ROLE OF THE IMMUNE SYSTEM IN TUMOR PROGRESSION 1

ROLE OF THE IMMUNE SYSTEM IN TUMOR
PROGRESSION


TOH PANG KIAT, BENJAMIN
(B.Sc. (Hons.), NUS)


A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR
OF PHILOSOPHY

NUS Graduate School for Integrative Sciences and Engineering

NATIONAL UNIVERSITY OF SINGAPORE
2011

i

Acknowledgements
I would like to acknowledge my supervisor, Jean-Pierre Abastado, for his continued
help and support throughout the course of my PhD. He has been a great mentor and
guide from whom I have learnt a great deal. I would also like to thank my thesis
advisory committee members, Ren Ee Chee and Laurent Renia, for their guidance and
help.

I would like to show my appreciation to all members of the Tumor Immunology
Laboratory in the Singapore Immunology Network (SIgN). Special thanks go to

Karen Khoo, Jeremy Wang and Jo Keeble for their help and discussions about the
work presented in this thesis.

Next, I would like to thank my collaborators for their help in this project. Laurent
Renia (SIgN) for the NIMP-R14 antibody, Ng Lai Guan (SIgN) for providing me with
the IL8R-KO and tdTomato mice, Esther Koh for help in the cell tracking software,
Poon Lai Fong (SIgN) for help with cell sorting, Josephine Lum (SIgN) for the
microarray work and Wong Wing Cheong (BII) for the analysis of the microarray
data. Special thanks to Masashi Kato (Chubu University, Aichi, Japan) and Armelle
Prevost-Blondel (Institut Cochin, Paris, France) for providing the RET mice. I would
also like to thank Jean-Paul Thiery (IMCB) and Sim Wen Jing (IMCB) for their help
and discussion regarding the EMT assays.

Last but not least, I would like to thank my family for their support, especially my
wife, who painstakingly helped with the editing of this thesis.

ii

Table of Contents
Acknowledgements i
Summary v
List of Tables vi
List of Figures vii
List of Appendices ix
List of Videos ix
List of Publications x
List of Abbreviations xi

Introduction 1
Inflammation, immunity and cancer 1

Immunosurveillance theory 2
Immunoediting theory 3
Roles of immune cells 6
Melanoma 9
Diagnosis and treatment 11
Melanoma and the immune system 15
Objectives 16

Experimental Procedures 18
Mice 18
In vivo PMN-MDSCs depletion 18
Flow cytometry analysis 19
Isolation of PMN-MDSCs and macrophages 20
Microarray analysis 21
Cytospin and May-Grunwald/Giemsa stain 22
Tumor cell detection by qRT-PCR 23
Low density microarray 23
Immunohistochemistry and calculations 24
Migration assay 25
Tumor proliferation assay 26

iii

OVA-specific T cell proliferation assay 27
E-Cadherin assays 27
MT assay 28
Statistics 29

Chapter 1: Not All Tumors Are Made Equal 30
Introduction 30

RETAAD – Spontaneous mouse model of melanoma 31
Results 35
Different tumors from the same mouse have different immune
infiltrates 35
Granulocytes are increased in the periphery during tumor progression 39
CXCL1, 2 and 5 and CCL19 are up-regulated in primary tumors 41
CXCR2 ligands are able to attract PMN-MDSCs 42
CXCR2 is necessary for the attraction of PMN-MDSCs to the tumor
in vivo 43
CXCL1 and 2 are expressed by the PMN-MDSCs while CXCL5 is
expressed in tumor cells 44
Discussion 46

Chapter 2: Role of PMN-MDSCs in Tumor Progression 53
Introduction 53
Myeloid-derived suppressor cells 53
Metastasis and epithelial-mesenchymal transition 62
Results 65
Depletion of PMN-MDSCs reduces tumor growth in vivo 65
PMN-MDSCs promote cancer cell proliferation in the primary tumor 67
PMN-MDSCs secrete soluble factors that promote cancer cell
proliferation in vitro 69
PMN-MDSCs favor multinodular development of primary tumors 70
PMN-MDSCs induce cancer cell dissemination to regional and
distant sites 71
PMN-MDSCs favor metastatic outgrowth 73
PMN-MDSCs induce cancer cell MT in vitro 74

iv

PMN-MDSCs induce down-regulation of epithelial marker, E-
Cadherin, in melanoma cells 77
PMN-MDSCs induce melanoma cell MT in vivo 78
Tumor cells express EGF, while PMN-MDSCs express HGF and
TGF-β
1
81
PMN-MDSCs induce MT through multiple pathways 82
Discussion 84
Induced proliferation of cancers cells by PMN-MDSCs 84
PMN-MDSCs induce MT in cancer cells 86

