the immune response to colorectal cancer: implications for ... · immune markers were identified...

The immune response to colorectal cancer:

Implications for prognosis

Paul Rameri Salama MBBS FRACS

School of Surgery

The University of Western Australia

This thesis is presented for the degree of Doctor of Philosophy The University of Western Australia

The research presented in this thesis was performed at the School of Surgery, Queen Elizabeth II Medical Centre, Nedlands,

The University of Western Australia, and the Pathology Laboratory at St John of God Hospital, Subiaco, Western Australia

2012

– i –

Declaration

This is to certify that this thesis does not incorporate, without

acknowledgement, any material previously submitted for a degree or

diploma from any university and that, to the best of my knowledge and

belief, does not contain any material previously published or written by

another person except where due reference is made in the text.

Signed Name Paul Rameri Salama

Date: 20 March 2012

– ii –

Abstract

Background

It has been known for several decades that infiltration of colorectal cancers

(CRCs) by host immune cells is beneficial. More recently it has been

demonstrated that specific immune cell subtypes have strong prognostic

significance. Some authors, however, expressed the view that tumours may

recruit inhibitory immune cells (Tregs – T regulatory cells) to suppress the

anti-tumour host response. As yet, however, measurement of immune cells

has not come into routine practice and tumour-node-metastasis (TNM)

remains the gold standard for prognostication. This generally serves us well;

however, robust markers are required for the identification of high risk stage

II CRC patients whose survival is highly variable and in whom the benefits

of adjuvant chemotherapy are uncertain.

Aims

� To identify and quantify previously examined immune cells (CD8+

and CD45RO+ T cells) within CRC that were previously known to

confer a beneficial prognostic effect.

� To identify and quantify Tregs and investigate their prognostic

significance within CRC.

� To compare the prognostic significance of Tregs with the active

component (GrB – Granzyme B) of CD8+ T cells.

� To validate the prognostic significance of tumour-infiltrating Tregs on

a separate patient cohort of stage II colon cancer.

– iii –

� To investigate the prognostic significance of immune markers within

histologically normal mucosa taken from the surgical margin of stage

II colon cancers.

Methods

Immune markers were identified with immunohistochemistry (IHC) and

quantified using digital image analysis. Aims 1-3 were performed on a

tissue microarray (TMA) consisting of tumour cores from 967 patients with

stage II and III CRC. Aims 4-5 were performed on “full face sections” from

independent cohort of 165 patients with colon cancer who did not receive

adjuvant chemotherapy.

Results

Chapter 3 (Aims 1-2)

� CD8+ and CD45RO+ T cells no longer retained prognostic

significance when the density of Tregs were assessed.

� A high density of tumour-infiltrating Tregs was an independent

prognostic marker for good prognosis.

� A high density of Tregs with the normal colonic mucosa was an

independent prognostic marker for poor prognosis.

� Prognostication of stage II cancers was significantly improved when

the density of Tregs were included in the multivariate analysis.

Chapter 4 (Aim 3)

� GrB, although associated with improved survival, was not an

independent prognostic marker. Low levels of GrB were found to be

– iv –

significantly associated with node positivity, vascular and perineural

invasion.

Chapter 5 (Aims 4-5)

� A high density of Tregs within lymphoid follicles found within the

normal colonic mucosa of the surgical margin, strongly predicted for

adverse cancer outcomes.

� A high frequency of lymphoid follicles within the normal mucosa was

an independent marker for good cancer outcomes for proximal

tumours.

� Vascular invasion in the most important standard histological marker

for stage II colon cancer.

Conclusions

This work has demonstrated that Tregs have strong prognostic significance

and can improve prognostication of stage II CRC. Furthermore, it has been

discovered that lymphoid follicles within the normal colonic mucosa

contain highly significant prognostic information. These findings support

the theory that immune parameters reflect the host’s susceptibility to the

development of metastasis and ultimately survival. Further research is

required to elucidate the underlying mechanisms.

– v –

Acknowledgements

The completion of this PhD thesis was dependent upon many factors and the

contributions of many people.

Heartfelt thanks go out to my Mentors and Supervisors.

My principal supervisor, Professor Barry Iacopetta, provided me with many

stimulating and enjoyable discussions. His critical appraisal of manuscripts

was pivotal in their subsequent publication.

My Co-Supervisor, Professor Cameron Platell, sets a wonderful and unique

example as a surgeon. Since the commencement of my surgical training in

2002, he has been a steady mentor, always encouraging me to go one step

further.

My sincere gratitude goes out to Fabienne Grieu and Lisa Spalding for

imparting their knowledge of IHC and their friendly help which made lab

work so enjoyable. A special thanks to Anne Marie Shearwood who showed

me the basics of image analysis.

I would also like to thank my parents for providing me with everything I

could ever need and for being so supportive over many years. I would

especially like to thank my wife Gemma and our three beautiful children for

all the love and happiness I experienced during this time.

– vi –

Statement of candidate contribution

This thesis contains published work which has been co-authored. The

bibliographical details of the work and where it appears in the thesis are

outlined below.

Chapter 1

Salama P, Platell C. Host response to colorectal cancer. ANZ J Surg. 2008;

78: 745-53.

Paul Salama retrieved and interpreted all the relevant literature. Drafting of

the manuscript was performed by Paul Salama and Prof Cameron Platell.

Chapter 3

Salama P, Phillips M, Grieu F, Morris M, Zeps N, Joseph D, Platell C,

Iacopetta B. Tumor-infiltrating FOXP3+ T regulatory cells show strong

prognostic significance in colorectal cancer. J Clin Oncol. 2009; 27: 186-92.

Paul Salama was involved in the conception, design and execution of

experimental work. PS performed the IHC of the TMA with the assistance

of Fabienne Grieu. PS also performed all high resolution scanning of the

glass slides and digital image analysis, including selection and optimisation

of algorithm, and annotation of all images. PS collected, analysed and

interpreted all data. Michael Phillips (Biostatistician) was consulted for

further expert assistance. Drafting of the manuscript was performed by Paul

Salama and Professor Barry Iacopetta.

– vii –

Chapter 4

Salama P, Phillips M, Platell C, Iacopetta B. Low expression of Granzyme

B in colorectal cancer is associated with signs of early metastastic invasion.

Histopathology. 2011 Aug;59(2):207-15.


experimental work. IHC and high resolution scanning was performed by

Fabienne Grieu and Anne Goebbels. PS performed all digital image

analysis, including selection and optimisation of algorithm, and checking of

all image annotations. PS collected, analysed and interpreted all data.

Michael Phillips (Biostatistician) was consulted for further expert

assistance. Drafting of the manuscript was performed by Paul Salama and

Professor Barry Iacopetta.

Chapter 5

Salama P, Stewart C, Forrest C, Platell C, Iacopetta B. FOXP3+ cell density

in lymphoid follicles from histologically normal mucosa is a strong

prognostic factor in early stage colon cancer. Cancer Immunol Immunother.

2012; 61(8):1183-90


experimental work. PS identified patients through a prospective database

and pathology records and retrieved all glass slides and blocks. PS

performed all IHC with the assistance of Lisa Spalding. PS also performed

all high resolution scanning of the glass slides and digital image analysis,

including selection and optimisation of algorithm, and annotation of all

– viii –

images. PS collected, analysed and interpreted all data. Drafting of the

manuscript was performed by Paul Salama and Prof Barry Iacopetta.

_______________________ (candidate)

Paul Rameri Salama

(Principal Supervisor)

Prof Barry Iacopetta

– ix –

Contents

Declaration................................................................................................................................................... i

Abstract....................................................................................................................................................... ii

Acknowledgements..................................................................................................................................... v

Statement of candidate contribution ....................................................................................................... vi

Contents ..................................................................................................................................................... ix

List of tables.............................................................................................................................................xiii

Abbreviations .......................................................................................................................................... xiv

1. Introduction: The immune response to colorectal cancer............................................................... 1

1.1. Background ......................................................................................................................................... 1

1.2. The host immune response to colorectal cancer.................................................................................. 2

1.3. Innate immunity .................................................................................................................................. 3

1.3.1. Innate humoral immunity ...................................................................................................... 4 1.3.2. Innate cellular immunity........................................................................................................ 4

1.3.2.1. Neutrophils....................................................................................................................... 5

1.3.2.2. Macrophages.................................................................................................................... 5

1.3.2.3. Natural killer cells ........................................................................................................... 6

1.3.2.4. Mast cells ......................................................................................................................... 7

1.4. Acquired immunity ............................................................................................................................. 8

1.4.1. Antigen recognition ............................................................................................................... 9 1.4.2. Dendritic cells...................................................................................................................... 10 1.4.3. Tumour-infiltrating lymphocytes......................................................................................... 12

1.4.3.1. CD4+ T cells................................................................................................................... 13

1.4.3.2. CD45RO+ memory T cells predict the absence of invasion and metastasis ....................................................................................................................... 14

1.4.3.3. CD8+ T cells have prognostic significance .................................................................... 14

1.4.3.4. Tumour location of tumour-infiltrating lymphocytes and colorectal cancer prognosis ............................................................................................................ 15

1.4.3.5. CD4+CD25+ Tregs ......................................................................................................... 16

1.4.3.6. Microsatellite instability and tumour-infiltrating lymphocytes...................................... 17

1.5. Prognostication of CRC .................................................................................................................... 18

1.6. Aims of this research......................................................................................................................... 19

1.6.1. Aim 1 ................................................................................................................................... 20

1.6.2. Aim 2 ................................................................................................................................... 20

1.6.3. Aim 3 ................................................................................................................................... 21

2. Methods ............................................................................................................................................. 23

2.1. Study populations.............................................................................................................................. 23

2.1.1. Study population – Cohort 1................................................................................................ 23 2.1.2. Study population – Cohort 2................................................................................................ 24

2.2. Construction of tissue microarray ..................................................................................................... 25

2.3. Immunohistochemistry...................................................................................................................... 25

– x –

2.4. High resolution scanning of glass slides ........................................................................................... 26

2.4.1. Digital image analysis – lymphocyte quantification............................................................ 31 2.4.2. Digital image analysis – Granzyme B quantification .......................................................... 34

2.5. Evaluation of full face sections – Cohort 2 (Chapter 5) .................................................................... 38

2.5.1. Pathology review of H&E slides ......................................................................................... 38 2.5.2. Immunohistochemical staining for FOXP3 ......................................................................... 38 2.5.3. Quantification of FOXP3+ Treg cell density in full face sections........................................ 38 2.5.4. Assessment of normal colonic mucosa from the surgical margin........................................ 39

2.6. Statistical analysis ............................................................................................................................. 40

2.6.1. Statistical methods used in Chapter 3 .................................................................................. 40 2.6.2. Statistical methods used in Chapter 4 .................................................................................. 40 2.6.3. Statistical methods used in Chapter 5 .................................................................................. 41

2.7. Immunohistochemistry protocols ...................................................................................................... 41

2.7.1. CD8 staining of tissue microarray ....................................................................................... 41 2.7.2. CD45RO staining of tissue microarray................................................................................ 43 2.7.3. FOXP3 staining of tissue microarray and full face sections ................................................ 44

2.7.4. GrB staining of tissue microarray........................................................................................ 45

3. T regulatory cells in colorectal cancer ............................................................................................ 49

3.1. Abstract ............................................................................................................................................. 49

3.2. Introduction....................................................................................................................................... 50

3.3. Materials and methods ...................................................................................................................... 52

3.4. Results............................................................................................................................................... 52

3.5. Discussion ......................................................................................................................................... 60

4. Granzyme B in colorectal cancer .................................................................................................... 68

4.1. Abstract ............................................................................................................................................. 68

4.2. Introduction....................................................................................................................................... 68

4.3. Methods............................................................................................................................................. 70

4.4. Results............................................................................................................................................... 70

4.4.1. Correlation of Granzyme B expression with T cell subtype densities...................................... 71

4.4.2. Correlation of Granzyme B expression with histopathological features and microsatellite instability status...................................................................................... 71

4.4.3. Prognostic significance of Granzyme B expression ............................................................ 73

4.5. Discussion ......................................................................................................................................... 77

5. Lymphoid follicles in colon cancer.................................................................................................. 83

5.1. Abstract ............................................................................................................................................. 83

5.2. Introduction....................................................................................................................................... 84

5.3. Methods............................................................................................................................................. 87

5.4. Results............................................................................................................................................... 87

5.5. Discussion ......................................................................................................................................... 94

– xi –

6. General discussion.......................................................................................................................... 102

6.1. Background ..................................................................................................................................... 102

6.1.1. Identification of high risk stage II colorectal cancer.......................................................... 102 6.1.2. Peritumoural inflammatory infiltrate is associated with improved

survival .............................................................................................................................. 103

6.1.3. Host immunity is important for surviving cancer .............................................................. 104 6.1.4. T helper type 1 immune cells are associated with improved survival................................ 104

6.2. Major findings................................................................................................................................. 106

6.2.1. Tumour-infiltrating Tregs have strong prognostic significance......................................... 106

6.2.2. Low expression of Granzyme B is associated with signs of early metastasis........................................................................................................................... 108

6.2.3. Immune parameters retain prognostic significance even when vascular and serosal invasion are carefully assessed ....................................................................... 108

6.2.4. Tregs within lymphoid follicles of histologically normal colonic mucosa are associated with adverse outcome.................................................................... 109

6.2.5. Lymphoid follicles within the normal colonic mucosa have a protective effect ................................................................................................................. 110

6.3. Future research................................................................................................................................ 110

6.4. Conclusions..................................................................................................................................... 112

6.4.1. Summary of major findings ............................................................................................... 112 6.4.2. Future studies emanating from this work........................................................................... 113

7. Bibliography ................................................................................................................................... 114

Appendices

– xii –

List of figures

Figure 1.1. Interactions between the immune system and the tumour cell. .............................................. 9

Figure 1.2. Presentation of tumour antigen by DCs. .............................................................................. 12

Figure 1.3. Locations of TILs................................................................................................................. 13

Figure 2.1. Example of a TMA section as displayed by ImageScope. ................................................... 25

Figure 2.2. TMA map: step 1. ................................................................................................................ 27

Figure 2.3. TMA map: step 2. ................................................................................................................ 28

Figure 2.4. The TMA work page............................................................................................................ 29

Figure 2.5. Full screen image of an individual core stained for GrB and viewed through Aperio ImageScope. ............................................................................................... 30

Figure 2.6. Example of FOXP3+ lymphocytes within a lymph follicle in the normal colonic mucosa before (left) and after (right) digital image analysis with the IHC nuclear algorithm. ............................................................................ 32

Figure 2.7. Representative area selected for analysis of GrB expression. .............................................. 35

Figure 2.8. Selected area analysed with the colour deconvolution algorithm. ....................................... 35

Figure 2.9. The colour deconvolution algorithm calibrated to detect DAB staining of GrB. ................................................................................................................................. 37

Figure 3.1. FOXP3 staining for Tregs in CRC. ...................................................................................... 54

Figure 3.2. CD8 staining of CRC. .......................................................................................................... 55

Figure 3.3. CD45RO staining of CRC.................................................................................................... 55

Figure 4.1. Kaplan-Meier survival analysis for CRC subgroups............................................................76

Figure 5.1. Section of histologically normal colonic mucosa from the surgical margin.................................................................................................................................. 89

Figure 5.2. (A) Representative low power image of normal colonic mucosa from the surgical margin. ............................................................................................................. 90

Figure 5.2. (B) High power image of lymphoid follicle showing immune cells stained positively for the FOXP3 marker. ........................................................................... 90

Figure 5.3. Kaplan-Meier survival analysis for stage II colon cancer patient subgroups............................................................................................................................. 93

Figure 6.1. In stage II CRC with no vascular, perineural or lymphatic invasion, the density of tumour-infiltrating Tregs can further stratify patients into low and high risk groups.................................................................................................... 107

– xiii –

List of tables

Table 2.1. Output from IHC nuclear algorithm. ................................................................................... 33

Table 3.1. Median density of the T cell markers CD8+, CD45RO+ and FOXP3+ in normal colonic mucosa (N) and in colorectal tumour (T) tissues (cells/mm2)........................................................................................................................... 53

Table 3.2. Associations between T cell marker densities in normal (N) and tumour (T) tissue from CRC patients. .................................................................................. 56

Table 3.3. Univariate analysis for associations between high density of tumour-infiltrating T cell types and pathological features of CRC. ................................................. 57

Table 3.4. Univariate survival analysis for pathological features and for T cell density in normal and malignant colorectal tissue from stage II and III CRC patients. Cox proportional hazards regression method. .............................................. 58

Table 3.5. Multivariate analysis showing the significant prognostic indicators in stage II and stage III CRC (n=445)...................................................................................... 59

Table 3.6. Multivariate analysis for prognostic significance of pathological features and T cell marker density in stage II CRC. ............................................................ 60

Table 4.1. Correlations between GrB expression and the density of T cell subtypes in the normal colonic mucosa (N) and tumour (T) tissue of CRC patients................................ 71

Table 4.2. Associations between the expression of GrBT and histopathological markers in CRC. .................................................................................................................. 72

Table 4.3. Associations between GrBT/FOXP3+T and histopathological markers

in CRC. ................................................................................................................................ 74

Table 4.4. Univariate survival analysis for the prognostic significance of GrBT expression in CRC stage and MSI subgroups...................................................................... 74

Table 4.5. Multivariate analysis for the prognostic significance of histopathological and immune cell markers in CRC............................................................ 77

Table 5.1. Clinical and histopathological features of 165 stage II colon cancers. ................................ 87

Table 5.2. FOXP3+ Treg density (cells/mm2) in tumour tissue and in lymphoid follicles from histologically normal colonic mucosa at the surgical margin.................................................................................................................................. 88

Table 5.3. Univariate survival analysis for clinicopathological features and FOXP3+ Treg density in stage II colon cancer.....................................................................92

Table 5.4. Multivariate analysis for indicators of cancer-specific survival in stage II colon cancer. .................................................................................................................... 92

– xiv –

Abbreviations

CART Classification and Regression Tree

CRC Colorectal cancer

DAB Diaminobenzidine

DC Dendritic cells

EMVI Extramural vascular (venous) invasion

FOXP3 Transcription factor forkhead box P3

GrB Granzyme B

GrBT GrB in tumour tissue

HR Hazard ratio

IHC Immunohistochemistry

mGPS Modified Glasgow Prognostic Score

MHC Major histocompatibility complex

MSI Microsatellite instability

MSS Microsatellite stable

NK Natural killer

qRT-PCR Quantitative reverse transcription-PCR

TGF-β Transforming growth factor beta

Th1 T helper type 1

Th2 T helper type 2

TILs Tumour-infiltrating lymphocytes

TMA Tissue microarray

TNM Tumour-node-metastasis

Tregs T regulatory cells

Introduction:

The immune response to colorectal cancer

This introduction is based on a review published in the ANZ Journal of

Surgery (Salama and Platell, vol 78: p 745-53, 2008). It reflects the state of

knowledge in the literature at June 2007 just prior to undertaking the

experimental work for this study.

