siSRF797siGL2NT
0
50
100
150
200
250
300
% c
ell n
umbe
r no
rmal
ized
to
GL2
trea
ted
cells
b. HuH7 colony areas, day3
0
2000
4000
6000
8000
10000
12000
siSRF797 siGL2 NT
μm
squ
are
b. HuH7 colony areas, day3
0
2000
4000
6000
8000
10000
12000
siSRF797 siGL2 NT
μm
squ
are
c. HuH7 number of colonies, day3
0
5
10
15
20
25
siSRF797 siGL2 NT
num
ber
of c
olon
ies
c. HuH7 number of colonies, day3
0
5
10
15
20
25
siSRF797 siGL2 NT
num
ber
of c
olon
ies
Results
60
With regard to the amount of JHH6 cell number upon siSRF797 treatment, this cell line behaved
similarly to HuH7 where no clear reduction (15.2% ± 13.7) in cell number was observed
compared to siGL2 treated cells (Fig 13). More evident was in contrast the reduction compared
to not-treated cells (aspecific reduction). No data in terms of the areas and number of colonies
were available as JHH6 do not grow in colonies.
Fig. 13: siSRF797 effects on JHH6 cell line: a tendency towards a reduction in cell number compared to siGL2
treated cells was observed three days after transfection; evident is the reduction compared to NT cells;
data are expressed as means ± SEM, n=5; NT=not-treated cells.
JHH6 cell counting
50
100
150
200
250
300
day1 day2 day3
siSRF797siGL2NT
% c
ell n
umbe
r no
rmal
ized
to
GL2
trea
ted
cells
JHH6 cell counting
50
100
150
200
250
300
day1 day2 day3
siSRF797siGL2NT
siSRF797siGL2NT
% c
ell n
umbe
r no
rmal
ized
to
GL2
trea
ted
cells
Results
61
6. Effects of SRF depletion on cell cycle phase distribution.
Cell cycle progression was evaluated by flow cytometry after bromodeoxyuridine (BrdU) pulse
and DNA staining by propidium iodide (PI). This methodology allows the identification of the
newly synthesised DNA (BrdU incorporation) and total DNA content (DNA PI staining)
permitting to distinguish cells in the different phases of the cell cycle (Dolbeare et al., 1983;
Dekens et al., 2003). Thus, this method allowed not only to evaluate the proliferation inhibition
potential of siSRF797 but also the consequences of SRF knock down in terms of cell cycle phase
distribution in HCC cell lines.
In HepG2, siSRF797 caused a reduction of about 20% of S phase cells compared to control
siGL2-treated cells as reported in a representative experiment in Fig.14 and summarized in
Fig.15 (*p<0.001); a tendency towards an increase of G1/G0 cell was also observed.
Fig. 14: A representative dot plot of HepG2 is shown.
A:siGl2 treated cells; B:siSRF797 treated cells.
Q1: S-phase cells
Q2/Q4: G2/M phase cells
Q3: G1/G0 phase cells.
PI-A: Propidium Iodide staining; FITC-H: FITC labelled Ig anti BrdU
HepG2 treated by siGL2
25.0% 6.2%
21.7%47.1%
HepG2 treated by siSRF797
3.8%
22.9%
15.9%
57.3%
A BHepG2 treated by siGL2
25.0% 6.2%
21.7%47.1%
HepG2 treated by siSRF797
3.8%
22.9%
15.9%
57.3%
A B
Results
62
Fig. 15: Cell cycle phase distribution.
Data are expressed as means ± SEM, n=4.
Depletion of SRF diminished the S-phase cells by 20% compared to siGL2 treated cells (*p<0.001).
NT=not treated cells.
This decrease is followed by a tendency of an increase in G0/G1 phase cells.
In HuH7, only a tendency toward the reduction of S-phase cells was observed in siSRF797
treated cells compared to siGL2 treated cells. In contrast, evident was the reduction of S-phase
cells in siSRF797 treated cells compared to not treated cells, suggesting an aspecific effect of
siRNA transfection in this cell line.
Fig. 16: Cell cycle phase distribution.
Data are expressed as means ± SEM, n=4. NT=not treated cells.
Depletion of SRF resulted in a tendency towards a decrease of S-phase cells compared to siGL2 treated cells.
HepG2 day2
0
20
40
60
80
100
120
140
NT
norm
aliz
ed to
GL2
trea
ted
cells
s iSrf797
*
HepG2 day2
0
20
40
60
80
100
120
140
NT
norm
aliz
ed to
GL2
trea
ted
cells
s iSrf797
*
HuH7 day3
020406080
100120140160180
NT siSrf797
norm
aliz
ed to
GL2
trea
ted
cells
HuH7 day3
020406080
100120140160180
NT siSrf797
norm
aliz
ed to
GL2
trea
ted
cells
Results
63
In JHH6, SRF depletion did not substantially reduced the amount of S-phase cells as reported in
Fig.17:
Fig. 17: Cell cycle phase distribution.
Data are expressed as means ± SEM, n=4. NT=not treated cells.
Depletion of SRF did not substantially reduce the amount of S-phase cells compared to siGL2 treated cells.
To discriminate between cells in G1 or G0-phase of cell cycle, Ki67, an antigen expressed in
G1/S/G2/M phase cells, but not in G0 phase cells, was quantified by flowcitometry. As no major
variations in the amount of G0 phase cells was observed (data not shown), we deduced that the
G0/G1 increase was mainly due to a G1 increase.
JHH6 day3
020406080
100120140160180
NT siSrf797
norm
aliz
ed to
GL2
trea
ted
cells
JHH6 day3
020406080
100120140160180
NT siSrf797
norm
aliz
ed to
GL2
trea
ted
cells
Results
64
In JHH6 and HuH7 the depletion of the newly synthesized SRF form by siSRF797 was not
sufficient to induce a clear reduction in S-phase cells and in the total number of cells. Thus it
seems that the presence of the mature SRF form is sufficient to sustain cell proliferation. This
hypothesis implies that the levels of the SRF mature form in JHH6 and HuH7 are substantially
constant and poorly dependent on the amount of SRF newly synthesized form. This indirectly
means that the levels of SRF mature form are mostly independent from the stimulation of
physiological inducers, such as serum. In this sense it is interesting to note that in JHH6 and
HuH7 the levels of SRF mature form are substantially independent from serum stimulation, as
reported in a representative experiment in Fig.18A and fig. 18B and summarized in Fig.19. In
contrast, a clear dependence of the amount of SRF mature form to serum stimulation, is evident
in HepG2 and VSMC, undertaken as a normal control (Fig.18C and Fig. 18D). Moreover,
whereas the levels of newly synthesized SRF form depends on serum stimulation in HepG2, this
is only partially the case in JHH6 and not the case in HuH7.
Fig.18A: Time course of SRF protein in JHH6 cell line detected by immunoblotting.
GAPDH protein served as a loading control.
Fig.18B: Time course of SRF protein in HuH7 cell line detected by immunoblotting.
GAPDH protein served as a loading control.
GapdH
SRF mature form
SRF neo-synthesized form
T0 1h 2h 4h 8h 16h 20h 24h 32hA. JHH6
0.161 0.288 0.224 0.397 0.747 0.898 0.713 0.909 1.045
0.779 0.882 0.961 0.944 0.981 0.764 0.680 0.699 0.799
GapdH
SRF mature form
SRF neo-synthesized form
T0 1h 2h 4h 8h 16h 20h 24h 32hA. JHH6
0.161 0.288 0.224 0.397 0.747 0.898 0.713 0.909 1.045
0.779 0.882 0.961 0.944 0.981 0.764 0.680 0.699 0.799
GapdH
SRF mature form
SRF neo-synthesized form
T0 1h 2h 4h 8h 16h 20h 24h 32hB. HuH7
0.530
0.611
0.316
0.602
0.477
0.601
0.483
0.611
0.451
0.612
0.487
0.640
0.462
0.654
0.492
0.729
0.480
0.854
GapdH
SRF mature form
SRF neo-synthesized form
T0 1h 2h 4h 8h 16h 20h 24h 32hB. HuH7
0.530
0.611
0.316
0.602
0.477
0.601
0.483
0.611
0.451
0.612
0.487
0.640
0.462
0.654
0.492
0.729
0.480
0.854
Results
65
Fig.18C: Time course of SRF protein in HepG2 cell line detected by immunoblotting.
GAPDH protein served as a loading control.
Fig.18D: Time course of SRF protein in VSMC detected by immunoblotting.
GAPDH protein served as a loading control.
GapdH
SRF mature form
SRF neo-synthesized form
T0 1h 2h 4h 8h 16h 20h 24h 32hD. VSMC
0.530
0.181
0.416
0.434
0.477
0.581
0.483
0.511
0.491
0.622
0.527
0.560
0.562
0.744
0.592
0.737
0.430
0.681
GapdH
SRF mature form
SRF neo-synthesized form
T0 1h 2h 4h 8h 16h 20h 24h 32hD. VSMC
0.530
0.181
0.416
0.434
0.477
0.581
0.483
0.511
0.491
0.622
0.527
0.560
0.562
0.744
0.592
0.737
0.430
0.681
GapdH
SRF mature form
SRF neo-synthesized form
T0 1h 2h 4h 8h 16h 20h 24h 32hC. HepG2
0.465
0.117
1.569
0.286
1.004
0.831
0.749
1.018
0.367
0.749
0.330
0.894
0.384
0.617
0.680
0.410
0.861
0.404
GapdH
SRF mature form
SRF neo-synthesized form
T0 1h 2h 4h 8h 16h 20h 24h 32hC. HepG2
0.465
0.117
1.569
0.286
1.004
0.831
0.749
1.018
0.367
0.749
0.330
0.894
0.384
0.617
0.680
0.410
0.861
0.404
Results
66
Fig. 19: Time course of SRF protein.
Data are expressed as means ± SEM, n=3.
These data would suggest an increased stability of the mature form of SRF in JHH6 and HuH7.
For this reason, in a variation of protocol 1 (see Materials and Methods) JHH6 were double
transfected by siSRF797 at day 0 and at day 3, and the amount of total cells evaluated at day 6.
Also under this condition, no evident reduction in cell number was observed. Similar results
were obtained with HuH7 (Fig.20)
Fig. 20: siSRF797 effects on cell counting with modified transfection conditions;
data are expressed as means ± SEM, n=3; NT=not-treated cells.
SRF time course in JHH6
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
t0 1h 2h 4h 8h 16h 20h 24h 32h
norm
aliz
ed to
Gap
dH
SRF time course in JHH6
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
t0 1h 2h 4h 8h 16h 20h 24h 32h
norm
aliz
ed to
Gap
dH
Mature SRFNewly sinthesized SRFMature SRFNewly sinthesized SRF
SRF tine course in HuH7
0.0
0.2
0.4
0.6
0.8
1.0
1.2
t0 1h 2h 4h 8h 16h 20h 24h 32hno
rmal
ized
toG
apdH
SRF tine course in HuH7
0.0
0.2
0.4
0.6
0.8
1.0
1.2
t0 1h 2h 4h 8h 16h 20h 24h 32hno
rmal
ized
toG
apdH
SRF time course in HepG2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
t0 1h 2h 4h 8h 16h 20h 24h 32h
norm
aliz
ed to
Gap
dH
SRF time course in HepG2
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
t0 1h 2h 4h 8h 16h 20h 24h 32h
norm
aliz
ed to
Gap
dH
HuH7JHH6
Cell counting
020406080
100120140160180200
NT siSrf797 NT siSrf797
norm
aliz
ed to
GL2
trea
ted
cells
Normal transfection Double transfection
HuH7JHH6HuH7JHH6
Cell counting
020406080
100120140160180200
NT siSrf797 NT siSrf797
norm
aliz
ed to
GL2
trea
ted
cells
Normal transfection Double transfection
Results
67
7. Effects of SRF depletion on cell death.
The apoptotic potential of the selected siRNAs in the target cells was investigated by studying
the externalisation of phosphatidylserine (PS). In apoptotic cells, PS accumulates on the outer
part of the cellular membrane (Geske and Gerschenson, 2001) as a consequence of increased
externalisation from the inner part to outer part of the cellular membrane and decreased
internalisation. Thus, with a specific antibody direct against PS it is possible to detect the number
of apoptotic cells. To distinguish between early and late apoptotic cells, an additional staining
with propidium iodide (PI) is required. PI can penetrate the damaged cellular membrane of late
apoptotic cells (and stain DNA) but not the normal membrane of early apoptotic cells. Thus, cell
positive for both PI and PS staining, represent late apoptotic, cells positive for PS staining only,
represent early apoptotic cells, cells positive for PI only represent cell debris and cells negative
for both staining represent normal living cells.
As an additional test to confirm apotosis, Poly-ADPRibose-Polymerase (PARP) cleavage was
evaluated. In apoptotic cells, this DNA repair protein of 113kDa is cleaved into two fragments
by the caspases cascade. As this event is limited to apoptotic cells, it represents a reliable and
specific marker for apoptosis.
With regard to HepG2, SRF depletion resulted in an increase in the amount of apoptotic cells
(annexin V positive cells) two days after transfection as shown in a representative experiment in
Fig.21 and summarized in Fig.22 (* p<0.001):
Fig. 21: Effects of SRF depletion on cell apoptosis: the amounts of apoptotic HepG2 cells were determined two
days after transfection by annexin V and PI staining, followed by flow cytometry analysis. The percentage of
apoptotic cells is indicated in the two right quadrants. FITC-A: annexin V; PI-A: propidium iodide staining.
HepG2 treated by siGL2 HepG2 treated by siSRF797
1.2% 4.1%
HepG2 treated by siGL2 HepG2 treated by siSRF797
1.2% 4.1%
Results
68
Fig. 22: Annexin V positive cells two days after transfection. Data are expressed
as means ± SEM, n=4, (* p<0.001 compared to siGL2 treated cells). NT=not treated cells.
The pro-apoptotic effect was confirmed by the increased cleavage of the Poly-ADPRibose-
Polymerase (PARP) in siSRF-treated cells compared to controls (Fig. 23):
Fig. 23: PARP cleavage. GAPDH was used as loading control.
In HuH7 and JHH6, the depletion of the newly synthesized form of SRF did not result in an
increase of apoptotic cells compared to controls (Fig 24):
Fig. 24: Annexin V positive cells three days after transfection.
Data are expressed as means ± SEM, n=4. NT=not treated cells.
HepG2 day2
0
100
200
300
400
500
NT siSrf797
norm
aliz
ed to
GL2
trea
ted
cells
*
HepG2 day2
0
100
200
300
400
500
NT siSrf797
norm
aliz
ed to
GL2
trea
ted
cells
*
siGL2 siSRF797 NT
Cleaved PARP
GapdH
UncleavedPARP
siGL2 siSRF797 NT
Cleaved PARP
GapdH
UncleavedPARP
Apoptotic cells
0
50
100
150
200
250
NT siSrf 797
norm
aliz
ed to
GL2
trea
ted
cells
Apoptotic cells
0
50
100
150
200
250
NT siSrf 797
norm
aliz
ed to
GL2
trea
ted
cells
HuH7
JHH6
HuH7
JHH6
Results
69
Possible siRNA cytotoxic effects, either depending on the specific depletion of SRF or an
aspecific effect of siRNA transfection into the cells, were evaluated by measuring the activity of
lactate dehydrogenase (LDH). This enzyme is normally found in the cytosol of all cells but it is
rapidly released into the supernatant upon plasma membrane damage. As reported in Fig.25A, B
and C, no significant toxicity was observed in all treatments compared to not treated cells. As
positive control, triton treated cells were introduced.
