Universidade de Lisboa Faculdade de Ciências

Departamento de Química e Bioquímica

CROSSTALK BETWEEN IMMUNOSUPPRESSIVE MYELOID AND

EFFECTOR LYMPHOID CELLS IN THE TUMOUR

MICROENVIRONMENT

Sofia Mensurado Santos

Dissertação

Mestrado em Bioquímica

Especialização: Bioquímica

Orientadores: Prof. Doutor Bruno Silva-Santos

Prof. Doutora Margarida Telhada

2015

Universidade de Lisboa Faculdade de Ciências

Departamento de Química e Bioquímica

CROSSTALK BETWEEN IMMUNOSUPPRESSIVE MYELOID AND

EFFECTOR LYMPHOID CELLS IN THE TUMOUR

MICROENVIRONMENT

Sofia Mensurado Santos

Dissertação

Mestrado em Bioquímica

Especialização: Bioquímica

Orientadores: Prof. Doutor Bruno Silva-Santos

Prof. Doutora Margarida Telhada

2015

TABLE OF CONTENTS

ACKNOWLEGMENTS/AGRADECIMENTOS ....................................................................................................................... i

ABBREVIATION LIST ....................................................................................................................................................... iii

ABSTRACT ....................................................................................................................................................................... v

SUMÁRIO ......................................................................................................................................................................vii

INTRODUCTION .............................................................................................................................................................. 1

1. The immune system ........................................................................................................................................ 1

2. γδ T cells .......................................................................................................................................................... 1

2.1. γδ T cell development and TCR repertoire .................................................................................................... 2

2.2. γδ T cell effector subsets and functions ........................................................................................................ 3

3. Tumour immune surveillance .......................................................................................................................... 5

4. Tumour immunoediting and escape ................................................................................................................ 8

4.1. Cellular and molecular mediators of tumour escape .................................................................................... 9

5. Cancer immunotherapy ................................................................................................................................. 14

HYPOTHESIS AND OBJECTIVES OF THIS THESIS ............................................................................................................ 17

METHODS ..................................................................................................................................................................... 19

1. Mice ............................................................................................................................................................... 19

2. Cell culture ..................................................................................................................................................... 19

3. Lentiviral transduction for luciferase expression ........................................................................................... 19

4. In vivo transplantable B16 tumour model ..................................................................................................... 19

5. Flow cytometry analysis and cell sorting ....................................................................................................... 20

6. Gene expression analysis ............................................................................................................................... 22

7. Statistical Analysis ......................................................................................................................................... 22

RESULTS ....................................................................................................................................................................... 23

1. Role of γδ T cells in intraperitoneal B16 melanoma growth in vivo............................................................... 23

2. Assessing the presence of suppressive subsets in the tumour environment ................................................ 27

3. PMN-MDSC inhibit Vγ6 T cell accumulation .................................................................................................. 28

4. Dissecting the mechanism of inhibition of Vγ6 T cell accumulation by PMN-MDSC ..................................... 32

5. Addressing the role of γδ T cells, IL-17 and PMN-MDSC in intraperitoneal B16 tumour growth .................. 34

SUPPLEMENTARY FIGURES .......................................................................................................................................... 37

DISCUSSION.................................................................................................................................................................. 39

1. Experimental limitations ................................................................................................................................ 40

2. Regulation of γδ T cell responses .................................................................................................................. 41

3. Role of PMN-MDSC/ γδ T cell crosstalk in tumour progression ..................................................................... 42

4. Translation and implications of our findings ................................................................................................. 44

5. Future perspectives ....................................................................................................................................... 45

REFERENCES ................................................................................................................................................................. 47

i

ACKNOWLEGMENTS/AGRADECIMENTOS

Em primeiro lugar quero agradecer ao Prof. Bruno Silva-Santos pela oportunidade e confiança,

mas acima de tudo pelo exemplo e entusiasmo, e por me ajudar a crescer como cientista.

Agradeço a todos os elementos do laboratório pelo companheirismo, boa disposição,

entreajuda e discussões científicas, mas especialmente à equipa que trabalhou directamente

comigo. Deixo um agradecimento muito especial à Margarida Rei, por acreditar em mim, pela

paciência e por depositar em mim a confiança para desenvolver este projecto. Quero

igualmente agradecer à Natacha pela amizade, companheirismo, discussões e ajuda na

execução experimental. Não podia também deixar de agradecer à Joana Martins pelas longas

conversas e entreajuda. Também ao Hiroshi Kubo, o meu muito obrigada pela disponibilidade

e simpatia. Claro que não podia deixar de agradecer à Karine Serre, por me supervisionar e

orientar, pelas longas discussões e principalmente pelo conhecimento transmitido.

Quero ainda agradecer aos elementos dos laboratórios do Henique Veiga-Fernandes e do Prof.

Luis Graça, pelos protocolos, reagentes e simpatia. Um obrigada pela simpatia e prestabilidade

a todos os membros das unidades que mais utilizei: o biotério e a unidade de citometria de

fluxo. Um obrigada especial à Iolanda, Carlos, Ana e Sílvia.