Introduction: The immune response to colorectal cancer

– – 1

1. Introduction: The immune response to colorectal cancer

1.1. Background

The prognosis for patients with CRC has traditionally been predicted by the

tumour’s histological features. Although this approach has been in use for

the last century, there is now widespread recognition that more accurate

prognostic indicators are required. While most attention has been focused

on biomarkers such as oncogenes and tumour suppressor genes, there is now

also a renewed interest in the host immune response to CRC as a prognostic

factor.

It has long been established that inflammation and immunity play critical

roles in the pathogenesis, invasion and eventual metastasis of cancers. The

advent of sophisticated animal models and immunological markers has led

to a greater understanding of the host response to cancer. Individual immune

cells are dynamic structures that have variable behaviour controlled by

complex interactions within the tumour micro-environment. In the setting of

CRC it was first observed that peritumoural inflammatory infiltrates were

associated with improved prognosis. IHC has revealed the individual cell

types within these infiltrates. It now appears that an adaptive immune

response, differentiated along the T helper type 1 (Th1) pathway, controls

tumour invasion and metastasis. Furthermore, the immune system exerts

selection pressure leading to the evolution of tumour cell variants that can

induce tolerance and disable adaptive immunity. These tumour cells then

utilise the mechanisms of innate immunity to facilitate further growth,

angiogenesis, invasion and eventual metastasis. Harnessing the immune


– – 2

response to defeat CRC has been a topic of intense investigation, but has so

far proven unsuccessful. Nevertheless some researchers remain optimistic

that immunotherapy will play an important role in the treatment of this

common disease.

1.2. The host immune response to colorectal cancer

“The function of the immune system is to prevent takeover of the body by

genomes other than that encoded in the germ line. Central to this function is

the ability to kill (Nathan, 2006).”

The colon and rectum represent unique environments in the human body.

They form an important interface between the external environment and the

host’s immune system. A relatively large number of immune competent

cells line the bowel wall and interact with high concentrations of foreign

antigens in a tolerogenic but active manner. This interface is separated by

millimetres from the peritoneal cavity that is primed through its local

defence mechanisms to react aggressively to any breach in the bowel’s

continuity.

A number of early observations served to highlight the interaction between

the host and CRC. Patients who suffered post-operative sepsis (i.e.

anastomotic leaks) were found to have worse stage-adjusted prognosis from

their cancers (Law et al., 2007), suggesting that systemic inflammation may

promote the progression of metastases (Coussens et al. 2006). On the other

hand, it was observed that the presence of large numbers of lymphocytes

adjacent to the primary tumour seemed to inhibit its progression (Dunn et

al., 2002).


– – 3

Clearly, the host’s immune response and the local tissue environment are

important for the development and progression of CRCs. Two current

theories serve to highlight these observations. Firstly, a “smouldering”

inflammatory environment favours the development of cancers (Balkwill et

al., 2005). Secondly, cancers actively escape the normal immune

mechanisms that serve to destroy abnormal genetic material (Dunn et al.,

2002). In other words, the selective pressure exerted by the immune system

allows the evolution of tumour cells that are able to “escape” or proliferate

undetected. These cancers are less immunogenic and hence this process has

been called immunoediting (Dunn et al., 2002).

This introduction seeks to explore the immune system and its influence on

the development and progression of CRC.

1.3. Innate immunity

The innate immune response serves to combat pathogens and exists

regardless of prior exposure (Abbas et al., 2001, Roitt, 1997). It does not

improve with repeated exposure to pathogen. The innate immune response

in the gut consists initially of physical barriers to infection (mucous,

enterocytes and the bowel wall). If pathogens succeed in penetrating these

barriers they are confronted by phagocytic cells (neutrophils and

macrophages), the inflammatory and complement pathways, and the

humoral responses (e.g. acute phase protein and cytokine production).

Within the abdomen, these mechanisms are concentrated in the bowel wall,

peritoneal cavity and omentum.


– – 4

1.3.1. Innate humoral immunity

Innate humoral immunity refers to a layer of defence against

microbiological agents mediated by soluble factors (Roitt, 1997). Innate

humoral immunity can act by inducing the acute inflammatory state either

by the complement cascade or activation of macrophages. Under normal

circumstances, this serves as a defence against invading organisms and

allows for the initiation of wound healing. The release of pro-inflammatory

cytokines (TNF-α, IL-1β and IL-6) by cells of the innate immune system

has a range of effects including increased vascular permeability, the

expression of adhesion molecules, chemotaxis of inflammatory cells,

angiogenesis, influx of fibroblasts and regeneration of epithelial layers.

Macrophages are central in maintaining a chronic inflammatory state.

(Balkwill 2005) Cancers benefit from the presence an inflammatory state to

promote their own growth, invasion and metastases. (Coussens et al., 2002,

Balkwill et al., 2005) Chronic inflammation of the bowel increases the risk

of colon cancer while the use of aspirin and non-steroidal anti-inflammatory

medications reduces the risk. (Coussens et al., 2002, Balkwill et al., 2005)

1.3.2. Innate cellular immunity

Typically around colon cancers there exists some degree of inflammatory

infiltrate. The cells that form the infiltrate tend to be within the stroma of

the tumour rather than within the epithelial component. (Banner et al., 1993,

Jackson et al., 1996) There is limited data on the individual cell types that

form this infiltrate, although the majority are lymphocytes. Svennevig et al.

reported that 47% were lymphocytes, 19% plasma cells, 15% macrophages,

15% neutrophils and 5% mast cells (Svennevig et al., 1982).


– – 5

1.3.2.1. Neutrophils

Neutrophils are present in the circulation in large numbers and respond

rapidly to tissue injury (Abbas et al., 2001). They have the ability to destroy

host connective tissue and cells along with cellular structures that contain

foreign DNA (Nathan, 2006). In so doing they stimulate the inflammatory

cascade and trigger adaptive immunity by sending signals to monocytes,

dendritic cells (DCs) and lymphocytes. Importantly, by their signalling, they

influence the type of response from these various immune cells (Nathan,

2006). Neutrophils may form up to 15% of the inflammatory infiltrate

associated with CRCs and this proportion increases within areas of tumour

necrosis (Svennevig et al., 1982). In patients with rectal cancer, high

tumoural densities of neutrophils are independent predictors of improved

prognosis, especially in association with microscopic abscesses (Uehara et

al., 2007).

1.3.2.2. Macrophages

Macrophages are derived from circulating monocytes and are present within

the bowel wall (Abbas et al., 2001). They are long-lived cells that perform a

phagocytic function to defend the body from intracellular organisms and

possibly cancer cells (Abbas et al., 2001, Roitt, 1997). They also secrete

pro-inflammatory cytokines (IL-1β, TNF-α). Macrophages form an

important bridge to the acquired immune response. They do this by

producing IL-12 and TNF-α that cause lymphocyte proliferation and

differentiation. Macrophages can also function as antigen presenting cells

and thereby initiate the acquired immune response.


– – 6

In patients with CRC, macrophages are found particularly around necrotic

areas of tumour and the advancing tumour margin (Ambe et al., 1989).

Some studies have found that high levels of tissue macrophages are

associated with earlier disease stage, absence of nodal and lympho-vascular

metastases and an overall better prognosis (Funada et al., 2003, Tan et al.,

2005). A high level of macrophage infiltration in combination with a high

T cell infiltration was associated with even better prognosis than

macrophages alone (Funada et al., 2003).

In contrast, other authors have reported that macrophages can promote the

development of CRC based upon observations that the number of

macrophages increases with tumour stage (Dalerba et al., 2003). In theory,

macrophages play a central role in the production of a chronic inflammatory

state (Balkwill et al., 2005). Tumour-associated macrophages through

release of cytokines, promote angiogenesis and the growth of tumour stroma

while inhibiting adaptive immunity (Balkwill et al., 2005). Depending on

context, macrophages could either promote a chronic inflammatory state or

play an important supporting role for the adaptive immune response.

1.3.2.3. Natural killer cells

Natural killer (NK) cells are granule-containing lymphocytes that form part

of the innate cellular immune response. They kill cells infected with

intracellular organisms and activate macrophages by secreting interferon

gamma (Abbas et al., 2001). Cytotoxic T cells share the same cytolytic

mechanism as NK cells (described below) (Roitt, 1997). NK cells also

facilitate the maturation of DCs and thus provide an important link between

innate and adaptive immunity (Zou, 2005). In CRC, a high number of NK


– – 7

cells in the inflammatory infiltrate is associated with better prognosis

(Kubota et al., 1992; Coca et al., 1997; Koda et al., 1997; Menon et al.,

2004; Tachibana et al., 2005). The number of NK cells decreases with

increasing cancer stage (Kubota et al., 1992). Similarly, low pre-operative

levels of blood NK cell activity in patients undergoing curative resections

are associated with disease recurrence (Koda et al., 1997). It has been

postulated that NK cells can rapidly eliminate tumour cells without prior

exposure, whereas cytotoxic T cells require prior sensitisation and therefore

more time to become effective (Menon et al., 2004). The NK/CD3+CD69+

ratio in the peripheral blood was found to have prognostic significance on

multivariate analysis in patients with colon cancer (Vesely et al., 2005) It is

also of interest that 5-FU based chemotherapy increases the number of NK

cells in the peripheral blood (Holcombe et al., 1999).

1.3.2.4. Mast cells

Mast cells are located predominantly in the muscularis mucosa and lamina

propria of the bowel wall. They are best known for immediate

hypersensitivity (allergic) reactions and IgE-mediated inflammatory

reactions (Abbas et al., 2001; Parslow, 2001). Mast cells interact with the

adaptive immune response by expressing surface receptors for IgE.

Degranulation of mast cells results in acute inflammation (Abbas et al.,

2001; Roitt, 1997; Parslow, 2001). This can be mediated either through

soluble factors of the complement cascade or IgE (allergic). Similar to other

immune cell types, a high number of mast cells is associated with earlier

CRC stage (Tan et al., 2005) and improved survival (Nagtegaal et al., 2001;

Nielsen et al., 1999). Interestingly, the number of mast cells progressively


– – 8

decreases from normal mucosa through premalignant conditions and the

lowest numbers are seen in cancers (Lachter et al., 1995).

1.4. Acquired immunity

The acquired immune response consists of defence mechanisms that are

customised to recognise each particular pathogen (Abbas et al., 2001; Roitt,

1997). On first exposure, these mechanisms may have a weak response, but

on subsequent exposures they rapidly become more effective. This response

is dependent on the molecular recognition and presentation of both

intracellular and extracellular antigens to T cells that mediate the production

of antibodies and apoptosis of infected cells. The gut-associated lymphoid

tissue represents one of the largest immune organs in the body and so has a

major capacity for acquired immune responses.

The innate and acquired immune responses are linked. Neutrophils and the

complement cascade (innate) together with antibody production (acquired)

are important defence mechanisms against extracellular organisms. On the

other hand, macrophages, NK cells, cytokines (innate) and T cells

(acquired) are responsible for intracellular infections (Roitt, 1997). The

immune response may have dual effects against cancer, as shown in Figure

1. 1. The ongoing activation of innate immune cells may actually promote

tumour growth by producing cytokines and growth factors. In contrast, the

adaptive immune response may inhibit tumour growth by exerting direct

effects on cancer cells (Sacchi et al., 2003).


– – 9

Figure 1.1. Interactions between the immune system and the tumour cell.

From Salama, 2008.

1.4.1. Antigen recognition

The critical event in the acquired immune response is the recognition of

non-self. This process is heavily dependent on what are termed “recognition

molecules”. Such molecules include the Class 1 major histocompatibility

complex (MHC) proteins that are expressed on almost all adult cells and are

important for the presentation of intracellular antigens to immune competent

cells (Roitt, 1997). Class II MHC proteins are expressed only on

macrophages, antigen presenting cells and B lymphocytes and are important

for presenting extracellular antigens to relevant cells.

One mechanism by which cancers cells can evade the acquired immune

response is by their failure to express MHC class I. CD8+ cytotoxic T cells

can only destroy target cells when antigens are presented in association with

MHC class I. It now appears that loss of MHC class I expression is an


– – 10

important mechanism by which cancer cells evade cytotoxic CD8+ T cells

(Dalerba et al., 2003; Titu et al., 2002) The selection of cancer cells with

loss of antigen presenting machinery is in keeping with the theory of tumour

escape and immunoediting (Figure 1.1) (Dunn et al., 2002). Although loss

of MHC class I may protect tumour cells from attack by CD8+ T cells, it

predisposes them to lysis by NK cells. It remains unclear how the loss of

MHC class I expression influences the peritumoural lymphocytic infiltrate

and whether this has any effect on prognosis (Dalerba et al., 2003; Sandel et

al., 2005; Watson et al., 2006; van den Ingh et al., 1987).

Normal colonic epithelial cells rarely express MHC class II proteins. They

can be stimulated to do so under the influence of inflammatory cytokines,

resulting in the subsequent ability to present antigens (Dalerba et al., 2003).

In contrast to normal colonic epithelial cells, MHC class II is expressed in a

high proportion of colon cancer cells (42%). Well differentiated tumours are

more likely to express MHC class II proteins. Higher rates of lymphatic

invasion and lymph node metastases are associated with colon cancers that

lack MHC class II expression (Matsushita et al., 2006; Warabi et al., 2000).

However, no relationship has been found between the expression of MHC

class II on tumour cells and the presence of lymphocytic infiltrate. It would

appear that expression of MHC class II proteins by cancer cells allows the

host to develop a more effective immune response against the tumour.

1.4.2. Dendritic cells

DCs are the most important antigen presenting cells in the body and are

derived from the bone marrow (Abbas et al., 2001; Roitt, 1997). They are

present in the gut wall and peritoneal cavity and have characteristic thin


– – 11

cytoplasmic projections that give them a stellar shape. DCs present antigens

to resting CD4+ T cells in association with MHC type II proteins, leading to

activation of the latter cells (see Figure 1.2). Once antigens have been

captured in the gut wall, DCs migrate to regional lymph nodes where they

regulate both the innate immune response (via NK cells) and the adaptive

immune response (via cytotoxic lymphocytes) (Browning et al., 1996). In

CRC, the DC forms clusters with CD4+, CD8+ and CD45RO+ T cells at the

invasive margin of the tumour (Suzuki et al., 2002).

High numbers of DCs in CRC are associated with the density of

lymphocytic infiltrate and with the degree of paracortical hyperplasia in

regional lymph nodes (Ambe et al., 1989, Dadabayev et al., 2004). This

suggests DCs regulate the immune response both at the site of the primary

cancer and in the lymph nodes (Ambe et al., 1989). The presence of DCs in

direct contact with cancer cells (ie. the intraepithelial compartment) is

associated with higher numbers of CD45+, CD4+ and CD8+ T cells and

with improved survival (Ambe et al., 1989). In contrast, DCs in the stroma

do not show these correlations (Sandel et al., 2005). The anti-cancer activity

of DCs is influenced by their activation status, location and the micro-

environment. Under aseptic conditions, tumour tolerance is likely to

develop if DCs capture a tumour antigen and presents it to T cells in the

draining lymph nodes. If, however, the same antigen is presented under

conditions of acute inflammation, an effective immune response is more

likely to occur (Melero et al., 2006; Sporri et al., 2005; Sakaguchi et al.,

2003). Therefore, factors in the tumour environment affect DC activation


– – 12

which may then determine the nature of the immune response ie. tumour

tolerance or cytotoxic response (see Figure 1.2).

Figure 1.2. Presentation of tumour antigen by DCs. From Salama, 2008.

1.4.3. Tumour-infiltrating lymphocytes

Lymphocytes are the most abundant cell in the immune system and tumour-

infiltrating lymphocytes (TILs) appear to have the strongest impact on CRC

prognosis of all the immune cell types evaluated so far (Pagès et al., 2005;

Nagtegaal et al., 2001). T cell lymphocytes are identified by the marker

CD3. The important lymphocytic subtypes for CRC prognosis are CD4+

T cells, CD8+ T cells and CD45RO+ T cells. Not only is the function of

these cells important but also their location relative to the tumour. Three

arbitrary tumour compartments have been described: the tumour epithelium,

the tumour stroma and the advancing margin (Naito et al., 1998; Figure

1.3).


– – 13

Figure 1.3. Locations of TILs.

A) advancing margin, B) tumour stroma, C) intraepithelial. (Taken from Dalerba et al., 2003).

1.4.3.1. CD4+ T cells

CD4+ T cells play an important role in driving the immune response and

determining its nature. They recognise antigens in association with MHC

class II on antigen presenting cells (eg DCs) to become T helper cells that

respond in one of two ways depending on their subsequent differentiation

(Roitt, 1997). Naïve CD4+ T helper cells differentiate into either Th1 cells

in response to intracellular pathogens or T helper type 2 (Th2) cells in

response to extracellular pathogens (Roitt, 1997). This process is controlled

by the presence of specific cytokines (Sazbo et al., 2003). Macrophages

produce IL-12 which causes differentiation of naïve T cells into Th1 cells.

NK cell derived IL-4 is responsible for differentiation of naïve CD4+ T

helper cells into Th2 cells (Roitt, 1997). Th1 cells are responsible for the

initiation of cell-mediated immunity characterised by CD8+ cytotoxic

T cells. In the setting of CRC, CD4+ T cells are thought to differentiate

along the invasive margin into Th1 cells (Musha et al., 2005). Cancer cells

are analogous to intracellular infections in that they contain “foreign” DNA

and are capable of taking over the body. The Th1 response thus promotes


– – 14

CD8+ T cell mediated immunity and is therefore protective in patients with

CRC (Pagès et al., 2005, Sazbo et al., 2003, Galon et al., 2006).

1.4.3.2. CD45RO+ memory T cells predict the absence of invasion and metastasis

CD45RO+ T cells, sometimes referred to as “effector-memory” T cells

(Galon et al., 2006), mediate reactive memory in response to antigenic

stimulation (Sallusto et al., 2004). These cells are highly sensitive to

antigenic stimulation and strongly activate DCs (Sallusto et al., 2004). Once

antigenic presentation occurs they initially produce IL-2 and subsequently

proliferate and differentiate into effector cells (Sallusto et al., 2004).

