atm gene alterations in chronic lymphocytic leukemia...
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ATM gene alterations in chronic lymphocytic leukemia patientsinduce a distinct gene expression profile and predict disease progression
by Anna Guarini, Marilisa Marinelli, Simona Tavolaro, Emanuele Bellacchio, Monia Magliozzi, Sabina Chiaretti, Maria Stefania De Propris, Nadia Peragine,Simona Santangelo, Francesca Paoloni, Mauro Nanni, Ilaria Del Giudice, Francesca Romana Mauro, Isabella Torrente, and Robin Foà
Haematologica 2011 [Epub ahead of print]
Citation: Guarini A, Marinelli M, Tavolaro S, Bellacchio E, Magliozzi M, Chiaretti S, De Propris MS, Peragine N, Santangelo S, Paoloni F, Nanni M, Del Giudice I, Mauro FR, Torrente I, and Foà R. ATM gene alterations in chronic lymphocytic leukemiapatients induce a distinct gene expression profile and predict disease progression. Haematologica. 2011; 96:xxx doi:10.3324/haematol.2011.049270
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Copyright 2011 Ferrata Storti Foundation.Published Ahead of Print on October 11, 2011, as doi:10.3324/haematol.2011.049270.
ATM gene alterations in chronic lymphocytic leukemia patients induce a
distinct gene expression profile and predict disease progression
Running title: ATM gene alterations in CLL
Anna Guarini,1 Marilisa Marinelli,1 Simona Tavolaro,1 Emanuele Bellacchio,2
Monia Magliozzi,2 Sabina Chiaretti,1 Maria Stefania De Propris,1 Nadia Peragine,1
Simona Santangelo,1 Francesca Paoloni,3 Mauro Nanni,1 Ilaria Del Giudice,1
Francesca Romana Mauro,1 Isabella Torrente,2 and Robin Foà1
1Division of Hematology, Department of Cellular Biotechnologies and Hematology,
“Sapienza” University, Rome; 2IRCCS, Ospedale Casa Sollievo della Sofferenza, San
Giovanni Rotondo and CSS-Mendel Institute, Rome, Italy and 3GIMEMA Data Center,
GIMEMA Foundation, Rome, Italy
Correspondence
Robin Foà Division of Hematology, “Sapienza” University of Rome,
Via Benevento, 6, 00161, Rome, Italy. Phone: international +39.06.85795753.
Fax: international +39.06.85795792 E-mail: [email protected]
Key words: ATM, Chronic lymphocytic leukemia, Gene expression profiling, MLPA,
del11q.
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Abstract
Background. The genetic characterization of chronic lymphocytic leukemia cells
correlates with the behavior, progression and response to treatment of the disease.
Design and Methods. Our aim was to investigate the role of ATM gene alterations,
their biologic consequences and their value in predicting disease progression. The ATM
gene was analyzed by Denaturing High Performance Liquid Chromatography and
Multiplex Ligation Probe Amplification in a series of patients at diagnosis. The results were
correlated with the immunoglobulin genes mutations, cytogenetic abnormalities, ZAP-70
and CD38 expression, TP53 mutations, gene expression profile and treatment-free
interval.
Results. Mutational screening of the ATM gene identified point mutations in 8/57 cases
(14%). Multiplex Ligation Probe Amplification analysis identified 6 patients with 11q
deletion: all of them harbored at least 20% of deleted cells by FISH analysis. Overall, ATM
point mutations and deletions were detected in 14/57 (24.6%) cases at presentation,
representing the most common unfavorable genetic anomalies in chronic lymphocytic
leukemia, including also stage A patients. Both deleted and mutated ATM patients showed
a significantly reduced treatment-free interval compared to patients without ATM
alterations. ATM-mutated cases presented a peculiar gene expression profile
characterized by the deregulation of genes involved in apoptosis and DNA repair. Finally,
the structure definition of the ATM-mutated protein allowed to hypothesize functional
abnormalities responsible of the unfavorable clinical course of patients carrying these point
mutations.
Conclusions. In chronic lymphocytic leukemia, ATM alterations are present at diagnosis
in about 25% of individuals, are associated with a peculiar gene expression pattern and a
reduced treatment-free interval.
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Introduction
Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in the Western
hemisphere. It is characterized by a clonal accumulation of small, mature-looking
lymphocytes in the blood, marrow and secondary lymphoid tissues.1 The disease presents
a highly variable clinical course, with some patients surviving for many years without
requiring treatment and others who witness a rapidly progressing disease, associated with
a short life expectancy, despite aggressive treatment.
Several biological and genetic properties of the leukemic cells, such as the mutational
status of the immunoglobulin heavy chain variable genes (IGHV),2 chromosome
aberrations,3 CD38 and ZAP-70 expression,4,5 and p53 dysfunction6 bear an important
prognostic value and have enabled to stratify patients into risk categories. These
parameters are in fact important independent predictors of disease progression and
survival.
The deletion of chromosome 11q22-q23, that occurs in 10-20% of cases,3 represents the
second most common genetic abnormality in CLL and defines a subgroup of patients
characterized by progressive disease and an overall unfavorable prognostic likelihood;7 in
fact, leukemic cells show increased survival rates, possibly due to inhibited apoptosis and
to alterations of the genes involved in cell-cycle control and cell survival.8
The ATM (ataxia-telangiectasia mutated) gene maps to chromosome 11q22-q23 within the
minimal region of loss described in CLL9 and several data indicate that the 11q deletion
results in ATM gene inactivation.10 The ATM gene is a member of the phosphatidylinositol-
3 kinase (PT3K) family of genes and consists of 66 exons, of which 62 are coding exons.11
The ATM protein is a nuclear serine/threonine kinase of 350 kDa whose activities are
DOI: 10.3324/haematol.2011.049270
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induced by chromosomal double-strand breaks that arise endogenously or after exposure
to DNA-damaging agents, including ionizing radiation (IR) and drugs.12
The ATM protein is a pleiotropic molecule that protects the integrity of the genome by
regulating the cell-cycle arrest at G1/S and G2/M to prevent processing of damaged DNA,
and activating DNA-repair pathways and inducing apoptosis if the DNA damage cannot be
repaired.13 Many of these effects are mediated via a phosphatidylinositol-3 kinase domain
in the C-terminus of the ATM protein (residues 2656-3056). The homozygosus mutation of
the ATM gene is known to be the cause of ataxia-telangiectasia (A-T), an autosomal
recessive disorder characterized by neurological and immunological symptoms,
radiosensitivity and predisposition to cancer, particularly of the lymphoid system.14 Several
epidemiological studies suggest that the frequency of the A-T heterozygous carriers
ranges between 0.5% and 1% in different countries; these individuals have a significantly
increased risk of developing breast cancer15 and CLL.16,17 One third of CLL patients have
an inactive ATM and exhibit defects in the p53 damage response and in IR-induced
apoptosis.18,19 These findings have considerable clinical implications because ATM
mutations may be important in predicting potential treatment failures.20
In the present study we examined the mutational status of the ATM gene in a series of
CLL patients studied at diagnosis. A multiplex gene dosage analysis of the ATM gene was
also performed by MLPA. The results were then correlated with the known biological
prognostic factors, including coexisting cytogenetic abnormalities, IGHV status genes,
CD38 and ZAP-70 expression, TP53 mutations, as well as with gene expression profile.