Por fim, um enorme obrigada à minha família, sem a qual esta etapa não teria sido

concretizada. Aos meus avós, mãe e irmã por acreditarem em mim, vibrarem com os meus

feitos e por se orgulharem como orgulham. À minha mãe e ao meu pai quero agradecer todo o

apoio, a liberdade de escolha, o nunca terem posto em causa o caminho que quero seguir,

mesmo que às vezes não pareça ser o mais estável: obrigada por me proporcionarem a

oportunidade de chegar até aqui nos meus estudos. À minha mãe, à minha irmã e ao Tomás

quero agradecer a enorme paciência para o meu mau feitio e mau humor, especialmente ao

fim de longos dias de experiências. Ao Tomás quero ainda agradecer todo o suporte, respeito e

felicidade partilhada.

ii

iii

ABBREVIATION LIST

Arg1 Arginase-1 BrdU Bromodeoxyuridine Bref Brefeldin CAR-T Chimeric antigen receptor T cell CCL Chemokine ligand CCR C-C chemokine receptor CD Cluster of differentiation CTLA-4 Cytotoxic T-lymphocyte antigen 4 DC Dendritic cell DETC Dendritic epidermal T cells DMEM Dulbecco’s modified Eagles’ medium DMSO Dimethyl sulfoxide DN Double negative EDTA Ethylenediamine tetraacetic acid FACS Fluorescence-activated cell sorting FCS Foetal calf serum FDA Food and drug administration FoxP3 Forkhead box P3 FSC Forward scatter GFP Green fluorescent protein GITR Glucocorticoid-induced TNFR related gene GM-CSF Granulocyte macrophage colony-stimulating factor HIF-1 α Hypoxia inducible factor 1α HMBPP Hydroxy-2-methylbut-2-enyl 4-diphosphate i.p. Intraperitoneal IEL Intestinal epithelial lymphocytes IFN Interferon IL Interleukin iNOS Inducible nitric oxide synthase Iono Ionomycin IRS-1 Insulin receptor substrate 1 LPM Large peritoneal macrophages mAb Monoclonal antibody MCA Methylcholanthrene M-CSF Macrophage colony-stimulating factor MDSC Myeloid-derived suppressor cells MHC Major histocompatibility complex MMLV Moloney murine leukemia virus MMP Matrix metallopeptidase Mo-MDSC Monocytic-MDSC NK Natural killer NKG2D Natural killer group 2 member D NKT Natural killer T cells NOD Non-obese diabetic PBS Phosphate buffered salt PCR Polymerase chain reaction PD-1 Programmed cell death-1 PDGF Platelet-derived growth factor PMA Phorbol 12-myristate 13-acetate PMN-MDSC Polymorphonuclear-MDSC

iv

RAG Recombinant activating gene RNS Reactive nitrogen species RORγt RAR-related orphan receptor γt ROS Reactive oxygen species RPMI Roswell park memorial institute medium s.c. Subcutaneous SCID Severe combined immunodeficient SPM Small peritoneal macrophages SSC Side scatter STAT Signal transducer and activation of transcription TAM Tumour-associated macrophages TAN Tumour-associated neutrophils TCR T cell receptor TGF-β Transforming growth factor β Th T helper TIM3 T cell immunoglobulin and mucin domain-containing protein 3 TNF-α Tumour necrosis factor α TRACK Transgenic model of cancer of the kidney TRAIL TNF-related apoptosis-inducing ligand receptors Tregs Regulatory T cells VEGF Vascular endothelial growth factor WT Wild-type

v

ABSTRACT

The tumour microenvironment contains a variety of immune cells that can either inhibit or

promote tumour growth. These immune populations comprise γδ T cells, which have been

described to provide large amounts of anti-tumour molecules, such as interferon-γ (IFN-γ) and

cytolytic enzymes, but can also produce interleukin-17 (IL-17) that supports tumour growth. By

contrast, in this thesis we report that, in a peritoneal melanoma B16 tumour model, γδ T cells

are unresponsive and thus neutral to tumour growth. Upon tumour challenge, γδ T cells were

unable to accumulate and to upregulate IL-17, IFN-γ, granzyme B and perforin expression, in

comparison to steady-state. Consistent with this, TCRδ-/- mice displayed similar tumour growth

kinetics to wild-type (WT) controls, further corroborating the inability of γδ T cells to respond

to tumour challenge. Concomitantly, we observed an accumulation of myeloid-derived

suppressor cells (MDSC), both of monocytic (Mo-MDSC) and polymorphonuclear (PMN-MDSC)

origin, which are known to suppress tumour immunity. Hence, we hypothesized that MDSCs

could prevent γδ T cell response in this model. To modulate MDSC we employed an anti-Gr-1

monoclonal antibody (mAb), which led to specific depletion of PMN-MDSC. Such manipulation

resulted in γδ T cell-specific accumulation and increased proportion of IL-17-producing γδ T

cells. These γδ T cells were characterized by the expression of a Vγ6+ T cell receptor, and by

lack of CD27 expression. Analysis of TCRδ-/- and IL17-/- mice upon PMN-MDSC depletion

revealed, by comparison with WT controls that both γδ T cells and IL-17 contributed to tumour

growth. Collectively, the work presented in this thesis showed, for the first time, that γδ T cells

can be targeted by PMN-MDSCs and that, contrary to their well-established pro-tumour role,

this myeloid subset can also mediate host protection in the tumour context.