Subsets of CD4+ and CD8+ T cells persist as quiescent memory cells and

may therefore explain the phenomenon of immunosurveillance (Sallusto et

al., 2004). These cells are considered as part of the Th1 adaptive immune

response. Infiltration of CRCs with high numbers of CD45RO+ T cells has

been associated with the absence of vascular, lymphatic and perineural

invasion and lymph node metastasis (Pagès et al., 2005) These cells may

therefore play an important role at the primary tumour site to suppress

invasion and subsequent metastasis.

1.4.3.3. CD8+ T cells have prognostic significance

The CD8+ T cell response is mediated by differentiation of T cells along the

Th1 pathway. Cells and mediators of this pathway have been associated

with improved prognosis in CRC (Pagès et al., 2005; Galon et al., 2006;

Menon et al., 2004; Nagtegaal et al., 2001; Chiba et al., 2004; Naito et al.,

1998; Prall et al., 2004). CD8+ T cells recognise antigens associated with

MHC class I proteins on target cells leading to destruction through the


– – 15

release of perforin and granzymes (Roitt, 1997). Perforin creates a pore in

the target cell through which granzymes enter and trigger apoptosis (Roitt,

1997). CD8+ T cells located within tumour cell nests, as opposed to the

stroma or invasive margin, are most significantly associated with improved

survival (Chiba et al., 2004; Naito et al., 1998).

CD8+ T cells appear to play an important role in immuno-surveillance. A

high CD8+/CD4+ T cell ratio and a high frequency of activated CD8+

T cells in colon cancer was associated with the presence of activated anti-

cancer T cells in the blood and bone marrow. The density of CD8+ T cell

infiltration was inversely correlated with tumour stage (Menon et al., 2004;

Naito et al., 1998; Koch et al., 2006) and was higher in tumours that did not

show early signs of invasion (Pagès et al., 2005) Increasing CRC stage has

also been correlated with deactivation of CD8+ T cells (Koch et al., 2006).

The degree of infiltration with CD8+ T cells has been claimed to have

comparable prognostic significance as Duke’s staging (Naito et al., 1998).

Some researchers have concluded these cells must therefore suppress CRC

progression (Pagès et al., 2005). Alternatively, as the tumour phenotype

develops greater invasive and metastatic potential, it simultaneously evolves

to evade and actively inhibit the immune response. This could explain why

more advanced tumours show a less pronounced immune response.

1.4.3.4. Tumour location of tumour-infiltrating lymphocytes and colorectal cancer prognosis

The location of TILs in relation to the tumour appears to be of importance in

predicting survival from CRC. Naito et al. demonstrated that CD8+ cells

within cancer cell nests were more important for prognosis than those at the


– – 16

advancing margin or tumour stroma (Naito et al., 1998). In a much larger

study, Galon et al. used TMA to examine the immune response both at the

centre of the tumour and at the invasive margin (Galon et al., 2006).

Tumours with high numbers of adaptive immune response cells (CD8+,

CD3+, CD45RO+) in both areas showed better survival, independently of T

stage, lymph node involvement and differentiation (Galon et al., 2006).

Furthermore, the ratio of CD3+ cells in the centre of the tumour to the

invasive margin was the most significant predictor for overall survival

amongst the variables evaluated, including TNM staging.

1.4.3.5. CD4+CD25+ Tregs

Not all lymphocytes in a cancer are thought to be beneficial. Tregs are

CD4+CD25+ lymphocytes that have been reported to modulate the immune

response, in particular the Th1 response (Oldenhove et al., 2003; Curiel et

al., 2007). FOXP3 has proven to be an accurate marker for Tregs (Roncador

et al., 2005). These cells inhibit anti-tumour CD8+ and CD4+ T cells

through the production of cytokines (IL-10 and transforming growth factor

beta – TGF-β) and through cell to cell contact (Curiel et al., 2007). Tregs

have been found at elevated levels in the primary tumours and peripheral

blood of cancer patients (Zou, 2005; Curiel et al., 2007). The presence of

Tregs favours the development of immune tolerance and diminishes the

cytotoxicity of CD8+ T cells (Zou, 2005). A high density of tumour-

infiltrating FOXP3+ Tregs has been associated with poor outcome in

various solid tumours including ovarian (Curiel et al., 2004; Sato et al.,

2005), pancreatic (Hiraoka et al., 2006) and hepatocellular carcinoma

(Kobayashi et al., 2007; Gao et al., 2007). The failure of various anti-cancer


– – 17

immunotherapies, particularly adoptive T cell transfer, has been attributed

to the inhibitory effects of Tregs (June et al., 2007). The Treg depleting

drug Denileukin difitox has been found to have some beneficial effect in

certain cancer types such as cutaneous T cell leukaemia and melanoma

(Curiel et al., 2007). There is very limited data on the role of Tregs in CRC

patients (Loddenkemper et al., 2006, Ling et al., 2007) and anti-Treg

immunotherapies have yet to be trialled in this cancer type (Correale et al.,

2005).

1.4.3.6. Microsatellite instability and tumour-infiltrating lymphocytes

The microsatellite instability (MSI) phenotype arises because of defects in

DNA mismatch repair genes. MSI is a hallmark of tumours from patients

with the familial cancer condition known as Lynch Syndrome. However,

most MSI CRCs arise sporadically following age-related methylation of the

MLH1 mismatch repair gene. CRC with MSI are characterised by extensive

lymphocytic infiltration in addition to a poorly differentiated and mucinous

phenotype. Clinically these tumours tend to occur in the proximal colon and

have a better prognosis than sporadic CRC (Prall et al., 2004; Phillips et al.,

2004; Dolcetti et al., 1999, Guidoboni et al., 2001). The lymphocytic

infiltrates comprise predominantly activated cytotoxic CD8+ T cells

(Phillips et al., 2004; Michael-Robinson et al., 2001) and are associated

with high rates of tumour cell apoptosis (Phillips et al., 2004; Michael-

Robinson et al., 2001). Whether MSI status is an independent prognostic

indicator for survival is controversial (Gryfe et al., 2000). Prall et al. (2004)

demonstrated that MSI positivity in combination with CD8+ T cell


– – 18

infiltration was associated excellent prognosis, particularly in patients who

received 5 FU-based chemotherapy.

1.5. Prognostication of CRC

It has been established for some decades now that a peritumoral infiltrate is

associated with better survival outcomes (Jass et al., 1986). Now it appears

that a Th1 immune response, characterised by cytotoxic CD8+ T cells,

confers this advantage (Jass, 1985). Naito et al. (1998) were the first to

identify that cytotoxic CD8+ T cells have prognostic significance and their

impact on survival is similar to Dukes’ staging. Almost a decade later,

Galon et al. (2006) claimed the type, density and location of immune cells

predicted clinical outcome and were superior to currently used TNM

staging. They postulated that the Th1 immune response suppresses vascular,

lymphatic and perineural invasion (Pagès et al., 2005).

These findings by Pagès and Galon have not been widely reproduced, and

prognostication with the TNM staging system remains the standard of care.

The major use of staging is to determine risk of recurrence and therefore

which patients should have adjuvant therapies. The Australian NHMRC

2005 guidelines recommend that all stage III patients receive adjuvant

chemotherapy. The guidelines state that adjuvant chemotherapy should not

be given for stage II disease except for selected high risk cases who should

be entered into a clinical trial. Unfortunately there are no guidelines to

identify high risk stage II patients despite the 5-year disease free survival for

this group ranging between 51-73% (Gill et al., 2004).


– – 19

A recent population based study of patients with stage II CRC revealed that

T4 stage and vascular invasion were the only histopathological prognostic

markers for cancer specific mortality (Morris et al., 2006). It was also

demonstrated in the same population that chemotherapy conferred a survival

advantage for stage II patients (Morris et al., 2007) Unfortunately, these

histopathological prognostic markers tend to be under-reported even though

their presence reflects the risk of disease specific mortality (Stewart et al.,

2007).

In the study populations by Naito (1998), Pagès (2005) and Galon (2006),

pathology sections were not re-evaluated for vascular and serosal invasion,

therefore it is not known if immune markers are indeed better than careful

histopathological assessment. In addition, a variety of molecular markers

(eg MSI, thymidylate synthase, MSI, p53, Kras and deleted in colon cancer)

have been developed. Again, there appears insufficient evidence for their

use as routine prognostic markers (Duffy et al., 2007). It remains, however,

that more accurate methods are required for prognostication of stage II

patients.

1.6. Aims of this research

It is now clear that the host attempts to mount an immune response against

CRC. The strength of this response can be measured and has prognostic

value. It remains to be established whether the immune response suppresses

metastases and invasion or whether the occurrence of these phenomena

coincide with the cancer cells’ evolution to evade the host response through

active inhibition of cytotoxic cells and the induction of tolerance. Current


– – 20

literature would suggest that cancers in general can inhibit host immunity

through the release of cytokines and the recruitment of Tregs.

1.6.1. Aim 1

Several studies have demonstrated that the lymphocytic response has

prognostic significance in CRC. The published data suggests that CD8+ and

CD45RO+ lymphocytes are the cells of greatest importance. As yet, the

prognostic significance of FOXP3+ Tregs has not been determined.

Aim 1: Do FOXP3+ Tregs have prognostic significance in CRC?

This aim was addressed in Chapter 3. The results from this work were

published in: Paul Salama, Fabienne Grieu, Melinda Morris, Michael

Phillips, Nik Zeps, David Joseph, Cameron Platell, Barry Iacopetta.

Tumour-infiltrating T regulatory cells show strong prognostic significance

in colorectal cancer. Journal of Clinical Oncology 2009; 27: 186-192.

1.6.2. Aim 2

FOXP3+ Tregs were demonstrated to have strong prognostic significance in

CRC. In addition, high concentrations were associated with improved

survivial which was in contrast to other solid tumourtypes. The mechanism

underlying this observation has not been determined. GrB (the effector

molecule) is utilised by the cytotoxic T cells of the adaptive immune

response to facilitate target cell killing.

Aim 2: Does the level of GrB within the tumour explain the prognostic

significance of FOXP3+ Tregs?


– – 21

This aim was addressed in Chapter 4. The results of this work were

published in: Salama P, Phillips M, Platell C, Iacopetta B. Low expression

of Granzyme B in colorectal cancer is associated with signs of early

metastastic invasion. Histopathology. 2011; 59: 207-15.

1.6.3. Aim 3

The results from Chapter 3 revealed that measurement of FOXP3+ Treg

density allowed for more accurate prognostication of stage II CRC.

Furthermore, the density of FOXP3+ Tregs within the normal colonic

mucosa had strong prognostic significance.

Aim 3.1: Does the quantification of FOXP3+ Tregs give any further

prognostic information after careful assessment of vascular and serosal

invasion?

Aim 3.2: What is the prognostic significance of immune parameters within

the normal colonic mucosa taken from the surgical margin?

This aim was addressed in Chapter 5. The results of this work have been

published in: Paul Salama, Colin Stewart, Cynthia Forrest, Cameron Platell,

Barry Iacopetta. FOXP3+ cell density in lymphoid follicles from

histologically normal mucosa is a strong prognostic factor in early stage

colon cancer. Cancer Immunology Immunotherapy. 2012; 61: 1183-90

Chapter 2: Methods

Chapter 2: Methods

– – 23

2. Methods

2.1. Study populations

2.1.1. Study population – Cohort 1 Cohort 1 comprised of 967 consecutive patients with stage II and stage III

colon and rectal cancer who underwent surgical resection at the Sir Charles

Gairdner Hospital, Western Australia, between 1991 and 1999. Normal and

tumour tissue blocks from this CRC population were used to construct the

TMA used in Chapters 3 and 4. Information on patient demographics (sex

and age) and the tumour features (shown in Table 3.3) were obtained from

the pathology record of each case. Tumour site was classified as proximal to

and including, or distal, to the splenic flexure. A total of 593 AJCC stage II

and 374 AJCC stage III CRC comprised the total of 967 cases. Information

on T stage, anatomical site, histological grade, vascular invasion, lymphatic

invasion, perineural invasion, lymphocytic response and MSI determined

using the BAT-26 marker was available for 100, 96, 65, 76, 72, 70, 91 and

95% of cases, respectively. Compared with the five panel marker, BAT-26

has been shown to have a high sensitivity for the detection of MSI tumours

(Loukola et al., 2001).

Information on disease-specific survival was obtained from the Cancer

Registry of Western Australia. The median follow-up time for patients with

AJCC stage II disease was 69.7 months and for patients with stage III it was

52.4 months. Information on the use of adjuvant chemotherapy with 5-

FU/leucovorin-based regimens was obtained from hospital medical records.

Seven percent of stage II and 37% of stage III cases received 5FU. At the

Chapter 2: Methods

– – 24

end of the study period, 31% of patients had died of disease recurrence and

25% from other causes. Ethics approval was obtained from the Sir Charles

Gairdner Hospital Human Research Ethics Committee.

2.1.2. Study population – Cohort 2

Patients with stage II colon cancer (n=165) who underwent curative

resection between 1996 and 2006 at the Fremantle and St John of God

hospitals were identified from a prospectively maintained clinical database

and corresponding pathology records. This CRC cohort was used in the

studies described in Chapter 5.

Exclusion criteria were positive surgical margins and the use of adjuvant

chemotherapy. Surgery was performed by four specialist colorectal

surgeons in a standardised manner to ensure adequate resection margins and

lymph node harvest. There were no significant differences between

surgeons for either lymph node harvest (mean=16.8, SD=7.7) or patient

survival. Tumour site was classified as proximal or distal according to

location relative to the splenic flexure. Information on patient demographics

and tumour features were obtained from the pathology report. Cancer-

specific survival information was obtained from the Cancer Registry of

Western Australia and from medical records. The median length of follow-

up time was 72 months. At the end of the study period 27 patients (16%)

had died from recurrence of their cancer and a further 37 patients (22%) had

died from other causes. Ethics approval for the project was obtained from

the Human Research Ethics Committees of the Fremantle and St John of

God hospitals.

Chapter 2: Methods

– – 25

2.2. Construction of tissue microarray

Construction of the TMA for Cohort 1 has been described elsewhere (Chai

et al., 2004). Briefly, formalin-fixed and paraffin-embedded tissue blocks

and the corresponding H&E stained slides were retrieved from pathology

archives. A pathologist marked on the H&E glass slide the area of tissue to

be cored from the corresponding block. One tissue core was taken from

normal colonic mucosa – usually from the surgical margin – while two

cores were taken at random from the tumour. Each core was 1mm in

diameter and was placed into a recipient paraffin block. The histology

(normal or tumour) along with the pathology specimen number,

histopathological details and clinical outcome were recorded by way of an

“x-y” coordinate system. Thin sections for IHC were cut from the paraffin

blocks containing the tissue cores (Figure 2.1).

Figure 2.1. Example of a TMA section as displayed by ImageScope.

2.3. Immunohistochemistry

IHC of TMA sections (Cohort 1) was performed at the School of Surgery

QEII Medical Centre, University of Western Australia, while IHC of full

Chapter 2: Methods

– – 26

face sections (Cohort 2) was carried out at St John of God Hospital,

Subiaco, WA. The CD8, CD45RO, and GrB antibodies were purchased

commercially from Dako, Copenhagen, Denmark and the FOXP3 antibody

was purchased from Abcam, United Kingdom. Detailed IHC protocols for

these antigens are shown in Section 2.7.

2.4. High resolution scanning of glass slides

Glass slides were scanned with a high resolution scanner [ScanScope XT,

Aperio] at 40X magnification. This created virtual slides upon which digital

image analysis was performed.

Each TMA slide was segmented into x and y coordinates with the

specialised software TMA lab v8.0 [Aperio] for results described in Chapter

3, and Spectrum v10 [Aperio] for results described in Chapter 4. Each TMA

core was assigned an x-y coordinate which allowed matching of patient data

to the core and for a score to be assigned by the digital image analysis

software (see Figures 2.2-2.4). Figures 2.2 - 2.4 are screen saves from

Spectrum v10.

Chapter 2: Methods

– – 27

Figure 2.2. TMA map: step 1.

A TMA map is created by determining the number of rows and columns. The x-y coordinates are placed accordingly.

Chapter 2: Methods

– – 28

Figure 2.3. TMA map: step 2.

The TMA map created in step 1 is placed over the digitised image of the TMA section, thus allowing each core to be assigned an x-y coordinate.

Chapter 2: Methods

– – 29

Figure 2.4. The TMA work page.

The top left corner displays the identifying coordinates by row and column with a visual representation. A thumbnail of the core is displayed bottom left. The results of analysis are displayed at the bottom right of page.

Chapter 2: Methods

– – 30

A full screen image of each individual core was viewed through an

accompanying software package [ImageScope version 9]. This provided

high resolution of the image with zooming, thus allowing careful annotation

of individual cores (Figure 2.5).

Figure 2.5. Full screen image of an individual core stained for GrB and viewed through Aperio ImageScope.

The green line is a manual annotation which marks the area to be analysed.

Chapter 2: Methods

– – 31

2.4.1. Digital image analysis – lymphocyte quantification

Included in the Aperio package were digital image analysis algorithms

which allowed objective quantification of positive diaminobenzidine (DAB)

stain within a defined area. The IHC nuclear algorithm v9 [Aperio] was

initially designed to quantify nuclear staining; however, it was also

successfully used to calculate the number of positively staining

lymphocytes. With minimal adjustment of the algorithm parameters,

positively staining lymphocytes were accurately quantified (Figure 2.6).

Integral to this process was annotation of the digital image. The area of

interest was manually annotated using a mouse or Wacom Tablet pen tool.

The density of the individual cell types for each core was calculated by

dividing the cell count (as quantified by the algorithm) by the area. The

algorithm creates an output table (example shown in Table 2.1) from which

data can be collected and analysed.

Chapter 2: Methods

– – 32

Figure 2.6. Example of FOXP3+ lymphocytes within a lymph follicle in the normal colonic mucosa before (left) and after (right) digital image analysis with the IHC nuclear algorithm.

Chapter 2: Methods

– – 33

The post digital image analysis was: Red 3+, strong staining; Orange 2+,

medium staining; Yellow 1+, weak staining; Blue 0+, no stain. The

algorithm output is shown in Table 2.1.

Table 2.1. Output from IHC nuclear algorithm.