Fig. 25: LDH test two or three days after transfection.
Data are expressed as means ± SEM, n=4. NT=not treated cells.
0
20
40
6080
100120
NT siGL2 siSrf 797 triton
HepG2 day2
norm
aliz
ed to
trit
ontr
eate
d ce
lls
A
0
20
40
6080
100120
NT siGL2 siSrf 797 triton
HepG2 day2
norm
aliz
ed to
trit
ontr
eate
d ce
lls
0
20
40
6080
100120
NT siGL2 siSrf 797 triton
HepG2 day2
norm
aliz
ed to
trit
ontr
eate
d ce
lls
A
0
2040
60
80100
120
NT siGL2 siSrf 797 triton
HuH7 day3
norm
aliz
ed to
trit
ontr
eate
d ce
lls
B
0
2040
60
80100
120
NT siGL2 siSrf 797 triton
HuH7 day3
norm
aliz
ed to
trit
ontr
eate
d ce
lls
B
0
20406080
100120
NT siGL2 siSrf 797 triton
JHH6 day3
norm
aliz
ed to
trit
ontr
eate
d ce
lls
C
0
20406080
100120
NT siGL2 siSrf 797 triton
JHH6 day3
norm
aliz
ed to
trit
ontr
eate
d ce
lls
C
Results
70
8. Effects of SRF depletion on other cell cycle regulators.
Upon treatment with siSRF797 we found some interestingly variations of other relevant cell
cycle genes, such as the transcription factor E2F1 and the G1/S cyclin E1.
The reduction of SRF total levels caused an evident decrease in E2F1 protein levels (60%, 70%
and 20% of reduction for HepG2, HuH7 and JJH6 respectively) as shown in a rapresentative blot
in Fig. 26A and summerised in Fig.26B; the decrease might be attributable to a post-
transcriptional effect in HuH7 and JHH6 since E2F1 transcript levels were not affected (Fig.27)..
In contrast, a transcriptional mechanism can be advocated for HepG2 where E2F1 mRNA level
was reduced compared to siGL2 treated cells (Fig.27).
Fig. 26A : Reduction of E2F1 protein by siSRF797 was detected by immunoblotting.
GAPDH protein served as a loading control.
Fig.26B: E2F1 protein levels.
Data are expressed as means ± SEM, n=3. NT=not treated cells.
GapdH
HepG2 day2 HuH7 day3 JHH6 day3
E2F1
siGL2
siSRF7
97
NT
siGL2
siSRF7
97
NT
siGL2
siSRF7
97
NT
GapdH
HepG2 day2 HuH7 day3 JHH6 day3
E2F1
siGL2
siSRF7
97
NT
siGL2
siSRF7
97
NT
siGL2
siSRF7
97
NT
HepG2HuH7JHH6
E2F1 protein levels
0
20
40
60
80
100
120
140
160
NT siSrf 797
norm
aliz
edto
GL2
tr
eate
d ce
lls HepG2HuH7JHH6
HepG2HuH7JHH6
E2F1 protein levels
0
20
40
60
80
100
120
140
160
NT siSrf 797
norm
aliz
edto
GL2
tr
eate
d ce
lls
Results
71
Fig.27: siSrf797-mediated indirect reduction of E2F1 transcript levels evaluated
by quantitative RT- PCR (data were normalized to 28S).
Data are expressed as means ± SEM, n=6. NT=not treated cells. (*p < 0.001).
In contrast to E2F1, no significant variations in the amount of the phosphorylated form of the
retinoblastoma protein pRb were observed (Fig.28).
Fig.28: Levels of the iperphosphorylated form of pRb;
data are expressed as means ± SEM, n=3. NT=not treated cells.
E2F1 mRNA levels
0
50
100
150
200
250
NT siSrf 797
HepG2HuH7JHH6
*
norm
aliz
edto
GL2
tr
eate
d ce
lls
E2F1 mRNA levels
0
50
100
150
200
250
NT siSrf 797
HepG2HuH7JHH6
*
norm
aliz
edto
GL2
tr
eate
d ce
lls
pRb levels
NT siSrf 797
0
20
40
60
80
100
120
140
norm
aliz
edto
GL2
tr
eate
d ce
lls HepG2HuH7JHH6
pRb levels
NT siSrf 797
0
20
40
60
80
100
120
140
norm
aliz
edto
GL2
tr
eate
d ce
lls HepG2HuH7JHH6
HepG2HuH7JHH6
Results
72
The depletion of SRF was paralleled by a clear increase in CyE1 protein levels in HepG2 cell
line but not in HuH7 and JHH6 (Fig. 29A and Fig. 29B).
Fig. 29A : Increase of cyclin E1 protein by siSRF797 was detected by immunoblotting.
GAPDH protein served as a loading control.
Fig.29B CyE1 protein levels.
Data are expressed as means ± SEM, n=3. NT=not treated cells.
siGL2
siSRF7
97
NT
GapdH
HepG2 day2 HuH7 day3 JHH6 day3
CyE1
siGL2
siSRF7
97
NT
siGL2
siSRF7
97
NT
siGL2
siSRF7
97
NT
GapdH
HepG2 day2 HuH7 day3 JHH6 day3
CyE1
siGL2
siSRF7
97
NT
siGL2
siSRF7
97
NT
CyE1 protein levels
0
50
100
150
200
250
300
NT siSrf 797
HepG2HuH7JHH6
norm
aliz
edto
GL2
tr
eate
d ce
lls
CyE1 protein levels
0
50
100
150
200
250
300
NT siSrf 797
HepG2HuH7JHH6
norm
aliz
edto
GL2
tr
eate
d ce
lls
Results
73
The increased CyE1 protein levels in HepG2 prompted us to evaluate whether this was a
transcriptionally or post-transcriptionally phenomenon. Compared to controls, a reduction of
CyE1 mRNA was observed (Fig.30).
Fig.30: Reduction of CyE1 transcript levels evaluated by quantitative RT-PCR
(data were normalized to 28S). Data are expressed as means ± SEM, n=6. NT=not treated cells.
Thus we draw our attention on the stability of CyE1 protein. Notably, the decrease of CyE1
mRNA, was consistent with the reduction of the major transcription factor, i.e. E2F1. Moreover,
no increase in the expresson level of LRH-1, an hepatic specific transcription factor for CyE1,
was observed (data not shown). Therefore, the phosphorylation status of CyE1 Thr395 residue
was investigated (phosphorylation at this site is required for proteasome-mediated degradation of
CyE1 and the extent of phosphorylation is directly proportional to the degradation rate) as
reported in a representative experiment (Fig.31A) and summarized in Fig.31B. A decrease in the
amount of phosphorylation on CyE1 Thr 395 residue was observed in Hepg2 compared to
controls. No evident variation were in contrast observed in HuH7 and JHH6 cell lines.
Fig. 31A: Reduction of P-Cyclin E1 by siSRF797 was detected by immunoblotting.
GAPDH protein served as a loading control.
CyE1 mRNA levels
0
50
100
150
200
250
300
NT siSrf 797
HepG2HuH7JHH6
*norm
aliz
edto
GL2
tr
eate
d ce
llsCyE1 mRNA levels
0
50
100
150
200
250
300
NT siSrf 797
HepG2HuH7JHH6
*norm
aliz
edto
GL2
tr
eate
d ce
lls
mRNA levelsRNA levels
NTsiGL2
siSRF7
97
GapdH
P-CyE (Thr395)
NTsiGL2
siSRF7
97
GapdH
P-CyE (Thr395)
HepG2 day2
mRNA levelsRNA levels
NTsiGL2
siSRF7
97
GapdH
P-CyE (Thr395)
NTsiGL2
siSRF7
97
GapdH
P-CyE (Thr395)
HepG2 day2
Results
74
Fig.31B: p-CyE1 protein levels;
data are expressed as means ± SEM, n=3. NT=not treated cells.
Finally no relevant variation in the expression levels of cyclin E2, cyclin D1, cyclin A, p27kip1,
p16INK4 and p21cip1 were observed (data not shown).
In conclusion, our data show the identification of an active siRNA directed against SRF able to
specifically and efficiently reduce the SRF mRNA in the hepatic cell line Hepg2, JHH6 and
HuH7. SRF mRNA depletion resulted in a significant inhibition of cell proliferation (reduction
in S-phase cells) and apoptosis induction in HepG2 but not in JHH6 and HuH7. This is most
likely due to the impossibility to deplete the mature SRF form in JHH6 and HUH7. In HepG2,
SRF depletion was paralleled by a decrease of E2F1 mRNA and protein levels, a fact which can
contribute to explain the down modulation of cell proliferation. Consistently with the E2F1
expression down regulation, cyclin E1 mRNA was also reduced; however, total cyclin E1 protein
levels were increased due to reduced phosphorylation at Thr395.
p-CyE1 protein levels
020406080
100120140160180
NT siSrf 797
HepG2HuH7JHH6
norm
aliz
edto
GL2
tr
eate
d ce
lls
p-CyE1 protein levels
020406080
100120140160180
NT siSrf 797
HepG2HuH7JHH6
HepG2HuH7JHH6
norm
aliz
edto
GL2
tr
eate
d ce
lls
Results
75
Depletion of CyE1, CyE2 and E2F1 in HCC cell lines
In the previous paraghraps, we have presented data about the possibility to control HCC cell
growth by the inhibition of SRF, a widely expressed transcription factor involved in cellular
development and proliferation. Only in the case of most differentiated HepG2 we could observe
a clear anti-proliferative and pro-apoptotic effect of the selected siSRF797. Thus, in an attempt
to find strategies able to down regulate the proliferation also of the less differentiated HCC cell
lines, such as HuH7 and JHH6, additional siRNAs targets, i.e. CyE1 and E2F1, were considered.
Therefore, siRNAs direct against the position 1415 of cyclin E1 mRNA (siCyE1-1415), the
position 647 of cyclin E2 mRNA (siCyE2-647) and the position 1324 of E2F1 mRNA (siE2F1-
1324) were used.
Suitable transfection systems were undertaken to test siCyE1-1415, siCyE2-647 and siE2F1-
1324 efficiency in HepG2, HuH7 and JHH6 cell lines. Non treated cells, and cells treated by a
control siRNA directed against the luciferase gene (siGL2), were analysed in parallel. Optimized
analysis times were two and three days after transfection for HepG2 and HuH7-JHH6,
respectively according to Protocol 2 (Materials and Methods).
In all reported histogram the data belonging to the three different cell lines and they are
normalized to the respective siGL2 control: this implies that it is not possible to compare the
reported values among the three different cell lines.
Results
76
9. siRNAs effects on CyE1, CyE2 and E2F1 mRNA and protein levels.
To investigate the specificity and the effects of siRNAs, siCyE1-1415, siCyE2-647 and siE2F1-
1324 were transfected into all HCC cell lines and the mRNA and protein levels of cyclin E1,
cyclin E2 and E2F1 evaluated.
Between two and three days after transfection, every specific siRNA was able to strongly reduce
the mRNA levels (* p<0.0001 and § p<0.005) of the respective target, compared to siGL2
treated cells (Fig.32).
Fig. 32: siRNA-mediated reduction of the respective target transcript levels by quantitative real time PCR
(data were normalized to 28S). Data are expressed as means ± SEM, n=6. NT=not treated cells.
(* p < 0.0001; § p < 0.05 compared to siGL2 treated cells).
In the reported histogram, as well as in the following, the data belonging to the three different cell lines are
normalized to the respective siGL2 control: this implies that it is not possible to compare the reported values
among the three different cell lines.
CyE1 mRNA levels
0
100
200
300
400
NT siCyE1 1415
* * §norm
aliz
ed to
GL2
trea
ted
cells
CyE1 mRNA levels
0
100
200
300
400
NT siCyE1 1415
* * §norm
aliz
ed to
GL2
trea
ted
cells
CyE2 mRNA levels
0
100
200
300
400
NT siCyE2 647
*§
*norm
aliz
ed to
GL2
trea
ted
cells
CyE2 mRNA levels
0
100
200
300
400
NT siCyE2 647
*§
*
CyE2 mRNA levels
0
100
200
300
400
NT siCyE2 647
*§
*norm
aliz
ed to
GL2
trea
ted
cells
E2F1 mRNA levels
0
40
80
120
160
NT siE2F1 1324
* § §
norm
aliz
ed to
GL2
trea
ted
cells
E2F1 mRNA levels
0
40
80
120
160
NT siE2F1 1324
* § §
norm
aliz
ed to
GL2
trea
ted
cells
Results
77
In all HCC cell lines, the decrease in mRNA upon transfection with the specific siRNA was
paralleled by a clear decrease in the respective protein levels as reported in a representative
experiment (Fig. 33a-c) and summarized in Fig 33d.
Fig. 33a: Reduction of endogenous cyclin E1 protein by siCyE1-1415 was detected by immunoblotting.
GAPDH protein served as a loading control.
Fig. 33b: Reduction of endogenous cyclin E2 protein by siCyE2-647 was detected by immunoblotting.
GAPDH protein served as a loading control.
Fig. 33c: Reduction of endogenous E2F1 protein by siE2F1-1324 was detected by immunoblotting.
GAPDH protein served as a loading control.
siGL2
siCyE
1-141
5
NT
GapdH
siGL2
siCyE
1-141
5
NT siGL2
siCyE
1-1415
NT
HepG2 day2
HuH7 day3
JHH6 day3
Cyclin E1
asiG
L2
siCyE
1-141
5
NT
GapdH
siGL2
siCyE
1-141
5
NT siGL2
siCyE
1-1415
NT
HepG2 day2
HuH7 day3
JHH6 day3
Cyclin E1
siGL2
siCyE
1-141
5
NT
GapdH
siGL2
siCyE
1-141
5
NT siGL2
siCyE
1-1415
NT
HepG2 day2
HuH7 day3
JHH6 day3
Cyclin E1
asiG
L2
siCyE
2-647
NT
GapdH
siGL2
siCyE
2-647
NT siGL2
siCyE
2-647
NT
HepG2 day2
HuH7 day3
JHH6 day3
Cyclin E2
b
siGL2
siCyE
2-647
NT
GapdH
siGL2
siCyE
2-647
NT siGL2
siCyE
2-647
NT
HepG2 day2
HuH7 day3
JHH6 day3
Cyclin E2
b
siGL2
siE2F
1 -1324
NT
GapdH
siGL2
siE2F
1-13
24
NT siGL2
siE2F
1-13
24
NT
HepG2 day2
HuH7 day3
JHH6 day3
E2F1
c
siGL2
siE2F
1 -1324
NT
GapdH
siGL2
siE2F
1-13
24
NT siGL2
siE2F
1-13
24
NT
HepG2 day2
HuH7 day3
JHH6 day3
E2F1
c
Results
78
Fig. 33d: CyE1, CyE2 and E2F1 protein levels;
data are expressed as means ± SEM, n=3. NT=not treated cells.