Keywords: γδ T cells, MDSC, IL-17, tumour immunology

vi

vii

SUMÁRIO

O sistema imunitário é constituído por estruturas organizadas e moléculas com papéis

específicos na defesa contra patogénios e células transformadas, e é habitualmente segregado

em dois principais componentes: o sistema inato e o adaptativo. O sistema inato está presente

em todos os organismos multicelulares e é caracterizado por apresentar uma resposta rápida a

padrões conservados em patogénios. O sistema adaptativo é caracterizado pela capacidade de

gerar uma grande variedade de receptores de antigénios e células de memória que respondem

de forma mais eficaz numa exposição repetida a um dado patogénio. O sistema inato é

composto por células fagocíticas (neutrófilos, monócitos e macrófagos), células ‘’natural killer’’

(NK) e células que produzem mediadores inflamatórios como os basófilos, mastócitos e

eosinófilos. O sistema adaptativo é composto por células T e B específicas para antigénios,

cujos receptores são produzidos por recombinação somática. As células B, que se desenvolvem

na medula óssea, após estimulação, secretam imunoglobulinas que são responsáveis pela

eliminação de microorganismos extracelulares. As células T, que se desenvolvem no timo,

apresentam funções auxiliadoras e citotóxicas, através da produção de citocinas e enzimas

citolíticas. Os linfócitos T podem ser categorizados de acordo com as cadeias que expressam

nos receptores de células T (TCR), em células Tαβ e células Tγδ. As células Tαβ ‘’naïve’’ são

activadas em orgãos secundários linfóides por células apresentadoras de antigénios que

processam e apresentam os antigénios conjugados com moléculas do complexo major de

histocompatibilidade (MHC - major histocompatibility complex) à sua superfície. Em oposição,

as células Tγδ populam os tecidos epiteliais e respondem rapidamente a sinais de stress.

As células Tγδsão linfócitos que expressam TCRs compostos por uma cadeia γ e uma cadeia δ

e que realizam recombinação somática para os originar. São, no entanto, consideradas células

“innate-like” devido à sua capacidade de actuar como primeira linha de defesa, iniciar uma

resposta inflamatória rápida e por se localizarem preferencialmente em tecidos epiteliais. São

células que se caracterizam funcionalmente pela capacidade de rápida produção de interferão-

gama (IFN-γ) e interleucina-17 (IL-17), em resposta a estímulos externos. Estas células são

consideradas como não redundantes relativamente às células Tαβ essencialmente por

apresentarem uma cinética de resposta diferente, reconhecerem antigénios distintos e

apresentarem uma distribuição anatómica também ela distinta. Dependendo das suas funções

efectoras, as células Tγδ podem ser categorizadas em duas populações: as produtoras de IFN-

γ, que expressam o marcador de superfície CD27, e as produtoras de IL-17, que não expressam

este marcador. As células Tγδ apresentam potentes propriedades antitumorais mediadas pela

produção de granzimas, perforinas, FasL, TRAIL e IFN-γ, o que já foi demonstrado ter um papel

viii

importante na imunovigilância de células cancerígenas, tanto em ratinhos como em humanos.

Nomeadamente, num modelo subcutâneo de melanoma (B16), estabelecido no laboratório de

acolhimento, ratinhos deficientes para estas células (TCRδ-/-) apresentaram um maior

desenvolvimento tumoral. Já em ratinhos da estirpe selvagem, as células Tγδ acumulam-se no

tumor, onde apresentam funções citotóxicas potentes e produzem IFN-γ No sentido oposto,

as células Tγδ foram recentemente associadas à promoção do desenvolvimento tumoral, em

modelos de cancro do fígado e de ovário, devido à produção de IL-17. No entanto, o papel

desta citocina no ambiente tumoral é muito controverso e continua a ser alvo de estudo.

Neste trabalho utilizou-se uma linha celular de melanoma (B16), injectada

intraperitonealmente, com o objectivo de estudar a resposta das células Tγδ durante o

desenvolvimento tumoral. Observou-se que neste modelo as células Tγδ , ao contrário de

outras células imunitárias como células T CD4, T CD8 e NK, não se acumulam em resposta ao

estímulo da injecção tumoral. A análise funcional das células Tγδ revelou ainda que estas não

são capazes de aumentar a expressão das citocinas IL-17 e IFN-γ nem de enzimas citolíticas,

como granzima B e perforina. Desta análise conclui-se que as células Tγδ no ambiente tumoral

deste modelo se encontram anérgicas. Em concordância com estes resultados, a análise do

crescimento tumoral em ratinhos TCRδ-/- revelou que estes apresentam uma cinética

semelhante aos ratinhos da estirpe selvagem. Estes resultados estabelecem que as células Tγδ

apresentam um papel neutro no crescimento tumoral, não sendo responsáveis nem pela

promoção nem pela eliminação da linha de melanoma B16 quando esta é injectada na

cavidade peritoneal.