Modeling structural analysis of the mutated ATM protein was carried out in order to
understand the effects of the mutation on the behavior of the neoplastic cells. The results
obtained indicate that both patients with ATM gene mutations or a large ATM gene
deletion present a distinct biologic and gene expression profile, as well as a reduced
treatment-free interval (TFI). Structural analysis of the protein kinase domain obtained by
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homology modeling helped to shed light into the functional abnormalities that lead to the
unfavorable clinical course of CLL patients carrying ATM mutations.
Design and Methods
CLL patients
Samples from 57 untreated CLL patients, collected between 1997 and 2005 at the
Hematology Institute of the “Sapienza” University of Rome, 28 females and 29 males,
median age of 50 years (range 29-64), were analyzed. The diagnosis of CLL was based on
the presence of more than 4.000 clonal lymphocytes/!L in the peripheral blood with a
typical CLL immunophenotype (CD5/CD20+, CD23+, weak CD22+, weak sIg+, CD10-) and
morphology. According to Binet staging system, 42 patients were in stage A, 12 in stage B
and 3 in stage C. The patients presented a median of 27.679/L lymphocytes (range 4.118-
212.400) at the time of the study. The patients’ characteristics are presented in the online
Supplemental Table S1.
All samples were analyzed for CD38 and ZAP-70 expression, for the IGHV status and for
TP53 mutations as previously described.21
This study was approved by the Institutional Review Board of the Department of Cellular
Biotechnologies and Hematology, “Sapienza” University of Rome. All patients and controls
gave their informed consent to blood collection and to the biologic analyses included in the
present study according to the Declaration of Helsinki.
DNA was extracted from the leukemic cells of the 57 unrelated patients and tumor DNA
was analyzed to determine ATM mutations. The detected ATM alterations were
investigated in patient-matched buccal cells DNA to determine their germline or somatic
nature.
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DHPLC analysis of ATM gene
Mutation scanning was performed by DHPLC analysis, following previously published
protocols22,23 in which a 86% mutation detection rate in ATM mutated patients and a 100%
specificity has been reported.
Sixty-two out of the 66 exons of ATM, along with exon-intron junctions, were PCR-
amplified.22 Denaturing High Performance Liquid Chromatography (DHPLC) analysis
followed previously published protocols.22,23 All amplification products showing an
abnormal elution profile were re-amplified and sequenced in the forward and reverse
direction using the BigDye Terminator chemistry and an ABI PRISM 3100 automated DNA
sequencer (Applied Biosystems). The pathogenic role of novel missense and intronic
changes was evaluated by screening 360 control chromosomes from 180 unrelated
healthy individuals.
MLPA analysis of ATM gene
To estimate the contribution of single and multi-exon ATM gene copy-number changes,
that could be missed with large FISH probes, a MLPA analysis was performed using the
SALSA MLPA kit P123 ATM, available from MRC Holland (MRC-Holland, Amsterdam, The
Netherlands).
This assay consists of two reaction mixes containing probes for 33 of the 66 constitutive
ATM exons and control probes for sequences located in other genes. An aliquot of 150 ng
of denatured genomic DNA was used in the overnight annealing of the exon-specific
probes and subsequent ligation reaction. PCR was performed with FAM-labelled primers
using 10 ml of ligation reaction. Separation and quantification of the amplification products
were carried out using an ABI Prism 3130 Genetic Analyzer (Applied Biosystem). The
peak area for each fragment was measured with the GeneScan Analysis software V.3.7
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(Applied Biosystems) and the data were analyzed with the Coffalyser software (MRC-
Holland). The results are reported as the ratio between allele copy numbers (Relative
Copy Number, RCN) of the cells from a CLL patient and healthy controls. A ratio of 1
should be obtained if both alleles are present; a reduction or an increase in the peak area
values to 0.7 or 1.3 was considered an indication of a deletion or a duplication,
respectively.
Statistical analysis of TFI
TFI was calculated from the date of diagnosis to first treatment. The probability of TFI was
estimated using the Kaplan-Meier test; since no patient died before treatment, it was not
necessary to estimate TFI by means of cumulative incidence curves, considering death
before treatment as a competing risk. The Log-rank test was used to test differences
between groups.
RNA extraction and oligonucleotide microarray
Total RNA was extracted using the RNeasy mini procedure (Qiagen), according to the
manufacturer’s instructions with minor modifications. All samples analyzed contained at
least 90% leukemic cells. HGU133 Plus 2.0 gene chips (Affymetrix, Santa Clara, CA) were
used to determine gene expression profiles. Briefly, first strand cDNA was synthesized
from 5 ! g total RNA using T7-(dT)24 primers and reverse transcribed with the Roche
Applied Science Microarray cDNA Synthesis kit (Mannheim, Germany); after the second
strand cDNA synthesis, the product was used in an in vitro transcription reaction (Roche
Applied Science Microarray RNA Target Synthesis (T7) kit) to generate biotinylated
complementary RNA (cRNA). Eleven ! g of fragmented cRNA were hybridized on
microarrays for 16 hours and subsequently gene chips were washed, stained and
scanned.
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Statistical methods for microarray analysis
Oligonucleotide microarray analysis was performed with the dChip software
(www.dchip.org), which uses an invariant set normalization method where the array with
median overall intensity was chosen as the baseline for normalization. Model based
expressions were computed for each array and probe set using the PM-MM model.24
Non-specific filtering criteria for unsupervised clustering required the expression level to be
higher than 300 in >10% of the samples and the ratio of the standard deviation (SD) to the
mean expression across all samples to be between 1 and 1,000. Unsupervised clustering
was performed as described by Eisen et al.25
To identify genes differentially expressed between different CLL subclasses, a t-test was
applied: probe-sets were required to have an average expression >100 in at least one
group, a p-value <0.05 and a fold change >1.5. Identification of gene functional annotation
was performed using the DAVID database (http://david.abcc.ncifcrf.gov).
Real-time quantitative PCR analysis
One µg of total RNA was retro-transcribed using the Advantage RT-for-PCR Kit (Clontech,
Mountain View, CA, USA). Real-time quantitative-PCR (Q-PCR) analysis was performed
with an ABI PRISM 7500 sequence detection system and the SYBR green dye (Applied
Biosystems). The real-time PCR conditions were as follows: 1 cycle at 50ºC for 2 minutes,
1 cycle at 95ºC for 10 minutes, 1 cycle at 95ºC for 15 seconds, 1 cycle at 60ºC for 1
minute, for a total of 40 cycles. For each sample, GAPDH CT values were utilized for
normalization purposes. For each gene, relative expression levels were computed as the
difference (2-!CT) between the target gene CT and GAPDH CT.
Primers were designed by Primer Express 1.5.1 software (Applied Biosystems). Gene
symbols and primers are listed in the online Supplemental Table S2.
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Box plots and p-values were obtained using a tool available on the website
(http://www.physics.csbsju.edu/stats/).
Molecular modeling of the ATM kinase domain
The structure of the PI3K-like domain of ATM in the amino acid (a.a.) interval 2623-2953
was built by homology modeling using the program MODELLER (release 9v3)26 and using
as a template the structure of the homologous porcine PI3K" in complex with ATP (Protein
Data Bank, PDB, entry 1E8X), according to alignment of sequence and secondary
structure elements (the latter are predicted by PSIPRED for ATM and experimental for
porcine PI3K"), as shown in online Supplemental Figure S1.