Percent positive nuclei 25.5435

Intensity score 3

(3+) percent nuclei 22.9097




Average positive intensity 131.771

Average negative intensity 239.317

(3+) nuclei 548

(2+) nuclei 42

(1+) nuclei 21

(0+) nuclei 1781

Total nuclei 2392

Average nuclear RGB intensity 160.813

Average nuclear size (pixels) 1042.31

Average nuclear size (um2) 66.0331

Area of analysis (pixels) 8293288

Area of analysis (mm2) 0.52540382

FOXP3+ lymphocyte density is calculated by dividing the total number of

positively staining (3+, 2+ and 1+ nuclei) lymphocytes by the analysed area.

Density = total lymphocytes / area

= (548 + 42 + 21) / (0.52540382)

= 1162.92 FOXP3+ cells per mm2

The densities of CD8+, CD45+ and FOXP3+ lymphocytes were calculated in

the same way.

Chapter 2: Methods

– – 34

In Chapter 3, the evaluation of T cell marker density was carried out blinded

to clinicopathological information. Individual cores were examined by one

observer [PS] and annotated to ensure that only normal colonic epithelium

or viable tumour tissue was included in the area of analysis. No attempt was

made to evaluate the various tumour compartments separately (eg. stroma,

tumour cell nests). Results for cell density were exported into an Excel file

and individual cores were matched to corresponding clinicopathogical data.

2.4.2. Digital image analysis – Granzyme B quantification

Quantification of GrB expression was carried out using the colour

deconvolution algorithm [Aperio]. The GrB stain appeared as fine granules

within the cytoplasm of cytotoxic CD8+ T cells and NK cells (Figures 2.7

and 2.8). The nuclear algorithm described above was inadequate at

quantifying such small granules. The colour deconvolution algorithm

(Figure 2.9) separates the image into three channels depending on the stains

used (Colour Deconvolution Algorithm User’s Guide, 2007). The default

colour channels are Colour 1 haematoxylin; Colour 2 Eosin; and Colour 3

DAB. Each colour channel is calibrated by determining the Red Green Blue

(RGB) component of each stain. The algorithm can be calibrated to detect

any stain by calibrating the RGB component of the Colour Channel. Since

GrB was stained with DAB, only Colour Channel 3 was used.

Chapter 2: Methods

– – 35

Figure 2.7. Representative area selected for analysis of GrB expression.

Figure 2.8. Selected area analysed with the colour deconvolution algorithm.

Red = strong staining, Orange = moderate staining, Yellow = weak staining, Blue = no stain.

Rather than counting the number of positively staining cells for GrB, a score

(0-300) was calculated by the colour deconvolution algorithm.

• % Weak = % of analysed area with weak staining

• % Medium = % of analysed area with moderate staining

• % Strong = % of analysed area with strong staining

Score = 1.0*(%Weak) +2.0*(%Medium) + 3.0*(%Strong)

Chapter 2: Methods

– – 36

The intensity (detection) thresholds (weak, moderate or strong staining)

were calculated by the colour deconvolution algorithm as calibrated by the

user. The Threshold Intensity scale ranged from 0 (Black) to 240 (Clear

Area). The critical step was to determine the “weak” threshold at which the

algorithm would reject light background non-specific staining but still

detect weak but positively staining GrB granules. The “weak” threshold was

set after a process of careful trial and error. Areas of obvious or gross non-

specific staining were excluded from analysis by careful manual annotation.

Chapter 2: Methods

– – 37

Figure 2.9. The colour deconvolution algorithm calibrated to detect DAB staining of GrB.

The Thresholds determine the staining intensity as weak, moderate or strong.

Colour 3 is calibrated to detect DAB staining through its RGB components.

Positive Colour Channel indicates the colour the algorithm is detecting

The Threshold Intensity scale ranges from 0 (Black) to 240 (Clear Area).

Colour 1 and Colour 2 have been calibrated to detect haematoxylin and eosin respectively.

The algorithm can be calibrated to detect any stain by calibrating the RGB component of the Colour Channel.

Chapter 2: Methods

– – 38

2.5. Evaluation of full face sections – Cohort 2 (Chapter 5)

2.5.1. Pathology review of H&E slides

For Cohort 2, the original H&E slides were retrieved and reviewed by a

pathologist (Dr Colin Stewart) for the presence of serosal invasion and

extramural vascular venous invasion (EMVI) as described previously

(Stewart et al., 2007). EMVI was diagnosed only when there was

unequivocal involvement of muscularised vessels in the pericolic fat.

Serosal invasion was defined as a breach of the serosal surface by tumour

cells. The pathologist was blinded to the original pathology report.

Formalin-fixed, paraffin embedded tissue blocks that optimally

demonstrated the invasive tumour margin, together with histologically

normal colonic mucosa from the surgical margin were retrieved for IHC

analysis of FOXP3+ cell density.

2.5.2. Immunohistochemical staining for FOXP3

Refer to section 2.7 for full IHC staining protocol.

2.5.3. Quantification of FOXP3+ Treg cell density in full face sections

Following IHC staining for FOXP3, slides were scanned with a high-

resolution scanner [ScanScope XT; Aperio] at 40X magnification. Image

analysis software [Spectrum v10] was used to calculate the density of

stained cells (cells per mm2) as described in Chapter 2.5.1. The images

were examined by one observer [PS] who was blinded to the

clinicopathological data and were annotated to ensure that only normal

colonic epithelium or viable tumour tissue was included in the area of

analysis. Initial attempts to analyse the whole tumour section were not

Chapter 2: Methods

– – 39

feasible due to multiple software failures resulting from the large size of the

images. The density of FOXP3+ lymphocytes was measured at the tumour

core and at the invasive margin. The tumour core was defined as solid areas

of tumour excluding areas of necrosis, stroma or advancing margin. Using

digital image analysis (Chapter 2.4.1) the number of FOXP3+ lymphocytes

was evaluated in five representative areas (each 1mm2) and an average

density was obtained. The invasive margin was defined as the most

advanced front of the tumour beyond the muscularis propria and can be

considered as the interface between tumour and surrounding tissue. Five

representative areas (each 0.25mm2) were used to calculate the average

density of FOXP3+ lymphocytes at the invasive margin. Results for

FOXP3+ Treg density were exported into an Excel file and matched to

corresponding clinicopathologic data for each case.

2.5.4. Assessment of normal colonic mucosa from the surgical margin

Normal colonic mucosa at the surgical margin was assessed for the total

number of lymphoid follicles per centimetre. For proximal colon tumours

the normal sample was always from the distal margin, while for distal

tumours it was from either the proximal or distal ends of the resection. The

length of muscularis mucosa was measured with a pen tool and image

analysis software was used to calculate the number of lymphoid follicles per

centimetre of normal colonic mucosa.

The density of FOXP3+ Tregs within each lymphoid follicle present in or

just below the mucosa was evaluated by digital image analysis in the same

way as for the tumour sections. The perimeter of individual lymphoid

follicles was annotated to determine their area in mm2 and the number of

Chapter 2: Methods

– – 40

FOXP3+ Tregs within that area was determined using the algorithm

described in Chapter 2.4.1. In cases where multiple follicles were present,

the average FOXP3+ cell density was determined.

2.6. Statistical analysis

2.6.1. Statistical methods used in Chapter 3

The normality and log-normality of the distributions of continuous variables

was examined using the Shapiro-Wilks test. Variables with a log-normal

distribution were transformed using a natural logarithm. Analysis of the

association between variables was conducted using the Pearson correlation

coefficient, t-test and one-way ANOVA for transformed variables where

appropriate. The family-wise error rate was controlled by use of the Holm

adjustment for multiple comparisons. T cell densities were classified as

“high” or “low” in relation to the median value. Associations with survival

were explored using the Cox proportional hazards regression model.

Multivariate models were constructed according to methods described by

Harrell and assessed using Harrell’s concordance statistic C (Harrell et al.,

1996). The analysis was conducted using the Stata statistical package

[Version 9, StataCorp LP, College Station, TX, 2005].


Analysis of the associations between GrB scores and other immune cell

densities and histopathological markers (AJCC stage, vascular invasion,

etc.) was performed using Spearman’s correlation coefficient (non-

parametric test). Associations with cancer-specific survival were explored

using Kaplan-Meier analysis and a Cox proportional hazards regression

Chapter 2: Methods

– – 41

model. Cut-off values were determined by the median or by Classification

and Regression Tree (CART) analysis to identify high risk groups. The

analyses were performed using SPSS version 17 and STATA version 9

statistical packages [StataCorp, College Station, TX, USA].


Statistical analysis for cancer-specific survival was performed using Cox

proportional hazards regression modelling [STATA version 11 statistical

package, STATA Corp, College station, TX]. The parameters of FOXP3+

cell density and number of lymphoid follicles per centimetre of mucosal

length were classified as high or low in relation to the median value.

Logistic regression was used to explore associations between

clinicopathological variables and the density of FOXP3+ cells in tumour and

normal tissues. For the multivariate analysis, all variables with a P value of

<0.1 in univariate analysis were initially included. Non-significant variables

were removed sequentially. Kaplan-Meier survival curves with log-rank

values were generated for selected variables.

2.7. Immunohistochemistry protocols

2.7.1. CD8 staining of tissue microarray

Protocol for Dako Monoclonal Mouse Anti-Human CD8: Clone C8/144B:

• Affix sections (3-4µm) to charged slides and air-dry over night at

37oC.

• Incubation in oven at 60oC for 20 min.

• Dewax and rehydrate sections through descending alcohols to

distilled water.

Chapter 2: Methods

– – 42

• Transfer to Dako Target Retrieval Sol pH 6 (S1699) and heat at

121oC for 5 min in Decloaker pressure cooker.

• Allow slides to cool down to 90oC then remove container of slides

from Decloaker and allow cooling for a further 20 min before

transferring to TBS pH 7.3.

• Endogenous peroxidise activity is blocked by incubating the sections

with Dako-Real Peroxidase block Solution for 5 min.

• Wash sections twice in TBS for 5 min, the second containing 0.1%

Tween 20.

• Non-specific antibody binding is inhibited by incubating the sections

with Dako Protein Block Solution for 10 min.

• Decant excess blocking solution from the sections and apply the

primary antibody N 1592 (ready to use) for 10 min.

• Wash in 2 changes of TBS-T.

• Incubate sections with Labeled Polymer HRP Rabbit/mouse for 15

min.

• Wash sections in 2 changes of TBS-T.

• WEAR GLOVES

• Incubate sections with Dako-Chromogen Solution for 8 min.

• Wash sections in 2 changes of deionised water.

• Sections are lightly counterstained in Mayers haematoxylin, then

dehydrated through ascending graded alcohols, cleared in xylene and

mounted using Depex.

Chapter 2: Methods

– – 43

2.7.2. CD45RO staining of tissue microarray

Protocol for Dako Monoclonal Mouse Anti-Human CD45RO: Clone

UCHL1

• Affix sections (3-4µm) to charged slides and air-dry over night at

37oC.

• Incubation in oven at 60oC for 20 min.


distilled water.

• Transfer to Dako Target Retrieval Sol pH 6 (S1699) and heat at

121oC for 5 min in Decloaker pressure cooker.

• Allow slides to cool down to 900C then remove container of slides

from Decloaker and allow cooling for a further 20 min before

transferring to TBS pH 7.3.


with Dako-Real Peroxidase block Solution for 5 min.

• Wash sections twice in TBS, the second containing 0.1 % Tween 20

for 5 min.

• Nonspecific antibody binding is inhibited by incubating the sections

with Dako Protein Block Solution for 10 min.


primary antibody N 1592 (ready to use) for 8 min.


• Incubate sections with Labelled Polymer HRP Rabbit/mouse for 15

min.

• Wash sections in 2 changes of TBS-T.

Chapter 2: Methods

– – 44

• WEAR GLOVES

• Incubate sections with Dako-Chromogen Solution for 4 min.


• Sections are lightly counterstained in Mayers haematoxylin, then

dehydrated through ascending graded alcohols, cleared in xylene and

mounted using Depex.

2.7.3. FOXP3 staining of tissue microarray and full face sections

Protocol for Abcam Mouse Monoclonal Anti-Human FoxP3 antibody:

Clone 236A/E7

• Affix sections (3-4µm) to charged slides and air dry overnight at

37oC.

• Incubate in oven at 60oC for 20 minutes.


distilled water.

• Transfer to Dako Target Retrieval Sol pH 9 and heat at 121oC for 4

minutes for TMA or 6 minutes for full face sections in Decloaker

pressure cooker

• Allow slides to cool down to 90oC.

• Allow to cool for a further 20 minutes in water bath.

• Transfer to TBS

• Endogenous peroxidise activity is blocked by incubating sections for

5 minutes with Dako Real Peroxidase Block solution.

• TBS wash for 5 minutes and wash again in TBS-Tween for 5

minutes

Chapter 2: Methods

– – 45

• Incubate with Dako Protein Block Solution for 10 min to inhibit

non-specific protein binding.

• Decant excess blocking solution

• Apply the primary antibody (1:100 dilution) and incubate for 60

minutes.

• Wash in two changes of TBS-T

• Incubate sections with labelled Polymer HRP Rabbit/mouse for

30min


• WEAR GLOVES

• Incubate sections with Dako-Chromogen Solution for 8 minutes.


• Sections are lightly counterstained in Meyer’s haematoxylin for 30

seconds then dehydrated through ascending graded alcohols, cleared

in xylene and mounted using Depex.

2.7.4. GrB staining of tissue microarray

• Affix sections (4-5µm) to charged slides and air-dry overnight at

37oC.

• Incubation in oven at 60oC for 20 minutes.


distilled water.

• Transfer to Dako Target Retrieval Solution pH 9.9 (S3308) and heat

at 121oC for 5 minutes in Decloaker pressure cooker.

Chapter 2: Methods

– – 46

• Allow slides to cool down to 90oC then remove contained of slides

from Decloaker and allow to cool for a further 20 minutes before

transferring to TBS pH 7.3 for 5 minutes.


with Dako Real Peroxiase Block Solution for 5 minutes.

• Wash Sections in two changes of TBS, the last one containing 0.1%

Tween 20 (TBS-T) for 5 minutes.

• Non-specific antibody binding is inhibited by incubating the sections

with Dako Protein Block Solution for 10 minutes.


primary antibody M 7235 for 30 minutes (dilute 1:50 with antibody

diluent).

• Wash in two changes of TBS-T.

• Incubate sections with Biocare MACH3 mouse probe for 20

minutes.


• Incubate sections with Biocare MACH3 polymer- HRP for 10

minutes.


• WEAR GLOVES

• Incubate Sections with Dako Chromogen Solution (20 µl Bottle C

for 1ml Bottle B) for 8 minutes.

• Wash sections in 2 changes of deionised water

Chapter 2: Methods

– – 47

• Sections are lightly counterstained in Mayers haematoxylin (15sec)

then dehydrated through ascending alcohols, cleared in xylene and

mounted using depex.

Chapter 3: Tregs in CRC

The work described in this chapter was published in:

Salama P, Phillips M, Grieu F, Morris M, Zeps N, Joseph D, Platell C,

Iacopetta B. Tumour-infiltrating FOXP3+ T regulatory cells show strong

prognostic significance in colorectal cancer. J Clin Oncol. 2009; 27: 186-92.

Chapter 3: T regulatory cells in colorectal cancer

– – 49

3. T-regulatory cells in colorectal cancer

3.1. Abstract

The purpose of this chapter is to determine the prognostic significance of

FOXP3+ lymphocyte (Treg) density in CRC compared with conventional

histopathologic features and with CD8+ and CD45RO+ lymphocyte

densities. TMA and IHC were used to assess the densities of CD8+,

CD45RO+, and FOXP3+ lymphocytes in tumour tissue and normal colonic

mucosa from 967 stage II and stage III CRCs. These were evaluated for

associations with histopathologic features and patient survival.

FOXP3(+) Treg density was higher in tumour tissue compared with normal

colonic mucosa, whereas CD8+ and CD45RO+ cell densities were lower.

FOXP3+ Tregs were not associated with any histopathologic features, with

the exception of tumour stage. Multivariate analysis showed that stage,

vascular invasion, and FOXP3+ Treg density in normal and tumour tissue

were independent prognostic indicators, but not CD8+ and CD45RO+. High

FOXP3+ Treg density in normal mucosa was associated with worse

prognosis (hazard ratio [HR]=1.51; 95% CI, 1.07 to 2.13; P=.019). In

contrast, a high density of FOXP3+ Tregs in tumour tissue was associated

with improved survival (HR=0.54; 95% CI, 0.38 to 0.77; P=.001).

FOXP3+ Treg density in normal and tumour tissue had stronger prognostic

significance in CRC compared with CD8+ and CD45RO+ lymphocytes. The

finding of improved survival associated with a high density of tumour-

infiltrating FOXP3+ Tregs in CRC contrasts with several other solid cancer


– – 50

types. The inclusion of FOXP3+ Treg density may help to improve the

prognostication of early stage CRC.

3.2. Introduction

It has been known for many years that lymphocytic infiltrate surrounding

primary CRC is associated with improved prognosis (House et al., 1979;

Svennevig et al., 1984; Jass et al., 1986; Halvorsen et al., 1989; Murphy et

al., 2000; Ohtani et al., 2007). Although the mechanism remains unclear,

the adaptive immune system is thought to play an important role in

suppressing the progression of this disease. Naito et al. were the first to

demonstrate that infiltrating CD8+ cytotoxic T cells were a prognostic

factor in CRC (Naito et al., 1998). These findings have since been

supported by the work of other groups (Nagtegaal et al., 2001; Menon et al.,

2004; Prall et al., 2004; Chiba et al., 2004). A high density of CD8+ T cells

has been associated with the absence of tumour invasion, earlier stage and

improved patient survival (Pagès et al., 2005; Koch et al., 2006). Using

CD3 as a universal marker of T cells, the ratio of T cell density at the

advancing tumour margin compared to the central core was recently

proposed as having stronger prognostic significance than conventional TNM

staging (Galon et al., 2006).

Another T cell subtype shown to have prognostic significance in CRC was

CD45RO+ (Pagès et al., 2005; Oberg et al., 2002). These cells include both

CD4+ and CD8+ lymphocytes that have been exposed to antigen. Oberg et

al. (2002) reported that a high density of CD45RO+ cells in lymph node

metastases of CRC was associated with improved prognosis, while Pagès et


– – 51

al. (2005) subsequently demonstrated that a high density of CD45RO+ cells

within the tumour was associated with decreased invasiveness, lower stage

and improved survival. The above findings provide clear evidence that the

host immune response plays an important role in determining the outcome

from CRC.

Tregs were initially characterised by the CD4+CD25+ phenotype and are

thought to modulate the anti-tumour immune response (Curiel, 2007; Zou,

2006). Tregs can suppress the activity of cytotoxic T cells through direct

cell to cell contact or via the release of cytokines, especially TGF-β.