CyE1 protein levels
020406080
100120140160
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ted
cells
CyE1 protein levels
020406080
100120140160
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ted
cells
CyE2 protein levels
0
50
100
150
200
250
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
CyE2 protein levels
0
50
100
150
200
250
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
norm
aliz
ed to
GL2
trea
ted
cells
E2F1 protein levels
020406080
100120140160
NT siE2F1 1324
norm
aliz
ed to
GL2
trea
ted
cells
E2F1 protein levels
020406080
100120140160
NT siE2F1 1324
E2F1 protein levels
020406080
100120140160
NT siE2F1 1324
HepG2HuH7JHH6
HepG2HuH7JHH6
Results
79
10. Effects of CyE1, CyE2 and E2F1 depletion on cell morphology and cell-counting.
The morphology of HepG2, HUH7 and JHH6 cell lines upon siSRNA treatment is reported in
Fig.34, Fig.35 and Fig.36, respectively
HepG2
Fig. 34: siRNA effect on HepG2 morphology, two days after transfection.
Cell morphology was analysed by phase contrast microscopy
at 5x and 20x magnification. NT = not-treated cells.
NT
siGL2
siCyE1
siCyE2
siE2F1
5x 20x
100um
100um
NT
siGL2
siCyE1
siCyE2
siE2F1
5x 20x
NT
siGL2
siCyE1
siCyE2
siE2F1
5x 20x
100um
100um
Results
80
HuH7
Fig. 35: siRNA effect on HuH7 morphology, three days after transfection.
Cell morphology was analysed by phase contrast microscopy
at 5x and 20x magnification. NT = not-treated cells.
Whereas in HepG2 cell line, we observed that upon siRNAs treatment cells rounded up and
detached from plates (Fig.34), no major morphological variations were detected in HuH7 cell
line compard to controls (Fig.35).
NT
100um
siCyE2
100um
siGL2
100um
100um
100um
siCyE1
100um
100um
siE2F1
5x 20x
NT
100um
siCyE2
100um
siGL2
100um
100um
100um
siCyE1
100um
100um
siE2F1
NT
100um100um
siCyE2siCyE2
100um
siGL2
100um
siGL2
100um100um
100um
100um
siCyE1
100um
siCyE1
100um
100um
siE2F1
100um
siE2F1
5x 20x
Results
81
JHH6
Fig. 36: siRNA effect on JHH6 morphology, three days after transfection.
Cell morphology was analysed by phase contrast microscopy
at 5x and 20x magnification. NT = not-treated cells.
In the case of JHH6 cell line, we observed that transfected cells underwent a change in cell
shape: siSRF797 treated cells lost their elongated charachteristic shape and became more
poligonal (Fig.36). Finally, for all cell types a clear reduction in cell amount was observed upon
specific siRNA treatment.
siCyE1
siCyE2
siE2F1
siGL2
NT
5x 20x
100um
100um
100um
100um
siCyE1
siCyE2
siE2F1
siGL2
NT
5x 20x
100um100um
100um
100um100um
100um100um
Results
82
With regard to HepG2 and to HUH7, upon depletion of cyE1, CyE2 and E2F1, we observed a
clear reduction in cell number, paralleled by a reduction in colony areas, while the number of
colonies was maintened (Fig.37 and Fig.38).
Fig. 37: siRNAs effects on HepG2 cell line.
d. The amount of cell number was evaluated two days after transfection;
(*p<0.001 compared to siGL2 treated cells);
data are expressed as means ± SEM, n=4. NT=not treated cells.
e. Colonies area was evaluated two days after transfection
(*p<0.001compared to siGL2 teated cells);
data are expressed as means ± SEM, n=100. NT=not treated cells.
f. Colonies number was evaluated two days after transfection;
data are expressed as means ± SEM, n=100. NT=not treated cells
20
40
60
80
100
120
140
day1 day2 day3
% c
ell n
umbe
r nor
mal
ized
to
GL2
trea
ted
cells siGL2
siCyE1
siE2F1
siCyE2
a. HepG2 cell counting
*
20
40
60
80
100
120
140
day1 day2 day3
% c
ell n
umbe
r nor
mal
ized
to
GL2
trea
ted
cells siGL2
siCyE1
siE2F1
siCyE2
siGL2
siCyE1
siE2F1
siCyE2
a. HepG2 cell counting
*
05000
10000
1500020000
25000
3000035000
NT siCyE1 1415
siCyE2 647
siE2F1 1324
μm
squ
are
b. HepG2 colony areas, day2
***
05000
10000
1500020000
25000
3000035000
NT siCyE1 1415
siCyE2 647
siE2F1 1324
μm
squ
are
b. HepG2 colony areas, day2
***
01020304050607080
NT siCyE1 1415
siCyE2 647
siE2F1 1324
Num
bers
of c
olon
ies
c. HepG2 number of colonies, day2
01020304050607080
NT siCyE1 1415
siCyE2 647
siE2F1 1324
Num
bers
of c
olon
ies
c. HepG2 number of colonies, day2
Results
83
Fig. 38: siRNAs effects on HuH7 cell line.
a. The cell number was evaluated three days after transfection;
(*p<0.05 compared to siGL2 treated cells);
data are expressed as means ± SEM, n=4. NT=not treated cells.
d. Colonies area was evaluated three days after transfection
(*p<0.001 compared to siGL2 treated cells);
data are expressed as means ± SEM, n=100. NT=not treated cells .
e. Colonies number was evaluated three days after transfection;
data are expressed as means ± SEM, n=100. NT=not treated cells
0
20
40
60
80
100
120
day2 day3
a. HuH7 cell counting
siGL2
siCyE1
siE2F1
siCyE2
*
% c
ell n
umbe
r nor
mal
ized
to
GL2
trea
ted
cells
0
20
40
60
80
100
120
day2 day3
a. HuH7 cell counting
siGL2
siCyE1
siE2F1
siCyE2
siGL2
siCyE1
siE2F1
siCyE2
*
% c
ell n
umbe
r nor
mal
ized
to
GL2
trea
ted
cells
020004000600080001000012000
14000
NT siCyE1 1415
siCyE2 647
siE2F1 1324
b. HuH7 colony areas, day3
μm
squa
re
* **0
20004000600080001000012000
14000
NT siCyE1 1415
siCyE2 647
siE2F1 1324
b. HuH7 colony areas, day3
μm
squa
re
* **0
5
10
15
20
25
NT siCyE1 1415
siCyE2 647
siE2F1 1324
c. HuH7 number of colonies, day3
Num
bers
of c
olon
ies
0
5
10
15
20
25
NT siCyE1 1415
siCyE2 647
siE2F1 1324
c. HuH7 number of colonies, day3
Num
bers
of c
olon
ies
Results
84
Also in the case of JHH6 cell number, upon depletion of cyE1, CyE2 and E2F1, we observe a
clear reduction in cell number (Fig.39).
No data in terms of the areas and number of colonies were available as JHH6 do not grow in
colonies.
Fig. 39: siRNAs effects on JHH6 cell line: an evident reduction in cell number compared to siGL2 treated cells
was observed three days after transfection; data are expressed as means ± SEM, n=5;
(*p<0.05 compared to siGL2 treated cells).
0
20
40
60
80
100
120
day1 day2 day3
% c
ell n
umbe
r nor
mal
ized
toG
L2tre
ated
cells
a. JHH6 cell counting
siGL2
siCyE1
siE2F1
siCyE2*
0
20
40
60
80
100
120
day1 day2 day3
% c
ell n
umbe
r nor
mal
ized
toG
L2tre
ated
cells
a. JHH6 cell counting
siGL2
siCyE1
siE2F1
siCyE2
siGL2
siCyE1
siE2F1
siCyE2*
Results
85
11. Effects of CyE1, CyE2 and E2F1 depletion on cell cycle phase distribution.
Cell cycle phase distribution was determined by double DNA staining technique as previously
described.
SiRNAs treatment affected cell cycle phase distribution of HepG2 cell line by reducing S-phase
cell by about 20% (* p<0.05) compared to siGL2 treated cells, as shown in a representative
experiment in Fig.40 and summarized in Fig.41. This phenomenon was paralleled by a tendency
to an increase in G0/G1 cells.
Fig.40: A representative dot plot of HepG2 is shown.
A:siGl2 treated cells; B:siSCyE2-647 treated cells.
Q1: S-phase cells
Q2/Q4: G2/M phase cells
Q3: G1/G0 phase cells.
PI-A: Propidium Iodide; FITC-H: FITC labelled Ig anti BrdU.
22.2% 6.5%
24.5%46.8%
15.2% 5.1%
21.7%58.1%
HepG2 treated by siGL2 HepG2 treated by siCyE2-647A B
22.2% 6.5%
24.5%46.8%
15.2% 5.1%
21.7%58.1%
HepG2 treated by siGL2 HepG2 treated by siCyE2-647A B
Results
86
Fig.41: Cell cycle phase distribution.
Data are expressed as means ± SEM, n=4.
Depletion of CyE1, CyE2 and E2F1 diminished the S-phase cells by about 20%
compared to siGL2 treated cells (*p<0.05). NT=not treated cells.
This decrease is followed by a tendency of increase in G0/G1 phase cells.
As regard with HUH7, the data reported in a representative experiment (Fig.42) and below
summarized (Fig.43) demonstrated that three days after transfection, CyE1, CyE2 and E2F1
depletion induced an evident decrease of S-phase cells and an accumulation of cells in G0/G1
phases compared to siGL2 treated cells (*p<0.05; §p<0.001).
Fig.42: A representative dot plot of HuH7 is shown.
G1/G0
SG2/MG1/G0G1/G0
SG2/MG2/M
HepG2 day 2
0
20
40
60
80
100
120
140
NT siCyE11415
siE2F11324
siCyE2647
norm
aliz
ed to
GL2
trea
ted
cells *
G1/G0
SG2/MG1/G0G1/G0
SG2/MG2/M
HepG2 day 2
0
20
40
60
80
100
120
140
NT siCyE11415
siE2F11324
siCyE2647
norm
aliz
ed to
GL2
trea
ted
cells *
50.4% 26.5%
1.9%21.2%
HuH7 treated by siGL2A
16.5% 25.7%
12.9%45.0%
HuH7 treated by siCyE1-1415B
50.4% 26.5%
1.9%21.2%
HuH7 treated by siGL2A
50.4% 26.5%
1.9%21.2%
HuH7 treated by siGL2A
16.5% 25.7%
12.9%45.0%
HuH7 treated by siCyE1-1415B
Results
87
Fig.43: Cell cycle phase distribution.
Data are expressed as means ± SEM, n=4.
Depletion of CyE1, CyE2 and E2F1 diminished the S-phase cells from 40% to 80%
compared to siGL2 treated cells (*p<0.05; §p<0.001). NT=not treated cells.
This decrease is followed by a tendency of increase in G0/G1 phase cells.
Similar result were obtained also for JHH6 : in siRNA treated cells, it was evident the decrease
of S-phase cells which is paralleled by a tendency to increase in G0/G1 phases compared to
siGL2 treated cells (*p<0.05), as summarized in Fig.44.
Fig.44: Cell cycle phase distribution.
Data are expressed as means ± SEM, n=4.
Depletion of CyE1, CyE2 and E2F1 diminished the S-phase cells from 40% to 60%
compared to siGL2 treated cells (*p<0.05). NT=not treated cells.
This decrease is followed by a tendency of increase in G0/G1 phase cells.
HUH7 day3
020406080
100120140160180
NT siCyE11415
siE2F11324
siCyE2647
norm
aliz
ed to
GL2
trea
ted
cells
**§
HUH7 day3
020406080
100120140160180
NT siCyE11415
siE2F11324
siCyE2647
norm
aliz
ed to
GL2
trea
ted
cells
**§
G1/G0
SG2/MG1/G0G1/G0
SG2/MG2/M
JHH6 day3
020406080
100120140160180
norm
aliz
ed to
GL2
trea
ted
cells
NT siCyE11415
siE2F11324
siCyE2647
***
JHH6 day3
020406080
100120140160180
norm
aliz
ed to
GL2
trea
ted
cells
NT siCyE11415
siE2F11324
siCyE2647
***
Results
88
Finally, no significant variations in the amount of G0 cells was observed (as evaluated by Ki67
staining –data not shown-). This indicate that the slightly increase in G1/G0-phase cells was due
to an increase of G1-phase cells.
12. Effects of CyE1, CyE2 and E2F1 depletion on cell death.
Apoptosis was first investigated by means of annexin V assay. Cells were collected and stained
by fluorescein labelled antibody against annexin V and by Propidium Iodide (PI) and then
analyzed by flow cytometry.
With regard to HepG2, two days after transfection we observed that siRNAs treated cells shrank,
rounded up and detached from plates (as previously shown in Fig.34), suggesting apoptosis had
occurred. This increase in the rate of apoptosis is shown in a representative experiment (Fig.45)
and summarized in Fig.46 (*p<0.05).
Fig. 45: Effects of E2F1 depletion on cell apoptosis: the amounts of apoptotic HepG2 cells were determined two
days after transfection by annexin V and propidium iodide staining, followed by flow cytometry analysis.
The percentage of apoptotic cells is indicated in the two right quadrants.
FITC-A: annexin V; PI-A: propidium iodide staining.
HepG2 treated by siGL2
1.2%
HepG2 treated by siE2F1-1324
4.2%
HepG2 treated by siGL2
1.2%
HepG2 treated by siE2F1-1324
4.2%
Results
89
Fig. 46: Annexin V positive cells two days after transfection.
Data are expressed as means ± SEM, n=4. (*p<0.05 compared to siGL2 treated cells). NT=not treated cells.
These data were confirmed by PARP cleavage which showed the appearance of the cleaved form
of PARP in siRNAs treated cells compared to controls, as summarized in Fig.47.
Fig. 47: Amount of PARP cleavage expressed as ratio between the uncleved form of PARP ant the uncleaved one.
HepG2 day2
050
100150200250300350400450500
NT siCyE1 1415
siCyE2647
siE2F1 1324
norm
aliz
ed to
GL2
trea
ted
cells *
**
HepG2 day2
050
100150200250300350400450500
NT siCyE1 1415
siCyE2647
siE2F1 1324
norm
aliz
ed to
GL2
trea
ted
cells *
**
HepG2 PARP cleavage
0.0
1.0
2.0
3.0
4.0
5.0
6.0
NT siGL2 siCyE1 1415
siCyE2 647
siE2F1 1324
Unc
leav
ed P
AR
P/c
leav
ed P
AR
P
HepG2 PARP cleavage
0.0
1.0
2.0
3.0
4.0
5.0
6.0
NT siGL2 siCyE1 1415
siCyE2 647
siE2F1 1324
Unc
leav
ed P
AR
P/c
leav
ed P
AR
P
Results
90
No increased apoptosis was observed for HuH7 and JHH6 cell lines (Fig.48).
Fig. 48: Annexin V positive cells three days after transfection.
Data are expressed as means ± SEM, n=4. NT=not treated cells.
Finally, no significant cytotoxicity was observed in siRNAs treated cells compared to controls as
evaluated by LDH test (Fig.49).
Fig. 49: LDH test two or three days after transfection.