The alignment allowed to identify the nucleotide binding loop in the N-terminal side of the
kinase domain of ATM at about a.a. 2694-2699, owing to the congruence with the typical
secondary structure features for this protein region. The ATM a.a. interval 2795-2830
emerges as an insertion with respect to the porcine PI3K" sequence and has not been
modeled. However, this part of the protein does not appear to contribute to the kinase fold
because it shows a less strict a.a. conservation; in addition, the presence of several
charged residues suggest solvent exposure with probable implications in the mechanisms
of ATM activation and/or substrate recognition. The ATP co-factor has been modeled on
the kinase domain of ATM according to the binding conformation of the ATP ligand
reported in the crystallographic structure of PI3K".
To assess the congruence of the proposed architectural model, we have also verified
whether a.a. crucial for kinase activity are properly located inside the structure.
Specifically, we have identified the position of the lysine that interacts with the phosphate
group of ATP and the aspartic acid that acts as proton acceptor, which are the two active
site residues directly involved in kinase activity. The first of these two residues in ATM
appears to be the invariant Lys2717, because it aligns accurately with Lys833 of porcine
DOI: 10.3324/haematol.2011.049270
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PI3K", which in turn is known as the active site lysine for this homologous kinase.27 The
proton acceptor residue in ATM turns out to be the invariant Asp2870 owing to its
geometric coincidence with the annotated catalytic aspartic acid residue of another
structurally characterized kinase (PDB structure 1VYW, cell division protein kinase 2) that
is observed after rigid superposition of this latter structure with our model.
DOI: 10.3324/haematol.2011.049270
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Results
DHPLC analysis for ATM mutations
Fifty seven CLL patients were screened for mutations in the 62 coding exons of the ATM
gene. Mutational screening of the ATM gene identified 8 (14%) patients with heterozygous
mutations: 1 frameshift 2502insA, 1 splicing mutation IVS29+5G>A, 6 missense, 8095C>T
(P2699S), 8071C>T (R2691C), 2476A>C (I826L) and 1435G>T (D479Y) in 3 patients:
given the relatively high incidence of the latter mutation, in order to exclude the possibility
of a contamination, the presence of this mutation was screened, and confirmed in two
different DNA aliquots from the same individual (Table 1). In 4/8 cases, the ATM mutations
have also been tested on the non-neoplastic cell population, namely buccal cells, to verify
whether the alteration was germline or carried only by the neoplastic cells: in 1/4 cases the
mutation was germline (Table 1).
In addition, 9 different variants or polymorphisms, defined on the basis of referenced data,
were found in 14 patients (online Supplemental Table S3); their functional significance is
unknown. ATM mutations, variants and polymorphisms have been also evaluated in 180
healthy volunteers, to test in matched controls if these variants segregate in the Italian
population and to verify their frequency (online Supplemental Table S3).
MLPA analysis for ATM deletions/duplications
All 57 CLL patients were analyzed for ATM gene copy number variations by MLPA. This
method identified an entire gene deletion in 6/57 patients analyzed. In all 6 samples,
MLPA analysis showed a significant decrease in the peak heights for all ATM exons with
mean RCN values of 0.58. This finding confirmed previous results obtained by FISH
analysis, showing a deletion in at least 20% of the leukemic cells. No deletion was found in
patients carrying point mutations.
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Relationship between ATM gene mutations and prognostic factors
Patients with ATM point mutations
Analysis of the sequence of IGHV genes in the 8 ATM-mutated cases showed in 6 an
unmutated status and in 2 (MR 3664; AE 5646) a mutated status (Table 2).
ZAP-70 was expressed in 4/8 ATM-mutated cases (MR 3664; PD 3988; VA 4046; IA
5948). The CD38 antigen was present in more than 7% of leukemic cells in 5/8 cases (CF
5116; ID 5637; PD 3988; VA 4046; IA 5948), but only in 1 (VA 4046) more than 20% of the
cells were positive. Several cytogenetic imbalances, evaluated by FISH, were found in
ATM-mutated patients: deletion 13q14 in 5/8 patients (ID 5637; MR 3664; PD 3988; AE
5646; CF5116), deletion 14q32 in 2/8 patients (CF 5116; MR 3664) and deletion 17p13 in
3/8 patients, but in only one case (PD 3988) more than 20% of the cells were positive. Two
of 8 ATM-mutated cases had a coexisting mutation in the TP53 gene (PD 3988; IA 5948).
Deletion 11q23 was negative in all ATM-mutated patients, but patient CF 5116 developed
the deletion on 45% of leukemic cells at the time of disease progression.
Six patients were in stage A and two in stage B (GF 3706;PD 3988); 3 pts (AE 5646; GF
3706; PD 3988) showed lymphadenopathy.
At the time of data analysis, 6/8 of patients with ATM mutation had undergone treatment
(MR 3664; PD 3988; GF 3706; ID 5637; CG 5116) and the median TFI was 30.0 months.
Patients with ATM deletions
All cases showing a significant reduction of ATM gene expression, evaluated by MLPA
analysis, had a proportion of 11q23 deleted cells greater than 20% (Table 2). One case
showed a concomitant 17p13 deletion in 7% of the leukemic cells.
All 6 patients disclosed an IGHV unmutated status. CD38 was positive in 4/6 cases (CS
5700; PF 5216; PA 5704; VR 3835) and in all more than 20% of the leukemic cells
expressed the antigen. ZAP-70 was positive in all cases.
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Five patients were in stage A and 1 in B (CC 5394); 4 pts (CC 5394; CS 5700; PF 5216
VR 4046) showed lymphadenopathy.
At the time of data analysis, all 11q23 deleted patients had been treated and the median
TFI was 23.5 months.
Patients without ATM mutations or deletions
Forty-three of the 57 CLL analyzed showed no ATM gene mutation or 11q23 deletion
(Table 2). Two patients disclosed del17p13, but only 1 in more than 20% of the leukemic
cells, and 1 patient had a TP53 gene mutation. In 16/43 (37%) cases, an unmutated IGHV
gene status was recorded. CD38 was positive in 8/43 (19%) cases and ZAP-70 was
expressed in 12/39 (31%) patients. Thirty-one patients were in stage A, 9 in stage B and 3
in stage C. At the time of data analysis, 26/43 patients had been treated and the median
TFI was 64.2 months. When ATM-mutated and deleted patients were compared to
patients without ATM alterations, the difference in TFI was significant (p=0.0032)
(Figure 1).
Microarray analysis in CLL cells with ATM point mutations
To evaluate the effects of ATM mutations on CLL cells, we performed a gene expression
profile analysis on 41 of the 57 CLL patients characterized for the ATM mutational status.
We first utilized an unsupervised approach applying non-specific filtering criteria:
hierarchical clustering based on a list of 226 selected genes showed that 3/5 ATM-mutated
cases were included in the same cluster of patients; of note, two samples harbored the
same ATM mutation (1435G>T) (data not shown).
Subsequently, we performed a supervised analysis comparing the ATM-mutated cases
with the remaining CLL samples; as shown in Figure 2A, this approach revealed a
common pattern of expression for CLL cases with ATM mutations, identifying a set of 32
DOI: 10.3324/haematol.2011.049270
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differentially expressed genes. Among these, we found several genes involved in signal
transduction (TGFBR3, AXIN2, CD180, GABRB2, BACE2), regulation of transcription
(RXRA, EIF4A, XBP1), angiogenesis (LAMA5, COL4A3, TMPRSS6), apoptosis and cell-
cycle regulation (SRGN, LY86, SEPT10) (online Supplemental Table S4). Remarkably,
similar results were obtained when the same comparison was performed excluding
MLPA+ cases (data not shown): this approach was undertaken to prove that the signature
of ATM mutations is independent of 11q23 deletions.