Chapter 3: Significance and Implications 92
MT, metastasis and phenotype-switching 92
Multiple roles of PMN-MDSCs 101
Tumor dormancy 105
Therapeutic implications 109
Lymph node excisions 109
Inflammation 112
PMN-MDSCs 114
Chemotherapy and immunotherapy 118
Conclusion 121

Bibliography 124

Appendices………………………………………………………………. A


v

Summary
In order to metastasize, cancer cells need to acquire a motile phenotype. Previously,
development of this phenotype was thought to rely on the acquisition of selected,
random mutations and thus occur late in cancer progression. However, recent studies
show that cancer cells disseminate early, implying the existence of a different, faster
route to the metastatic motile phenotype. Using a spontaneous murine model of
melanoma, I show that a subset of bone marrow-derived immune cells (myeloid-
derived suppressor cells or MDSCs) preferentially infiltrates the primary tumor and
actively promotes cancer cell dissemination by inducing mesenchymal transition
(MT). In vitro and in vivo assays using purified MDSCs showed attraction of MDSCs
to the primary tumor is CXCR2-dependent and that TGF-β, EGF and HGF signaling
pathways are all used by MDSCs to induce MT in cancer cells. These findings explain
how cancer cells acquire a motile phenotype early and provide a mechanistic
explanation for the long recognized link between inflammation and cancer
progression.


vi

List of Tables
Table 1: Roles of different immune cell subsets in cancer. 7
Table 2: The ‘ABCD’ method of identifying early melanoma lesions. 12
Table 3: List of antibodies used 20
Table 4: Summary of the characteristics and differences of MDSCs. 61
Table 5: Summary of the characteristics and differences of MDSCs including the
present research 91


vii

List of Figures
Figure 1: Illustration of immunoediting theory. 5
Figure 2: Overall analysis of tumors. 35
Figure 3: Differential accumulation and morphology of macrophages and
granulocytes. 37
Figure 4: Comparison of tumors by immune subset. 38
Figure 5: Accumulation of granulocytes in tumor bearing mice. 40
Figure 6: Differential expression of chemokines and cytokines between
primary tumor and cutaneous metastases. 41
Figure 7: Migration of PMN-MDSCs to CXCR2 ligands. 43
Figure 8: CXCR2 ligands are important and necessary for PMN-MDSCs
migration to the primary tumor. 44
Figure 9: Expression of CXCR2 and its ligands in PMN-MDSCs and
tumor cells. 45
Figure 10: Depletion of intra-tumoral PMN-MDSCs. 66
Figure 11: Depletion of PMN-MDSCs reduces tumor growth but not
tumor vasculature. 67
Figure 12: Depletion of PMN-MDSCs reduces proliferation in young eye
tumors. 68
Figure 13: PMN-MDSCs induce proliferation of tumor cells in vitro
through soluble factors. 70
Figure 14: Depletion of PMN-MDSCs reduces nodular structure of the
primary tumor. 71

viii

Figure 15: Depletion of PMN-MDSCs reduce metastasis to lung and
lymph nodes. 72
Figure 16: Depletion of PMN-MDSCs reduces number of cutaneous
metastases but not their size. 73