Depletion of intra-tumoural Tregs enhances anti-tumour immunity and

tumour rejection in mouse models (Needham et al., 2006). Similarly,

depletion of Tregs in the peripheral blood of CRC patients was recently

shown to unmask CD4+ T cell responses to tumour antigens (Clarke et al.,

2006). The most specific Treg cell marker identified to date is the nuclear

transcription factor known as FOXP3 (Fontenot et al., 2003; Hori et al.,

2003). A high density of tumour-infiltrating FOXP3+ Tregs has been

associated with poor outcome in various solid tumours including ovarian

(Curiel et al., 2004; Sato et al., 2005), pancreatic (Hiraoka et al., 2006) and

hepatocellular carcinoma (Kobayashi et al., 2007; Gao et al., 2007).

Two groups have investigated infiltrating Tregs in CRC using FOXP3

staining. In a study of 40 patients, Loddenkemper et al. (2006) reported that

Treg density was lower in node positive disease but was not associated with

survival. Ling et al. (2007) found no significant difference in Treg density

between advanced and early stage disease, but did not evaluate the


– – 52

association with patient survival. The aim of the present study was therefore

to compare the prognostic value of FOXP3+ Treg cell density with that of

the established T cell markers CD8+ and CD45RO+ in a large cohort of

stage II and III CRC with long follow-up information.

3.3. Materials and methods

The patient cohort studied in this Chapter, together with the

immunohistochemical techniques, image analysis and statistical techniques

are described in Chapter 2.

3.4. Results

Examples of immunohistochemical staining using the CRC TMA are shown

for Tregs in Figure 3.1, CD8 in Figure 3.2 and CD45RO in Figure 3.3. The

densities of these cell types in tumour and adjacent normal mucosal areas

were quantified following high resolution scanning and image analysis at

40x magnification as described in Chapter 2.

A total of 6,202 images of normal and tumour tissue cores were used for the

analysis of T cell marker density in 593 stage II and 374 stage III CRC. A

log normal distribution was observed for the density of each marker. The

densities of CD8+ and CD45RO+ cells in tumour tissue (denoted CD8+T

and CD45RO+T) were lower compared to those of normal tissue (CD8+N

and CD45RO+N), whereas the FOXP3+ cell density was higher in tumour

tissue (Table 3.1). This observation was made for both the median and

geometric mean.


– – 53

Table 3.1. Median density of the T cell markers CD8+, CD45RO+ and

FOXP3+ in normal colonic mucosa (N) and in colorectal tumour (T) tissues

(cells/mm2).

Marker Normal (N) Tumour (T) Tumour/Normal ratio P

CD8+ 322 (704) 147 (910) 0.46 <0.0001

CD45RO+ 1287 (686) 935 (912) 0.73 <0.0001

FOXP3+ 44 (644) 116 (905) 2.64 <0.0001


– – 54

Figure 3.1. FOXP3 staining for Tregs in CRC.

The upper panel shows a 1mm tumour core from the TMA, while the lower panel

is a 40x magnification. The cells showing brown reaction product in their nucleus

with the FOXP3 antibody are Tregs.


– – 55

Figure 3.2. CD8 staining of CRC.

Magnification 40X.

Figure 3.3. CD45RO staining of CRC.

Magnification 40X.


– – 56

Correlations between the T cell markers are shown in Table 3.2. The

densities of markers were strongly associated with each other in normal and

in tumour tissues. The densities of CD8+T and CD45RO+T also correlated

with those of CD8+N and CD45RO+N from the same patient. However,

only a very weak correlation was observed between FOXP3+T and

FOXP3+N (r=0.041).

Table 3.2. Associations between T cell marker densities in normal (N) and tumour (T) tissue from CRC patients.

Correlation coefficient (r) P

Normal tissue

CD8+N vs CD45RO+

N 0.510 <0.0001

CD8+N vs FOXP3+

N 0.273 <0.0001

CD45RO+N vs FOXP3+

N 0.446 <0.0001

Tumour tissue

CD8+T vs CD45RO+

T 0.516 <0.0001

CD8+T vs FOXP3+

T 0.446 <0.0001

CD45RO+T vs FOXP3+

T 0.439 <0.0001

Normal vs tumour

CD8+N vs CD8+

T 0.306 <0.0001

CD45RO+N vs CD45RO+

T 0.164 <0.0001

FOXP3+N vs FOXP3+

T 0.041 0.011

Associations between the density of tumour-infiltrating T cells and

pathological features are shown in Table 3.3. Tumours with higher AJCC or

T stage were found to have lower densities of all three markers. The density

of CD45RO+T was significantly lower in tumours showing early signs of

metastasis (vascular and perineural invasion); however, this was not

observed for CD8+T or FOXP3+T. As expected, CD8+T and CD45RO+T

cell densities were higher in tumours reported as showing a lymphocytic


– – 57

response or MSI. In contrast, FOXP3+T was not associated with either of

these features. No significant associations were observed between the

density of T cell markers in CRC and patient age or gender (results not

shown).

Table 3.3. Univariate analysis for associations between high density of tumour-infiltrating T cell types and pathological features of CRC.

CD8+T CD45RO+

T FOXP3+T

Feature OR P OR P OR P

AJCC

Stage II 1.00 1.00 1.00

Stage III 0.60 <0.0001 0.57 <0.0001 0.86 0.0004

T stage

1+2 1.00 1.00 1.00

3+4 0.80 NS 0.61 0.002 0.51 0.007

Tumour site

Proximal 1.00 1.00 1.00

Distal 0.86 0.017 0.84 0.031 1.07 NS

Histological grade

Well/moderate 1 1 1

Poor 1.06 NS 1.21 NS 0.87 NS

Vascular invasion

Absent 1.00 1.00 1.00

Present 1.01 NS 0.77 0.009 0.94 NS

Lymphatic invasion

Absent 1.00 1.00 1.00

Present 0.96 NS 0.93 NS 1.13 NS

Perineural invasion

Absent 1.00 1.00 1.00

Present 0.80 NS 0.67 0.013 0.81 NS

Lymphocytic response

Absent 1.00 1.00 1.00

Present 1.42 <0.0001 1.24 NS 1.10 NS

MSI

Absent 1.00 1.00 1.00

Present 1.99 <0.0001 2.52 <0.0001 1.10 NS


– – 58

T cell densities were classified as “high” or “low” in relation to the median value.

Table 3.4 shows the results of univariate survival analysis for the major

pathological features and for T cell marker density in normal and tumour

tissue. Higher stage and the presence of vascular or perineural invasion were

strongly associated with worse patient outcome. A high density of CD8+N

was associated with better survival, whereas a high density of FOXP3+N was

associated with significantly worse outcome. High densities for each of the

T cell markers in tumour tissue were associated with good patient outcome,

including that of FOXP3+T. In exploratory subgroup analysis of stage III

patients, the good prognosis associated with high T cell marker density in

tumour tissue appeared to be limited to patients treated by surgery alone.

Table 3.4. Univariate survival analysis for pathological features and for T cell density in normal and malignant colorectal tissue from stage II and III CRC patients. Cox proportional hazards regression method.

Feature HR 95% CI P

Tumour feature

AJCC (III vs II) 3.07 2.44-3.88 <0.0001

Site (distal vs proximal) 1.04 0.82-1.31 NS

Grade (poor vs well/moderate) 1.73 1.17-2.57 0.006

Vascular invasion (yes vs no) 2.49 1.90-3.26 <0.0001

Lymphatic invasion (yes vs no) 2.39 1.50-3.86 0.0009

Perineural invasion (yes vs no) 1.99 1.32-3.00 0.001

Lymphocytic response (yes vs no) 0.64 0.44-0.95 0.026

Microsatellite instability (yes vs no) 0.60 0.38-0.94 0.027

T cell density (high vs low)

CD8+N 0.81 0.71-0.91 0.001

CD45RO+N 1.01 0.83-1.22 NS

FOXP3+N 1.19 1.05-1.36 0.007

CD8+T 0.74 0.67-0.82 <0.0001

CD45RO+T 0.74 0.65-0.84 <0.0001

FOXP3+T 0.78 0.70-0.87 <0.0001


– – 59

A multivariate model was used to identify independent prognostic factors in

the combined stage II and III CRC cohort (Table 3.5). The model included

all histopathological variables and T cell markers found to have significant

prognostic value in univariate analysis (Table 3.4). This analysis revealed

that tumour stage, vascular invasion, FOXP3+N and FOXP3+T were the only

markers to show independent prognostic significance. It also confirmed that

high densities of FOXP3+N and FOXP3+T were associated with opposite

effects on patient outcome. FOXP3+:CD8+ and FOXP3+:CD45RO+ ratios in

normal and tumour tissues were also examined and found not to be

significant in multivariate analysis.

Table 3.5. Multivariate analysis showing the significant prognostic indicators in stage II and stage III CRC (n=445).

NOTE: Cox proportional hazards regression model.

Feature HR 95% CI P

AJCC stage (III vs II) 3.29 2.25-4.81 <0.001


FOXP3+N (high vs low) 1.51 1.07-2.13 0.019

FOXP3+T (high vs low) 0.54 0.38-0.77 0.001

Accurate prognostic markers are of most importance clinically for the

stratification of stage II CRC. A multivariate model was therefore

developed to test for independent prognostic significance of pathological

features and of T cell densities in stage II cases (Table 3.6). In the first

model (A), only the major pathological features were included. This

revealed that vascular invasion and perineural invasion had the strongest

prognostic values. The second model (B) included these two features

together with the densities of each T cell marker in normal and tumour


– – 60

tissues except CD45RO+N, which had previously shown no prognostic value

in univariate analysis (Table 3.4). This model revealed that vascular

invasion, perineural invasion, FOXP3+N and FOXP3+T were the strongest

prognostic features. When these four features were included in a third model

(C), all were found to have independent prognostic value in stage II CRC.

As with the overall patient cohort, high FOXP3+N and FOXP3+T cell

densities showed opposite associations with cancer-specific patient survival.

Table 3.6. Multivariate analysis for prognostic significance of pathological features and T cell marker density in stage II CRC.

Prognostic feature HR 95% CI P

Model A (n=360)

Vascular invasion 1.88 0.77-4.63 0.17

Lymphatic invasion 0.82 0.29-2.32 0.70

Perineural invasion 2.73 1.13-6.56 0.02

Lymphocytic response 0.94 0.47-1.87 0.86

MSI 0.92 0.37-2.27 0.85

Model B (n=337)



CD8+N 0.82 0.53-1.28 0.38

CD8+T 1.04 0.63-1.71 0.88

CD45RO+T 0.95 0.50-1.84 0.89

FOXP3+N 1.41 1.00-2.01 0.05

FOXP3+T 0.74 0.44-1.24 0.25

Model C (n=381)



FOXP3+N 1.42 1.05-1.92 0.023

FOXP3+T 0.65 0.48-0.89 0.007


– – 61

3.5. Discussion

The CD8+ and CD45RO+ markers of cytotoxic immune response have

previously been associated with improved prognosis in CRC patients

(House et al., 1979; Svennevig et al., 1984; Jass et al., 1986; Halvorsen et

al., 1989; Murphy et al., 2000; Ohtani et al., 2007, Naito et al., 1998). In

agreement with these earlier reports, the current study confirmed the

importance of CD8+T and CD45RO+T cell density as prognostic factors. The

novelty of this study was that FOXP3+ was examined in parallel to CD8+

and CD45RO+ in both normal and malignant tissues. Tregs are generally

considered to be immunosuppressive and have been linked to poor outcome

in several types of solid tumour (Curiel et al., 2004; Sato et al., 2005;

Hiraoka et al., 2006; Kobayashi et al., 2007; Gao et al., 2007). The major

original findings of the present study were that FOXP3+T Tregs are

associated with better survival and show stronger prognostic significance

than CD8+T and CD45RO+T. Furthermore, FOXP3+N Tregs were associated

with worse prognosis.

T cell markers were assessed objectively and quantitatively using digitised,

high resolution images and specialised software, thus limiting observer bias.

The finding of a higher FOXP3+T Treg density compared to FOXP3+

N

(Table 3.1) is in agreement with previous studies (Loddenkemper et al.,

2006; Ling et al., 2007). The tumour/normal ratio for Treg density observed

here (2.64) was also very similar to that reported by Ling et al. (2007). In

contrast to FOXP3+, the CD8+ and CD45RO+ cell densities were lower in

tumour compared to normal colonic mucosa, suggesting these T cell types


– – 62

play a different role to Tregs. Supporting this notion, the correlation

between FOXP3+N and FOXP3+T densities was weaker than that observed

for CD8+ or CD45RO+ (Table 3.2).

The finding of lower CD8+T and CD45RO+T densities in more advanced

tumours (Table 3.3) agrees with the findings of several other groups

(Svennevig et al., 1984; Jass et al., 1986; Halvorsen et al., 1989; Murphy et

al., 2000; Ohtani et al., 2007). Previously reported associations between

high CD45RO+T cell density and signs of early metastasis (vascular and

perineural invasion; Pagès et al., 2005) were also confirmed in the present

study. As expected, tumours reported to show a lymphocytic response or

MSI also had higher densities of CD8+T and CD45RO+T. In keeping with the

suggestion of a different role for Tregs, FOXP3+T cell density was not

associated with early signs of metastasis, lymphocytic response or MSI.

Although not as pronounced as for CD8+T and CD45RO+T, the FOXP3+T

Treg density was lower in stage III tumours, confirming a recent report by

Loddenkemper et al. (2006).

Univariate survival analysis confirmed the poor prognosis associated with

the conventional histopathological markers of adverse outcome (Table 3.4).

To our knowledge, the present study is the first to investigate the prognostic

significance of T cell markers in normal colonic mucosa from CRC patients.

Similar to CD8+T, CD8+N could be expected to have anti-tumour reactivity,

thus explaining their association with better prognosis. The better prognosis

associated with high densities of CD8+T and CD45RO+T (Table 3.4) agrees

with earlier studies (Pagès et al., 2005; Oberg et al., 2002). High densities


– – 63

of these cells have been linked to the suppression of metastasis (Pagès et al.,

2005; Galon et al., 2006). Alternatively, they could also signal the existence

of a more antigenic tumour phenotype that has yet to acquire the ability to

evade immunosurveillance.

One of the original and intriguing findings of this study was the opposite

prognostic significance observed for high densities of FOXP3+T and

FOXP3+N Tregs (Tables 3.4 and 3.5). The worse outcome observed for CRC

patients with high FOXP3+N might be explained by the proposed role for

these cells in suppressing anti-tumour immunity (Curiel, 2007). However,

the observation of better survival for patients with a high density of

FOXP3+T Tregs is counter-intuitive and contrasts with what has been

reported for other solid tumour types including melanoma (Miracco et al.,

2007) and breast (Bates et al., 2006), ovarian (Curiel et al., 2004),

hepatocellular (Kobayashi et al., 2007; Gao et al., 2007) and pancreatic

(Hiraoka et al., 2006) cancers. Functional studies of FOXP3+T and

FOXP3+N Tregs may shed more light on their role in the anti-tumour

response and help to explain the observed associations with prognosis.

Current recommendations for the treatment of CRC are that patients with

stage III disease receive adjuvant chemotherapy. The discovery and

validation of novel prognostic indicators are therefore of greatest

importance for the management of stage II disease. Of the three T cell

markers investigated in this study, only FOXP3+T and FOXP3+N Tregs

showed independent prognostic value in a multivariate model of stage II

CRC (Table 3.6). The other significant prognostic factors in this model were


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vascular and perineural invasion, both of which are indicators of early

metastasis and have been reported previously (Quirke et al., 2007; Morris et

al., 2006). As discussed earlier, the CD45RO+T cell density was inversely

related to the presence of vascular and perineural invasion, whereas

FOXP3+T Tregs showed no association (Table 3.3). This is likely to explain

why CD45RO+T failed to show independent prognostic value in a

multivariate model that included these pathological features. The Harrell’s

concordance statistic C (Harrell et al., 1996) using stage together with

vascular invasion was 69. This improved to 74 with the addition of

FOXP3+T and FOXP3+N Treg densities. The present results indicate that

FOXP3+T and FOXP3+N Treg densities, in combination with vascular and

perineural invasion, could provide clinically useful prognostic stratification

for early stage CRC.

One of the limitations of this study was that much of the histopathological

information was obtained from a period that predated the introduction of

synoptic reporting. The presence of vascular and perineural invasion are

therefore likely to have been under-reported at the initial diagnosis (Stewart

et al., 2007). Another limitation was the evaluation of T cell marker density

in 1mm diameter cores from tissue arrays. Although tissue arrays allow for

large cohorts to be assessed quickly, the relatively small area investigated

represents only a small proportion of the total tumour volume. Furthermore,

the cores were taken at random from within the tumour block face and their

location relative to the tumour margin was not recorded. In combination

with T cell type and density, the location of TILs relative to the invading

margin and central tumour area has recently been reported to have


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prognostic value (Galon et al., 2006). To address the above limitations,

further studies are underway in stage II CRC that use full block face tissue

sections to assess FOXP3+T and FOXP3+N Treg densities and where the

presence of vascular and perineural invasion are reviewed by a pathologist

(see Chapter 5).

While there have been several publications using FOXP3 to identify

tumour-infiltrating Tregs (Gao et al., 2007; Loddenkemper et al. 2006; Ling

et al., 2007; Bates et al., 2006; Alvaro et al., 2006), some workers have

questioned the validity of this marker for defining Tregs in humans

(Roncarolo et al., 2008). FOXP3+ Tregs were identified in the current study

by IHC using the monoclonal antibody clone 236A/E7. This antibody has

previously undergone extensive evaluation by Roncador et al. (2005). Based

on this study and other supporting evidence in the literature (Clarke et al.,

2006; Walker et al., 2005; Wang et al., 2007), the vast majority of FOXP3+

cells identified by mAb 236A/E7 are CD4+CD25+ Tregs. Although a small

proportion of FOXP3+ cells may also be CD8+ or CD25- (Roncador et al.,

2005), it remains that FOXP3+ lymphocyte density showed strong and

independent prognostic significance in CRC (Table 3.6).

In conclusion, the present study is the first to report on the prognostic

significance of FOXP3+T and FOXP3+N Treg densities in CRC patients.

Multivariate models showed these markers had stronger prognostic value

than CD8+T or CD45RO+T. Although further studies are required before

changes in clinical practice can be recommended, the present results suggest

that assessment of FOXP3+T and FOXP3+N Treg densities in combination


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with vascular and perineural invasion should improve the prognostic

stratification of early stage CRC. The better survival associated with a high

density of FOXP3+T Tregs in CRC is in marked contrast to observations in

other solid tumour types.