Na tentativa de perceber se a “anergia” das células Tγδ se deve a um mecanismo de

imunossupressão analisou-se a presença de células supressoras no ambiente tumoral. Nessa

análise, verificou-se que a frequência de células T reguladoras, caracterizadas pela expressão

dos marcadores de superfície CD4 e CD25, pelo factor de transcrição FoxP3 e pelas suas

potentes capacidades de supressão de células T, está diminuida. Por esse motivo, estas são

improváveis mediadores da supressão das células Tγδ. Pelo contrário, detectámos uma

frequência aumentada de células supressoras de origem mielóide (MDSC, myeloid derived

suppressor cells). As MDSC são uma população heterogénea de progenitores mielóides e

células mielóides imaturas que são induzidas em situações patológicas, incluindo no

desenvolvimento tumoral. Estas células são caracterizadas pela co-expressão dos marcadores

de superfície CD11b e Gr-1. Em ratinho, as MDSC podem ser divididas em duas principais

subpopulações, as células monocíticas supressoras de origem mielóide (Mo-MDSC, monocytic

myeloid–derived suppressor cells) e as células polimorfonucleares supressoras de origem

ix

mielóide (PMN-MDSC, polymorphonuclear myeloid-derived suppressor cells). As Mo-MDSCs

apresentam o fenótipo CD11b+Gr-1intLy6G-Ly6C+ enquanto as PMN-MDSC são caracterizadas

por serem CD11b+Gr-1highLy6G+Ly6Cint. As MDSC têm a capacidade de suprimir as respostas de

linfócitos T, tanto in vitro como in vivo, através de vários mecanismos conhecidos, como a

produção de óxido nítrico e a diminuição da arginina disponível no meio. Sabe-se que as MDSC

suprimem as células T CD8 citotóxicas e induzem o desenvolvimento de células T reguladoras,

contribuindo para um desequilíbrio da resposta imunitária, no sentido de promover a

tolerância e assim contribuindo para o desenvolvimento tumoral. No entanto, pouco se sabe

sobre a interação entre as MDSC e as células Tγδ

No nosso modelo (melanoma B16 intraperitoneal), observou-se um aumento tanto da

subpopulação monocítica como da polimorfonuclear de MDSC, em relação a ratinhos sem

tumor. Para perceber se as MDSC poderiam ter impacto na resposta das células Tγδ,

recorremos ao anticorpo monoclonal anti-Gr-1 para as depletar. A injecção deste anticorpo em

ratinhos com tumor levou à depleção específica de PMN-MDSC, visto que estas expressam

níveis mais elevados do marcador de superfície Gr-1, relativamente às Mo-MDSCs. Esta

depleção resultou na acumulação selectiva de células Tγδ no ambiente tumoral, sem alteração

da frequência de células T CD4, T CD8 e NK. As células Tγδ que se acumularam em

consequência da depleção das PMN-MDSC expressam a cadeia Vγ6 do receptor de células T e

não expressam o marcador de superfície CD27. Em concordância com a falta de expressão

desse marcador, estas células são produtoras de IL-17. Visto a IL-17 ter um papel controverso

no contexto tumoral, avaliou-se qual o papel desta citocina e das células Tγδ no

desenvolvimento tumoral, após depleção das PMN-MDSC. Observou-se que tanto os ratinhos

IL-17-/- como os ratinhos TCRδ-/- apresentam um crescimento tumoral diminuido em relação

aos ratinhos da estirpe selvagem. Esta observação implica que tanto as células Tγδ como a

citocina IL-17 desempenham um papel pro-tumoral neste modelo.

Os resultados apresentados nesta tese mostram, pela primeira vez, que as células Tγδ podem

ser alvo de inibição pelas PMN-MDSC e que, contrariamente ao seu conhecido papel pro-

tumoral, esta população mielóide pode mediar a protecção do hospedeiro, no contexto

tumoral.

Palavras-chave: Linfócitos Tγδ, MDSC, interleucina-17, oncoimunologia

Introduction

1

INTRODUCTION

1. The immune system

The immune system is composed by organized structures of cells and molecules with

specialized roles in defending against pathogens and transformed cells. It is usually segregated

in two main components: the innate and adaptive immunity. The innate system appears to be

present in all multicellular organisms (Beutler 2004) and is characterized by quickly responding

to conserved patterns on pathogens (Janeway and Medzhitov 2002). The adaptive immune

system has the peculiar ability to generate a vast range of antigen receptors and long-lived

memory cells that engender more effective responses in a repeated encounter with a given

pathogen. Thus, innate responses occur to the same extent independently of the number of

times a pathogen is encountered, while adaptive responses improve upon repeated exposures

(Delves and Roitt 2000).

The innate immune system is composed by phagocytic cells (neutrophils, monocytes and

macrophages), natural killer cells and cells that produce inflammatory mediators such as

basophils, mast cells and eosinophils. The adaptive arm of the immune system is composed by

antigen-specific B and T cells, whose receptors are produced by somatic V(D)J recombination

(Tonegawa 1983). B cells, which develop in the bone marrow, upon proper stimulation, secrete

immunoglobulins that are responsible for elimination of extracellular microorganisms (Delves

and Roitt 2000). T cells, which develop in the thymus, perform cytotoxic and helper functions,

through production of cytolitic enzymes and cytokines, respectively. T cells may further be

divided in αβ T cells, the largest subset, and γδ T cells, according to the chains that constitute

their T cell receptor (TCR). Naïve αβ T cells circulate and are activated in secondary lymphoid

organs by antigen-presenting cells that process antigens and display them conjugated with

MHC molecules at their surface (Cooper and Alder 2006). By contrast, most γδ T cells populate

epithelial tissues where they quickly respond to stress signals expressed by local cells (Hayday

2009).