Figure 17: PMN-MDSCs induce MT in vitro. 75
Figure 18: PMN-MDSCs down-regulate E-Cadherin expression. 77
Figure 19: S100A4 expression in primary tumors. 80
Figure 20: Differential expression of TGF-β
1
, HGF and EGF in PMN-
MDSCs and tumor cells. 81
Figure 21: Inhibition of PMN-MDSC induced mesenchymal transition. 82
Figure 22: Diagram illustrating the differences between the two models of
tumor progression. 96
Figure 23: Diagram illustrating the progression of tumors in RETAAD
mice. 99
Figure 24: In silico modeling of tumor growth in non-vascularised tumors. 103
Figure 25: Graph illustrating that micrometastases occur before detection
of the primary tumor. 106
Figure 26: Illustration of interactions between PMN-MDSCs and tumor
cells. 122



ix

List of Appendices
Appendix 1: Calculations of proliferation and estimate of size ………………… B
Appendix 2: Immune profiling gating strategy ………………………………… … E
Appendix 3: Table of chemokine/cytokine expression …………………………… F
Appendix 4: Mitf expression in LN ……………………………………… ……… G
Appendix 5: Alternate inhibitors of HGFR, EGFR and TGF-βR1 ………………… H
Appendix 6: Dct expression in lungs of CD8-depleted mice at seven weeks ………. I
Appendix 7: Dct expression in lungs of tumor-bearing MMP9-KO mice ………… J

List of Videos
Video 1: Time lapse of NBT-II cells without stimulation.
Video 2: Time lapse of NBT-II cells with EGF.
Video 3: Time lapse of NBT-II cells with PMN-MDSCs.

x

List of Publications
1. Toh B, Wang X, Keeble J, Sim WJ, Khoo K, Wong WC, Kato M, Prevost-
Blondel A, Thiery JP and Abastado JP Mesenchymal Transition and
Dissemination of Cancer Cells is driven by Myeloid-Derived Suppressor Cells
Infiltrating the Primary Tumor. PLoS Biol 9(9): e1001162.
doi:10.1371/journal.pbio.1001162

2. Toh B, Nardin A, Dai X, Keeble J, Chew V and Abastado JP Detection,
enumeration and characterization of immune cells infiltrating melanoma
tumors. Chapter for “Molecular Methods in Dermatology” Humana Press,
USA (under Review)

3. Liang Zhi, Benjamin Toh, and Jean-Pierre Abastado Myeloid derived
suppressor cells: subsets, expansion, and role in cancer progression Chapter
for “Tumor Microenvironment and Myelomonocytic Cells” ISBN: 979-953-
307-100-7. Intech (under Review)

4. Bourgault-Villada

I, Hong M, Khoo

K, Tham M, Toh B, Wai LE and Abastado

JP (In Press) Current insight into the metastatic process and melanoma cell
dissemination. Chapter for “Melanoma” ISBN: 978-953-307-293-7. Intech
(Accepted on March 23, 2011)

5. Eyles J, Puaux AL, Wang X, Toh B, Prakash C, Hong M, Yan TG, Zheng L,
Ong LC, Jin Y, Kato M, Prevost-Blondel A, Chow P, Yang H and Abastado
JP (2010) Tumor cells disseminate early, but immunosurveillance limits
metastatic outgrowth, in a mouse model of melanoma. J Clin Invest 120:
2030-2039.




xi

List of Abbreviations
APC = Antigen presenting cells
Arg = Arginase
CD = Cluster of differentiation
DC = Dendritic cells
ECM = Extracellular matrix
EGF = Epidermal growth factor
EMT = Epithelial mesenchymal transition
h = Hour
HGF = Hepatocyte growth factor
IL = Interleukin
iNOS = Inducible nitric oxide synthase
IFN = Interferon
IHC = Immunohistochemistry
LN = Lymph nodes

KO = Knock-out
MDSC = Myeloid-derived suppressor cells
MET = Mesenchymal epithelial transition
Mets = Metastases
mins = Minutes
MHC = Major histocompatibility complex
mm = millimeter
MMP = Matrix metalloproteinases
Mo = Monocytes
MT = Mesenchymal transition
μm = micrometer
NK cells = Natural killer cells
NO = nitric oxide
PMN = Polymorphonuclear
qRT-PCR = Quantitative real-time polymerase chain reaction
RNA = Ribonucleic acid
ROS = Reactive oxygen species
s = seconds
TAM = Tumor associated macrophages
TGF = Transforming growth factor
TNF = Tumor necrosis factor
Tregs = Regulatory T cells
TRP = Tyrosinase related protein
UV = Ultraviolet
Wt = Wild-type

1

Introduction
Inflammation, immunity and cancer

Tumors do not consist of a homogeneous population of cells; rather they are a
composite of the cancer cells, mesenchymal and endothelial cells, and immune cell
populations. The link between cancer progression and inflammation was recognized
by R. Virchow in the late 19
th
century [1,2,3,4,5]. Now, the role of inflammation in
tumorigenesis is generally accepted and an inflammatory microenvironment is an
essential component in all tumors [3,4,6,7].