Data are expressed as means ± SEM, n=4. NT=not treated cells.
Triton treated cells were introduced as positive control.
Apoptotic cells
0
20
40
60
80
100
120
140
160
NT siCyE1 1415
siCyE2 647
siE2F1 1324
norm
aliz
ed to
GL2
trea
ted
cells
HUH7JHH6
Apoptotic cells
0
20
40
60
80
100
120
140
160
NT siCyE1 1415
siCyE2 647
siE2F1 1324
norm
aliz
ed to
GL2
trea
ted
cells
HUH7JHH6
HepG2 day2
0
20
40
60
80
100
120
NT siGL2 siCyE11415
siE2F11324
siCyE2647
triton
norm
aliz
ed to
trit
ontr
eate
d ce
lls
A HepG2 day2
0
20
40
60
80
100
120
NT siGL2 siCyE11415
siE2F11324
siCyE2647
triton
norm
aliz
ed to
trit
ontr
eate
d ce
lls
A
HUH7 day3
norm
aliz
ed to
trit
ontr
eate
d ce
lls
B
0
20
40
60
80
100
120
NT siGL2 siCyE11415
siE2F11324
siCyE2647
triton
HUH7 day3
norm
aliz
ed to
trit
ontr
eate
d ce
lls
B
0
20
40
60
80
100
120
NT siGL2 siCyE11415
siE2F11324
siCyE2647
triton
JHH6 day3
0
20
40
60
80
100
120
NT siGL2 siCyE11415
siE2F11324
siCyE2647
triton
C
norm
aliz
ed to
trit
ontr
eate
d ce
lls
JHH6 day3
0
20
40
60
80
100
120
NT siGL2 siCyE11415
siE2F11324
siCyE2647
triton
C
norm
aliz
ed to
trit
ontr
eate
d ce
lls
Results
91
13. Effects of CyE1, CyE2 and E2F1 depletion on cell cycle regulators.
The decrease of S-phase cells and the accumulation of cells in G0/G1 phases induced by siCyE1-
1415, syCyE2-647 and siE2F1-1324, prompted us to evaluate the effects of CyE1, CyE2 or E2F1
depletion on some mediators of the G1/S cell cycle phases.
In all HCC cell lines, depletion of CyE1 causes a consistent decrease of E2F1 protein levels as
shown in a representative blot in Fig.50A and summarized in Fig.50B. this decrease in protein
levels is paralleled by a decrease in mRNA (* p<0.05; § p<0.001) levels as indicated in Fig.51.
Fig. 50A : Reduction of E2F1 protein by siCyE1-1415 was detected by immunoblotting.
GAPDH protein served as a loading control.
Fig. 50B: E2F1 protein levels following siCyE1-1415 transfection;
data are expressed as means ± SEM, n=3. NT=not treated cells
siGL2
siCyE
1-141
5
NT
GapdH
siGL2
siCyE
1-141
5
NT siGL2
siCyE
1-1415
NT
HepG2 day2
HuH7 day3
JHH6 day3
E2F1
siGL2
siCyE
1-141
5
NT
GapdH
siGL2
siCyE
1-141
5
NT siGL2
siCyE
1-1415
NT
HepG2 day2
HuH7 day3
JHH6 day3
E2F1
E2F1 protein levels
020406080
100120140160
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ed c
ells
HepG2
HuH7JHH6
E2F1 protein levels
020406080
100120140160
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ed c
ells
HepG2
HuH7JHH6
HepG2
HuH7JHH6
Results
92
Fig. 51: siRNA-mediated reduction of E2F1 transcript levels by quantitative RT- PCR
(data were normalized to 28S). Data are expressed as means ± SEM, n=6.
NT=not treated cells. (*p <0.05; §p <0.001 compared to siGL2 treated cells).
This data confirm the strong correlation between these two cell cycle promoting proteins also in
this model cell lines of HCC (Fig.52).
Fig. 52: E2F1/pRb-Cye1 correlation
E2F1 mRNA levels
020406080
100120140160
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ed c
ells
§ * *HepG2
HuH7JHH6
E2F1 mRNA levels
020406080
100120140160
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ed c
ells
§ * *HepG2
HuH7JHH6
HepG2
HuH7JHH6
Cyclin E
Cyclin E gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE
DPE2F/DPinactive
E2F1pRb
PpRb
pre-E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
Cyclin E1
Cyclin E1 gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE1
DPE2F/DPinactive
E2F1pRb
PpRb
-initiationcomplex
E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
E2F1/DPactive
E2F1/DPactive
DPDP
E2F1
Cyclin E
Cyclin E gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE
DPE2F/DPinactive
E2F1pRb
PpRb
pre-E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
Cyclin E1
Cyclin E1 gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE1
DPE2F/DPinactive
E2F1pRb
PpRb
-initiationcomplex
E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
E2F1/DPactive
E2F1/DPactive
E2F1/DPactive
E2F1/DPactive
DPDPDPDP
E2F1E2F1
Results
93
In all HCC cell lines, the depletion of CyE2 causes a consistent decrease of E2F1 protein and
mRNA levels (*p <0.05) (Fig. 53A and B and Fig.54).
Fig. 53A : Reduction of E2F1 protein by siCyE2-647 was detected by immunoblotting.
GAPDH protein served as a loading control.
Fig. 53B: E2F1 protein levels following siCyE2-647 transfection;
data are expressed as means ± SEM, n=3. NT=not treated cells.
Fig.54: siRNA-mediated reduction of E2F1 transcript levels by quantitative RT- PCR
(data were normalized to 28S). Data are expressed as means ± SEM, n=6.
NT=not treated cells. (*p <0.05 compared to siGL2 treated cells).
siGL2
siCyE
2 -647
NTGapdH
siGL2
siCyE
2 -647
NT siGL2
siCyE
2 -647
NT
HepG2 day2
HuH7 day3
JHH6 day3
E2F1
siGL2
siCyE
2 -647
NTGapdH
siGL2
siCyE
2 -647
NT siGL2
siCyE
2 -647
NT
HepG2 day2
HuH7 day3
JHH6 day3
E2F1
E2F1 protein levels
020406080
100120140160
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells HepG2
HuH7JHH6
E2F1 protein levels
020406080
100120140160
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
E2F1 protein levels
020406080
100120140160
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells HepG2
HuH7JHH6
HepG2
HuH7JHH6
E2F1 mRNA levels
020406080
100120140160
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
*HepG2
HuH7JHH6
* *
E2F1 mRNA levels
020406080
100120140160
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
*HepG2
HuH7JHH6
HepG2
HuH7JHH6
* *
Results
94
These data suggest that CyE2 could have the same role and functions of CyE1 in the HCC cell
lines considered (Fig.55).
Fig. 55: E2F1/pRb-Cye2 hypothesis of correlation.
The results of these experiments, driven us through another question: what’s happens to
CyE1/CyE2 protein and mRNA levels when E2F1 is knocked down?
In all HCC cell lines, the depletion of E2F1 caused an evident decrease in CyE1 mRNA levels (*
p<0.05; § p<0.001), in accordance with the established role of E2F1 in promoting cyclin E1
expression (Fig.56b). Only in HuH7 cell line, the decrease in mRNA levels was paralleled by a
decrease in protein levels (Fig.56a).
Fig. 56: a. CyE1 protein levels following siE2F1-1324 transfection;
data are expressed as means ± SEM, n=3. NT=not treated cells.
b. siRNA-mediated reduction of CyE1 transcript levels by quantitative RT- PCR
(data were normalized to 28S). Data are expressed as means ± SEM, n=6.
NT=not treated cells. (*p <0.05; §p <0.001 compared to siGL2 treated cells).
Cyclin E
Cyclin E gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE
DPE2F/DPinactive
E2F1pRb
PpRb
pre-E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
Cyclin E2
Cyclin E2 gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE2
DPE2F/DPinactive
E2F1pRb
PpRb
-initiationcomplex
E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
E2F1/DPactive
E2F1/DPactive
DPDP
E2F1
?Cyclin E
Cyclin E gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE
DPE2F/DPinactive
E2F1pRb
PpRb
pre-E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
Cyclin E2
Cyclin E2 gene
phosphorylation of pRB by
cdk2/cyclin E
P
cdk 2
CyclinE2
DPE2F/DPinactive
E2F1pRb
PpRb
-initiationcomplex
E2F1
Cyclin EmRNA
cdk 2,4
Cyclin D
DP
E2F1/DPactive
E2F1/DPactive
E2F1/DPactive
E2F1/DPactive
DPDPDPDP
E2F1E2F1
?
a. CyE1 protein levels
0
50
100
150
200
250
300
NT siE2F1 1324
norm
aliz
ed to
GL2
trea
ted
cells
a. CyE1 protein levels
0
50
100
150
200
250
300
NT siE2F1 1324
norm
aliz
ed to
GL2
trea
ted
cells
b. CyE1 mRNA levels
050
100150200250300350400
NT siE2F1 1324
§ * *norm
aliz
ed to
GL2
trea
ted
cells
b. CyE1 mRNA levels
050
100150200250300350400
NT siE2F1 1324
§ * *norm
aliz
ed to
GL2
trea
ted
cells Hepg2
HUH7
JHH6
Hepg2
HUH7
JHH6
Results
95
This reduction was not observed in HepG2 and JHH6.
The increased CyE1 protein levels with a reduced mRNA amount, implies that an increased
stability of the proteins may occur. In this regard, in HepG2, it is possible to observe a reduced
phosphorylation of CyE1 Thr395 residue, a known target for proteasome-mediated degradation
(Fig.57).
Fig. 57: Reduction of p-CyE (Thr395) upon siE2F1-1324 tratment was detected by immunoblotting.
GAPDH protein served as a loading control.
In the case of JHH6, no variations in the Thr395 residue were observed (data not shown); this
does not exclude that another phosphorylation site involved in protein degradation could have
been hypophosphorilated.
Upon E2F1 depletion, we observed a clear reduction of cyclin E2 mRNA levels compared to
siGL2 treated cells (*p <0.05) (Fig.58b), indicating the role of E2F1 in promoting cyclin E2
expression in the HCC cell lines considered. In this case, the decrease in mRNA levels was
paralleled by a clear and a more moderate decrease in protein levels in JHH6 cell line, and in
HepG2-HuH7 cell line, respectively (Fig.58a).
Fig. 58a: CyE2 protein levels following siE2F1-1324 transfection;
data are expressed as means ± SEM, n=3. NT=not treated cells.
HepG2 cell line
GapdHP-CyE (Thr395)
NTsiGL2
siE2F
113
24
HepG2 cell line
GapdHP-CyE (Thr395)
NTsiGL2
siE2F
113
24
GapdHP-CyE (Thr395)
NTsiGL2
siE2F
113
24
NTsiGL2
siE2F
113
24
NT siE2F1 1324
a. CyE2 protein levels
0
50
100
150
200
250
norm
aliz
ed to
GL2
trea
ted
cells
NT siE2F1 1324
a. CyE2 protein levels
0
50
100
150
200
250
norm
aliz
ed to
GL2
trea
ted
cells
Hepg2
HUH7
JHH6
Hepg2
HUH7
JHH6
Results
96
Fig. 58b: siRNA-mediated reduction of CyE2 transcript levels by quantitative RT- PCR
(data were normalized to 28S). Data are expressed as means ± SEM, n=6.
NT=not treated cells. (*p <0.05 compared to siGL2 treated cells).
In addition to induce a decrease of E2F1 expression, depletion of CyE1 caused also a reduction
in CyE2 mRNA levels in HuH7 and JHH6 cell lines. Less evident was the effect on the protein
levels. No major differences were observed in HepG2 cell line (Fig.59a and b).
Fig. 59: a. CyE2 protein levels following siCyE1-1415 transfection;
data are expressed as means ± SEM, n=3. NT=not treated cells.
b. siRNA-mediated reduction of CyE2 transcript levels by quantitative RT- PCR
(data were normalized to 28S). Data are expressed as means ± SEM, n=6.
NT=not treated cells. (*p <0.05 compared to siGL2 treated cells ).
b. CyE2 mRNA levels
0
100
200
300
400
500
NT siE2F1 1324
* * *norm
aliz
ed to
GL2
trea
ted
cells
b. CyE2 mRNA levels
0
100
200
300
400
500
NT siE2F1 1324
* * *norm
aliz
ed to
GL2
trea
ted
cells
Hepg2
HUH7
JHH6
Hepg2
HUH7
JHH6
a. CyE2 protein levels
0
50
100
150
200
250
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ted
cells
a. CyE2 protein levels
0
50
100
150
200
250
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ted
cells
b. CyE2 mRNA levels
0
100
200
300
400
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ted
cells
* *
b. CyE2 mRNA levels
0
100
200
300
400
NT siCyE1 1415
norm
aliz
ed to
GL2
trea
ted
cells
* *
Hepg2
HUH7
JHH6
Hepg2
HUH7
JHH6
Results
97
Cyclin E2 depletion did not affect the mRNA levels of CyE1 (Fig.60).
Fig. 60: siRNA-mediated reduction of CyE1 transcript levels by quantitative RT- PCR
(data were normalized to 28S).
Data are expressed as means ± SEM, n=6. NT=not treated cells.
This finding was somewhat surprising if we considered the fact that E2F1, the major cyclin E1
transcription factor, was down regulated. In the liver, another cyclin E1 trenscripttion is known,
i.e. LRH. We therefore studied the expression level of this gene in the hypothesis it could be
upregulated to take over cyclin E1 transcritpion in place of E2F1. Unexpectedly, no increase in
the expresson level of LRH-1 was observed (Fig.61).
Fig. 61: siRNA-mediated reduction of LRH-1 transcript levels by quantitative RT- PCR
(data were normalized to 28S).
Data are expressed as means ± SEM, n=6. NT=not treated cells..
CyE1 mRNA levels
050
100150200250300350400
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
CyE1 mRNA levels
050
100150200250300350400
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
LRH mRNA levels
0
50
100
150
200
250
NT siCyE2 647
hepG2huh7JHH6
LRH mRNA levels
0
50
100
150
200
250
NT siCyE2 647
hepG2huh7JHH6
Hepg2
HUH7
JHH6
Hepg2
HUH7
JHH6
Results
98
In contrast, an increase of cyclin E1 protein levels were observed (Fig.62).
Fig. 62. CyE1 protein levels following siCyE2-647 transfection;
data are expressed as means ± SEM, n=3. NT=not treated cells.
This result prompted us to investigate a possible increase in stability of cyclin E1 protein,
verifying the reduction in the phosphorylation of CyE1 Thr395 residue in HepG2 by Western
Blot analysis (Fig.63).
Fig. 63: Reduction of p-CyE (Thr395) by siCyE2-647 was detected by immunoblotting.
GAPDH protein served as a loading control.
With regard to HuH7 and JHH6, no variation was detected on Thr395 residue (data not shown).
HepG2 cell line
GapdHP-CyE (Thr395)
NTsiGL2
siCyE
267
4
HepG2 cell line
GapdHP-CyE (Thr395)
NTsiGL2
siCyE
267
4
CyE1 protein levels
050
100150200250300350400450
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
CyE1 protein levels
050
100150200250300350400450
NT siCyE2 647
norm
aliz
ed to
GL2
trea
ted
cells
Hepg2
HUH7
JHH6
Hepg2
HUH7
JHH6
Results
99
With regard to other cell cycle related genes, we did not observe any change in the
phosphorylation status of pRb and in cyclin A protein levels (data not shown). On the other
hand, some variations were observed for cyclin D1 protein and mRNA levels (Fig.64a and b).