2. γδ T cells

γδ T lymphocytes are defined by the surface expression of a TCR composed by a γ and a δ

chain. Because these cells own a TCR that is generated by somatic recombination, which

potentially endows them with the ability to mediate antigen-specific responses, they are

considered to be part of the adaptive immune system. However, given that γδ T cells are fast

responders, preferentially locate in epithelium, display a reduced TCR repertoire and present

Introduction

2

unconventional development and activation requirements, they are considered to be innate-

like lymphocytes. γδ T cells main functional features are the production of pro-inflammatory

cytokines, namely interferon-gamma (IFN-γ) and interleukin-17 (IL-17), and the briskness of

their production in response to external stimuli. γδ T cells are seen as non-redundant with αβ T

cells mainly because of five of their properties: recognition of distinct antigens, different

response kinetics, unique functional potentials, differential anatomical distribution,

importance in young individuals (Vantourout and Hayday 2013).

2.1. γδ T cell development and TCR repertoire

γδ T cells start to develop in the embryonic thymus, from a common progenitor cell that can

give rise to both αβ and γδ lineages, but also natural killer and some thymic dendritic cells

(DC). T cell precursors are named double negative (DN) because they lack the expression of the

co-receptors CD4 and CD8. DN cells can be subdivided into DN1, DN2, DN3 and DN4, according

to their surface expression of CD44, CD25 and c-kit. When cells go through DN2 and DN3

stages the upregulation of the expression of recombinant activating gene (RAG) enables the

rearrangement of TCRγ, TCRδ and TCRβ chains. The successful in-frame rearrangement of TCRγ

and TCRδ genes results in the expression of a TCRγδ complex and favors the differentiation

towards γδ T cell lineage (Taghon and Rothenberg 2008).

One of the characteristics of γδ T cells that set them aside from T cells is that they develop

in coordinated waves that sequentially populate different tissues. These sequential waves

have been initially defined by their Vy chain usage (Figure 1A), but recently it became apparent

that the acquisition of some functions was also dependent on this embryonic kinetics, as

depicted in Figure 1B (Carding and Egan 2002; Prinz, Silva-Santos, and Pennington 2013).

Briefly, Vγ5Vδ1 T cells develop between embryonic days 13 and 16 and migrate to the skin

which they populate as dendritic epidermal T cells (DETC). DETC, that represent more than

90% of epidermal T cells, have been shown to be important players in wound healing (Jameson

et al. 2002) and cancer surveillance (Girardi et al. 2001). Vγ6Vδ1 T cells develop from

embryonic days 14 to around birth and home to the reproductive tract, lung and tongue.

These two subsets that are exclusively generated in the fetal thymus, have no junctional

diversity due to the absence of terminal deoxyucleotidyl transferase (TdT), and thus are

essentially oligoclonal (Itohara et al. 1990). Vγ4 and Vγ1 T cell development starts at

embryonic days 16 and 18, respectively, and extends throughout life. Both these subsets

populate mainly the secondary lymphoid organs and blood; however they display different

Introduction

3

cytokine production biases. Vγ4 T cells tend to be more prone to produce IL-17 whereas Vγ1 T

cells are more IFN-γ-biased, although this segregation is not strict.

Figure 1: Waves of γδ T cell development according to their Vγ chain usage (A) and function (B).

Adapted from Carding & Egan 2002 and from Prinz, Silva-Santos & Pennington 2013.

IL-17-producing γδ T cells are a heterogeneous population that includes mostly Vγ6 and Vγ4 T

cells, as well as some Vγ1 T cells. In the periphery γδ17 T cells are found in the peritoneal

cavity, dermis, cornea, tongue, central nervous system, reproductive tract and secondary

lymphoid organs (Shibata et al. 2007; Gray, Suzuki, and Cyster 2011; Prinz, Silva-Santos, and

Pennington 2013; Haas et al. 2009).

Another functional wave generates γδ NKT cells which develop with a restricted TCR

repertoire, during fetal live, but with a more polyclonal one at later stages. These cells are

preferentially localized in the spleen and liver (Gerber et al. 1999). Vγ7 T cells, which can

supposedly develop extrathymically, home to the gut epithelium (Hayday and Gibbons 2008)

where they are found as intestinal epithelial lymphocytes (IEL). They show cytoprotective,

immunomodulatory and antibacterial functions that are mediated by cytokines, cytotoxic

molecules and epithelial cell trophic factors.

2.2. γδ T cell effector subsets and functions

According to effector functions, our laboratory has pioneered the categorization of γδ T cells in

two main subsets: IL-17 and IFN-γ producers, that can be distinguished by expression levels of

CD27, a member of the tumour necrosis factor receptor superfamily (Ribot et al. 2009). CD27+

γδ T cells display the ability to produce IFN-γ (γδ1 T cells), whereas CD27- cells comprise the IL-

A B

Introduction

4

17 producers (γδ17 T cells). Further characterization of these two subsets can be achieved by

CCR6 and NK1.1 expression that are restricted to IL-17-producing and IFN-γ-producing γδ T

cells, respectively (Haas et al. 2009). This commitment to specific cytokine production is

established during thymic development, maintained in periphery (Ribot et al. 2009) and

regulated at epigenetic and transcriptional levels (Schmolka et al. 2013). The molecular cues

that control the development towards one fate or the other still need to be fully unraveled but

include TCR and CD27 (Jensen et al. 2008; Ribot et al. 2009), NF-kB (Powolny-Budnicka et al.

2011) and Notch (Shibata et al. 2011) pathways. Furthermore, while CD27+ γδ T cells have

been shown to be functionally stable, CD27- cells have the ability to produce IFN-γ under

certain inflammatory conditions, which shows that this γδ T cell subset is characterized by

functional plasticity. Such plasticity has been observed in vivo in models of ovarian cancer and

Listeria monocytogenes infection (Schmolka et al. 2013; Sheridan et al. 2013).