Inflammation is the response to an infection or tissue injury, whereby complex
networks of chemical signals initiate and maintain a host response to ‘heal’ the
afflicted or infected tissue [8]. Acute inflammation is the initial early response of the
body against harmful stimuli. Chronic inflammation occurs when the body is unable
to resolve an acute inflammation or when inflammation itself has a slow onset.
However it starts, chronic inflammation can last for months and years. Inflammation
is not beneficial all the time. It has been shown that chronic inflammation is a
significant risk factor in cancer development and tumor progression. Up to 20% of
cancers are directly linked to chronic infections, 30% can be attributed to tobacco
smoking and inhaled pollutants (such as silica and asbestos), and 35% to dietary
factors (20% of which includes obesity) [3]. All these initiating events are able to
induce inflammation. Persistent infections by Helicobacter pylori and human
papilloma virus have been identified as major risk factors in gastric cancer and
cervical cancer respectively [9]. Inflammation in these cases is actually part of the

2

normal host response to pathogens. However, these microbes can subvert this host
response to establish a chronic inflammatory environment for their own benefit [3].
Interestingly, inducing acute inflammation can be effective in treating some cancers
like the treatment of superficial bladder cancer with Mycobacterium bovis bacillus

Calmette–Guérin (BCG) instillation [10]. Chronic inflammatory diseases have also
been linked to cancer i.e. inflammatory bowel syndrome and colorectal cancer [11].
Despite these associations between the host immune responses and cancer
development, the exact molecular mechanisms and complex interactions between
cells of the tumor microenvironment have yet to be fully understood.

Immunosurveillance theory
In cancer, it has been proposed that the immune system plays a key role in preventing
the natural occurrence of malignant cells, seen as foreign bodies, in humans. This
concept was first proposed in the 1900s by Paul Ehrlich. However, it was only in
1957, with a deeper understanding of the immune system, that Burnet and Thomas
formally proposed the hypothesis of cancer immunosurveillance. This was defined by
Burnet as follows: “In large, long-lived animals, like most of the warm-blooded
vertebrates, inheritable genetic changes must be common in somatic cells and a
proportion of these changes will represent a step toward malignancy. It is an
evolutionary necessity that there should be some mechanism for eliminating or
inactivating such potentially dangerous mutant cells and it is postulated that this
mechanism is of immunological character. [12]” The role that the immune system
plays in controlling cancer development can be seen in transplant patients. These
patients are under immunosuppressive drugs for prolonged periods to prevent
rejection of their transplant organ. A 4-fold increase in incidence of in situ melanoma

3

can be found in patients that had undergone transplants [13]. In a study of 162 patients
that received transplants, melanoma constituted 5.2% of post-transplant skin cancers
in patients compared with the incidence of 2.7% in the general population [14].
Transplant patients were also three times more likely to develop non-Kaposi’s
sarcomas [15]. In a study of 608 cardiac transplant patients, the prevalence of lung
tumors was 25-fold higher than in the general population [16]. In another study of

5,692 patients that had undergone renal transplants, 2- to 5-fold excess risks were
seen for cancers of the colon, lung, bladder, kidney, ureter, endocrine tumors and
malignant melanomas as opposed to the general population [17]. Immunosuppression
increases the risk of cancer, even for those of no known viral etiology, as seen in the
examples above. Of course, in cancer cases with known viral etiology,
immunosuppression also results in an increased risk of cancer [13].