The depletion of cyclin E1 caused an increase in cyclin D1 protein levels, paralleled by an
increase in mRNA levels in JHH6. In HuH7 this effect was more evident at the mRNA level,
while no clear variation were observed for HepG2.
The depletion of cyclin E2 caused a certain decrease in cyclin D1 protein levels, paralleled by a
decrease in mRNA levels. No substantially differences in cyclin D1 expression were observed in
siE2F1-1324 treated cells compared to controls.
Fig. 64: a. CyD1 protein levels following siRNAs transfection;
data are expressed as means ± SEM, n=3. NT=not treated cells.
b. CyD1 transcript levels by quantitative RT- PCR (data were normalized to 28S).
Data are expressed as means ± SEM, n=6. NT=not treated cells.
(*p <0.05 compared to siGL2 treated cells).
a. CyD1 protein levels
0
100200300400
500
600700
800
norm
aliz
ed to
GL2
trea
ted
cells
NT siCyE1 1415
siCyE2 647
siE2F1 1324
a. CyD1 protein levels
0
100200300400
500
600700
800
norm
aliz
ed to
GL2
trea
ted
cells
NT siCyE1 1415
siCyE2 647
siE2F1 1324
Hepg2
HUH7
JHH6
Hepg2
HUH7
JHH6
0
b. CyD1 mRNA levels
50100150200250300350400450
norm
aliz
ed to
GL2
trea
ted
cells
NT siCyE1 1415
siCyE2 647
siE2F1 1324
*
*
0
b. CyD1 mRNA levels
50100150200250300350400450
norm
aliz
ed to
GL2
trea
ted
cells
NT siCyE1 1415
siCyE2 647
siE2F1 1324
*
*
Results
100
Moreover, whereas no major variations in mRNA levels of the CDK inhibitors p27kip1 were
observed, an increase of p21cip1 was detected in HuH7 and JHH6 cell line following the depletion
of cyclin E1 (Fig 65a and b).
Fig. 65: a. p27kip1 transcript levels by quantitative RT- PCR (data were normalized to 28S).
Data are expressed as means ± SEM, n=6. NT=not treated cells.
b. p21cip1 transcript levels by quantitative RT- PCR (data were normalized to 28S).
Data are expressed as means ± SEM, n=6. NT=not treated cells.
In conclusion, we have identified siRNAs targeted against pivotal cell cycle controlling genes,
i.e. cyclin E1, cyclin E2 and E2F1, which are able to efficiently down modulate the expansion of
the HCC cell lines here considered. Whereas in HepG2 the mechanism is sustained by both
apoptosis induction and inhibition of cell proliferation, in HuH7 and JHH6 inhibition of cell
proliferation is predominant. The interrelation between cyclin E1, E2 and E2F1 have been also
investigated: the data are summarized in tab 3.
a. p27kip1 mRNA levels
0
50
100
150
200
250
300
350
400
norm
aliz
ed to
GL2
trea
ted
cells
NT siCyE1 1415
siCyE2 647
siE2F1 1324
norm
aliz
ed to
GL2
trea
ted
cells
b. p21cip1 mRNA levels
0
100
200
300
400
500
600
NT siCyE1 1415
siCyE2 647
siE2F1 1324
a. p27kip1 mRNA levels
0
50
100
150
200
250
300
350
400
norm
aliz
ed to
GL2
trea
ted
cells
NT siCyE1 1415
siCyE2 647
siE2F1 1324
norm
aliz
ed to
GL2
trea
ted
cells
b. p21cip1 mRNA levels
0
100
200
300
400
500
600
NT siCyE1 1415
siCyE2 647
siE2F1 1324
b. p21cip1 mRNA levels
0
100
200
300
400
500
600
NT siCyE1 1415
siCyE2 647
siE2F1 1324
Hepg2
HUH7
JHH6
Hepg2
HUH7
JHH6
Results
101
To summarize:
Table 3: Protein and mRNA levels of cell cycle related genes upon siRNAs transfection.
siE2F1-1324
siCyE2-647
siCyE1-1415
E2F1CyE2CyE1siRNA
treatment
=
= = =
HepG2
HuH7
JHH6
mRNA LEVELS
siE2F1-1324
siCyE2-647
siCyE1-1415
E2F1CyE2CyE1siRNA
treatment
=
= = =
HepG2
HuH7
JHH6
mRNA LEVELS
siE2F1-1324
siCyE2-647
siCyE1-1415
E2F1CyE2CyE1siRNA treatment
= ==
= =
PROTEIN LEVELS
HepG2
HuH7
JHH6
siE2F1-1324
siCyE2-647
siCyE1-1415
E2F1CyE2CyE1siRNA treatment
= ==
= =
PROTEIN LEVELS
HepG2
HuH7
JHH6
Results
102
Depletion of SRF in VSMC
Anti-proliferative drugs released from endo-vascular stents have substantially contributed to
reduce in-stent restenosis rates in patients bearing coronary single primary lesions by down
regulating VSMC growth. However, the considerably lower drug efficacy shown in the treatment
of patients bearing more complex coronary lesions and in diabetic patients, suggests that
alternative anti-proliferative approaches can be beneficial. Here, we explored the use of siRNAs
as tools to knock down SRF, a transcription factor involved in the proliferation of different cell
types and for which only limited data exist about its function in primary human VSMCs.
Suitable transfection systems were undertaken to test siSRF797 effects in vascular smooth
muscle cells (VSMC). If not otherwise indicated, protocol 2 has been chosen as transfection
protocol (see materials and methods).
Non treated cells and cells treated by a control siRNA directed against the luciferase gene
(siGL2), were analysed in parallel. Optimal analysis time was found to be three days after
transfection.
14. siSRF797 effects on SRF mRNA and protein levels.
To test the activity of siSRF797, it was transfected into VSMC, previously kept under starving
conditions for 48 hours. Three days after transfection, a clear reduction (p<0.001) in the amount
of SRF mRNA was observed in cells transfected by siSRF797, compared to siGL2 treated cells
(Fig.66).
Fig. 66: siRNA-mediated reduction of SRF transcript levels evaluated by quantitative real time PCR
(data were normalized to 28S). Data are expressed as means ± SEM, n=6. NT=not treated cells.
*p < 0.001 compared to siGL2 treated cells.
SRF mRNA levels
020406080
100120
140160
NT siSRF797
norm
aliz
ed to
GL2
trea
ted
cells
*
SRF mRNA levels
020406080
100120
140160
NT siSRF797
norm
aliz
ed to
GL2
trea
ted
cells
*
Results
103
The decrease in SRF mRNA levels was paralleled by a strong decrease in SRF protein as
reported in a representative experiment (Fig. 67a) and summarized in Fig 67b. In contrast to
what revealed in the HCC cell lines JHH6 and HuH7, a clear reduction of both the mature and
the newly synthesized form of SRF was observed.
Fig. 67a: Reduction of endogenous SRF protein by siSRF797 was detected by immunoblotting.
GAPDH protein served as a loading control.
Fig. 67b: : SRF protein levels;
data are expressed as means ± SEM, n=3. NT=not treated cells.
SRF protein levels
0
20
40
60
80
100
120
NT siSRF797
norm
aliz
ed to
GL2
trea
ted
cells
SRF protein levels
0
20
40
60
80
100
120
NT siSRF797
norm
aliz
ed to
GL2
trea
ted
cells
s iGL2
siSRF7
97
NTGapdH
SRF mature form
SRF neo-synthesized form
siGL2
siSRF7
97
NTGapdH
SRF mature form
SRF neo-synthesized form
Results
104
15. Effects of SRF depletion on cell morphology and cell-counting.
SiSRF797 treatement significantly reduced VSMC number, without affecting significantly cell
morphology, as reported in Fig.68.
VSMC
Fig. 68: Effect of SRF depletion by siSRF797 on VSMC morphology, three days after transfection.
Cell morphology was analysed by phase contrast microscopy
at 5x and 20x magnification. NT = not-treated cells.
100 μm
100 μm
100 μm
100 μm
siGL2
NT
100 μm
siSRF797
5x 20x
100 μm
100 μm
100 μm
100 μm
100 μm
100 μm100 μm
100 μm100 μm
100 μm100 μm
100 μm100 μm
siGL2
NT
100 μm
siSRF797
5x 20x
100 μm
Results
105
Compared to control cultures, SRF-depleted VSMC showed a substantially lower confluence
three days after transfection (Fig.68), which was accompanied by a significant decrease in cell
number according to cell counting (*p<0.05) (Fig.69). Thus, SRF depletion impairs VSMC
expansion.
Fig. 69: siSRF797 effects on VSMC: a reduction in cell number compared to not-treated cells (NT) and to siGL2
treated cells was observed three days after transfection (*p<0.05 compared to siGL2 treated cells);
data are expressed as means ± SEM, n=5. NT=not treated cells.
a. Cell counting
siSRF797siGL2NT
0
20
40
60
80
100
120
140
160
day1 day2 day3
% c
ell n
umbe
r no
rmal
ized
toG
L2tr
eate
d ce
lls
*
a. Cell counting
siSRF797siGL2NT
0
20
40
60
80
100
120
140
160
day1 day2 day3
% c
ell n
umbe
r no
rmal
ized
toG
L2tr
eate
d ce
lls
*
Results
106
16. Effects of SRF depletion on cell cycle phase distribution.
For cell cycle analysis, cells were incubated for 12 hours with BrdU and then stained by PI and
FITC-conjugated anti-BrdU antibody as described for HCC cell lines.
SiSRF797 treatment caused a significant decrease of S-phase cells compared to untreated or
control siGL2 treated cells (*p<0.05) as reported in a representative experiment in Fig.70a and
summarized in Fig.70b; concomitantly, the fraction of G0/G1 cells rose approximately 20%
(*p<0.05).
Fig. 70a: A representative dot plot of VSMC is shown:
Q1: S-phase cells; Q2/Q4: G2/M phase cells; Q3: G1/G0 phase cells.
PI-A: Propidium Iodide; BrdU FITC-H: FITC labelled Ig anti BrdU.
Fig. 70b: Cell cycle phase distribution.
Data are expressed as means ± SEM, n=8. NT=not treated cells.
Three days after transfection, depletion of SRF diminished the S-phase cells by 40%
compared to siGL2 treated cells (*p<0.05).
This decrease is followed by a tendency of increase in G0/G1 phase cells (*p<0.05).
VS MC treated by siSRF797
12.8%
8.0%
21.6%
57.6%
VS MC treated by siGL2
8.1% 8.8%
11.2%71.1%
VS MC treated by siSRF797
12.8%
8.0%
21.6%
57.6%
VS MC treated by siGL2
8.1% 8.8%
11.2%71.1%
Cell cycle phases distribution
0
20
40
60
80
100
120
140
NT siSRF797
norm
aliz
ed to
GL2
trea
ted
cells
S
G2/M
G1/G0*
*
Cell cycle phases distribution
0
20
40
60
80
100
120
140
NT siSRF797
norm
aliz
ed to
GL2
trea
ted
cells
S
G2/M
G1/G0*
*
Results
107
To discriminate between cells in G1 or G0-phase of the cell cycle, Ki67 was tested: no
significant variations in the amount of G0 cells was observed, indicating that the slightly increase
in G1/G0-phase cells was due to an increase of G1-phase cells.
Thus, all these data suggest that SRF impairs VSMC proliferation and that SRF contributes to
the G1-S phase transition in VSMC.
In contrast to these results, recently, it has been observed that stable depletion of SRF in rat
VSMC resulted in an increase of cell proliferation upon PDGF-ββ or low serum (10%)
stimulation. To investigate this point in our experimental set-up, human VSMC were stimulated
by PDGF-ββ or low serum (10%) as described (Kaplan-Albuquerque et al., 2005) and cell
proliferation evaluated by BrdU incorporation. As a result of this experiment, we could show
that also after PDGF-ββ/low serum (10%) stimulation, the depletion of SRF resulted in a
decrease of cell proliferation (*p<0.05) (Fig.71).
Fig. 71: Data are expressed as means ± SEM, n=4. NT=not treated cells.
Three days after transfection, depletion of SRF inhibited cell proliferation also after
PDGF-ββ/low serum stimulation compared to siGL2 treated cells (*p<0.05).
siSrf797 and PDGF -ββ /low serum stimulation
0
20
40
60
80
100
120
NT+PDGF-ββ
siSRF797+PDGF -ββ
NT+10% siero
siSRF797+10% siero
norm
aliz
ed to
GL2
trea
ted
cells
**
siSrf797 and PDGF -ββ /low serum stimulation
0
20
40
60
80
100
120
NT+PDGF-ββ
siSRF797+PDGF -ββ
NT+10% siero
siSRF797+10% siero
norm
aliz
ed to
GL2
trea
ted
cells
**
Results
108
The very early onset of VSMC proliferation in restenotic lesions and the possible presence of
pre-existing proliferating CSMCs in atherosclerotic plaques, implicates that, in vivo, variable
amounts of VSMCs may be proliferating when the therapeutic drug is applied. As it is not
possible to precisely reproduce this situation in cultured cells, we decided to evaluate the
proliferation inhibitory effects of our siRNA under the two possible extreme conditions. In the
first case siRNA were administered to actively growing cells (proliferating cells protcoll x) while
in the second case cells were starved and then treated with siRNA and foetal calf serum at the
same time (re-proliferating cells, protocol x). Proliferation inhibition efficacies were measured
evaluating siRNA abilities to alter cell cycle phase distribution.
(Fig.72).
Fig. 72: Cell cycle phase distribution.
Data are expressed as means ± SEM, n=4. NT=not treated cells.
Three days after transfection, depletion of SRF diminished the S-phase cells by 40% also in proliferating cells
(*p<0.05 compared to siGL2 treated cells).
This decrease is followed by a tendency of increase in G0/G1 phase cells (*p<0.05).
Cell cycle phases
0
20
40
60
80
100
120
140
NT siSRF797norm
aliz
ed to
GL2
trea
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cells
S
G2/M
G1/G0*
*
Protocol 1 t reated cells
Cell cycle phases
0
20
40
60
80
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140
NT siSRF797norm
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S
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*
Protocol 1 t reated cells
Cell cycle phases
0
20
40
60
80
100
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140
NT siSRF797norm
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S
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G1/G0*
*
Protocol 1 t reated cells
Results
109
The experiments so far presented were performed in condition of normal glucose concentration
(5.5mmol/l). However, VSMC hyperproliferation is a patho-fisiological event that frequently
occurring in diabetic patients, i.e. in condition of high blood glucose (22mmol/l) (Zanetti et al.,
2008). Thus, to understand whether our approach may potentially be effective also in diabetic
patients, siSRF797 antiproliferative effect was tested in conditions of high glucose (see Materials
and Methods).
Fig. 73: Cell cycle phase distribution.
Data are expressed as means ± SEM, n=2. NT=not treated cells.