Furthermore, given the documented association between ATM mutations and unmutated
IGHV genes,20 we compared ATM-mutated vs ATM wild-type (WT) cases exclusively on
IGHV unmutated CLL. This analysis provided even more interesting results, as shown by a
more homogeneous pattern of expression and the identification of a larger set of
differentially expressed genes (Figure 2B).
Microarray analysis in CLL cells with ATM deletions
The unsupervised analysis on CLL samples highlighted that 4/6 MLPA+ patients were
included in the cluster with ATM-mutated samples mentioned above (data not shown).
We subsequently performed a supervised analysis using a t-test between MLPA+ cases
and the other CLL samples, independent of ATM mutations (Figure 3A). This comparison
identified 98 differentially expressed genes, as reported in the online Supplemental Table
S5. Among the more significant functional groups, we found different genes involved in
signal transduction (TCL1A, P2RX1, CNR1, IL10RA, CXCR5, CACNA1A, FMOD,
TXNDC5), regulation of transcription (RXRA, BMI1, ZNF92, NR4A2, EIF3C, HOXC4,
ZNF331), cell adhesion (PCDH9, SIGLEC10, VCL, LY9, COL18A1, CNTNAP2), lipid
metabolism (APOD, ALG13, NPC2, FDX1, ALOX5, TSPO, PAFAH1B2, NRIP1) and
cytoskeleton organization (DMD, ADD3, TUBB6).
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Moreover, our results highlighted a more distinctive signature associated with ATM
deletions, coupled with a concomitant gene dosage effect. In fact, among the
downmodulated genes, we detected a reduced expression of several transcripts localized
on the chromosome region 11q22-q23, such as ATM, FDX1, MLL, CUL5, IL10RA, BIRC3,
CXCR5, UBE4A, TMEM123, CCDC84, PAFAH1B2, CWF19L2 and KIAA0999 genes.
In line with these findings, the decrease of expression levels of this set of genes correlated
with the percentage of cells carrying the deletion (Figure 3B).
Furthermore, as already done for ATM mutations, in order to exclude the effects of IGHV
mutational status, the same analysis was performed exclusively on CLL IGHV unmutated
samples, achieving analogous results (data not shown).
Validation of gene expression data by Q-PCR analysis
To further validate the microarray results, we performed a Q-PCR analysis on 5 CLL
patients with ATM mutations, 5 MLPA+ cases and 5 CLL without ATM alterations. As
expected, the Pearson correlation index between the gene expression and Q-PCR #CT
values was high, confirming a good concordance between these two techniques.
Among the transcripts differentially expressed in the ATM-mutated vs ATM WT CLL
selected by microarray, the Q-PCR approach confirmed the significant upregulation of
TGFBR3 (p=0.034) and XBP1 (p=0.045) and a significant downmodulation of SEPT10 (p=
0.05) in the first subgroup of patients (online Supplemental Figure 2A). Similarly, Q-PCR
analysis showed significantly different expression levels of ATM (p=0.039), BIRC3
(p=0.0060), TCL1A (p=0.0024) and TSPO (p= 0.0014) between MLPA+ and MLPA- cases
(online Supplemental Figure 2B).
Furthermore, we also evaluated the expression of a set of transcripts commonly
deregulated in CLL with ATM alterations. In agreement with the gene expression data,
BACE2 and TMPRSS6 were significantly down-regulated in both ATM-mutated and
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deleted patients, whereas PCDH9 and RXRA were modulated in the opposite way in these
two subclasses compared to the other CLL (online Supplemental Figure 2C).
Finally, when we extended the analysis to an additional cohort of cases, including ù
5 CLL with ATM point mutations and 5 CLL with del11q, comparable results were obtained
(data not shown).
ATM protein mutations modeling
Mutation D479Y was analyzed since it was detected in 3 ATM-mutated cases (Table 1).
The understanding of the implications of this a.a. change on ATM function was difficult,
since this region of the protein has so far not been studied. D479Y is included in the $ -
helix formed by a.a. 478-494 (secondary structure prediction by PSIPRED) and shows a
high conservation across species having as a much less frequent alternative only
glutammic acid, which is also a negatively charged residue. These features suggest the
importance of this residue.
To understand the effects of the R2691C and P2699S mutations, we have built the
structure of the PI3K-like domain of ATM by homology modeling. The match between the
pattern of secondary structures of ATM kinase and PI3K" (online Supplemental Figure S1)
allows an unambiguous localization of the sites of R2691C and P2699S mutations in the
pocket that binds the ATP co-factor (Figure 4). The R2691C mutation implies the
replacement of a large and positively charged arginine with the small and neutral cysteine
residue, introducing significant structural and electrostatic changes in the ATP binding
pocket. As for the P2699S mutation, according to the alignment and predicted secondary
structure, the presence of a proline at position 2699 suggests that this residue acts as a
breaker of the %-sheet formed by a.a. 2700-2706 (proline residues are commonly found as
$-helix and %-sheet disruptor), thus initiating the formation of a reverse turn that is followed
N-terminally by another %-sheet (a.a. 2690-2693). Such secondary structure arrangement
DOI: 10.3324/haematol.2011.049270
17
is essential for kinases and it is likely to be lost with the P2699S mutation in which the
invariant proline is replaced by a serine.
Owing to such important effects in a region critical for the binding of the co-factor, R2691C
and P2699S mutations are each expected to impair the kinase activity of ATM.
I826L modeling was not evaluated since the mutation falls outside the PI3K-like domain.
DOI: 10.3324/haematol.2011.049270
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DISCUSSION
The purpose of this study was to analyze the ATM gene in CLL patients, considering that
chromosome 11q22-q23 deletion, where the gene is located, represents the second most
common cytogenetic imbalance and a biologic parameter associated to an unfavourable
prognosis in CLL.3,7 We asked the question if CLL cells that carry ATM gene mutations
and/or deletions showed a peculiar behavior, if there was a molecular explanation and if a
peculiar therapy must be administrated.28 ATM gene mutations not associated with
11q22.23 deletion were observed in 8/57 patients, indicating that this gene is often (14%)
affected in CLL. Notably, all investigated patients were evaluated at diagnosis and before
any treatment. The few reported data concerning the frequency of ATM gene mutations in
untreated CLL patients are in agreement with our results (12%).20 In particular, no data are
available concerning Italian CLL patients. All point mutations but one (2502insA)29
detected in this study are reported for the first time in CLL patients.
Our results suggest that the ATM gene behaves as the TP53 gene:19 deletions and
mutations can be independent processes, but both impact on prognosis. If both deleted
and mutated ATM patients are considered, these alterations are present in a highly
significant proportion of CLL patients at presentation (24.6%). Notably, in this study only
patients with &65 years have been investigated and this could possibly account for the
frequency of the mutations.30,31
The majority of patients with ATM mutations showed poor prognostic biologic features: an
IGHV unmutated status, ZAP-70 and CD38 expression.32 Altogether, these parameters
correlate with the clinical behavior of the disease; in fact, the majority of patients carrying
ATM mutations required treatment for disease progression over a short observation time:
100% of deleted ATM patients required therapy within a median of 23.5 months and 62.5%
of patients with ATM point mutations needed treatment within a median of 30.0 months
after diagnosis. Overall, the TFI of CLL patients with ATM alterations was significantly
DOI: 10.3324/haematol.2011.049270
19
shorter compared to that of patients not harboring such abnormalities (64.2 months).