Immunoediting theory
However, the immunosurveillance theory only explains one half of the story. The
immunoediting theory proposed by Schreiber [18,19] is the updated version of
previous theories that now takes into account evidence of tumor escape mechanisms.
In this theory, shown in Figure 1, it is proposed that there are three distinct sequential
stages of tumor progression – 1) elimination, 2) equilibrium and 3) escape. 1) The
elimination stage is an updated version of the immunosurveillance theory. This is the
stage in which innate and adaptive immune systems work to detect and destroy an
incipient tumor before it becomes clinically apparent. Examples that support this have
been stated in the preceding paragraphs. However, since this elimination event takes
place without clinical symptoms, this stage has never been directly observed in vivo.
The next stage of tumor progression is 2) equilibrium. At this stage, the immune

4

system, comprising tumor-specific CD8
+
and CD4
+
T cells and natural killer (NK)
cells, is able to control the growth of the tumor. This is typically the longest of all the
three stages and is characterized by dormancy of the tumor [19]. Dormancy refers to a
state of cellular quiescence with cells in G

0
–G
1
arrest [20]. Latency may also occur
during this period. Latency is the perceived dormancy of the tumor due to the equal
rates of proliferation and elimination of the cancer cells. Latency is important to
Schreiber’s immunoediting theory because proliferation of the tumor cells is required
for the cells to gain sufficient mutations for escape. Thus, during equilibrium, the
tumors do not grow as the adaptive immune system prevents further tumor cell
outgrowth. Schreiber postulates that rare tumor cell variants may survive the
elimination and enter the equilibrium stage. He also postulates that due to the
selection pressure of antigen-specific T cells, tumor cells that are not immunogenic
are preferentially selected. If the immune system is successful in controlling tumor
development, this could be the stable end stage for some patients, whereby the tumor
is present but under tumor specific control [19].

The final stage is 3) escape. In this stage, the escape from immune control can occur
in two ways – a tumor cell-intrinsic acquired mechanism that evades recognition by
the immune system or the establishment of an immunosuppressive state within the
tumor microenvironment. The acquisition of an ‘escape’ phenotype is believed to be
the end result of tumor cell population changes in response to the immune system’s
selection or editing. These include phenotypic changes such as down-regulation MHC
Class I expression, disruption in the antigen processing machinery, down-regulation
of tumor antigens or up-regulation of anti-apoptotic genes such as Bcl-2 [21]. These
escaping tumor cells may also gain the ability to modulate the host immune system,

5

increasing cancer-induced immunosuppression [19]. For example, the secretion of
indoleamine 2, 3 dioxygenase (IDO) can deprive the microenvironment of tryptophan,

inducing apoptosis of effector T cells [21]. Up-regulation of FasL on tumor cells can
also cause T cell apoptosis through Fas/FasL pathway [22].


Figure 1: Illustration of immunoediting theory.
In Scheiber’s model of immunoediting [19], tumor progression occurs in three progressive and distinct
stages – elimination, equilibrium and escape. Newly formed tumors are eradicated by the immune
system effectively most of the time. However, in certain instances, rare tumor cells might evade this
immune system mediated destruction and persist. In these cases, tumor-specific mechanisms, such as
CD8
+
and CD4
+
tumor-specific T cells are activated in the immune systems to control these tumors.
Immunogenic tumor cells are then eliminated from the system while non-immunogenic tumor cells are
selected for and remain in equilibrium with the immune system in a state of dormancy. When these
dormant tumor cells have gained sufficient mutations to circumvent the immune system, they emerge
from dormancy and progress rapidly in the tissue. [Taken from Scheiber (2011)] [19]


6

Roles of immune cells
Almost all immune cells have been implicated in both protective and suppressive
roles during cancer progression (Table 1). Generally, macrophages and T cells are the
most numerous and they are the most studied immune cell types in the tumor
microenvironment. In humans, intratumoral T cell infiltrate has commonly been
associated with a good prognosis in several cancers such as colorectal cancer,
hepatocellular carcinoma and melanoma [23,24,25]. However, it has been shown that
T cells subsets, CD4