Chapter 4: Granzyme B in colorectal cancer

This work was published in:Salama P, Phillips M, Platell C, Iacopetta B.

Low expression of Granzyme B in colorectal cancer is associated with signs

of early metastastic invasion. Histopathology 2011 59(2):207-15.


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4. Granzyme B in colorectal cancer

4.1. Abstract

In Chapter 3 it was found that tumour-infiltrating FOXP3+ Tregs have

stronger prognostic significance than cytotoxic CD8+ T cells in CRC. Since

there is evidence that some tumour-infiltrating CD8+ T cells may be

inactive, the present study was aimed at investigating the prognostic

significance of GrB, one of the major effecter molecules of T cells.

A TMA containing 963 CRCs was stained immunohistochemically for GrB

and the level of expression quantified by digital image analysis.

GrB expression was higher in tumours with MSI (p<0.0001), a dense

lymphocytic infiltrate (p<0.0001) and location in the proximal colon

(p=0.009), but lower in tumours with vascular invasion (p=0.007),

perineural invasion (p=0.041) and positive nodal status (p<0.001). Elevated

expression of GrB was associated with improved survival in univariate

analysis (HR=0.65; 95%CI: 0.51-0.84; p=0.001), but not in a multivariate

model that included stage, vascular invasion and FOXP3+ Treg cell density.

Low expression of GrB was associated with early signs of metastasis in

CRC. The stronger prognostic significance of FOXP3+ Tregs is in keeping

with animal models that suggest these cells act as gatekeepers for the release

of GrB from CD8+ T cells.

4.2. Introduction

It has been known for several decades that a peri-tumoural infiltrate around

CRC is associated with better survival outcomes (House et al., 1979).


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Currently, it appears this survival advantage is conferred by a Th1 immune

response characterised by cytotoxic CD8+ T cells. Naito et al. first reported

that cytotoxic CD8+ T cell density has prognostic significance of similar

value to Dukes’ staging (Naito et al., 1998). More recently, Galon and co-

workers claimed the type, density and location of tumour-infiltrating

immune cells was strongly predictive of clinical outcome and was even

superior to the currently used TNM staging system (Galon et al., 2006;

Pagès et al., 2005). These workers suggested the Th1 immune response was

protective against early metastatic invasion as defined by vascular,

lymphatic and perineural invasion.

The work described in Chapter 3 found that a high density of tumour-

infiltrating FOXP3+ Tregs could be used in conjunction with the absence of

vascular and perineural invasion to more accurately identify stage II CRC

patients with a low risk of recurrence (Salama et al., 2009). An independent

study has confirmed that high FOXP3+ Treg cell density shows strong

prognostic significance for better outcome of CRC patients (Frey et al.,

2010). The above findings were somewhat unexpected since FOXP3+ Tregs

are widely believed to suppress the anti-tumour immune response (Zou,

2005). A possible explanation for the relatively weaker prognostic

significance of CD8+ cell density compared to FOXP3+ cell density is that

many of the former cells may be inactive. There is evidence to suggest that

some tumour-infiltrating CD8+ T cells in CRC may be functionally inactive,

as revealed by low expression of activation markers (Koch et al., 2006) and

of the effecter molecule GrB (Mulder et al., 1997). GrB is contained mostly

within the granules of cytotoxic T cells and enables the destruction of target


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cells in a perforin-dependent manner (Peters et al., 1991; Cullen et al.,

2008; Chowdhury et al., 2008). Since tumour-infiltrating cytotoxic CD8+

T cells may be inactive, it could be more informative to evaluate the

expression of GrB. The primary aim of the work described in this Chapter

was therefore to evaluate the prognostic significance of GrB in CRC.

Secondary aims were to correlate the expression of GrB with the densities

of several of the major immune cell subtypes (CD8+, CD45RO+ and

FOXP3+) and with other established histopathological markers of prognosis.

4.3. Methods

The methods used in this Chapter were described in Chapter 2.

4.4. Results

GrB was expressed mainly in granules within lymphocytes present in

tumour and normal tissues. A representative example of GrB expression in

CRC is shown in Chapter 2, Figure 2.7. The expression of GrB in tumour

tissue (GrBT) demonstrated a log normal distribution (results not shown)

and was higher than in normal colonic mucosa (GrBN; median values 8.16

vs 3.26; P<0.0001, Wilcoxon rank sum test). In Chapter 3 it was

demonstrated that CD8+ T cell density was higher in normal colonic mucosa

compared with tumour tissue (Salama et al., 2009). These findings would

suggest that CD8+ T cells with the normal colonic mucosa are inactive,

since the expression of GrB is much lower.


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4.4.1. Correlation of Granzyme B expression with T cell subtype densities

Correlations between GrB expression and the density of T cell subtypes in

normal (N) and tumour (T) tissues are shown in Table 4.1. GrBN expression

was positively correlated with CD8+N and CD45RO+N, but only weakly with

FOXP3+N. Stronger correlations were seen between GrBT expression and

the densities of each of the three T cell subtypes in tumour tissue. The

GrBT/CD8+T ratio was used as an estimate of the relative cytotoxic activity

of tumour-infiltrating CD8+ T cells. As expected in view of the postulated

immunosuppressive role of Tregs, a negative correlation was observed

between GrBT/CD8+T and the FOXP3+T cell density.

4.4.2. Correlation of Granzyme B expression with histopathological features and microsatellite instability status

Associations between GrBT expression and histopathological markers were

explored using logistic regression (Table 4.2). GrBT expression was lower in

more advanced tumours and those with vascular or perineural invasion, but

higher in tumours with positive MSI status, the presence of TILS or location

in the proximal colon.

Table 4.1. Correlations between GrB expression and the density of T cell subtypes in the normal colonic mucosa (N) and tumour (T) tissue of CRC patients.

Correlation coefficient (r) P Normal tissue

GrBN vs CD8+N 0.239 <0.0001

GrBN vs CD45RO+N 0.196 <0.0001

GrBN vs FOXP3+N 0.137 0.012

Tumour tissue

GrBT vs CD8+T 0.516 <0.0001

GrBT vs CD45RO+T 0.446 <0.0001

GrBT vs FOXP3+T 0.439 <0.0001

GrBT/CD8+T vs FOXP3+

T -0.204 <0.0001


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r=Spearman’s Rho; P values are two tailed.

Table 4.2. Associations between the expression of GrBT and histopathological markers in CRC.

GrBT

Feature (n) OR 95%CI P

AJCC stage

II (488) 1 – –

III (317) 0.61 0.46-0.81 <0.001

T stage

1+2 (15) 1 – –

3+4 (788) 1.14 0.41-3.17 NS

Vascular invasion

Absent (470) 1 – –

Present (155) 0.6 0.42-0.87 0.007

Lymphatic invasion

Absent (333) 1 – –

Present (60) 0.71 0.41-1.23 NS

Perineural invasion

Absent (536) 1 – –

Present (44) 0.52 0.28-0.97 0.041

MSI

Absent (687) 1 – –

Present (82) 3.8 2.23-6.49 <0.0001

TILS

Absent (119) 1 – –

Present (83) 3.45 1.81-6.57 <0.0001

Tumour site

Distal (489) 1 – –

Proximal (332) 1.46 1.10-1.95 0.009

The balance of effecter to regulatory molecules has been reported to have

prognostic significance in various tumour types (Alvaro et al., 2005; Kelley

et al., 2007; Gao et al., 2007; Sato et al., 2005). In the present study the

GrBT/FOXP3+T ratio was used to represent this balance. Associations


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between this ratio and commonly reported histopathological factors are

shown in Table 4.3. The GrBT/FOXP3+T ratio was significantly lower in

tumours with positive nodal status and vascular invasion, whereas positive

MSI status, presence of TILS and proximal location were strongly

associated with a high GrBT/FoxP3+T ratio. The GrBT/CD8+T ratio and GrBN

were not significantly associated with any of the histopathological markers

examined here (results not shown).

4.4.3. Prognostic significance of Granzyme B expression

The prognostic significance of various T cell subtype densities and

histopathological features have been reported previously for this tumour

cohort (Salama et al., 2009). In the present study, Kaplan-Meier and Cox

regression analyses were used to evaluate the prognostic significance of

GrBT (Table 4.4, Figure 4.1A) and of GrBT/FOXP3+T (Figure 4.1B) and

GrBT/CD8+T (Figure 4.1C) ratios. High levels of GrBT expression were

associated with better cancer-specific survival in the overall cohort and in

both the stage II and III subgroups. The better outcome associated with high

GrBT expression appeared to be restricted to microsatellite stable (MSS)

tumours (Table 4.4).


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Table 4.3. Associations between GrBT/FOXP3+T and histopathological

markers in CRC.

GrBT/FOXP3+T

Feature (n) OR 95%CI P

AJCC stage

II (463) 1 – –

III (310) 0.69 0.52-0.92 0.012

T stage

1+2 (15) 1 – –

3+4 (756) 2.03 0.69-6.00 0.2

Vascular invasion

Absent (447) 1 – –

Present (149) 0.64 0.44-0.94 0.02

Lymphatic invasion

Absent (314) 1 – –

Present (57) 0.65 0.37-1.15 0.14

Perineural invasion

Absent (509) 1 – –

Present (43) 0.64 0.34-1.19 0.16

MSI

Absent (662) 1 – –

Present (79) 3.17 1.88-5.35 <0.0001

TILS

Absent (111) 1 – –

Present (79) 2.07 1.12-3.82 0.02

Tumour site

Distal (425) 1 – –

Proximal (315) 1.59 1.18-2.13 0.002

Table 4.4. Univariate survival analysis for the prognostic significance of GrB T expression in CRC stage and MSI subgroups.

Feature (n) HR 1 95% CI P

Total (780) 0.65 0.51-0.84 0.001

Stage II (475) 0.74 0.49-1.12 0.159

Stage III (305) 0.75 0.54-1.04 0.08

MSS (667) 0.66 0.50-0.86 0.002

MSI (78) 1.26 0.36-4.44 0.72 1 High vs low expression of GrBT


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The prognostic significance of the ratio of GrBT to immune cell density was

also examined. High GrBT/FOXP3+T was associated with a trend for

improved cancer-specific survival (Figure 4.2B). When analysed as a

continuous variable by Cox regression modelling, GrBT/CD8+T showed

strong prognostic significance in both univariate and multivariate analysis.

CART analysis identified a high risk subgroup (n=32) that was not

associated with any of the established histopathological markers of poor

prognosis. The Kaplan-Meier survival curve generated using the optimal

cut-off value identified by CART analysis is shown in Figure 4.2C. Digital

images of tumour cores from this high risk group were individually

reviewed to exclude non-specific GrB staining as a possible cause for their

elevated GrBT/CD8+T values.


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Figure 4.1. Kaplan-Meier survival analysis for CRC subgroups.

Stratified according to (A) GrB expression, (B) GrB/POXP3+ ratio and (C) GrB/CD8+ ratio.


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Multivariate analysis revealed that GrBT, GrBN and GrBT/FOXP3+T were

not significant prognostic variables in a model that included vascular

invasion, perineural invasion, FOXP3+T and FOXP3+N (Table 4.5).

Although the GrBT/CD8+T ratio was an independent prognostic factor in this

model, it did not improve the prognostic accuracy as determined by the

Harrell’s C statistical coefficient, probably due to the small size of the

GrBT/CD8+T high subgroup (n=32).

Table 4.5. Multivariate analysis for the prognostic significance of histopathological and immune cell markers in CRC.

Feature HR 95% CI P

AJCC stage (III vs II) 3.34 2.22-5.03 <0.0001


FOXP3+N (high vs low) 1.72 1.17-2.52 0.006

FOXP3+T (high vs low) 0.52 0.36-0.76 0.001

GrBT/CD8+T (high vs low) 3.16 1.56-6.39 0.001

4.5. Discussion

The major finding of this study is that low levels of GrB expression in CRC

was associated with pathological evidence of early metastasis such as

vascular and perineural invasion. To our knowledge, this is the first report

on the prognostic significance of GrB expression in CRC. The strengths of

this study included the objective quantification of GrB expression using

digital image analysis and the long period of patient follow-up. The large

sample size also allowed correlation of GrB expression with T cell subtype

density and with commonly reported histopathological features and MSI

status.


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Similar to previous reports in CRC (Mulder et al., 1997; Le Gouvello et al.,

2008), GrB expression was elevated in tumour tissue compared to normal

colonic mucosa. This suggests that CD8+ T cells within normal colonic

mucosa are inactive. In keeping with the work of Mulder et al. (1997), an

inverse relationship was observed between GrBT expression and tumour

stage (Table 4.2). As expected, GrBT expression was significantly elevated

in tumours with high levels of TILS (Table 4.2) and with high CD8+ and

CD45RO+ cell densities (Table 4.1). In addition, the 3.8-fold higher

expression of GrB observed in MSI compared to MSS tumours (Table 4.2)

was almost identical to the 3.7-fold higher level reported in an earlier study

using IHC (Phillips et al., 2004), but less than the 9-fold higher level

reported by Dolcetti et al. (1999). Le Gouvello et al. (2008) also found

higher mRNA expression of GrB in MSI+ tumours using quantitative

reverse transcription-PCR (qRT-PCR).

Tumours with vascular or perineural invasion demonstrated significantly

lower levels of GrB expression (Table 4.2). These results are in agreement

with those of Pagès et al. who used qRT-PCR to demonstrate that GrB

mRNA levels were lower in CRC that showed signs of early metastasis

(Pagès et al., 2005). These workers defined early metastasis as pathological

evidence of vascular, lymphatic or perineural invasion. Together, the above

results support the notion that invasion and metastasis may be inhibited by

an active anti-tumour immune response, thereby impacting upon survival

outcomes.


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A novel finding from this study was that high GrBT expression was

prognostic for better cancer-specific survival in univariate analysis (Figure

4.1A and Table 4.4). This was not unexpected in view of the inverse

association between GrBT expression and pathological signs of early

metastasis. Interestingly, the prognostic significance of GrBT appeared to be

restricted to MSS tumours. The reason for the apparent lack of prognostic

significance in MSI tumours is unclear and requires confirmation in further

studies. GrBT did not retain prognostic significance in multivariate analysis,

presumably due to its strong associations with stage, early metastasis and

T cell subtype densities (Tables 4.1 and 4.2). The stronger prognostic

significance of FOXP3+ cell density may be explained by the observation in

animal models that Tregs control the release of GrB from CD8+ cells.

In several cancer types, the ratio of effecter to regulatory immune cell

markers has been reported to show stronger prognostic significance than

individual markers (Alvaro et al., 2005; Kelley et al., 2007; Gao et al.,

2007; Sato et al., 2005). A high GrBT/FOXP3+T ratio was associated with

improved prognosis in Hodgkin’s lymphoma (Kelley et al., 2007) and in

hepatocellular carcinoma (Gao et al., 2007). In the present study of CRC,

high GrBT/FOXP3+T was also associated with features of good prognosis

(Table 4.3) and a trend for better cancer-specific survival in univariate

analysis (Figure 4.1B). This is not surprising since high GrBT/FOXP3+T

would indicate the overall balance of the immune response is tipped towards

effector molecules that are responsible for the destruction of target tumour

cells.


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CD8+T cells may be present within tumours but inactive. The GrBT/

CD8+T ratio was therefore used as a surrogate marker for the cytotoxicity

of these cells. This ratio was not associated with clinical or

histopathological features of CRC; however, an inverse relationship was

observed between GrBT/CD8+T and the density of FOXP3+T Tregs. This

suggests that FOXP3+T cells might down-regulate the expression of GrB in

CD8+ cells, thus reducing their functional capacity. Despite retaining

prognostic significance in multivariate analysis (Table 4.5), the

GrBT/CD8+T ratio did not improve overall prognostic accuracy, probably

due to the small proportion of patients classified as being high risk (n=32, or

3% of the study population).

While several interesting observations were made here regarding GrB

expression in CRC, there are several limitations with this work that should

be highlighted. Firstly, the histopathological information was obtained from

original reports and it is likely that the features of vascular, perineural and

serosal invasion were under-reported (Stewart et al., 2007; Liebig et al.,

2009). Secondly, measurement of GrB expression from multiple tumour

cores or full face sections may have led to stronger associations with

histopathological features. Thirdly, although the expression of GrB occurs

predominately in cytotoxic T cells and NK cells, we cannot be certain that it

was restricted to these cells. GrB expression has also been reported in DCs,

mast cells and murine Tregs (Chowdhury et al., 2008). Additional

experiments using double staining techniques are required to determine the

full range of cell types in which GrB is expressed in CRC. Furthermore, the

evaluation of other cytotoxic markers such as perforin and FasL (Vermijlen


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et al. 2001) would increase our understanding of the host response. Future

efforts should also be directed at the tumour-host interface in order to assess

the concentration of various immune markers and how these impact upon

tumour growth patterns and response to adjuvant therapies (Zlobec et al.,

2009).

In conclusion, the density of tumour-infiltrating FOXP3+ Treg cells was

found in this study of CRC to have stronger prognostic value than

expression of the effecter molecule GrB. This is of particular importance for

stage II CRC, where robust prognostic factors are needed to assist with

decisions regarding the use of adjuvant therapies. There is now solid

evidence to support the hypothesis that quantitative measures of immune

cell infiltration (Galon et al., 2006; Pagès et al., 2005; Salama et al., 2009;

Frey et al., 2010; Pagès et al., 2010), in combination with accurate

assessment of vascular, serosal and perineural invasion by tumour cells

(Morris et al., 2007; Peterson et al., 2002; Morris et al., 2006; Stewart et al.,

2007; Littleford et al., 2009; Shepherd et al., 1997; Liebig et al., 2009), will

allow early stage CRC patients to be stratified into clinically useful

prognostic subgroups. Although requiring validation in prospective studies,

this approach may prove to be simpler, less expensive and more robust than

the use of recently described gene expression signatures (Wang et al., 2004;

Barrier et al., 2006; Watanabe et al., 2009).