These findings extend previously published data.7,20,30 In an attempt to explain this
phenomenon, we measured the functional consequences of ATM deletions and point
mutations by evaluating gene expression profile. By supervised analysis, leukemic cells
carrying the 11q22.23 deletion (cut-off >20%), showed a downmodulation of the ATM,
MLL, CUL5 and BIRC3 genes involved in the apoptosis machinery and DNA repair,
mapping to the 11q23 region, thus pointing to a gene dosage effect.33,34 ATM
downmodulation, also validated by Q-PCR analysis, represents a bona fide result.
It has been recently reported that other genes (i.e. NCAM1, TTC12, ANKK1, DRD2,
TMPRSS5, ZW10, USP28, HTR3B, HTR3A, PLZF, NNMT, C11orf71, RBM7, REXO2,
FAM55A, FAM55B and TSLC1) are included in the minimally deleted region on 11q;35 in
our cohort, these transcripts were downmodulated, but without significant differences when
compared to the entire CLL series.
Similarly, Ouillette et al.36 identified a frequent association between ATM deletions and
monoallelic loss of Mre11 and/or H2AFX; in line with these findings, mRNA levels were
lower, but not significantly, in cases with del11q compared with the other CLL samples.
Furthermore, Weston et al.37 have shown that ATM deleted CLL cells exhibit an impaired
activation of the NFR2-ARE detoxification pathway; consequently, ATM mutant cells can
be differentially targeted for killing by agents that activate the NFR2-ARE pathway. The
targeted approach may provide novel treatment options for otherwise chemoresistant ATM
mutant tumors and additionally reduce morbidity in patients.
When considering ATM point mutations, unsupervised analysis revealed that 3 of the 5
cases with ATM aberrations clustered in the same branch, although not tightly: as
suggested by Stankovic et al.,38 this might mean that prior to a DNA damage a distinctive
signature is not evident. At variance, supervised analysis comparing the ATM-mutated
cases with the remaining CLL samples identified 32 differentially expressed genes. Among
DOI: 10.3324/haematol.2011.049270
20
the upregulated genes, we found TGFBR3, that codifies for a TGFB receptor, XBP1 that
encodes a transcription factor expressed in almost 80% of estrogen receptor-alpha (ER)+
breast tumors,39-43 SRGN, that encodes for a protein associated with the macromolecular
complex of granzymes and perforin, and EIF4A and RBM8A, both involved in regulation of
transcription. Among the downmodulated genes, it is worth mentioning CD180 and LY86,
that encode two surface molecules associated in a receptor complex (RP105/MD-1) with a
role in B-cell recognition and signaling of lipopolysaccharide,44 AXIN2, that proved
specifically associated with carcinogenesis when silenced in colorectal carcinoma with
microsatellite instability,45 and, finally, LAMA5 and SEPT10, both involved in the
pathophysiology of CLL.46, 47
The peculiar gene expression profile of ATM-mutated and deleted patients was confirmed
when the analysis was restricted to IGHV unmutated cases, suggesting that ATM gene
alterations induce a peculiar gene expression profile in itself.
Our results suggest that both deletions and mutations of the ATM gene peculiarly affect
gene expression profile. However, the genes involved are different in the two groups, with
only a small set of 4 genes commonly deregulated in both mutated and deleted CLL
patients. These results suggest that, at the biological level, different mechanisms might be
involved in the impairment of the ATM pathway, but provide a similar adverse clinical
effect.
These conclusions are strengthened by the evidence that no specific signatures have
been highlighted in leukemic cells carrying ATM polymorphisms. These results are in
agreement with the knowledge that ATM mutations are pathogenic rather than
polymorphic, because ATM polymorphisms are not associated with a defect in ATM-
dependent cellular responses.18
The differences observed in gene expression profile among ATM-mutated leukemic cells
can be the consequence of mutations in different coding regions. In fact, mutations
DOI: 10.3324/haematol.2011.049270
21
observed in the cases hereby analyzed occur in different exons, leading to the
deregulation of different domains of the ATM protein: given the small number of patients a
comparison of the gene expression effects of the different mutations was not feasible,
although this approach might be particularly useful towards understanding the functional
consequence of each mutation.
The ATM protein has a key role in the response to DNA double strand breaks that are
potentially harmful to cells. Involvement of ATM in this process results in a rapid increase
in the kinase activity residing in a protein domain characterized by the typical motifs of the
PI3K family. Bakkenist and Kastan have proposed that, in unperturbed cells, ATM proteins
associate forming homodimers or higher-order homomultimers devoid of kinase activity
owing to mutual steric hindrance on the enzyme active site.48 After DNA damage, one
ATM molecule phosphorylates serine 1981 on an interacting ATM molecule, enabling
dissociation of this latter protein and its activation in the phosphorylation of cellular
target.48
Two patients carrying the Asp479Tyr mutation fell in the same cluster of gene expression
profile suggesting that the mutation could play a role in the behavior of the leukemic cells.
The PI3K-like domain of ATM built by homology modeling allows to locate the sites of
R2691C and P2699S mutations in the pocket that binds the ATP co-factor (Figure 4B).
This region shows a high vulnerability to mutations since it is directly involved in the
interaction with the co-factor. The important changes associated with each of the two
mutations modify critically this part of the structure impairing ATM kinase activity.
Important biological consequences can be envisioned for R2691C and P2699S mutants.
Indeed, it has been observed that heterozygous missense mutations resulting in ATM
proteins devoid of phosphorylation activity dramatically increase the risk of cancer. This
phenomenon can be explained by the dominant-negative effect. Specifically, ATM inactive
kinase mutants interact with ATM wild type proteins without inducing their activation
DOI: 10.3324/haematol.2011.049270
22
through phosporylation of serine 1981 as it is expected after DNA damage.48 Hence, these
inactive mutants sequester wild type proteins preventing their cell response to the
carcinogenic effects associated with a variety of physical and chemical insults (ionizing
radiations, radicals, either produced endogenously or from exogenous toxins).
Furthermore, Willemore et al. have suggested that, because the DNA-PK activity was
significantly higher in ATM mutant compared to wild type CLL cells, the link between DNA-
PK activity and ATM mutation must be examined as it provides a possible mechanism and
proof of concept of increased sensitization by DNA-PK inhibitors. These results suggest
that DNA-PK inhibition can sensitize ATM mutant CLL cells to chemotherapeutics. Their
data are consistent with the concept of synthetic lethality, where the tumor cells harboring
a DNA repair defect can be killed by targeting the compensatory DNA repair pathway and
suggest that a group of patients may benefit from this combination.49
In conclusion, the results of this study indicate that ATM gene mutations - both point
mutations and deletions - occur in a high proportion of CLL cases (24.6%), from the time of
disease onset, thus representing the most frequent unfavorable genetic anomaly in CLL. In
view of the role played by ATM mutations on the behavior of CLL cells and progression of
the disease, it is important that both deletions and point mutations are considered in an
optimal prognostic stratification and therapeutic approach of CLL patients.