+
or CD8
+
, Th1 (rarely) or Th2, and regulatory T cells (Tregs)
have tumor promoting roles. In mice with chemically-induced skin cancer, CD8
+
T
cells have been found to secrete IFN-γ, TNF-α, and cyclooxygenase-2 that contribute
to inflammation and cancer progression [26]. IL-13 secreted by CD4
+
Th2 T cells
have also been shown to promote tumor progression in mice [27]. Regulatory T cells
have constantly been implicated in tumor progression due to their ability to suppress
an effective anti-tumoral immune response. In humans, elevated levels of tumor-
infiltrating regulatory T cells are correlated with a reduced overall survival in
numerous cancers [28]. T cells play an important role in tumor development. They
shape the immune response by secreting cytokines and one of the important immune
subsets they can affect is the macrophage subset.








7

Immune Cell Types
Anti-Tumor

Tumor Promoting
Macrophages,
Dendritic cells,
Myeloid-derived
suppressor cells
Antigen presentation
Production of cytokines (IL-
12 and type I IFN)
Immunosuppression
Production of cytokines,
chemokines, proteases,
growth factors, and
angiogenic factors
Mast cells
Production of cytokines
B cells
Production of tumor-specific
antibodies
Production of cytokines
Activation of mast cells
Immunosuppression
Inflammation
CD8
+
T cells
Direct lysis of cancer cells
Production of cytotoxic
cytokines
Production of cytokines
CD4

+
Th2 cells
Education of
macrophages
Production of cytokines
B cell activation
CD4
+
Th1 cells
Help to cytotoxic T
lymphocytes (CTLs) in
tumor rejection
Production of cytokines
(IFNγ)
Production of cytokines
CD4
+
Th17 cells
Activation of CTLs Production of cytokines
Inflammation
CD4
+
Treg cells
Suppression of inflammation
(cytokines and other suppressive
mechanisms)
Immunosuppression
Production of cytokines
Natural Killer cells
Direct cytotoxicity toward

cancer cells
Production of cytotoxic
cytokines

Natural Killer T cells
Direct cytotoxicity toward
cancer cells
Production of cytotoxic
cytokines

Neutrophils
Direct cytotoxicity
Regulation of CTL
responses
Production of cytokines,
proteases, and ROS
Table 1: Roles of different immune cell subsets in cancer.
Immune cell can play paradoxical roles in cancer development depending on the environment and the
polarization of the different subsets. Different cancers induce different subsets of immune cells and
some immune cells can play an important role in one type of cancer and not another. The roles and
functions of each subset are not fixed. These can be altered during the course of the disease or during
treatment. [Taken from Grivennikov et al (2010)][3]

8


Tumor associated macrophages (TAMs) play an important role in tumor development.
Macrophages are generally split into two subsets – M1 and M2; with TAMs
supposedly being of the M2-like subset. The M2 subset is polarized in vitro by IL-4,
IL-10 and IL-13 [29]. They down-regulate major histocompatibility complex (MHC)

class II and IL-12 expression and show increased expression of the anti-inflammatory
cytokine IL-10, scavenger receptor A, and arginase (Arg). These macrophages are
mainly involved in wound healing processes and angiogenesis [29]. This is in contrast
with M1 macrophages which are more inflammatory and are activated by IFNγ and
toll-like receptor (TLR) agonists. These macrophages express high levels of pro-
inflammatory cytokines like TNF-α, IL-1, IL-6, IL-12 and inducible nitric oxide
synthase. They are the main macrophages involved in killing pathogens and priming
anti-tumor immune responses [29]. However, it is now recognized that, although
useful, segregation of the macrophage into distinct subsets is an over-simplification
[30]. This is due to the plasticity of the macrophages and their ability to differentiate
along a continuous spectrum of phenotypes that lie between M1 and M2. However,
what is consistent among TAMs, to a certain degree, is that they seem to primarily
favor tumor growth. They are capable of creating a suppressive immune environment
through Arg expression. They secrete angiogenic factors such as vascular endothelial
growth factor (VEGF) and epidermal growth factor (EGF) that help in tumor
angiogenesis. TAMs also express matrix metalloproteases (MMP) like MMP2 that
help break down extracellular matrix and (1) release ECM bound factors such as
TGF-β and/or (2) allow metastasis of tumor cells. These functions vary depending on
the type of tumor and the location of the TAMs in the tumor e.g. TAMs in hypoxic

9

areas of the tumor express more angiogenic factors compared to TAMs in other parts
of the tumor [8,30].