Chapter 5: Lymphoid follicles in colon cancer

The work described in this chapter was published in:Salama P, Stewart C,

Forrest C, Platell C, Iacopetta B. FOXP3+ cell density in lymphoid follicles

from histologically normal mucosa is a strong prognostic factor in early

stage colon cancer. Cancer Immunol Immunother. 2012; 61(8): 1183-90


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5. Lymphoid follicles in colon cancer

5.1. Abstract

There are few clearly established prognostic factors available to guide the

use of adjuvant chemotherapy in early stage colon cancer patients. Some of

the most promising candidates include the invasion of extramural blood

vessels by tumour cells and the densities of FOXP3+ Tregs in tumour and

adjacent normal colonic mucosal tissue. The aim of the study described in

this chapter was to evaluate the prognostic significance of these markers in

AJCC stage II colon cancer, with particular reference to lymphoid follicles

in the mucosa.

Histopathological review for the presence of vascular and serosal invasion

was conducted on a series of 165 stage II colon cancers treated by surgery

alone. Immunohistochemical staining for FOXP3 was performed on tumour

tissue and on histologically normal colonic mucosa from the surgical

margin. Image analysis software was used to evaluate the density of

FOXP3+ cells in the tumour core, invading margin and lymphoid follicles

from the colonic mucosa. For the analysis of patient survival, cases were

classified into high or low density FOXP3+ cells according to the median

value.

The mean density of FOXP3+ Tregs in lymphoid follicles was 2-fold and 5-

fold higher than in the invading margin and tumour core, respectively.

Multivariate analysis identified EMVI (HR 2.47, 95% CI 1.00-6.07, p=0.05)

and high FOXP3+ cell density in lymphoid follicles (HR 4.22, 95% CI 1.49-

11.91, p=0.007) as independent factors for worse survival, whereas a high


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frequency of lymphoid follicles in histologically normal colonic mucosa

was associated with better survival (HR 0.31, 95% CI 0.12-0.79, p=0.014).

These results suggest that host factors related to the immune system have

major prognostic significance in early stage colon cancer. The density of

FOXP3+ cells within lymphoid follicles and the frequency of these

structures in normal colonic mucosa represent novel and independent

prognostic factors.

5.2. Introduction

The prognosis of CRC has traditionally been estimated using the TNM

staging system (Sobin et al., 1997). The additional histopathological

features of tumour cell invasion into extramural vascular and perineural

spaces have also proven to be strong and independent risk factors for poor

outcome (Quirke et al., 2007; Williams et al., 2007; Peterson et al., 2002).

The need for robust and accurate prognostic indicators is especially

important for AJCC stage II (T3 or T4, N0, M0), or node-negative colon

cancer patients, comprising approximately one-third of all newly diagnosed

cases. Better prognostication would allow patients with more aggressive

tumours to be considered for adjuvant chemotherapy. The 5-year disease-

free survival of stage II colon cancer patients is approximately 70-80%

(Morris et al., 2006). This varies markedly, however, depending upon the

presence or absence of serosal invasion (T3/T4) and the presence of EMVI

and perineural invasion by tumour cells (Quirke et al., 2007; Peterson et al.,

2002; Morris et al., 2006; Stewart et al., 2007; Desolneux et al., 2010;

Courtney et al. 2009).


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In addition to TNM staging and vascular/perineural tumour invasion, the

presence of a dense lymphocytic infiltrate has consistently been shown to

have prognostic value in colon cancer (Naito et al., 1998; Ropponen et al.,

1997; Prall et al., 2004; Chiba et al., 2004; Ohtani, 2007). Indeed, some

workers have proposed that the density of CD3+ TILs may be a more

accurate predictor of outcome for CRC than the TNM system (Galon et al.,

2006; Pagès et al., 2005). However, a subsequent study found the

prognostic value of TILs was restricted to node-negative cancer (Laghi et

al., 2009), thus ruling out replacement of a TNM-based system with one

based upon the anti-tumour immune reaction. Furthermore, these studies did

not review the original pathology slides for assessment of important,

standard histological markers such as EMVI that may be under-reported. It

therefore remains to be established whether the immune response has

independent prognostic value in the context of accurate reporting of nodal

involvement and of vascular and serosal invasion.

Tregs are thought to play a major role in cancer through the suppression of

anti-tumour immune responses (Sakaguchi et al., 2010). The FOXP3 is a

specific nuclear marker for Tregs that allows these cells to be distinguished

from other T cell types. In Chapter 3 it was demonstrated that the density of

tumour-infiltrating FOXP3+ Tregs, together with vascular and perineural

invasion, were independent prognostic factors in a study of 381 stage II

CRCs (Chapter 3; Salama et al., 2009). In contrast to other cancer types in

which high Treg density is associated with poor prognosis, several groups

have subsequently confirmed our initial observation of an association with

favourable outcome for CRC (Frey et al., 2010; Correale et al., 2010; Nosho


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et al., 2010). These results also concur with an earlier report that Treg

infiltration was significantly higher in CRC with limited disease stage

(UICC I and II) compared to those with more advanced stage (UICC III and

IV) (Loddenkemper et al., 2006). The paradoxical findings for CRC may be

due to the suppression by Tregs of a tumour-promoting, inflammatory

immune response generated by translocation of bacteria across the mucosal

barrier (Loddenkemper et al., 2006; Ladoire et al., 2011).

An additional observation from the work described in Chapter 3 was that

high FOXP3+ Treg density in histologically normal colonic mucosa from

the surgical margin was associated with poor prognosis (Salama et al.,

2009). This original finding has yet to be validated in an independent patient

cohort. Our earlier study used TMA and histological information obtained

from the initial pathology report. The use of full face sections would yield a

greater area of tumour for analysis and would allow investigation of

whether FOXP3+ Tregs at the invasive margin have greater prognostic

significance than those within the tumour core. The aim of work in this

Chapter was therefore to investigate the prognostic significance of FOXP3+

cell densities in neoplastic and normal colonic mucosa from an independent

series of stage II colon cancers that were carefully reviewed for the presence

of EMVI and serosal invasion. Full face tissue sections, which are larger

and therefore more representative than the cores used in TMA, were

analysed to determine FOXP3+ Treg density in tumour tissue and in

histologically normal colonic mucosa from the surgical margin.


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5.3. Methods

All methods used in this Chapter were described in Chapter 2.

5.4. Results

The clinical and histopathological features of the 165 stage II colon cancers

investigated in this study are shown in Table 5.1. The proportion of cases

that showed EMVI or serosal invasion upon histological review was 25%

and 32%, respectively. Tumours with EMVI were significantly more likely

to show serosal invasion (OR 3.14, 95% CI 1.33-7.39, p=0.009).

Table 5.1. Clinical and histopathological features of 165 stage II colon cancers.

Feature n (%) *

Age (years, mean [SD]) 71.5 (10-8)

Sex

Male 80 (48)

Female 85 (52)

Tumour site

Proximal 95 (58)

Distal 69 (42)

EMVI

No 118 (75)

Yes 40 (25)

Serosal invasion

No 107 (68)

Yes 51 (32)

Perforation

No 148 (91)

Yes 14 (9)

* Information on tumour site, EMVI, serosal invasion and perforation was not available for 1, 7, 7 and 3 cases, respectively.


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Immunohistochemical analysis for the FOXP3 marker specific to Tregs was

performed on tumour tissue and on matched normal colonic mucosa from

the surgical margin as described in Chapter 3. Representative images for

normal colonic mucosa are shown in Figure 5.1. Sections were of adequate

quality to allow the density of FOXP3+ Tregs in the tumour core and

invading margin to be quantified in 145 and 133 cases, respectively (Table

5.2). The FOXP3+ cell density was 2-3_fold higher at the invading margin

compared to the tumour core (p<0.0001, Wilcoxon rank sum test). Tumours

with a high density of FOXP3+ Tregs at the invading margin were less likely

to show EMVI (OR 0.39, 95% CI 0.17-0.94, p=0.035), in keeping with the

good prognosis associated with this feature (Salama et al., 2009).

Table 5.2. FOXP3+ Treg density (cells/mm2) in tumour tissue and in lymphoid follicles from histologically normal colonic mucosa at the surgical margin.

Site (n) Median Mean (SD) Range

Tumour core (145) 152 196 (150) 6-1,026

Tumour invasive margin (133) 435 475 (274) 40-1,696

Normal mucosa lymphoid follicle (137) 885 958 (412) 166-2,152

In histologically normal colonic mucosa from the surgical margin, the

highest density of FOXP3+ Tregs was found in lymphoid follicles and

particularly in the mantle zone surrounding the germinal centres (Figure

5.2). The FOXP3+ cell density in lymphoid follicles was 2-fold higher than

at the invasive tumour margin (Table 5.2; p<0.0001, Wilcoxon rank sum

test).


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Figure 5.1. Section of histologically normal colonic mucosa from the surgical margin.

Lymphoid follicles (arrows) were evaluated for both their frequency per centimetre

of mucosal length and the density of FOXP3+ T regulatory lymphocytes within

these structures.


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Figure 5.2. (A) Representative low power image of normal colonic mucosa from the surgical margin.

Three lymphoid follicles are delineated for measurement of the FOXP3+ cell

density within these structures.

Figure 5.2. (B) High power image of lymphoid follicle showing immune cells stained positively for the FOXP3 marker.

Most FOXP3+ cells are located within the peripheral mantle zone.


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No correlations were observed between FOXP3+ cell densities in the

lymphoid follicles and tumour tissue from the same patient, nor with age,

gender, tumour site, EMVI or serosal invasion (results not shown). No

attempt was made to measure the FOXP3+ cell density in the area of normal

colonic mucosa adjacent to the lymphoid follicles.

The median length of normal colonic mucosa assessed for the presence of

lymphoid follicles in each patient was 4.61 cm (mean ± SD, 5.16 ± 2.59).

The median frequency of lymphoid follicles from 138 cases for which

there was suitable histological material to conduct analysis was 1.12

follicles per cm of mucosal length (mean ± SD, 1.35 ± 1.02; range, 0-

5.88). Higher frequencies were found in patients with distal tumours

(mean ± SD, 1.67 ± 1.11) compared to those with proximal tumours (1.07

± 0.87; p=0.0004, Wilcoxon rank sum test). No significant associations

were found with FOXP3+ cell density or with any other clinical or

histopathological features.

The results of univariate survival analysis for the variables described above

are shown in Table 5.3. As expected, EMVI and serosal invasion were

associated with significantly worse patient survival. High FOXP3+ cell

density in tumour tissue was associated with better survival, although this

failed to reach significance. Patients with a high frequency of lymphoid

follicles showed a trend for better survival (p=0.07), but those with a high

density of FOXP3+ cells in these structures showed significantly worse

survival (p=0.007).


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Table 5.3. Univariate survival analysis for clinicopathological features and FOXP3+ Treg density in stage II colon cancer.

Feature HR 95% CI P

Sex (male vs female) 0.80 0.36-1.77 0.58

Tumour site (proximal vs distal) 0.93 0.42-2.04 0.85

EMVI (yes vs no) 2.99 1.36-6.58 0.006

Serosal invasion (yes vs no) 2.36 1.07-5.20 0.033

Perforation (yes vs no) 2.61 0.89-7.66 0.08

Normal mucosa LF density (high vs low) * 0.43 0.17-1.07 0.07

FOXP3+ cells: tumour core (high vs low) 0.73 0.31-1.74 0.48

FOXP3+ cells: tumour IM (high vs low) 0.63 0.26-1.50 0.30

FOXP3+ cells: normal mucosa LF (high vs low) 4.02 1.47-11.01 0.007

* LF density is the number of lymphoid follicles per cm of colon mucosa. EMVI; LF, lymphoid follicles in the normal mucosa from the surgical margin; IM, invasive margin.

A multivariate model was used to identify independent prognostic factors.

This model included all variables that showed a p-value <0.1 in univariate

survival analysis (EMVI, serosal invasion, perforation, lymphoid follicle

frequency in normal mucosa, FOXP3+ cell density in lymphoid follicles).

Forward stepwise regression was performed to retain variables at a

significance level of 0.05. The significant variables identified by

multivariate analysis were EMVI, lymphoid follicle frequency and FOXP3+

cell density in lymphoid follicles (Table 5.4). Kaplan-Meier survival curves

for these independent prognostic factors are shown in Figure 5.3.

Table 5.4. Multivariate analysis for indicators of cancer-specific survival in stage II colon cancer.

Feature HR 95% CI P

EMVI (yes vs no) 2.46 1.00-6.07 0.050

Normal mucosa LF frequency (high vs low) 0.31 0.12-0.79 0.014

FOXP3+ cell density in LF (high vs low) 4.22 1.49-11.91 0.007

EMVI; LF, lymphoid follicle in histologically normal colonic mucosa from the surgical margin.


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Figure 5.3. Kaplan-Meier survival analysis for stage II colon cancer patient subgroups.

These are presented according to (A), the presence or absence of EMVI, (B) lymphoid follicle frequency in histologically normal colonic mucosa from the surgical

margin, or (C) the density of FOXP3+ staining immune cells in lymphoid follicles. P values shown are from the log-rank test.


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5.5. Discussion

Prognostic factors in colon cancer are of greatest clinical relevance for

AJCC/UICC stage II disease (T3 or T4, N0, M0). The identification,

validation and routine application of robust prognostic markers would allow

node-negative patients with poorer survival prospects to be considered for

adjuvant chemotherapy, while sparing many others the toxicity and expense

of such treatment. This study found a strong association between EMVI and

worse outcome (Table 5.4 and Figure 5.3), thus confirming several previous

reports showing independent prognostic value for this feature in CRC

(Quirke et al., 2007; Peterson et al., 2002; Morris et al., 2006; Desolneux et

al., 2010; Courtney et al., 2009; Betge et al., 2011). Although not reaching

statistical significance, the present results also confirm the prognostic value

of tumour-infiltrating FOXP3+ Tregs (Salama et al., 2009; Frey et al., 2010;

Correale et al., 2010; Nosho et al., 2010; Lee et al., 2010). Furthermore, the

results support the finding described in Chapter 3 that high FOXP3+ Treg

density in the normal colonic mucosa was associated with poor survival

(Salama et al., 2009). This earlier observation has now been confirmed and

extended in a separate patient cohort where high FOXP3+ cell density within

mucosal lymphoid follicles was found to be a strong and independent factor

for unfavourable outcome (Table 5.4). Moreover, we report for the first time

that the frequency of these lymphoid follicles in the colonic mucosa also

showed prognostic value.

The need for careful evaluation of EMVI has been highlighted by several

groups over the past decade (Quirke et al., 2007; Williams et al., 2007;

Peterson et al., 2002; Stewart et al., 2007; Desolneux et al., 2010; Betge et


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al., 2011). Approximately 10-15% of CRCs were reported to show EMVI in

routine practice in the UK (Quirke et al., 2007) and Australia (Morris et al.,

2006). However, it has been argued that proper specimen preparation and

more thorough evaluation by pathologists increases this frequency to around

25-30% (Quirke et al., 2007; Williams et al., 2007). All cases in the present

study were reviewed, resulting in a frequency of 25% for EMVI. The HR

associated with EMVI was 2.46 in a multivariate analysis that included the

FOXP3+ marker (Table 5.4). This result compares with a HR of 2.16 in our

previous study of 381 stage II colon cancers that also included FOXP3+ cell

density but in which the pathology was not reviewed (Chapter 3; Salama et

al., 2009). An earlier population-based study of 1,306 stage II colon cancer

patients found a HR of 1.63 for vascular invasion; however, again the

pathology was not reviewed and the reported frequency was only 12%

(Morris et al., 2006). This latter result is similar to another study of 362

node-negative CRCs in which the HR for venous invasion was reported to

be 1.96, but its frequency was just 13% (Desolneux et al., 2010). The

importance of careful histological review was recently highlighted in a

study of 381 node-negative CRCs which showed the HR associated with

venous invasion (23% frequency) was 4.45 following review, but only 1.05

based on routine reporting (Betge et al., 2011). Taken together, the above

findings demonstrate that EMVI, providing it is carefully evaluated, should

be a key factor in future algorithms for the prognostic stratification of stage

II colon cancer patients.

A large volume of literature clearly demonstrates that a strong TILs reaction

is associated with favourable prognosis in CRC (Naito et al., 1998;


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Ropponen et al., 1997; Prall et al., 2004; Chiba et al., 2004; Ohtani, 2007;

Galon et al., 2006; Pagès et al., 2005). This is likely to be due to the

suppression of early metastatic invasion by a local immune response

involving activated T cells (Galon et al., 2006; Pagès et al., 2005).

Importantly, the good prognosis associated with a high density of CD3+

TILs appears to be confined to patients with node-negative disease (Laghi et

al., 2009). In Chapter 3 it was shown that the density of FOXP3+ Tregs in

CRC shows stronger prognostic significance than the density of CD8+ and

CD45RO+ cell markers associated with the cytotoxic immune response

(Salama et al., 2009). In most cancer types, Tregs suppress anti-tumour

immune responses and high densities of these cells are associated with

worse patient outcome (Ladoire et al., 2011). However, several studies have

now shown that a high density of FOXP3+ Tregs in CRC correlates with

better survival (Salama et al., 2009; Frey et al., 2010; Correale et al., 2010;

Nosho et al., 2010; Lee et al., 2010). Ladoire et al. have argued that the

paradoxical result observed for CRC could be due to Treg-mediated

suppression of a tumour-promoting, inflammatory immune response that is

generated by translocation of bacteria across the mucosal barrier (Ladoire et

al., 2011). Most cancers occur in relatively sterile environments, whereas

colon cancers occur in a highly contaminated environment in which the

immune system is geared towards tolerance of the bacteria.

The good prognosis associated with a high density of FOXP3+ Tregs in the

tumour core (HR 0.73) and invasive margin (HR 0.63) did not reach

statistical significance in the present study of 165 stage II colon cancers

(Table 5.3). However, these HR values were similar to those reported in our


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earlier study of 967 stage II and III CRCs (HR 0.78; Chapter 3; Salama et

al., 2009) and to other large studies of 613 mismatch repair-proficient and

223 mismatch repair-deficient CRC (HR 0.70 and HR 0.63, respectively;

Frey et al., 2010) and of 768 stage I-IV CRCs (HR 0.48; Nosho et al.,

2010). It is likely that the low number of cancer-related deaths (n=26) in the

present cohort of early stage colon cancer patients prevented the density of

tumour-infiltrating FOXP3+ cells from reaching significance as a prognostic

marker for favourable outcome. Further work is required to determine

whether the density of tumour-infiltrating FOXP3+ cells is an independent

prognostic marker in stage II colon cancers in which EMVI has been

carefully evaluated.