Three days after transfection, depletion of SRF diminished the S-phase cells by 30%
(*p<0.05 compared to siGL2 treated cells) also in conditions of high glucose (HG).
As indicated in Fig.73 a significant reduction of S-phase cell (*p>0.05) was observed also in
VSMC cultured in high glucose condition.
Cell cycle phases
0
20
40
60
80
100
120
140
NT siSRF797
norm
aliz
ed to
GL2
trea
ted
cells
S
G2/M
G1/G0
HG
*
Cell cycle phases
0
20
40
60
80
100
120
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NT siSRF797
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S
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G1/G0
HG
*
Results
110
17. Effects of SRF depletion on cell death.
The apoptotic potential of the SRF depletion was investigated three days after transfection. Cells
were collected and stained by fluorescein labelled antibody against annexin V and by Propidium
Iodide (PI) and then analyzed by flow cytometry. Reported is a representative experiment
showing similar amounts of apoptotic cells in siSRF797 treated cells compared to control siGL2
treated cells (Fig.74).
Fig. 74: Effects of SRF depletion on cell apoptosis: the amounts of apoptotic VSMC were determined three days
after transfection by annexin V and propidium iodide staining, followed by flow cytometry analysis. The percentage
of apoptotic cells is indicated in the two right quadrants.
Citotoxicity was evaluated by LDH test. As reported in Fig.75, no substantial differences were
detected among siSRF797 treated cells and the controls. As positive control, triton treated cells
were introduced.
Fig. 75: LDH test three days after transfection.
Data are expressed as means ± SEM, n=4. NT=not treated cells.
siGL2siSRF797
1.9% 2.2%
siGL2siSRF797
1.9% 2.2%
siGL2siSRF797
1.9% 2.2%
VS MC day3
NT siGL2 siSRF797 triton0
20
40
6080
100120
norm
aliz
ed to
trit
ontr
eate
d ce
lls
VS MC day3
NT siGL2 siSRF797 triton0
20
40
6080
100120
norm
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trit
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d ce
lls
Results
111
18. Effects of SRF depletion on cell cycle regulators.
At the molecular level, SRF depletion caused an increase of the CDK2 inhibitor p27kip1 (25%).
Moreover, a decrease in the hyperphosphorylated form of pRb (P-pRb) and in the S/G2/M cyclin
A of 45% and 40%, respectively were observed. Representative blots are reported in Fig.76a
and summarized in Fig.76b.
Fig. 76a: Increase of p27kip1, reduction of P-pRb and cyclin A upon SRF depletion.
GAPDH protein served as a loading control.
Fig. 76b: pRb, CyA and p27kip1 levels;
data are expressed as means ± SEM, n=3. NT=not treated cells.
p27siG
L2
siSRF7
97
NT
GapdH
p27siG
L2
siSRF7
97
NT
GapdH
p27siG
L2
siSRF7
97
NT
GapdH
siGL2
siSRF7
97
NT
GapdH
siGL2
siSRF7
97
NT
CyA
GapdH
siGL2
siSRF7
97
NT
CyA
GapdH
siGL2
siSRF7
97
NT
CyA
GapdH
P-pRb
GapdH
siGL2
siSRF7
97
NT
P-pRb
GapdH
siGL2
siSRF7
97
NT
norm
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ed to
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trea
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cells
P-pRb
CyAp27
0
20
40
60
80
100
120
140P-pRb, CyA and p27kip1 levels
NT siSRF797
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trea
ted
cells
P-pRb
CyAp27
0
20
40
60
80
100
120
140P-pRb, CyA and p27kip1 levels
NT siSRF797
Results
112
The increased of p27kip1 might be attributable to a post-transcriptional effect since p27kip1
transcript levels were not affected by transfection with siSRF797 (Fig.76c).
Fig. 76c: p27kip1 transcript levels evaluated by quantitative real time PCR (data were normalized to 28S).
Data are expressed as means ± SEM, n=6. NT=not treated cells.
Additionally, we did not observe any changes in the protein and transcript levels of the CDK4
inhibitor p16INK4, the CDK2 inhibitor p21cip1, the pRb partner protein E2F1, the G1 cyclin D1
and the G1/S cyclin E1 and E2 (Fig.77a and b).
Fig. 77a: Protein levels of different cell cycle related genes;
data are expressed as means ± SEM, n=3. NT=not treated cells.
p27kip1 mRNA
0204060
80100120140
NT siSRF797
norm
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ed to
GL2
trea
ted
cells
p27kip1 mRNA
0204060
80100120140
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cells
Protein levels
0
20
40
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160
p16 p21 CyD1 CyE1 CyE2 E2F1
norm
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ed to
GL2
trea
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cells
Protein levels
0
20
40
60
80
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120
140
160
p16 p21 CyD1 CyE1 CyE2 E2F1
norm
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ed to
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trea
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cells
Results
113
Fig. 77b: mRNA levels of different cell cycle related genes evaluated by
quantitative real time PCR (data were normalized to 28S).
Data are expressed as means ± SEM, n=6. NT=not treated cells.
Since cyclin A, but not cyclin D1, cyclin E1 or cyclin E2 protein levels were affected by
siSRF797, a SRF knock-down probably arrest VSMC cell cycle late in G1.
In conclusion, our results show that SRF is crucially involved in the control of human primary
VSMC proliferation which complements the well-established role of SRF in VSMC
differentiation and demonstrates the important role of SRF in human primary VSMCs.
Moreover, the possibility to down modulate VSMC growth in condition of high glucose
potentially makes our approach attractive also for the treatment of diabetic patients. At the
molecular level, SRF depletion is paralleled by an increase in the protein levels of p27, a
decrease of the phosphorylated form of p-RB and of cyclinA1. These observation well correlate
with the S-phase reduction and G1-G0 increase induced by SRF depletion in VSMC.
mRNA levels
020406080
100120140160180
p21 CyD1 CyE1 CyE2 E2F1
norm
aliz
ed to
GL2
trea
ted
cells
mRNA levels
020406080
100120140160180
p21 CyD1 CyE1 CyE2 E2F1
norm
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ed to
GL2
trea
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cells
Discussion
114
DISCUSSION
Exuberant and non-controlled cellular proliferation underlines the ethio-pathogenesis of many
human pathological conditions, including tumour and non-tumour diseases. Thus, the possibility
to control this complex process can be extremely useful in terms of prevention/control of disease
progression, especially in the light of the limited efficacy of current therapeutic approaches. In
this project we draw our attention on the down regulation of cell proliferation in the context of
two human diseases, namely hepatocellular carcinoma (HCC), as an example of tumour
pathology and in stent- restenosis, example of non-tumour pathology. Beside the obvious
advantages deriving from the prevention of cell growth in these two pathological conditions, we
thought interesting the comparison between the mechanisms regulating the growth of tumour vs
non tumour cells.
1. Hepatocellular carcinoma data
HCC is a leading cause of cancer death world-wide, with an estimated 564,000 new cases and
almost as many deaths in 2000 (Thorgeirsson and Grisham, 2002). There is no clinically tested
useful therapy for the advanced stage of the disease and any effective treatment has not been
assessed in large controlled randomized trials for this kind of hyper-vascular and chemotherapy-
resistant tumor. Thus, the development of novel effective therapeutic approaches are of utmost
relevance.
Our strategy to prevent HCC development is based on the inhibition of tumour cell proliferation
targeting the transcription factors SRF and E2F1 and cyclins E1 and E2 by means of siRNAs,
short double stranded RNA molecules able to induce the specific degradation of a homologue
mRNA (Scherr et al., 2003).
1.1 Effects of SRF depletion on HCC cell lines.
The transcription factor SRF has been considered as target in this work because of its
involvement in the control of the expression of proliferation-related genes in many primary cell
types. Furthermore, SRF has been recently shown to be directly implicated in the proliferation of
the HCC cell line HepG2 (Shao et al., 2005). Additional evidence of SRF relation to HCC
growth has been provided evaluating its expression in human specimens of HCC (Park et al.,
2007). As a result of this analysis it was found that SRF is expressed in HCC tissue but not in
Discussion
115
normal/cirrhotic liver. Even more interestingly, over-expression of SRF was reported in high
grade, poorly differentiated, HCC forms. These observation together with the absolute lack of
any published data about the investigation about a direct depletion of SRF in HCC cell lines,
prompted us to generate a specific siRNA anti SRF and test its effect in three HCC cell lines, i.e.
HepG2, HuH7 and JHH6. The choice of these cell lines was based on the fact that, although they
all are HCC tumor-derived cells, they display different phenotypes and thus phenotypic-related
effects of SRF depletion can be studied. In particular, HepG2, HuH7 and JHH6 can be assigned
to high, medium and low hepatocytic differentiation grade on the base of the capacity to
synthesize albumin, a known marker of hepatic differentiation (Grassi et al., 2007). It should be
noted that JHH6, the most undifferentiated cells, although not able to synthesize albumin (data
not shown) can still produce ferritin, indicating a residual hepatic phenotype (data not shown).
The selected siSRF797 is able to drastically reduce the amount of SRF mRNA in all three cell
line tested (Fig.6) compared to the control siGL2 and non treated cells. This observation
demonstrates the potent and sequence specific action of siSRF797. The specificity of action is
further strengthened by the fact that siSRF797 does not elicit any significant expression of the
gene AOS, a known marker of an a-specific IFN response (Fig.5) which double stranded RNAs
may trigger (Bridge et al., 2003). Consistently with the reduction of the mRNA levels, also the
total SRF protein levels are reduced in all cell lines (Fig.7). However, whereas in HepG2 both
the mature (67 kDa) and newly synthesized (63 kDa) SRF form are reduced, in JHH6 and HuH7
only the newly synthesized form is clearly reduced. The reasons for this behavior are unclear. A
possibility is that in JHH6-HuH7 the mature form is more stable than in HepG2. Consistent with
this anomalous behavior of SRF mature form there is the observation (Fig.18A and B) that in
JHH6 and HuH7 SFR protein levels of the mature form are substantially independent from
serum stimulation, in contrasts to what occurs in HepG2, and other differentiated cells such as
vascular smooth muscle cells (Fig.18C and D) and in fibroblasts (Misra et al., 1991). The fact
that in the more differentiated HepG2 cell line but not in the less differentiated JHH6-HuH7,
SRF protein forms seem to be regulated in a physiologically fashion, indicates a phenotypic
dependent regulation of SRF. It is possible that in more aggressive and less differentiated cells,
stable levels of the mature form of SRF confers and advantage in terms of tumor expansion. This
hypothesis is in agreement with the very recent observation (Park et al., 2007) that SRF is more
abundant in high grade poorly differentiated human HCC tumors. Notably, in this HCC type,
SRF increased cell migration and invasion probably providing HCC and advantage in terms of
diffusion and expansion.
Discussion
116
Despite the possibility to only reduce the protein levels of the newly synthesised form of SRF by
siSRF797 in JHH6 and HuH7, a significant reduction of the total SRF protein levels were
achieved compared to controls (Fig.7). Therefore, the examination of the effects of SRF down
regulation were conducted also in JHH6 and HuH7, in addition to HepG2.
In HepG2 cell line siSRF797 transfection resulted in a clear reduction in cell number (Fig.11)
paralleled by a concomitant decrease of colony areas but not colony number. This observation
suggest a cyto-static rather than a cyto-toxic effect as also supported by the fact that no
significant elevation of LDH enzymes were observed in treated cells compared to controls
(Fig.25). Consistently with the above observation, SRF depletion resulted in a cell cycle down
modulation (Fig.14 and Fig.15) with a reduction of S-phase cells. It is worth noting that a similar
behaviour was observed in VSMC (Fig.70), suggesting a similar mechanism of action for SRF in
these two cell type, albeit for what concern the effects on cell cycle.
SRF depletion in HepG2 is not limited to the down modulation of proliferation, it also induces
apoptosis (Fig.21-23). This phenomenon, seems to be more contained than cell proliferation
inhibition. Whereas the total amount of apoptotic cells rises only up to 4-5% , the decrease in the
amount of S-phase cells corresponds to about 20%. Despite this observation, the biological
meaning of apoptosis induction should not be underscored. It may represent the response to the
confounding effects resulting from outside (serum stimulation) and inside (SRF depletion) the
cell. This may indicate a certain capacity of a physiological response of this HCC cell line to
confounding signals, a property typically lacking in poorly differentiated tumour cells which in
contrast display high resistance towards apoptosis. Notably, apoptosis induction does not seems
to be specific for SRF depletion as we (Fig.46 and Fig.47) and other (Li et al., 2003) have
observed that also upon cyclin E and E2F1 depletion apoptosis is induced in HepG2.
In contrast to what observed for HepG2, in JHH6 and HuH7 transfection by siSRF797 neither
induced a significant reduction in cell number nor significantly affected cell cycle progression
and apoptosis rate. These observation may be due to different factors. First, SRF may not be
essential to promote proliferation in poorly differentiated HCC cells such as JHH6 and HuH7, in
contrast to what occur in the more differentiated HepG2 and the fully differentiated VSMC (see
also next paragraph). It is therefore possible that in JHH6 and HuH7 the SRF control on cell
proliferation is bypassed by alternative pathways. This hypothesis, however, would contradict
the observation of the relevant role exerted by SRF in the development of high grade, poorly
differentiated HCC forms (Park et al., 2007). Second, the reduction of total SRF protein levels,
although being evident in our experiments, may not be sufficient to abrogate SRF biological
functions. Our difficulties to deplete SRF total protein amount may be due to an increased SRF
Discussion
117
stability in JHH6 and HuH7. To explore this aspect, siSRF797 was transfected in JHH6-HuH7
twice (protocol 1, transfection at day 0 and 3 and analysis at day 6) instead of only once
(protocol 1, transfection at day 0 and analysis at day 3) as done for all the experiments above
commented. Disappointingly, also under these conditions of a more prolonged siSRF797 action,
no significant decrease in cell number, a parameter taken to indirectly evaluate SRF depletion,
was observed. This experiment is in favour of an high stability of SRF mature form in JHH6 and
HuH7. Probably, only by means of an expression vector stably producing the siSRF797 within
the cells it is possible to properly deplete SRF in these HCC cell lines (work in progress). It
should be noted that we were unable to perform more that two consecutive siSRF797
transfection because of the a-specific transfection-induced cell toxicity. A third possible
explanation for the lack of any clear biological effect of siSRF7979 in JHH6 and HuH7 may
reside in the biological role of the mature and newly synthesised SRF forms. It is not possible to
exclude that, as in fibroblasts (Misra et al., 1991), the biologically active form is the mature one
while the newly synthesised form gradually acquire this ability during the post-trabscriptional
modification (mostly phosphorilation). Whether this is the case also in JHH6 and HuH7 remains
to be determined.