In summary, inflammation and the immune system play critical roles in both tumor
suppression and tumor progression. Understanding the complex interactions that
occur within the tumor microenvironment is key to re-activating the immune system
against the tumor. However, we must also realize that not all tumor
microenvironments are the same. Tumors can occur throughout the body. Each organ

has its own vasculature system, lymphatic drainage and even organ-specific immune
cells. Tumor cells can further modulate this environment with its own secretions,
making the microenvironment unique. Therefore, the study of the cross-talk between
cancer cells and the immune system must be analyzed in the context of the organ in
which the tumor exists and the type of cells that the tumor recruits.

Melanoma
In Singapore, cancer mortality rates are on the rise. Cancer now accounts for more
than a quarter of all deaths in Singapore, as compared to 14.8% in 1968-1973 [31].
Skin cancer is the most common site of cancer development in humans, accounting
for almost half of the new cancers cases in the United States of America [32]. Skin
cancers, including melanoma, are the 8
th
most common cancers in males and the 9
th

most common in females in Singapore [31].

Melanoma is the malignancy of melanocytes – neural crest-derived pigmented cells
that produce melanin. Melanoma is generally found on the skin but can be found in
any organ that contains melanocytes i.e. eye (uveal tract), mouth, nasal cavities,

10

oesophagus, stomach, rectum and anus [31]. In Singapore, melanomas form 6% of all
skin cancers and 27% of all ocular cancers [31] but account for 75% of all skin cancer
deaths [33]. Worldwide, the incidence of melanoma has been climbing since the
1930s with a rate of increase higher than any type of cancer [32]. Fair-skinned
individuals are more at risk of melanoma. Australia and Israel have the highest
incidence of melanoma in the world (approximately 40 in 100,000 individuals per

year) [32]. In Singapore, the incidence is much lower, with only 106 cases diagnosed
locally between 2003-2007 [31]. Even though melanoma incidence is lower in darker-
skinned populations, it is important to recognize that it does occur in these
populations too. Melanoma can be cured if excised early. However, once it has
disseminated to distant organs, the median survival of melanoma patients drops below
nine months [34].

Two genes have been associated with an increased risk of melanoma – cyclin-
dependent kinase inhibitor 2A (CDKN2A) and cyclin-dependent kinase 4 (CDK4). 10%
of melanoma patients have at least two first-degree relatives with melanoma. This, in
turn, corresponds with a 2-fold increase in the risk of melanoma [32]. Ultra-violet
(UV) radiation is also a major risk factor in melanoma development. UV radiation
causes genetic changes in the skin, impairs immune functions, increases local growth
factor production and induces reactive-oxygen species production that affects
keratinocytes and melanocytes [35,36]. The incidence of melanoma among
Caucasians is inversely related to latitude of residence [37], implying higher exposure
to the sun in tropical/sub-tropical areas as a risk factor. UV B radiation (290 to 320
nm) is the cause of most of the DNA damage in the skin while UV A radiation (320 to
400 nm) is responsible for the oxidative damage and immunosuppression. Indeed,

11

splenic immune cells transferred from mice exposed to UV A radiation are not able to
reject UV-induced skin tumors [38]. Melanomas are associated with intense
intermittent exposure in contrast to other skin cancers like basal cell or squamous cell
carcinoma which are associated with chronic UV exposure [35]. Upon intense UV
exposure, damaged melanocytes, unlike keratinocytes, do not undergo apoptosis but
rather survive, mutate and divide [35]. This division can be seen extrinsically in the
form of freckles that appear in children after a bout of sun exposure. These freckles
are thought to be the clones of mutated dividing melanocytes and are associated with

the risk of melanoma [39]. Moles are benign tumors of melanocytes that, after an
initial period of growth, have undergone oncogene-induced senescence [40].