DOI: 10.3324/haematol.2011.049270
23
Funding
Supported by Associazione Italiana per la Ricerca sul Cancro (AIRC), Milan and AIRC
Special Program Clinical Oncology 5 per mille, Milan; Ministero dell’Università e Ricerca
(MIUR), COFIN and FIRB projects, Rome; Compagnia di San Paolo, Turin; Progetto
“Oncologia”, Ministero della Salute, Rome; Fondazione Cenci Bolognetti, Rome, Italy.
Authorship and Disclosures
AG and MM performed research, analyzed data and wrote the paper; ST and SC
performed and analyzed gene profile data; EB performed ATM point mutation modelling;
MM and IT performed and analyzed ATM gene sequence and dosage data; MSDP, NP,
SS, MN performed research; FP performed statistical analysis; DGI and FRM provided
clinical assistance; RF designed research and revised critically the manuscript. The
authors reported no potential conflicts of interest.
DOI: 10.3324/haematol.2011.049270
24
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31
Table 1 . ATM gene point mutations in CLL patients.
ID Number Patients
ATM gene mutation Nucleotide Aminoacidic Type Exon/ Change Change Intron
Germline (G)/
Somatic (S)
Allelic Status
3664 M.R. 1435G>T D479Y Missense 12 n.e. Heterozygous
5948 I.A. 1435G>T D479Y Missense 12 S Heterozygous
5646 A.E. 1435G>T D479Y Missense 12 n.e. Heterozygous
3988 P.D. 2476>C I826L Missense 19 n.e. Heterozygous
4046 V.A. 2502insA – Frameshift 19 n.e. Heterozygous
5116 C.F. IVS29+5G>A – Splicing 29 S Heterozygous
3706 G.F. 8095C>T P2699S Missense 57 S Heterozygous
5637 I.D. 8071C>T R2691C Missense 57 G Heterozygous
n.e. : not evaluated
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Table 2. Biological and clinical features of CLL patients studied.
Biologic features Patients with
ATM mutations
(n = 8)
MLPA+
(n = 6)
Patients without
ATM gene
alterations (n = 43)
del11q22.3 (FISH)
>5% <20% >20%
0/8 0/8
0/6 6/6 (100%)
0/43 0/43
del17p13.1 (FISH)
>5% <20% >20%
2/8 (25%) 1/8 (13%)
1/6 (17%) 0/6
1/43 (2%) 1/43 (2%)
IGHV
unmutated mutated
6/8 (75%) 2/8 (25%)
6/6 (100%) 0/6
16/43 (37%) 27/43 (63%)
ZAP-70>20% 4/8 (50%) 6/6 (100%) 12/39 (31%)
CD38>7% 5/8 (62%) 4/6 (67%) 8/43 (19%)
TP53 mutated 2/8 (25%) 0/6 1/43 (2%)
N° of treated patients
TFI Median (months)
5/8 (62.5%)
30.0
6/6 (100%)
23.5
26/43 (60.4%)
64.2
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33
Figure legends
Figure 1. Statistical analysis of TFI. Evaluation of treatment-free interval in ATM-
mutated and deleted CLL patients compared to patients without ATM alterations.
Figure 2. Comparison between ATM-mutated and non-mutated CLL patients.
Differentially expressed genes between ATM-mutated and ATM wild-type (WT) cases in all
the CLL patients analyzed (A) and in IGHV unmutated samples (B), respectively. Upper
legend: green represents ATM-mutated cases, yellow ATM WT cases. Relative levels of
gene expression are depicted with a color scale: red represents the highest level of
expression and blue represents the lowest level.
Figure 3. Comparison between MLPA+ and MLPA- CLL patients. Identification
of 98 differentially expressed genes between MLPA+ cases and the remaining CLL
samples. Upper legend: purple represents MLPA+ cases, light green MLPA- cases (A).
Correlation between percentage of 11q22-23 deleted cells and expression levels of 6/13
transcripts localized on this chromosome region (B).
Figure 4. ATM model. Shown is the ribbon representation of the model of the ATM
kinase domain (A). The a.a. residues involved by mutations (Arg2691 and Pro2699) and
the ATP co-factor are in ball and stick representation. Details of the ATP binding region
and the site of mutations are shown in B.
!
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Figure 1
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Figure 2
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Figure 3
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Figure 4
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SUPPLEMENTARY APPENDIX
Supplementary Figure 1
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Supplementary Figure 2
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Supplementary Table 1. Biologic characteristics of the 57 CLL patients studied for
ATM mutations.
Parameters N° of patients studied (%)
CD38 expression 57
>7% 17 (30%)
<7% 40 (70%)
ZAP-70 expression 53
>20% 22 (42%)
<20% 31 (58%)
11q22.3 deletion 57
>5%-10% 4 (7%)
>10% 10 (18%)
17p13.1 deletion 57
>5%-20% 8 (14%)
>20% 2 (4%)
13q14 deletion 57
>5% 39 (68%)
14q32 deletion 57
>5% 16 (28%)
Trisomy 12 57
>5% 4 (7%)
IGHV mutation status 57
Unmutated 28 (49%)
Mutated 29 (51%)
TP53 57
Mutated 3 (5%)
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Supplementary Table 2. Gene symbols and primers evaluated by Q-PCR analysis.
Gene symbol
Primer forward Primer reverse
GAPDH CCACCCATGGCAAATTCC GATGGGATTTCCATTGATGACA
ATM AAATTTTCAACCAGTTTTCCGTTACTT ACACTGCGCGTATAAGCCAAT
BACE2 CGAGCCCCTGTGCAGAAAT AGTTGCTGGCTACATCCTCTGTT
BIRC3 TTTCCGTGGCTCTTATTCAAACT CTTCTCATCAAGGCAGAAAAATCTT
PCDH9 GCTTGTGCTTGTATTCCTTTATGTTAA CTCCATAGTCCTGCGGATCAA
RXRA AAGGACCGGAACGAGAATGA ATCCTCTCCACCGGCATGT
SEPT10 ACAGTGGGATTTGGTGACCAA GGCCTCAAACTGAGCATCTATGT
TCL1A GCCTGGGAGAAGTTCGTGTATT CTGTAACCTATCCTTTATCTCGATGGT
TGFBR3 TGCCAGAGAATGGACACGTTTA AGCACGTTTGGATGGCAAA
TMPRSS6 GCCACATTCCAGTGCAAAGA CGCTGCCGTTGAGACAATC
TSPO TGGAAAGAGCTGGGAGGCTT TGTCGGGCACCAAAGAAGAT
XBP1 TCTCAGCCCCTCAGAGAATGAT TCCGGAACGAGGTCATCTTCTA
Supplementary Table 3 . ATM gene variants and polymorphisms detected in CLL patients.