γδ T cell tropism to epithelial tissues, together with their pre-committed functions enable

them to quickly participate in multiple immune responses. Also, the ability to rapidly recognize

stress-induced antigens and to respond in large numbers without requiring extensive clonal

expansion allows γδ T cells to participate in the afferent phase of immune responses. Thus, γδ

T cells can act as sentinels, in synchrony with innate immune cells, thereby orchestrating

downstream efferent immune responses mediated by conventional lymphocytes. Overall, γδ T

cells have been shown to contribute to stress surveillance, tissue repair, infection,

autoimmunity and tumour immunity.

DETC, that populate the epidermis, exhibit a dendritic morphology and can contribute to stress

surveillance through recognition of the stress ligands Rae-1 and H60 that engage the NKG2D

receptor and through signaling of IL-1 and IL-15, which are upregulated by tissue dysregulation

(Girardi et al. 2001). Epidermal γδ T cells are also involved in tissue repair through production

of keratinocyte growth factor and insulin-like growth factor 1 (Jameson et al. 2002).

γδ T cells are also important players in responses to infections, and have been shown to be

protective in models of vaccinia virus (Selin et al. 2001), West Nile virus (Wang et al. 2006),

herpes simplex-2 virus (Nishimura et al. 2004), Listeria (Sheridan et al. 2013), E.coli (Shibata et

al. 2007) and plasmodium falciparum (D’Ombrain et al. 2007). In both West Nile and herpes

simplex-2 virus infections, γδ T are important inducers of CD8 and CD4 memory T cells,

respectively. Listeria induced the expansion of memory Vγ6 T cells that co-produced IFN-γ and

IL-17 and conferred protection against infection (Sheridan et al. 2013). In the case of E.coli

peritoneal infection, γδ T cells were shown to produce IL-17 which led to neutrophil

Introduction

5

recruitment and consequent increased bacterial clearance (Shibata et al. 2007). As for

plasmodium, γδ T cell protective role was mediated by IFN-γ production (D’Ombrain et al.

2007).

In autoimmune diseases, γδ T cells have been shown to be mainly pathogenic. However, in

diabetes type 1 their role is controversial. It was reported in non-obese diabetic (NOD) mice

that intranasal inhalation of insulin leads to the generation of a population of γδ T cells with

regulatory features, that limit the progression of diabetes (Harrison et al. 1996). On the other

hand, it was shown that γδ17 T cells contribute to the development of type-1 diabetes, also in

NOD mice (Markle et al. 2013). Furthermore, it was established that γδ T cells are the main

source of IL-17 in mouse models of psoriasis, thus leading to exacerbation of the disease

(Pantelyushin et al. 2012; Cai et al. 2011). Moreover, IL-17 production by γδ T cells has been

shown to amplify the production of this cytokine by CD4 T cells and lead to increased

susceptibility to experimental autoimmune encephalomyelitis, an experimental model of

multiple sclerosis (Sutton et al. 2009). Collectively, these reposts have demonstrated major

roles of γδ T cells in inflammatory responses, often with detrimental consequences for the

host.

3. Tumour immune surveillance

Nascent tumours arise from transformed cells as a consequence of accumulated genetic

alterations. However, malignant cells do not always lead to tumour development. In the early

20th century, Erlich was the first to propose that the immune system has the ability to

eradicate nascent transformed cells before they are clinically detected (Kim, Emi, and Tanabe

2007). Later, the term tumour immune surveillance emerged, which is now defined as the

ability of the immune system to specifically identify and eliminate tumour cells on the basis of

their expression of tumour-specific antigens or molecules induced by cellular stress (Swann

and Smyth 2007). The first strong evidences that supported tumour immune surveillance arose

with genetically modified mice. RAG2-/- (Shankaran et al. 2001), severe combined

immunodeficient (SCID)(Bosma, Custer, and Bosma 1983), IFN-γ-/- (Street et al. 2002) and

perforin-/- (Smyth et al. 2000) mice, among others, showed increased spontaneous tumour

development with age, when compared to wild-type mice. Also, TCRδ-/- and TCRβ-/- mice

displayed increased susceptibility to various tumours, including those induced by

methylcholanthrene (MCA) (Girardi et al. 2001; Silva-Santos, Serre, and Norell 2015), thus

placing T cells at the core of cancer immune surveillance.

Introduction

6

3.1. Cellular and molecular mediators of tumour immune surveillance

Several subsets of leukocytes are present in the tumour microenvironment at early stages of

tumour development, and display potent anti-tumour features. The main effectors of tumour

surveillance and their anti-tumour mechanims will be introduced in this section (reviewed in

Lança and Silva-Santos 2012).

T cytotoxic CD8 cells can recognize, via TCR, altered antigens presented by MHC I, produce

IFN-γ and efficiently kill transformed cells through cytotoxic molecules such as perforins,

granzymes and FasL that induce apoptosis in target cells. A common mechanism of tumour

evasion against CD8 cells consists in the downregulation, by tumour cells, of their MHC I

surface expression, which renders tumour cells ‘’invisible’’ to TCR-mediated recognition by

cytotoxic CD8 T cells.