It was previously reported that high FOXP3+ cell density in the normal

colonic mucosa from the surgical margin was associated with worse patient

outcome (Chapter 3; Salama et al., 2009). In the present work this original

finding was confirmed and extended in a separate cohort by showing that

high FOXP3+ cell density in the lymphoid follicles was a strong (HR 4.22)

and independent factor for poor survival (Table 5.4). An unexpected and

novel observation from the current study was that the frequency of

lymphoid follicles in the colonic mucosa was also an independent

prognostic factor. The total number of lymphoid follicles in the human large

bowel has been estimated from autopsy specimens to range from 12,000-

18,000 (Langman et al., 1986). Their number and diameter have been

shown to increase in inflammatory conditions (Nascimbeni et al., 2005),

while some workers have proposed that lymphoid follicles are intimately

involved in mucosal regeneration as well as in immune surveillance (Sipos


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et al., 2011). The density of intratumoural lymphoid structures has been

associated with improved survival in non-small cell lung cancer (Dieu-

Nosjean et al., 2008). Another study has reported the incidence of lymphoid

follicles associated with early colorectal neoplasms varies according to

patient gender and to tumour site and histology (Fu et al., 2005).

The present study is the first to investigate the prognostic significance of

FOXP3+ Treg density in lymphoid follicles from normal colonic mucosa

(Table 5.4). The worse outcome of patients with high Treg density is an

intriguing finding and we hypothesise this could be an indicator of increased

systemic susceptibility to metastasis. It will be interesting to determine

whether other immune cell subtypes present in follicles also have prognostic

significance and whether the density of FOXP3+ cells in follicles correlates

with their level in circulation. The predominant localisation of FOXP3+

Tregs to the mantle zone (Fig. 5.2A and 5.2B) is similar to the report by

Lim et al. in tonsil sections (Lim et al., 2005). Although not investigated

here, lymphoid follicles with small germinal centres (Treg poor) would thus

be expected to show higher FOXP3+ cell densities compared to those with

relatively larger centres. The apparently worse outcome associated with

high Treg density in mucosal lymphoid follicles (Table 5.4) could therefore

be a function of impaired B-cell reaction, as observed by a smaller germinal

centre response, rather than a direct effect of Tregs.

To our knowledge, the present study is also the first to investigate the

prognostic significance of lymphoid follicle frequency in the adjacent non-

tumour tissue of any cancer type. The observation of better outcome for


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patients with a high frequency of lymphoid follicles (HR 0.31) could be a

potentially important finding if confirmed by further studies. This factor is

relatively straightforward to quantify and provides prognostic information

that appears to be independent of both EMVI and FOXP3+ cell density

(Table 5.4). In exploratory subgroup analysis, the lymphoid follicle

frequency appeared to have stronger prognostic significance for patients

with proximal tumours (HR=0.13; 95%CI: 0.02-1.00, p=0.051) compared to

those with distal tumours (HR=0.64, 95%CI: 0.18-2.27, p=0.488). It is

currently unclear why this factor has prognostic significance; however, we

suspect that it could reflect the status of the alimentary or systemic immune

system, including its ability to respond to neoplasia.

Based on the present work and on earlier studies discussed above, there is

now abundant evidence that EMVI and TILs can provide clinically useful

information for the prognostic stratification of stage II colon cancer patients.

For EMVI, the need for high-quality pathology reporting and optimal

specimen preparation has already been emphasised (Quirke et al., 2007;

Williams et al., 2007; Betge et al., 2011). For TILs, further work is required

to determine the immune parameter(s) that provide the strongest and most

robust prognostic information. The work described in this Chapter and in

Chapter 3 suggests that histologically normal colonic mucosa should not be

overlooked as a potential source of clinically relevant markers. In particular,

the density of FOXP3+ cells within lymphoid follicles and the frequency of

these in the mucosa represent novel and independent prognostic factors.

These should now be validated in additional, large cohorts of stage II colon

cancers in which a minimum number of lymph nodes have been examined,


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EMVI has been carefully reviewed and patients have not received adjuvant

chemotherapy.

Chapter 6: General discussion


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6. General discussion

6.1. Background

Cancer of the colon and rectum is the second most commonly diagnosed

cancer in Australia and the second leading cause of cancer-related death

(AIHW, 2008). In 2007 there were 14,234 diagnoses of bowel cancer and

4,047 deaths from bowel cancer. Currently prognosis and recommendation

for adjuvant therapy is determined by TNM stage. Patients with stage I, II,

III and IV disease have progressively worse 5-year survival rates of 88%,

70%, 43% and 7% respectively (NH&MRC Guidelines). Adjuvant

chemotherapy is recommended for patients with stage III disease but not for

stage II disease, despite significant cancer related mortality in the latter

group. In stage II CRC, adjuvant chemotherapy is associated with a small

(3-5%) but statistically significant survival benefit (NH&MRC Guidelines;

Quasar, 2007). The NHMRC guidelines therefore state that “high risk sub-

groups” are more likely to benefit from adjuvant chemotherapy, but without

explicitly defining these groups.

6.1.1. Identification of high risk stage II colorectal cancer

The Peterson Index was developed to assist with risk stratification of stage

II colon cancer (Peterson et al., 2002). It is based on four standard

histopathological markers: vascular invasion, peritoneal involvement,

positive margins and tumour perforation. The Peterson score is calculated

by assigning one point for each risk factor except perforation, which

represents two points. Patients with a score of zero have a 5-year survival

rate of 94%, compared to 30% for patients with a score of three or more.


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The Peterson Index has been validated in a separate cohort (Roxburgh et al.,

2009); although this follow-up study found that all four histopathological

markers were only reported in 23.3% of cases. The survival difference

between high and low risk groups, although not as large as in the original

report, was statistically significant.

Newly released international guidelines (NCCN, 2012) recommend

chemotherapy for patients with high risk stage II colon cancer as defined by

high tumour grade, T4 status, lymphovascular/perineural invasion, bowel

obstruction, perforation, less than 12 nodes examined and indeterminate or

positive margins. These standard histological markers, in particular EMVI

and serosal invasion, are essential for accurate prognostication but are often

under-reported and suffer from inter-observer variation (Morris et al., 2007;

Stewart et al., 2007; Littleford et al., 2009).

6.1.2. Peritumoural inflammatory infiltrate is associated with improved survival

The focus of the current system of prognostication is the degree of invasion

and metastasis of the primary tumour. However, the host immune response

may be equally important. McCarty initially reported the good prognosis

imparted by a peritumoural inflammatory infiltrate (McCarty, 1931) and this

has since been supported by other authors and brought to prominence by

Jass (1986). Building on this work, Murphy et al. (2000) demonstrated that

the presence of an inflammatory infiltrate was associated with the clearance

of micrometastases from the bone marrow and improved survival. Klintrup

et al. (2005) classified peritumoural inflammation into either high or low

grade and claimed that high grade inflammation at the invasive margin was


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the most important prognostic factor for Dukes’ stage A and B CRC. This

finding was later “validated” by an independent group (Roxburgh et al.,

2009). Unfortunately, neither of these two studies documented vascular

invasion and T4N0 tumours were either excluded (Klintrup et al., 2005) or

not mentioned (Roxburgh et al., 2009). Furthermore, the Klintrup method of

classification of the peritumoural inflammatory response into either low or

high grade is subjective, requiring interpretation by a pathologist and

therefore prone to inter-observer variation.

6.1.3. Host immunity is important for surviving cancer

Despite the above-mentioned methodological shortcomings, other

observations suggest that a deficient host response contributes to the

development and progression of CRC. Chronic immunosuppression is

associated with significantly worse disease-free survival compared with

immunocompetent matched controls (Khoury et al., 2011). Renal

transplantation, which requires immunosuppression, is associated with a

twofold-increased risk of developing colonic cancer (Parnaby et al., 2010).

In addition kidney and liver transplant patients tend to present at an earlier

age and have worse survival (Johnson et al., 2007). Patients with HIV tend

to have earlier age of CRC onset and more advanced disease at presentation

(Alfa-Wali et al., 2011).

6.1.4. T helper type 1 immune cells are associated with improved survival

As discussed in Chapter 1, specific cells and molecules within the

inflammatory infiltrate have been examined using a variety of specialised

techniques. It has been widely claimed that the Th1 arm of the adaptive


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immune response confers the protective effect associated with the

surrounding inflammatory (Pagès et al., 2005, Sazbo et al., 2003, Galon et

al., 2006). Previous studies have demonstrated that increasing densities of

cells and molecules of the Th1 response are associated with improved

outcomes, but they are also associated with early stage tumours and the

absence of early invasion (Naito et al., 1998, Pagès et al., 2005, Galon et

al., 2006). This raises the question of whether the immune response seen

around the tumour has a protective effect, or whether it is simply reflective

of a more favourable tumour phenotype. Efforts to harness the immune

system to fight cancer have so far proven largely unsuccessful (Rosenberg

et al., 2004). This has been ascribed to the ability of the tumour to evade

detection (“tumour escape”) and to create a state of immune suppression by

the release of inhibitory cytokines and the recruitment of Tregs (Zou, 2005).

The purpose of the work in this thesis was therefore to determine whether

individual cell types of the immune response, identified by

immunohistochemical staining and quantified by digital image analysis, had

prognostic significance in stage II CRC. One of the novel features of this

study was the strong focus on the prognostic significance of FOXP3+Tregs

in CRC. In addition, these investigations sought to evaluate the anti-tumour

immune response in conjunction with accurate assessment of standard

histopathological markers, hitherto not previously performed. The final and

novel area of investigation was to examine immununological markers

within histologically normal colonic mucosa taken from the surgical margin.


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6.2. Major findings

The experimental work within this thesis utilised digital image analysis to

objectively measure immune parameters in the setting of CRC. Image

analysis algorithms were carefully calibrated [PS] to ensure optimal stain

detection and cell counting. Internal measures within the data, such as

higher immune cell densities within MSI tumours, revealed this to be a

robust system. One of the limitations of this thesis was that a validation

study assessing agreement between digital image analysis and manual

counting by the pathologist was not formerly performed. There is, however,

extensive literature demonstrating the accuracy of digital image analysis

(Krann et al., 2000; Haringman et al., 2005; Laurinaviciene et al., 2011;

Tuominen et al., 2012).

6.2.1. Tumour-infiltrating Tregs have strong prognostic significance

The density of Tregs within the tumour tissue was a strong and significant

prognostic marker (Table 3.5). In contrast to several other tumour types, a

high density of tumour-infiltrating Tregs was associated with better

prognosis in CRC. The addition of Treg density to vascular and perineural

invasion in multivariate analysis significantly improved the prognostication

of stage II CRC (Table 3.6). Furthermore, in patients who would normally

be considered as having low risk stage II CRC as determined by the absence

of vascular or perineural invasion, tumour-infiltrating Tregs could stratify

patients into high and low risk groups (Figure 6.1). Normally, such patients

would not be offered adjuvant therapy despite there being a significant

cancer-specific mortality rate.


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Figure 6.1. In stage II CRC with no vascular, perineural or lymphatic invasion, the density of tumour-infiltrating Tregs can further stratify patients into low and high risk groups.

Log-rank P value=0.002.

Since publication of the work described in Chapter 3, other groups have

independently confirmed the prognostic significance of tumour-infiltrating

Tregs in CRC (Frey et al., 2010; Correale et al., 2010; Nosho et al., 2010;

Lee et al., 2010). It has now been shown consistently that high densities of

tumour-infiltrating Tregs are associated with improved outcomes for CRC

patients. The mechanism behind this paradoxical finding remains to be

elucidated; however, it has been speculated that Tregs could suppress

bacterial-driven inflammation and in this manner slow the rate of tumour

growth (Ladoire et al., 2011).

An unexpected and novel finding from this study was that a high density of

Tregs within histologically normal colonic mucosa taken from the surgical


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margin was associated with adverse prognosis (Table 3.5). This finding was

confirmed in a separate cohort described in Chapter 5, although further

research is required to elucidate the underlying mechanism.

6.2.2. Low expression of Granzyme B is associated with signs of early metastasis

Although the CD8+ T cell density was measured in the work described in

Chapter 3, the cytotoxicity or activity of these cells was not evaluated. This

was investigated in the Chapter 4 by evaluating the expression of the

effector molecule, GrB, which facilitates target cell destruction. In keeping

with the earlier results of Pagès et al. (2005), low levels of GrB were

associated with vascular, perineural and lymph node metastasis. High levels

of GrB on the other hand were associated with location of the tumour in the

proximal colon, TILs, MSI+ tumours and better survival on univariate

analysis. On multivariate analysis that included standard histopathological

markers and Treg density, GrB expression was not a significant prognostic

marker.

6.2.3. Immune parameters retain prognostic significance even when vascular and serosal invasion are carefully assessed

As mentioned earlier, standard histological risk factors such as serosal and

vascular invasion are often under-reported and suffer from inter-observer

variability (Morris et al., 2007; Stewart et al., 2007; Littleford et al., 2009).

It therefore remained to be determined whether measurement of immune

cell parameters such as Treg density would retain prognostic significance in

the presence of careful and accurate pathological assessment. Furthermore,

the work described in Chapter 3 measured the density of immune cells in


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1mm cores from a random area within the tumour and the normal colonic

mucosa.

Hence, it was important to assess a larger tissue area from both the tumour

core and the advancing margin. In addition, the finding that a high Treg

density within the histologically normal colonic mucosa taken from the

surgical margin was associated with poor cancer specific outcomes (Table

3.5) required validation in an independent cohort. These issues lead to the

experimental work described in Chapter 5. Pathology review confirmed that

vascular and serosal invasion were the most important standard

histopathological markers for stage II colon cancer. High densities of Tregs

at the advancing margin of the tumour were associated with better survival,

but this did not reach statistical significance, possibly due to the low number

of cancer-related events and the relatively small study population. Of major

interest, however, was that immune parameters within the normal colonic

mucosa were highly significant for prognostic relevance on multivariate

analysis.

6.2.4. Tregs within lymphoid follicles of histologically normal colonic mucosa are associated with adverse outcome

A high density of Tregs within the normal colonic mucosa was associated

with worse prognosis (Table 3.5). In Chapter 5, this finding was expanded

further by measuring the density of Tregs with lymphoid follicles of the

normal colonic mucosa from the surgical margin. A high density of FOXP3+

cells within the lymphoid follicles was strongly associated with adverse

survival and appeared to be the strongest prognostic marker on multivariate

analysis (Table 5.4). This observation may be an indicator of the host’s


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ability to suppress metastasis. The predominant site of metastasis from

colon cancer is the liver and hence future studies could be directed at

exploring immune parameters within this organ.

6.2.5. Lymphoid follicles within the normal colonic mucosa have a protective effect

A high frequency of lymphoid follicles per length of histologically normal

colonic mucosa from the surgical margin was associated with better cancer-

specific survival (Table 5.4), particularly for patients with proximal colon

tumours. Similar to the density of FOXP3+ Tregs within the mantle zone of

these structures, the lymphoid follicle frequency may reflect the presence of

local or possibly even systemic factors that control invasion and metastasis.

Future research should explore for possible associations between the

frequency of lymphoid follicles and systemic immune parameters.

6.3. Future research

A significant amount of literature has been published regarding the

prognostic significance of two hepatic proteins: albumin and C-Reactive

Protein. The modified Glasgow Prognostic Score (mGPS) is thought to be a

measure of systemic inflammation and higher scores are associated with

worse cancer-specific outcomes (McMillan et al., 2007). The systemic

inflammatory response as measured by the mGPS was not found to be

associated with the Klintrup classification of peritumoral infiltrate, but both

parameters showed prognostic significance (Roxburgh et al., 2009). A

future topic of research would be to investigate for associations between the

density tumour-infiltrating Tregs with systemic markers of inflammation.


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The “seed and soil hypothesis” first proposed by Paget in 1889 states that

particular organs are more susceptible to metastasis from different cancer

types (Fidler, 2008). In this model the “soil” was the organ susceptible to

the development of metastasis. This hypothesis could be expanded to

include the patient as a whole and their propensity to develop metastasis as

there is mounting evidence that systemic factors (comorbidity, physiological

status) influence cancer specific survival (Jenkins et al., 2007; Richards et

al., 2010). It is therefore likely that patients with significant co-morbidity

have weakened anti-tumour immune responses. This idea could be

investigated further by searching for an association between immune

parameters in the histologically normal colonic mucosa and measures of co-

morbidity.

Tumour factors such as those described as the Peterson Index represent the

“seed” where as immune parameters along with measures of systemic

inflammation and physiology represents the “soil.” Neither is truly

independent of each other, rather there is a complex interplay between the

host and tumour both locally and systemically. Factors traditionally

associated with the tumour such as vascular invasion may actually reflect

the host’s susceptibility to invasion and metastasis. Furthermore, a cancer

cell can only arise from a host that has accumulated sufficient mutations due

to both genetic predisposition and environmental factors. Once this has

occurred the tumour cell must avoid elimination by the immune system.

Although the adaptive immune response is protective, the cancer may

induce immunosuppression (Heriot et al., 2000) and chronic inflammation

may further predispose and assist with tumour growth (Coussens 2002).


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6.4. Conclusions

Although the TNM staging system is generally effective in the

prognostication of CRC, the reliable identification of high risk stage II

patients remains a concern. Standard histological markers, in particular

vascular and serosal invasion, are very effective at identifying high risk

patients but are widely under-reported and suffer from inter-observer

variability. The assessment of host factors, in particular immunological

parameters, can improve prognostication even when standard histological

markers are accurately reported. The use of IHC and digital image analysis

provide objective measures of the host response and can thereby reliably

assist with prognostication. Immunological parameters seen at the tumour

site and within histologically normal colon are likely to reflect systemic

factors important for the development of metastasis.

6.4.1. Summary of major findings

• Tumour-infiltrating Tregs are associated with good prognosis in

CRC.

• Tregs within the lymphoid follicles of the normal colonic mucosa

are associated with poor prognosis.

• A higher frequency of lymphoid follicles in histologically normal

colonic mucosa at the surgical margin appears to have a protective

effect.

• Vascular and serosal invasion are the most important standard

histological markers for stage II colon cancer.


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6.4.2. Future studies emanating from this work

• Investigate the relationship between tumour-infiltrating Tregs and

� circulating Tregs

� systemic markers of inflammation

� co-morbidity

• Investigate the relationship between the density of Tregs within

lymphoid follicles and systemic markers of inflammation and co-

morbidity.

• Investigate if the presence of an immune response is predictive for

response to chemotherapy.

• Investigate whether the profile of circulating lymphocytes (including

Tregs) changes with chemotherapy and if this is prognostic.

• Validate the prognostic value of FOXP3+ Treg density in tumour

tissue and in lymphoid follicles from normal colonic mucosa. This

should be carried out by independent, prospective studies of stage II

colorectal cancer.

Chapter 7: Bibliography

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