DOI: 10.3324/haematol.2011.049270
42
ID Number
Patients
ATM gene variants
Nucleotide Change
Aminoacidic Change
Type Exon/Intron
Allelic* Frequency
Controls (%) Reference
§
5394 C.C. IVS62+8A>C ' Intronic 62 14
Castellvı-Bel et al. (50 ) 3707 B.P. IVS62+8A>C ' Intronic 62
5704 P.A. IVS14-55T>G ' Intronic 15
8 Castellvı-Bel et al.
(50) 5699 R.D. IVS14-55T>G ' Intronic 15
3442 S.A. IVS14-55T>G ' Intronic 15
5646 A.E. IVS14-55T>G
5557G>A '
D1853N Intronic
Missense 15 39
8 3
Sandoval et al. (51)
3459 S.A. 5557G>A D1853N Missense 39 3 Sandoval et al. (51)
3469 R.B. 5558A>T D1853V Missense 39 1 Sandoval et al. (51) Schaffner et al.(10)
3580 C.M. IVS38-8T>C ' Intronic 39 3
'
5281 B.A. IVS38-8T>C
2119T>C '
S707P Intronic
Missense 39 15
Meier et al. (52) Koinuma et al. (53)
3668 S.L. IVS57+90G>A ' Intronic 57 1 '
3751 D.C. 5748C>T D1914D Silent 40 1
'
3458 S.MG 5748C>T D1914D Silent 40 '
3664 M.R. IVS55+79T>C ' Intronic 55 0 #
*180 healthy control subjects § ATM gene variants and polymorphisms reported in the literature
# http://www.vmresearch.org/atm.htm
DOI: 10.3324/haematol.2011.049270
43
Supplementary Table 4. Differentially expressed genes between CLL patients with and
without ATM gene point mutations. Genes are rank-ordered according to their p-value.
Probeset ID Gene Symbol P-value Chromosomal
Location Gene Function
Expression in ATM-Mutated
Cases
224795_x_at IGK 0.000767 2p12 Immune response High
214836_x_at IGKC 0.00095 2p12 Immune response High
211787_s_at EIF4A 0.003262 17p13 Translation High
221651_x_at IGK 0.007507 2p12 Immune response High
1569110_x_at
LOC728613 0.007568 5p15.33 Unknown High
221671_x_at IGK 0.007701 2p12 Immune response High
222443_s_at RBM8A 0.012148 1q12 RNA processing High
201859_at SRGN 0.017273 10q22.1 Apoptosis High
204929_s_at VAMP5 0.018839 2p11.2 Vesicle-mediated tran sport High
200670_at XBP1 0.02972 22q12 Regulation of transcription,
DNA-dependent High
226625_at TGFBR3 0.045595 1p33-p32 Signal transduction High
1563473_at Unknown 0.047765 Unknown Unknown High
210150_s_at LAMA5 0.000084 20q13.2-q13.3 Angiogenesis Low
231735_s_at MALAT1 0.000906 11q13.1 Unknown Low
239369_at LCN8 0.002436 9q34.3 Phospholipid metabolic process Low
232471_at Unknown 0.004535 Unknown Unknown Low
217853_at TNS3 0.006553 7p12.3 Intracellular signaling cascade Low
205859_at LY86 0.008207 6p25.1 Immune response Low
219737_s_at PCDH9 0.011019 13q14.3-q21.1 Cell adhesion Low
1557122_s_at
GABRB2 0.011915 5q34 Ion tran sport Low
206206_at CD180 0.012872 5q12 Immune response Low
224823_at MYLK 0.013742 3q21 Protein amino acid
phosphorylation Low
222446_s_at BACE2 0.014523 21q22.3 Proteolysis Low
213502_x_at LOC91316 0.016196 22q11.23 Carbohydrate metabolic
process Low
202449_s_at RXRA 0.017499 9q34.3 Regulation of transcription,
DNA-dependent Low
217867_x_at BACE2 0.020668 21q22.3 Proteolysis Low
235522_at CLEC2D 0.020993 12p13 Cell surface receptor linked
signal transduction Low
212698_s_at SEPT10 0.02323 2q13 Cell cycle Low
222073_at COL4A3 0.023512 2q36-q37 Cell surface receptor linked
signal transduction Low
217950_at NOSIP 0.024734 19q13.33 Negative regulation of nitric-
oxide synthase activity Low
222696_at AXIN2 0.024758 17q23-q24 Signal transduction Low
209829_at C6orf32 0.030694 6p22.3-p21.32 Multicellular organismal
development Low
209469_at GPM6A 0.03877 4q34 Unknown Low
234367_x_at TMPRSS6 0.04024 22q12.3 Intracellular signaling cascade Low
212592_at IGJ 0.042982 4q21 Immune response Low
DOI: 10.3324/haematol.2011.049270
44
Supplementary Table 5. Differentially expressed genes between MLPA+ and MLPA-
CLL patients. Genes are rank-ordered according to their p-value.
Probeset ID Gene
Symbol P-value
Chromosomal Location
Gene Function Expression in MLPA+ Cases
209995_s_at TCL1A 0.000197 14q32.1 Multicellular organismal
development High
39318_at TCL1A 0.000425 14q32.1 Multicellular organismal
development High
202449_s_at RXRA 0.001776 9q34.3 Regulation of transcription,
DNA-dependent High
228476_at KIAA1407 0.00429 3q13.31 Unknown High
244740_at MGC9913 0.004904 19q13.43 Unknown High
210949_s_at EIF3C 0.005208 16p11.2 Regulation of translational
initiation High
219737_s_at PCDH9 0.005278 13q14.3-q21.1 Cell adhesion High
203454_s_at ATOX1 0.005982 5q32 Cellular copper ion
homeostasis High
200647_x_at EIF3C 0.006259 16p11.2 Regulation of translational
initiation High
229344_x_at FAM80B 0.006455 12p13.31 Protein modification process High
210401_at P2RX1 0.009813 17p13.3 Signal transduction High
221253_s_at TXNDC5 0.009822 6p24.3 Anti-apoptosis High
215440_s_at BEX4 0.009915 Xq22.1-q22.3 Unknown High
215230_x_at EIF3C 0.010132 16p11.2 Regulation of translational
initiation High
238919_at Unknown 0.011614 Unknown Unknown High
226164_x_at FAM80B 0.011676 12p13.31 Protein modification process High
203881_s_at DMD 0.013194 Xp21.2 Cytoskeletal anchoring High
1552807_a_at SIGLEC10 0.015718 19q13.3 Cell adhesion High
202180_s_at MVP 0.021829 16p13.1-p11.2 Protein tran sport High
218243_at RUFY1 0.021861 5q35.3 Protein tran sport High
235372_at FCRLA 0.022754 1q23.3 Cell differentiation High
203028_s_at CYBA 0.024543 16q24 Superoxide metabolic process High
213674_x_at IGHD 0.027414 14q32.33 Immune response High
201518_at CBX1 0.028095 17q Chromatin assembly or
disassembly High
223207_x_at PHPT1 0.028239 9q34.3 Dephosphorylation High
219359_at ATHL1 0.028367 11p15.5 Carbohydrate metabolic
process High
208741_at SAP18 0.031401 13q12.11 Regulation of transcription,
DNA-dependent High
213436_at CNR1 0.035432 6q14-q15 G-protein coupled receptor protein signaling pathway
High
207713_s_at RBCK1 0.036438 20p13 Protein modification process High
214366_s_at ALOX5 0.037884 10q11.2 Leukotriene metabolic process High
1560225_at CNR1 0.039142 6q14-q15 G-protein coupled receptor protein signaling pathway
High
204409_s_at EIF1AY 0.039817 Yq11.222 Translational initiation High