In HepG2, consistent with the reduction of S-phase cells upon siSRF797 treatment, we observed
a clear reduction in the protein level of the transcription factor E2F1 (Fig.26), a relevant
promoter of the G1 to S phase transition. This reduction seems to be regulated at the
transcription level as the E2F1 mRNA is significantly reduced (Fig.27). Since no SRF binding
sites are known on the E2F1 promoter, the down modulation of E2F1 transcription is likely to be
an indirect cause of SRF depletion. Furthermore, the fact that in VSMCs the down modulation of
SRF does not results in an appreciable reduction of E2F1 levels (see also next paragraph)
suggests a cell specific effect. Further analysis (DNA array) will be performed to clarify this
aspect. Consistently with the reduction of E2F1 expression, also the mRNA levels of cyclin E1,
one of E2F1 transcriptional target gene, are significantly reduced (Fig.30). Notably, however,
whereas the mRNA levels decrease, cyclin E1 protein levels are increased (Fig.29) suggesting an
increased protein stability. This hypothesis is confirmed by the reduced cyclin E1
phosphorylation at residues Thr 395, a site whose phosphorylation is known to drive cyclin E1
degradation (Hwang and Clurman, 2005). The increased cylin E1 protein levels together with the
un-altered protein levels of cyclin D1 and cyclin A, all cyclins concurring to phosphorylate the
retinoblastoma protein, are consistent with the presence in SRF depleted cells of an hyper
phosphrylation status of p-RB (Fig.28) similar to control. These observation, together with the
substantially non modified protein levels of the cell cycle inhibitors p27, p21 and p16, suggest,
Discussion
118
in HepG2, a mechanism of reduced G1-S phase transition upon SRF depletion mediated by the
decrease of E2F1. Despite being unbound to pRB, which is in its hyper-phosphorylated form like
control, E2F1 is probably not quantitatively adequate to properly promote the transcription of all
or a part of its target genes. Obviously, other mechanisms cannot be excluded. In this sense,
DNA array will certainly contribute to further understand this aspect.
In contrast to HepG2, in JHH6 no substantial variation in both protein and mRNA levels of E2F1
were observed (Fig.26 and Fig.27), consistently with the lack of any evident reduction of the G1-
S phase transition. As above discussed, it is possible that the permanence of the mature form of
SRF prevents the down regulation of E2F1. In HuH7, a reduction of E2F1 protein levels
comparable to HepG2 is observed (Fig.26). However, in contrast to HepG2, the down regulation
is post-transcriptional as E2F1 mRNA levels are un-affected (Fig.27). Despite this difference, it
remains unclear why the reduction of E2F1 does not result in a reduced G1-S phase transition,
especially in the light of the fact that a direct targeting of E2F1 by an siRNA in HuH7 (see next
paragraph) does result in a delayed G1-S phase transition. The only difference we observe is that
upon SRF depletion in HuH7 a decrease of E2F1 but not of cyclin E1 occurs while the direct
depletion of E2F1 is also accompanied by a marked cyclin E1 decrease (Fig.56). It is therefore
possible that in this last case the reduced cyclin E1 level cannot absolve its role in sustaining
DNA synthesis (Zhang, 2007; Hwang and Clurman, 2005) thus impairing proliferation.
In conclusion, our data show the identification of an active siRNA directed against SRF able to
specifically and efficiently reduce the SRF mRNA in the hepatic cell line HepG2, JHH6 and
HuH7. SRF mRNA depletion resulted in a significant inhibition of cell proliferation and
apoptosis induction in HepG2 but not in JHH6 and HuH7. Thus, the different phenotypes of the
cell line considered, hepatocyte-like for HepG2, intermediately differentiated for HuH7 and
undifferentiated and JHH6, respectively, play a relevant role in the response siSRF797 treatment.
This implies that in vivo not all HCC forms may respond similarly to a siSRF797 treatment.
Despite this fact, we have shown for the first time the involvement of SRF in hepatic cell
proliferation, expanding the cell types in which SRF is implicated in cell proliferation. These
results can pave the way to a better understanding of SRF involvement in cell proliferation and
possibly to identify novel effective anti HCC therapeutic strategies.
Discussion
119
1.2 Effects of E2F1, Cyclin E1/2 depletion on HCC cell lines.
Whereas in HepG2 siSRF797 was able to reduce cell expansion by decreasing cell proliferation
and increasing apoptotic rate, in the less differentiated HCC cell line JHH6 and HuH7 the effect
was far less evident if not absent. Thus, with the aim to identify siRNAs also able to down
modulate the expansion of less differentiated HCC cells, siRNAs directed against cyclin E1,
cyclin E2 and the transcription factor E2F1 were generated and tested in vitro. Cyclin E1 is an
ideal candidate to be suppressed for an anti HCC strategy as it is over-expressed in about 70% of
HCC patients (Jung et al., 2001) and this over-expression correlates with a poor prognosis.
Moreover, cyclinE1 over-expression was found to be stronger in high grade HCC (II and III
according to Edmondson classification) compared to low grade (I) (Zhu et al., 2003; Zhou et al.,
2003) and it was significantly more elevated that in HCC surrounding cirrhotic tissues (Masaki
et al., 2003). Consistent to HCC in humans, also in mice models cyclin E1 has been shown to be
over-expressed (Mauriz et al., 2007). Additionally, preliminary observations (Li et al., 2003)
indicate that in the HCC cell line HepG2 cell lines over-expressing cyclin E, the inhibition of this
gene results in the prevention of cell growth. For the HCC forms with no cyclin E1 over-
expression, the inhibition of cyclin E alone does not seem to be sufficient to prevent tumour cell
proliferation (Li et al., 2003). To try to down modulate cell cycle progression in these HCC cells
and to potentate it in HCC over-expressing cyclin E, we propose the knock out also of the
transcription factor E2F1. The inhibition of E2F1 was chosen because of its strict biological
connection to cyclin E1 as evidenced by the existence of a feed-forward loop between them
amplifying the G1 to S phase promoting signals (Geng et al., 1996). Additionally, E2F1 has been
recently implicated in the development of HCC in vitro (Arakawa et al., 2004) and in animal
models (Coulouarn et al., 2006; Pascale et al., 2002; Conner et al., 2000). Finally, as it is
becoming evident the role of the second member of the cyclin E family, i.e. cyclin E2, in the
E2F1-cyclin E1 pathway, also cyclin E2 was considered as target in our research. The suitability
of the specific destruction of E2F1 and cyclin E1/2 mRNAs by means of siRNAs, also depends
on the fact that these genes are regulated at the mRNA and protein levels in a cell cycle-
dependent manner. This means that they are synthesized de novo at each new G1 phase and then
rapidly degraded at the protein and mRNA level with the progression of the cell cycle so that no
active protein and mRNA is left for the next cycle.
The selected siRNAs are able to drastically reduce the amount of their target mRNAs (* p<0.05)
in all the three cell line tested (Fig.32) compared to the control siGL2 and non-treated cells. This
observation demonstrates the potent and sequence specific action of the selected siRNAs. The
specificity of action is further strengthened by the fact that they do not elicit any significant
Discussion
120
expression of the gene AOS, a known marker of an a-specific IFN response (Fig.5) which double
stranded RNAs may trigger (Bridge et al., 2003). Finally, the lack of any detectable citotoxicity
as evaluated by LDH test (Fig.49), supports the safeties of the considered siRNAs and of the
transfection protocol.
In general, in all the three cell lines, the siRNA against cyclin E1 significantly decreases the
amount of cell number by decreasing proliferation via the reduction of S-phase cells and a
certain increase of G1 cells (Fig.41, Fig.43 and Fig.44). In HepG2 however, the siRNA directed
against cyclin E1 (siCyE1-1415) only modestly reduces S-phase cells (Fig.41). This observation
is qualitatively in agreement with a previous observation (Li 2003) but differs from the
quantitative point of view as the extent of S phase cell reduction upon cyclin E1 depletion is
much less evident. We can exclude that the siRNA we used has lower efficacy in inducing cyclin
E1 depletion as comparable degrees of cyclin E1 protein reduction can be observed with Li’s
siRNA (compare Fig.33a with Fig.1B Li 2003). Most likely, this discrepancy depends on some
biological differences between our and Li’s HepG2 strain. This hypothesis seems to be supported
by the fact that our preliminary results (data not shown) indicate a similar behaviour of Li’s
siRNA when tested in our HepG2 strain. Despite this partial discrepancy, our and Li’s data
support the concept that cyclin E1 targeting by siRNA may have the potential to prevent HCC
cell growth. Moreover, our data expand this concept to the far less differentiated HCC cells
JHH6. This observation is particularly relevant in the light of the strong cyclin E1 expression in
high grade HCC types (Zhu et al., 2003; Zhou et al., 2003). Thus, here we provide evidence for
the broad HCC therapeutic potential of anti cyclin E1 siRNAs.
Compared to siCyE1, the E2F1 directed siRNA (siE2F1-1324) resulted to have even broader
proliferation inhibition effects as it could significantly reduce the amount of S-phase cells in all
three HCC cell lines tested (Fig.41, Fig.43 and Fig.44). In HepG2, our data are in agreement
with a previous work (Simile et al., 2004) where the down modulation of E2F1 mRNA
expression was achieved by an antisense oligodeoxy nucleotide. However, in this case the extent
of HepG2 proliferation inhibition was more evident that in our case. Beside the fact that the
partial discrepancy may arise from minor differences between the HepG2 strain used and the fact
Simile et al used an ODN (10 μM) and we an siRNA (0,22 μM), it is possible that a technical
step accounts for the quantitative difference. Whereas Simile et al used cell synchronized in low
serum, we have used a-synchronized growing cells. Compared to synchronized cells, a-
synchronized cells have a lower amount of G1 phase cells and an increased S or G2-M cells and
are therefore more refractory to siE2F1. In fact, siE2F1 action can only be exerted in G1 phase
when the target gene E2F1 is expressed, while in the subsequent cell cycle phases the lack of the
Discussion
121
target gene renders siE2F1 action impossible. In support of this hypothesis there is the
observation that depletion of E2F1 in synchronized vascular smooth muscle cells by an
hammerhead ribozyme (Grassi et al., 2005b) and an siRNA (work in progress) resulted in a more
evident reduction in cell proliferation (S-phase cell reduction) compared to a-synchronized
vascular smooth muscle cells . In this work we have used a-synchronized cells instead of
synchronized to better mimic the in vivo situation where HCC cells have free access to growth
factor and are in a-synchronized conditions. Despite this aspect, our and Simile data prove the
efficacy of E2F1 depletion in the down regulation of the growth of HepG2, an in vitro model of a
differentiated HCC cell type. Moreover, our data extend this concept also to the far less
differentiated HCC cells HuH7 and JHH6 thus broadening the attractiveness of an anti E2F1-
based strategy. Giving the growing evidence of the E2F1 direct implication in HCC
carcinogenesis (Arakawa et al., 2004; Coulouarn et al., 2006; Pascale et al., 2002; Conner et al.,
2000) it is evident the potential relevance of our observation.
The depletion of the third siRNA target, i.e. cyclin E2, has never been evaluated in any HCC cell
line. Its down regulation gave comparable results as cyclin E1 depletion with regard to cell cycle
inhibition in terms of the reduction in S-phase cell amount (Fig.41, Fig.43 and Fig.44). This
observation supports the concept that, although sharing only 47% homology with cyclin E1
(Lauper et al., 1998; Mazumder et al., 2004), cyclin E2 has similar functions. As a consequence,
also cyclin E2 depletion has the potential to be of interest for a novel HCC therapeutic approach.
Depletion of cyclin E2 like cyclin E1 and E2F1 induces apoptosis in HepG2 but not in JHH6 and
HuH7 (Fig.46 and Fig.48). In the case of cyclin E1 depletion, apoptotic induction is qualitatively
but not quantitatively in agreement with the work of Li (Li 2003). Also in this case we believe
that the difference observed just depends on some biological differences between our and Li’s
HepG2 strain. This hypothesis seems to be supported by the fact that our preliminary results
(data not shown) indicate a similar behaviour of Li’s and CyE1-1415 siRNA when tested in our
HepG2 strain.
In HepG2, apoptosis induction by siE2F1-1324, is more contained than cell proliferation
inhibition. Whereas the total amount of apoptotic cells rises only up to 4-5%, the decrease in the
amount of S-phase cells corresponds to more then 20% (Fig.41). Despite this observation, the
biological meaning of apoptosis induction should not be underscored. It may represent the
response to the confounding effects resulting from outside (serum stimulation) and inside (cyclin
E1/2 or E2F1 depletion) the cell. This may indicate a certain capacity of a physiological response
of this HCC cell line to confounding signals, a property typically lacking in poorly differentiated
tumour cells displaying high resistance towards apoptosis. As already observed for the siSRF
Discussion
122
treatment, the fact that the depletion of different cell cycle promoting genes induces apoptosis in
HepG2 suggest an a-specific response of this type of HCC to contrasting signals. This different
behaviour observed between HepG2 and JHH6-HuH7 stress the importance of the cell
differentiation grade as a factor influencing the therapeutic response.
At the molecular level, depletion of E2F1 leads to very similar effects with regard to the
influence on cyclin E1/2 expression. In all cell lines, E2F1 down regulation results in a reduction
of cyclin E1/2 mRNA levels (Fig.56b and Fig.58b). These findings extend the E2F1-mediated
cyclin E1-2 expression observed in different other cell types (see (Bracken et al., 2004) for a
review) also to the HCC cell line tested. However, at the protein levels some relevant differences
can be observed. Whereas upon E2F1 depletion cyclin E2 protein levels are consistently
decreased in all cell lines (Fig.58a), cyclin E1 protein levels varies in the different cell lines. No
substantial variations are observed in JHH6 cyclin E1 protein levels, while a reduction is
observed in HuH7 and a clear increased is observed in HepG2 (Fig.56a). In this last case we
could provide evidence of a decreased cyclin E1 phosphorylation at residues Thr395, a fact
which can be responsible for reduced protein degradation (Fig.57). Although the molecular
reasons for this variable behaviour of the protein levels in the three HCC cell lines are not clear,
it is highly probable that the different HCC cell phenotypes play a major role in the reported
differences.
Depleting cyclin E1/E2, a reduction in E2F1 protein amounts were observed in all cell lines
(Fig.50 and Fig.53). These data are substantially confirmed at the mRNA levels (Fig.51 and
Fig.54). This suggests that an E2F1 transcriptional inhibition occurs upon cyclin E1/2 down
modulation. As the major E2F1 transcriptional activator is E2F1 itself, one would expect to
detect a reduced p-RB phosphoryation status, due to the reduction of cyclin E1/2 levels.
Decreased p-RB phosphoryation in turn would reduce the free E2F1 available for its own
transcription. However, we could not detect major variation of p-RB phoshporylation status. One
possibility is that instead of being involved pRB, other pocket proteins, which also interact with
E2F1 (p107 and p130, (Moroy and Geisen, 2004), are involved. In this case the reduction in
cyclin E1/2 would reduce p107 and p130 phosphoryation and consequently the amount of free
E2F1 (work in progress).
Depletion of cyclin E2 has no substantial effects on the mRNA levels of cyclin E1 in all three
HCC cell lines (Fig.60). This finding is somewhat surprising if we consider the fact that E2F1,
the major cyclin E1 transcription factor, is down-regulated. In the liver, another cyclin E1
transcription factor is known, i.e. LRH (Fayard et al., 2004). However, we could show that LRH
is not up-regulated (Fig.61) and thus it is unlikely that it could have taken over cyclin E1
Discussion
123
transcription in place of E2F1. Our findings suggest either an increased cyclin E1 mRNA
stability or, most likely, the presence of other unknown cyclin E1 transcription factors. This
would not be too surprising considering the described E2F-independent transcription of cyclin
E1 (Lukas et al., 1997).