However, the immune system is prepared for the downregulation of MHC I expression by

tumour cells, as this is perceived by natural killer cells (NK) as a malignant event – “missing

self” – and thus leads to NK-mediated lysis of the target cell (Karlhofer, Ribaudo, and

Yokoyama 1992). Furthermore, NK can recognize and respond to tumours via NK cell

receptors, such as NKG2D, that specifically detects stress-associated molecules. These

molecules are usually not expressed by normal healthy cells but are critically upregulated

during the process of transformation. NK cytotoxicity is also mediated by production of

perforins, granzymes and FasL or TRAIL.

CD4 T cells differentiation into T helper (Th) subsets relies on expression of master

transcripton factors that enables selective expression of cytokines. CD4 T cells can differentiate

into several helper programmes being Th1, Th2 and Th17 the most studied ones. Th1 cells

express T-bet and produce IFN-γ and TNF-α (tumour necrosis factor α), thus being usually

involved in anti-tumour responses.

Natural killer T cells (NKT), unlike conventional T cells, recognize glycolipid antigens presented

by CD1d. In cancer, type I NKT cells are mostly protective through IFN-γ production, which

activates CD8 T, NK and dendritic cells.

Similarly, γδ T cells have long been recognized as potent anti-tumour cells. Studies on

chemically induced, transplantable, transgenic and spontaneous tumours have supported this

notion, in view of the reported susceptibility of γδ T cell-deficient mice. In subcutaneous B16

melanoma transplantable tumour model, γδ T cells infiltrate as soon as 3 days after tumour

inoculation and are an important source of IFN-γ (Gao et al. 2003). γδ T cell recruitment in that

Introduction

7

same model is mediated by the CCR2/CCL2 chemokine pathway (Lança et al. 2013). γδ T cells

are able to recognize malignant cells through the TCR or NK-like receptors, such as NKG2D

that, in mice, engages H60 and Rae-1, which are MHC-like molecules (Girardi et al. 2001). Their

anti-tumoral function is mediated not only by IFN-γ production but also by induction of

apoptosis via production of TRAIL and FasL, which engage death-inducing receptors,

respectively, TRAIL-R and Fas. Furthermore, γδ T cells can also mediate tumour cell cytolysis

through production of perforins and granzymes (Bonneville, O’Brien, and Born 2010).

Figure 2: Mechanisms of tumour elimination employed by γδ T cells

Macrophages are a subset of myeloid cells that express the surface markers CD11b and F4/80.

Tumour-associated macrophages (TAMs) have been associated to both anti-tumour and pro-

tumour role, which is explained by their heterogeneous phenotypes. Similar to the Th1/Th2

dicotomy, macrophages can also be divided in two main subsets : M1 macrophages, which are

usually anti-tumour; and M2, which often display pro-tumoural functions. M1 are efficient

antigen-presenting cells due their high expression of MHC II and co-stimulatory molecules. In

addition, this subset of macrophages also display an effective tumoricidal activity empowered

by their ability to produce reactive oxygen and nitrogen species.

Similarly, neutrophils, characterized by CD11b and Gr-1 expression, have also been suggested

to display a dual role in tumour progression, which is associated to N1 and N2 phenotypes. N1

neutrophils are able to promote tumour regression by several mechanisms. Tumour-

associated neutrophils (TANs) have an enhanced cytotoxicity profile, measured by reactive

oxigen species production and phagocytosis (Ishihara et al. 1998; Lichtenstein et al. 1989).

They have also been shown to be immunostimulatory since they promote recruitment and

activation of CD8 T cells through production of CCL3, CXCL9, CXCL10, IL-12, TNF-α and GM-CSF

(granulocyte macrophage colony-stimulating factor) (Fridlender et al. 2009; Scapini et al. 2000)

and activation of dendritic cells via TNF-α secretion (Van Gisbergen, Geijtenbeek, and Van

Kooyk 2005).

Granzymes

Perforin

IFN-γ TNF-α

γδ T cell

Tumour TRAIL

FasL

Introduction

8

All these leukocyte subsets have important anti-tumour functions and mount an immune

response that frequently leads to tumour elimination. This response is initiated by innate and

innate-like lymphocytes (NK, NKT, γδ T cells) that are able to recognize developing tumours

and constitute an early source of IFN-γ. IFN-γ is a potent anti-tumour cytokine that acts by

several different mechanisms. This cytokine can induce the production of angiostatic

chemokines such as CXCL9, CXCL10 and CXCL11, thus limiting tumour progression. Those

chemokines, together with IFN-γ, potentiate the infiltration of other immune effector cells in

the tumour bed. IFN-γ is also responsible for activation of lymphocytes and macrophage

cytotoxic functions. In the draining lymph nodes, IFN-γ, together with IL-12 create a favorable

milieu for the development of CD4 Th1 anti-tumour response that then gives rise to a cytotoxic

CD8 T cell response. The continued provision of IFN-γ further induces enhanced expression of

MHC I in tumour cells, thereby leading to increased immunogenicity and CD8 T cell

recognition boosting. CD8 T cells, along with NK, NKT and γδ T cells, are able to recognize and

directly kill tumour cells through the delivery of cytotoxic granules contents. The main

constituents of those granules are perforin and granzymes, which promote apoptosis when

delivered to the target cell cytosol. Perforin is a pore-forming protein which facilitates the

entry of granzymes into target cells by forming holes in their cell membranes. Granzymes are

serine proteases that are able to directly induce apoptosis. Granzyme A, is thought to promote

single-strand DNA degradation and to weaken the structural integrity of the nucleus by

targeting lamins A-C. Granzyme B activates caspase 3 and caspase 7 which leads to

degradation of cellular protein substrates and promotes fast and efficient apoptosis (Ikeda,

Old, and Schreiber 2002; Cullen, Brunet, and Martin 2010).