202098_s_at PRMT2 0.040657 21q22.3 Signal transduction High
200701_at NPC2 0.041376 14q24.3 Phospholipid transport High
38671_at PLXND1 0.041874 3q21.3 Signal transduction High
201400_at PSMB3 0.042024 17q12 Ubiquitin-dependent protein
catabolic process High
211395_x_at FCGR2C 0.04339 1q23.3 Immune response High
202096_s_at TSPO 0.043686 22q13.31 Steroid metabolic process High
214933_at CACNA1A 0.043866 19p13.2-p13.1 Calcium ion tran sport High
202709_at FMOD 0.046059 1q32 Transforming growth factor beta
receptor complex assembly High
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45
200931_s_at VCL 0.046774 10q22.1-q23 Cell adhesion High
219922_s_at LTBP3 0.047574 11q12 Growth factor binding High
222245_s_at FER1L4 0.047758 20q11.22 Unknown High
214916_x_at Unknown 0.048092 Unknown Unknown High
203531_at CUL5 0.000005 11q22-q23 Negative regulation of cell
proliferation Low
211967_at TMEM123 0.000052 11q22.1 Receptor activity Low
227208_at CCDC84 0.000106 11q23.3 Unknown Low
221580_s_at JOSD3 0.000135 11q21 Protein binding Low
210538_s_at BIRC3 0.000364 11q22 Anti-apoptosis Low
201034_at ADD3 0.000439 10q24.2-q24.3 Structural constituent of
cytoskeleton Low
206126_at CXCR5 0.000442 11q23.3 G-protein coupled receptor
protein signaling pathway; B cell activation
Low
203642_s_at COBLL1 0.000554 2q24.3 Cell adhesion Low
217979_at TSPAN13 0.000573 7p21.1 Signal transduction Low
201753_s_at ADD3 0.000626 10q24.2-q24.3 Structural constituent of
cytoskeleton Low
1558662_s_at BANK1 0.000702 4q24 B cell activation Low
212672_at ATM 0.000942 11q22-q23 DNA repair Low
215145_s_at CNTNAP2 0.000976 7q35-q36 Cell adhesion Low
219300_s_at CNTNAP2 0.001104 7q35-q36 Cell adhesion Low
226247_at PLEKHA1 0.001461 10q26.13 Phospholipid binding Low
219667_s_at BANK1 0.001462 4q24 B cell activation Low
202265_at BMI1 0.001485 10p11.23 Regulation of transcription,
DNA-dependent Low
222808_at ALG13 0.001855 Xq23 Carbohydrate metabolic
process Low
209750_at NR1D2 0.001871 3p24.2 Regulation of transcription,
DNA-dependent Low
222446_s_at BACE2 0.002378 21q22.3 Proteolysis Low
201752_s_at ADD3 0.003297 10q24.2-q24.3 Structural constituent of
cytoskeleton Low
225123_at Unknown 0.003584 Unknown Unknown Low
231839_at 2'-PDE 0.003588 3p14.3 Unknown Low
222915_s_at BANK1 0.003882 4q24 B cell activation Low
205882_x_at ADD3 0.003983 10q24.2-q24.3 Structural constituent of
cytoskeleton Low
222728_s_at JOSD3 0.004153 11q21 Protein binding Low
219301_s_at CNTNAP2 0.004342 7q35-q36 Cell adhesion Low
203647_s_at FDX1 0.004429 11q22 Electron transport; steroid
metabolic process Low
243798_at Unknown 0.004629 Unknown Unknown Low
238587_at UBASH3B 0.004685 11q24.1 Negative regulation of
endocytosis Low
235626_at CAMK1D 0.004936 10p13 Protein amino acid
phosphorylation Low
213034_at KIAA0999 0.005176 11q23.3 Protein amino acid
phosphorylation Low
203544_s_at STAM 0.00541 10p14-p13 Signal transduction Low
206194_at HOXC4 0.005749 12q13.3 Regulation of transcription,
DNA-dependent Low
204912_at IL10RA 0.005817 11q23 Receptor activity Low
202600_s_at NRIP1 0.005833 21q11.2 Regulation of transcription,
DNA-dependent Low
224777_s_at PAFAH1B2 0.005932 11q23 Lipid metabolic process Low
222792_s_at CCDC59 0.00599 12q21.31 Regulation of transcription,
DNA-dependent Low
209191_at TUBB6 0.007009 18p11.21 Microtubule-based process Low
1568249_at SNORA71B 0.007033 20q11.23 Unknown Low
202038_at UBE4A 0.008139 11q23.3 Ubiquitin-dependent protein
catabolic process Low
212119_at RHOQ 0.009427 2p21 Small GTPase mediated signal Low
DOI: 10.3324/haematol.2011.049270
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transduction
204621_s_at NR4A2 0.009608 2q22-q23 Regulation of transcription,
DNA-dependent Low
207826_s_at ID3 0.009871 1p36.13-p36.12 Negative regulation of
transcription Low
212080_at MLL 0.010466 11q23 Regulation of transcription,
DNA-dependent Low
209081_s_at COL18A1 0.010766 21q22.3 Negative regulation of cell
proliferation Low
235739_at Unknown 0.011077 Unknown Unknown Low
225768_at NR1D2 0.01231 3p24.2 Regulation of transcription,
DNA-dependent Low
210279_at GPR18 0.012375 13q32 G-protein coupled receptor protein signaling pathway
Low
228528_at Unknown 0.0124 Unknown Unknown Low
226981_at MLL 0.012427 11q23 Regulation of transcription,
DNA-dependent Low
237040_at CWF19L2 0.013473 11q22.3 Unknown Low
229390_at FAM26F 0.013655 6q22.1 Unknown Low
230499_at Unknown 0.014818 Unknown Unknown Low
219228_at ZNF331 0.016173 19q13.41 Regulation of transcription,
DNA-dependent Low
212076_at MLL 0.016895 11q23 Regulation of transcription,
DNA-dependent Low
224642_at FYTTD1 0.01713 3q29 Unknown Low
204622_x_at NR4A2 0.017188 2q22-q23 Regulation of transcription,
DNA-dependent Low
210258_at RGS13 0.017358 1q31.2 G-protein coupled receptor protein signaling pathway
Low
234367_x_at TMPRSS6 0.017908 22q12.3 Intracellular signaling cascade Low
226763_at SESTD1 0.018889 2q31.2 Unknown Low
218750_at JOSD3 0.019124 11q21 Protein binding Low
235170_at ZNF92 0.020987 7q11.21 Regulation of transcription,
DNA-dependent Low
242920_at Unknown 0.022263 Unknown Unknown Low
216834_at RGS1 0.023097 1q31 Immune response; G-protein signaling, adenylate cyclase
inhibiting pathway Low
205419_at EBI2 0.024464 13q32.3
Immune response; G-protein
coupled receptor protein signaling pathway
Low
231124_x_at LY9 0.025138 1q21.3-q22 Immunoglobulin mediated
immune response Low
230128_at IGL 0.02922 22q11.1-q11.2 tRNA aminoacylation for protein
translation Low
216248_s_at NR4A2 0.029801 2q22-q23 Regulation of transcription,
DNA-dependent Low
217867_x_at BACE2 0.031937 21q22.3 Proteolysis Low
225954_s_at MIDN 0.038338 19p13.3 Protein modification process Low
227189_at CPNE5 0.042492 6p21.1 Signal transduction Low
233952_s_at ZNF295 0.043895 21q22.3 Regulation of transcription,
DNA-dependent Low
201525_at APOD 0.048048 3q26.2-qter Lipid metabolic process Low
DOI: 10.3324/haematol.2011.049270