Diagnosis and treatment
Melanoma can be detected early. Early melanoma development can be assessed by
observing asymmetry, border irregularity, color and diameter of the lesion (Table 2).
Suspected melanoma lesions are excised with narrow margins of 1-3mm. Histological
evaluation is then carried out on these excised lesions to determine the extent of
invasion and the stage of the disease. Melanomas generally have two growth phases –
the radial growth phase and the vertical growth phase. In the radial growth phase, the
tumor cells are in the epidermis and papillary dermis with raised irregular growth at
the surface. During the vertical growth phase, the melanoma tumor grows to the
deeper layers of skin with increasing nodularity. The tumors in both the radial and
vertical phases are considered to be invasive. However, only the vertical growth phase
and the depth of invasion correlate with prognosis [32].



12

Feature
Benign Mole
Melanoma
Asymmetry
No
Yes
Border irregularity
No
Yes
Colour

Uniform, tan/brown
Variegated, black
Diameter
< 6mm
May be >6 mm

Table 2: The ‘ABCD’ method of identifying early melanoma lesions.
Recommended method of differentiating early melanoma from benign moles. Other signs can include
itching, bleeding ulceration or changes in pre-existing benign mole. [Adapted from Jensen et al
(2007)]
[32]

Staging of melanoma is determined by the TMN classification of melanoma. T
represents the primary tumor stage where thickness and ulceration of the primary
tumor is assessed. The thickness or invasiveness of the tumor is measured in two
ways. The first method is known as Clark’s levels whereby the invasion of the tumors
is determined by the histologically defined layers of the skin. However, this can be
inaccurate as the thickness of the different layers of the skin can vary between
individuals. The Breslow’s thickness is the alternate method of measurement. This
method measures the distance from the epidermal granular layer to the base of the
tumor. There is an inverse correlation between Breslow’s thickness and survival. N
refers to the extent of lymph node metastases found. The presence of lymph node
metastases is a bad sign regardless of the invasiveness of the primary tumor. The
number of lymph nodes detected with melanoma cells and the size of the metastases
(microscopic or macroscopic) help determine the aggressiveness of the disease. M
represents the distant metastases of melanoma cells to other organs. Stage I and II
patients have no lymph node or distant metastases. As such, severity is determined by
the Breslow’s thickness and Clark’s levels. In stage III patients, the number of nodes
and metastases are prognosis factors. Stage IV patients have distant metastasis.
Factors such as serum lactic dehydrogenase levels and visceral sites of metastases are

the prognosis factors [32].

13


Cutaneous melanoma is treated primarily by excision of the primary tumor as it is
readily accessable. An excision margin around the tumor is always recommended but
the thickness of the tumor determines the actual size of the margin taken [41].
However, for melanomas with a thickness of 2mm or less, excision margins of 2 or
5cm had no difference in local reoccurrence [42]. For melanomas in other parts of the
body such as the eye, treatment options include enucleation, radiation therapy, laser
hyperthermia and surgical resection. Although treatment of the primary tumor is
generally successful, hematogenous spreading is known to occur. This hematogenous
spreading of the tumor cells can be found in almost half of melanoma patients [43].
Patients with intermediate or thick primary melanomas (Breslow’s depth above 1mm)
are advised to undergo sentinel lymph node biopsy (SLNB) [44]. The sentinel lymph
node (SLN) is defined as the node that first drains the lymph from the primary tumor
site [45]. Injection of both a radioactive colloid and a blue dye is done around the
primary tumor to identify the SLN. Hematoxylin and eosin staining, as well as
immunohistochemistry, are done on the biopsied lymph node to determine the
presence of melanoma cells. S100B, HMB45 and Melan-A/MART1 are used as
markers for melanoma cells with the latter two used more for their specificity and
S100B for its sensitivity. Reverse transcriptase polymerase chain reaction is now
emerging as a molecular staging tool for missed micrometastases. Tyrosinase,
tyrosinase related protein (Trp)-2, Melan-A/MART-1 as well as other markers are
used to detect melanoma-specific transcripts [46,47,48]. Tyrosinase and Trp-2 both
play important roles in melanogenesis and are specifically expressed in melanocytes
and melanoma [49]. In cases of metastatic cells found in the lymph nodes, complete