In contrast to the unaffected cyclin E1 mRNA levels upon cyclin E2 depletion, we observed
increased cyclin E1 protein levels in all three HCC cell lines (Fig.62). In HepG2 cells, cyclin E1
protein level increase can depend on decreased cyclin E1 phosphorylation at residues Thr395
(Fig.63). In JHH6 and HuH7 no significant variation in the phosphorylation status of cyclin E1
residues Thr395 was observed. In these cases we cannot exclude that other cyclin E1
phosphorylation sites regulating protein degradation are affected.
Whereas cyclin E2 depletion induces in all three HCC cell lines comparable effects on cyclin E1
protein and mRNA levels, depletion of cyclin E1 variably affects cyclin E2 mRNA and protein
levels (Fig.59). In HepG2 it does not alter cyclin E1 mRNA/protein levels, in HuH7 and JHH6 it
mainly reduces the cyclin E1 mRNA levels, consistently with the reduction of E2F1. These
findings suggest that cyclin E1 and E2 may not only complement each other. It is possible that
they have unique functions and that these functions depends on the specific cell phenotype.
Finally, it has been proposed a reciprocal expression level between cyclin E1 and cyclin D in
HCC tissue samples (Jung et al., 2001). This trend seem to be confirmed in JHH6, the less
differentiated HCC cell line considered, where cyclin E1 depletion is paralleled by an increased
cyclin D expression (Fig.64). Much less evident is this phenomenon in HuH7 and substantially
absent in the most differentiated HepG2. Notably, cyclin E2 depletion does not result in any
reciprocal expression effect with cyclin D1, further stressing the concept that cyclin E1 and E2
may have also independent effects on cell cycle.
In conclusion, we have identified siRNAs targeted against pivotal cell cycle controlling genes,
i.e. cyclin E1, cyclin E2 and E2F1, which are able to efficiently down modulate the expansion of
the HCC cell lines here considered. Whereas in HepG2 the mechanism is sustained by both
apoptosis induction and inhibition of cell proliferation, in HuH7 and JHH6 inhibition of cell
proliferation is predominant. In contrast to what observed for siSRF studies, the different
phenotypes of the cell line considered, hepatocyte-like for HepG2, intermediately differentiated
for HuH7 and undifferentiated and JHH6, respectively, have a lower impact on the efficacy of
the strategy adopted. These results can contribute to a better understanding of E2F1-cyclin E1-
cyclinE2 involvement in cell proliferation and possibly to identify novel effective anti HCC
therapeutic strategies.
Discussion
124
2. VSMC data
Anti-proliferative drugs (such as rapamycin) released from endo-vascular stents have
substantially contributed to reduce in-stent restenosis rates in patients bearing coronary single
primary lesions by down regulating VSMC growth. However, the considerably lower drug
efficacy shown in treatment of patients bearing more complex coronary lesions and in diabetic
patients, suggests that alternative anti-proliferative approaches can be beneficial. In this regard,
the use of less aggressive and citotoxic drug has been proposed (Fajadet et al., 2005).
The understanding of the molecular mechanisms controlling VSMCs proliferation is therefore
crucial for the development of new therapeutic strategies. Here, we explored the use of siRNAs
as tools to knock down SRF, a transcription factor involved in the proliferation of different cell
types and for which only limited data exist about its function in primary human VSMCs (Chow
et al., 2007).
1.3.1 Effects of SRF depletion on primary VSMCs
SRF has been shown to control cellular processes such as adhesion, migration or cell survival
(Schratt et al., 2002) (Schratt et al., 2004), whereas its role in cellular proliferation remains
controversial. Additionally, there exist only very few data about the role of SRF in primary
human VSMCs (Chow et al., 2007). On the one hand, homozygous inactivation of both SRF
alleles does not severely affect the proliferation of murine embryonic stem (ES) cells (Schratt et
al., 2001). On the other hand, SRF has been shown to be an essential mediator of PI3-kinase-
regulated proliferation of PC12 cells, and ectopic expression of a constitutively active form of
SRF, SRF-VP16, was sufficient to induce proliferation of 3T3-L1 fibroblasts (Poser et al., 2000).
We show here that SRF suppression diminishes human primary VSMC proliferation, and inhibits
progression from G0/G1 phase to S phase of the cell cycle (Fig.70). This observation indicates
that, at least in more differentiated somatic cells such as VSMCs, fibroblasts, and in the highly
differentiated hepatic cell line HepG2 (our results), the SRF seems to be a positive regulator of
cell proliferation. Moreover, the discrepancy between the data obtained in differentiated cells
and those obtained in ES cells may stem from different experimental approaches. In the case of
differentiated cells ((Poser et al., 2000) and the present work), SRF was transiently modulated. In
contrast, inactivation of SRF was permanent in “knock-out” ES cells (Schratt et al., 2001).
Recently, Kaplan-Albuquerque and collaborators reported that rat aortic vascular SMC clones
stably expressing SRF small hairpin RNAs (shRNAs) displayed strongly diminished SRF levels,
but, in contrast to our findings, increased rates of proliferation compared to control cells were
observed (Kaplan-Albuquerque et al., 2005). The reasons for this discrepancy are unclear.
Discussion
125
Potential toxic side effects of the siRNA-lipid complexes we used could not account for the
observed anti-proliferative effects of transiently transfected SRF siRNAs, because only the
perfectly homologous SRF siRNAs siSRF797 inhibited VSMC proliferation, whereas the
sequence-unrelated control siGL2 had no effect (Fig.70). Moreover, Kaplan-Albuquerque et al.
studied the effects of SRF depletion in VSMCs stimulated by PDGF-BB or low serum (10%),
while we performed most of our investigation in the presence of high serum (15%). However,
also under their growth conditions, transient SRF depletion in our human VSMCs resulted in a
decreased proliferation rate confirming our data obtained in high serum (Fig.71). Thus, it is
possible that the cells stably expressing the shRNA may have adapted physiologically to the
reduced SRF levels during the clonal selection process. In contrast to stable shRNA expression,
our transient siRNA transfection approach is less likely to be affected by cellular adaptation
processes. Additionally, there could be differences between VSMCs from rat and men and
between aortic and coronary artery VSMCs. Finally, our results are in agreement with the
proliferation-supportive role of SRF in several cell types (Poser et al., 2000; Chai et al., 2004;
Lockman et al., 2004; Ding et al., 2001; Soulez et al., 1996; Wheaton and Riabowol, 2004).
Reduced cell proliferation upon SRF suppression is associated with an accumulation of VSMCs
in the G0/G1 phase of the cell cycle. This accumulation may be either due to an impaired cell
cycle progression through G1 or by a hindered transition from G1 to S phase. In our hands,
siRNA-mediated depletion does not substantially affect cyclin D1, cyclin E1 or E2F1 protein
levels (Fig.77). Furthermore, expression of the CDK4 inhibitor p16INK4 is not affected by SRF
suppression (Fig.77). Taken together, these results suggest that inhibition of SRF expression
does not interfere with cell cycle progression during mid G1. However, SRF siRNA induces the
CDK2 inhibitor p27kip1 (Fig.76a-b), which might interfere with CDK2 activity, thereby inhibiting
pRB phosphorylation and progression into S phase of the cell cycle. In line with this assumption,
protein levels of the S/G2/M cyclin A are reduced upon SRF depletion (Fig.76a-b).
SRF-dependent regulation of p27kip1 levels may proceed via transcriptional and
posttranscriptional mechanisms, e.g. by the ubiquitin-proteasome pathway. Since p27kip1 mRNA
levels were not affected by SRF siRNA transfection (Fig.76c), a transcriptional regulation is
unlikely. p27kip1 stability is regulated by at least two different pathways: translocation-coupled
cytoplasmic ubiquitination by KPC (KIP1 ubiquitination-promoting complex) at G1 phase, and
nuclear ubiquitination by an SKP2 (S-phase kinase-associated protein 2)-containing complex at
S and G2 phases. Inhibition of G1/S transition by SRF siRNAs favors a KPC-dependent p27kip1
degradation. In line with this assumption, SKP2 protein levels were not affected by SRF siRNAs
(data not shown). Therefore, SRF may influence p27kip1 stability either through affecting its
Discussion
126
intracellular localization or through modulation of KPC expression (Boehm et al., 2002; Kamura
et al., 2004).
The beneficial effects of an anti-SRF based approach are not limited to the anti-proliferative
effects here documented. Unlike commonly used anti-restenotic drugs such as rapamycin,
siRNA-mediated SRF suppression does not induce cell death (Roque et al., 2001) (Fig.74).
Therefore, it can be speculated that the application of SRF siRNAs may be advantageous over
the above-mentioned drug, which in long term may cause cell death associated with arterial wall
weakening and retarded re-endothelialization leading to the emergent problem of late stent
thrombosis (Serruys and Daemen, 2007). Moreover, SRF depletion is not associated with
increased pro-inflammatory cytokine expression (data not shown). This is a desirable feature for
a therapeutic approach to pathological conditions such as in-stent restenosis, where pro-
inflammatory stimuli contribute to its pathogenesis (Ferns and Avades, 2000). Finally, the SRF
siRNAs tested do not compromise CREB, a relevant down-regulator of CASMC proliferation
(data not shown) (Reusch and Watson, 2004).
The vast majority of the work (Knoll et al., 2006; Campisi, 2000; Schratt et al., 2004; Schratt et
al., 2001) dealing with the development of molecules to be used to prevent VSMC proliferation,
was performed using starved cells induced to proliferate after drug administration. This
experimental design is based on the simplified assumption that in vivo VSMCs are quiescent
before PTA treatment and stent implantation. However, this assumption often does not
completely reflect the in vivo situation where the very early onset of VSMC proliferation in
restenotic lesions and the possible presence of pre-existing proliferating VSMC in atherosclerotic
plaques (Heidenreich et al., 1999) implicates that variable amounts of VSMCs may be
proliferating when the therapeutic drug is applied. As it is not possible to precisely reproduce in
cultured cells the above mentioned in vivo situation, we evaluated the proliferation inhibitory
effects of our siSRF797 under the two extreme conditions represented by starved (see protocol 1
in Matherial and Methods) and actively proliferating cells (protocol2). Our data indicate that,
besides being very active when applied to starved cells siSRF797 is also very effective when
delivered to actively growing cells (Fig.72), thus showing its therapeutic potential also in the un-
favourable condition of lesions containing variable degrees of replicating cells.
Instent restenosis more frequently occurs in diabetic patients (Dibra et al., 2005). The reason for
this phenomenon are not completely understood, however, it is known that in vitro VSMCs
cultured in high glucose (to simulate the diabetic condition) tend to have an higher proliferation
rate that in normal glucose. To test the efficacy of our anti proliferative approach, the effect of
SRF depletion was also studied under high glucose concentration (Zanetti et al., 2008). The fact
Discussion
127
that a significant reduction of the S-phase cells upon SRF depletion occurred in our VSMCs
indicates the potential effectiveness of our approach also in diabetic patients, where restenosis
rate are higher compared to non diabetic patients, despite current therapeutic approaches
(Fig.73).
Taken together, our results show that SRF is crucially involved in the control of human primary
VSMC proliferation which complements the well-established role of SRF in VSMC
differentiation and demonstrates the important role of SRF in human primary VSMCs.
Moreover, the possibility to down modulate VSMC growth in condition of high glucose
potentially makes our approach attractive also for diabetic patients. Finally, the lack of any major
toxic effects on VSMCs confers to our approach milder effects on VSMC biology, in contrast to
what observed for currently used anti-proliferative drugs. Further studies will clarify whether
interfering with SRF function in vivo may result in effective strategy to combat
hyperproliferative vascular pathologies such as in-stent restenosis.
Conclusion
128
CONCLUSION
In this work we have identified siRNAs able to efficiently induce the destruction of the mRNAs
of different cell cycle related genes, i.e. the transcription factors SRF and E2F1 and the cyclins
E1 and E2. The anti-proliferative potential of these siRNAs have been tested in HCC-derived
cell lines and in VSMCs. HCC-derived cell lines were used to simulate in vitro HCC cell growth
while VSMC were considered to simulate in vitro the over-growth observed in VSMCs of
coronary arteries in which in-stent restenosis develops. SRF depletion has been shown to be
effective in down modulating the growth of VSMC and the most differentiated HCC cell, i.e.
HepG2, where apoptosis was also induced. In the less differentiated HCC cells, JHH6 and
HuH7, SRF depletion was only partially achieved probably because of an increased SRF protein
stability. This in turn resulted in a poor inhibition of JHH6 and HUH7 growth. In contrast to
SRF, E2F1 and cyclin E1/2 depletion was efficiently achieved in all HCC cell lines. Whereas in
the most differentiated HepG2 the down modulation of cell expansion was due to both apoptosis
induction and proliferation inhibition, in the less differentiated JHH6 and HuH7 only
proliferation inhibition was observed. Together these data support the rationale to continue the
studies for the development of future novel anti HCC and ISR approaches based on the use of
siRNAs.
Aknowledgements
129
ACKNOWLEDGEMENTS
This PhD thesis with this dissertation has been extensive and trying, but above all exciting,
instructive and fun! Without help, support and encouragement from several person, I would
never have been able to finish this work!
First of all I would like to express my sincere gratitude to Prof. Gabriele Grassi, who has been
my supervisor since the beginning of my study. He provided me with many helpful suggestions,
important advice and constant encouragement during the course of this work.
I am very privileged for having Dr. Barbara Dapas as my tutor (but expecially as my friend!),
whose calmness, caring and unwavering optimism often soothed me!
I sincerely thank my external supervisor Prof. Olaf Heidenreich, for taking interest in this study
as well as providing valuable suggestions that improve the quality of this study.
I am grateful to Prof. Gianfranco Guarnieri, head of the Department of “Scienze Cliniche,
Morfologiche e Tecnologiche” where my project has been carried out.
Many thanks to the official supervisor of my thesis, prof. Gianni Biolo, who has offered me the
opportunity to attend this PhD.
I also wish to express my appreciation to Prof. Gabriele Pozzato, who made many valuable
suggestions and gave constructive advice and to Dr. Bruna Scaggiante for providing useful ideas
and discussions.
I also thank Dr. Laura Uxa and the laboratory of clinical analysis for allowing us to use their
cytofluorimetry.
A special thank to Dr. Cristina Zennaro for her skilfull technical assistance in microscopy
analysis and for her moral supports.
Another special thank to Dr. Barbara Toffoli for the innumerable chats about the joy and grief
of this job.
I would like to thank all people in lab. (expecially Anna Maria, Mariella, Paola, Francesco) for
making me feel okay about drinking so much coffee!
Aknowledgements
130
I thank my family: my parents Carmen and Luciano for educating me, for their unconditional
support and encouragement to persue my interests; a special thank to my brother Gabriele for
rendering me the sense and the value of brotherhood and for reminding me that my research
should be useful!
And finally, never enough thanks to my husband David, who has encouraged me throughout the
whole course of my PhD: thank for your love and patience, thank for your silence and smiles,
thank for everything, because without you, I could not live!
THANK YOU!
References
131
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