4. Tumour immunoediting and escape

Despite tumour immune surveillance, cancers still develop in the presence of a functional

immune system. Therefore, the updated concept of tumour immunoediting is more complete

to translate the complex role of the immune system in tumour development and progression.

This concept, depicted in Figure 3, is divided in three phases: elimination, equilibrium and

escape. The elimination phase is exactly the same process described by tumour immune

surveillance. However, this new concept embraces two possibilities, either the elimination

phase is complete and the tumour is cleared or only a portion of the tumour is eliminated. If

the case is that of partial elimination there is a second phase that is characterized by

equilibrium between the immune system and the developing tumour. In this period tumour

cells either stay dormant or accumulate further changes becoming progressively resistant to

Introduction

9

immune effector cells. This process leads to immune selection of low immunogenic tumour

cells. These selected cells are more capable of surviving in an immunocompetent host as they

are able to resist, avoid or suppress the immune response, leading to the escape phase.

Tumour cells in this phase may escape because i) they are no longer recognized by the immune

system; ii) they become resistant to immune effector mechanisms; iii) they induce

immunosuppression in the tumour environment or iv) they create a physical barrier preventing

entry of immune cells, generating a privileged site. Once a tumour enters the escape phase its

growth can no longer be contained by the natural-occurring immune system (Swann and

Smyth 2007; Kim, Emi, and Tanabe 2007).

Figure 3: Tumour immunoediting. From Swann and Smyth 2007

4.1. Cellular and molecular mediators of tumour escape

Usually immune cells have the properties to eradicate tumour until they are subverted by the

tumour microenvironment and potentially even converted into pro-tumour populations. The

main immune cell types responsible for promotion of tumour growth will be introduced in this

section (reviewed in Lança and Silva-Santos 2012).

The role of Th17 CD4 T cell role in tumour progression is very controvertial. Th17 cells inversely

correlate with Treg numbers and positively correlate with NK and CD8 T cell frequencies,

Introduction

10

suggesting that they potentiate an anti-tumour response. However, Th17 cells, whose master

trascription factor is RORγt, mainly produce IL-17, a cytokine that has been mainly associated

to tumour progression, as it will be clarified below.

Regulatory T cells (Tregs) are CD4 T cells that express CD25 and the transcription factor FoxP3

and are caractherized by their suppressive activity against effector T cells. In fact, Tregs

suppress the activation, proliferation and effector functions of several immune cells, including

αβ and γδ T cells, NK, NKT , B cells, macrophages and dendritic cells. Treg suppressive

functions are mediated by a plethora of mechanisms. They include contact-dependent

processes, such as those that require the expression of the inhibitory molecules cytotoxic T

lymphocyte antigen-4 (CTLA-4), programmed death-1 (PD-1) and glucocorticoid-induced TNF

receptor-related protein (GITR); and contact-independent mechanisms such as production of

IL-10 and TGF-β or even uptake of IL-2. TGF-, besides being strongly immunosuppressive,

creates a potent feedback loop by promoting the differentiation of inducible Tregs (iTreg).

Despite the generalized concept that γδ T cells are potent anti-tumour mediators, studies

disclosing pro-tumour roles of γδ T cells have been increasing in recent years. γδ T cell

frequency has been positively correlated with advanced breast cancer stages and inversely

correlated with patient survival (Ma et al. 2012). Human γδ T cells have been shown to have

suppressive features: Vδ1 cells isolated from breast cancer biopsies inhibited the proliferation

of CD4, CD8 and Vδ2 γδ T cells, and also impaired the maturation and the T cell-priming ability

of dendritic cells (Peng et al. 2007). In mice, Vγ4 T cells were shown to be anti-tumour via

production of IFN-γ and perforin, whereas Vγ1 T cells were able to suppress these Vγ4 cells,

through production of IL-4, thus promoting melanoma growth (He et al. 2010; Hao et al. 2011).

Besides their ability to inhibit anti-tumour responses, the major mediator of pro-tumour γδ T

cell functions is IL-17. γδ T cells, in many circumstances, have been shown to be the main (or

one of the major) producers of this cytokine. γδ17 T cells were suggested to promote

angiogenesis in a fibrosarcoma model (Wakita et al. 2010). Moreover, in a pancreatic cancer

model, IL-17 produced by both γδ17 and Th17 cells led to increased IL-6/STAT3 (signal

transducer and activation of transcription 3) signaling, which was shown to upregulate pro-

survival and pro-angiogenic genes (Wang et al. 2009). Furthermore, IL-17 production by γδ T

cells is also linked to recruitment of pro-tumoural myeloid subsets. First, it was demonstrated

that γδ17 T cells mediated the mobilization of MDSCs which, in turn, suppress cytotoxic T cells,

in a hepatocellular carcinoma model (Ma et al. 2014). A similar capacity of γδ17 T cells was

reported in human colorectal cancer. γδ T cells were shown to promote migration,

proliferation and survival of MDSCs through IL-17, IL-8, GM-CSF and TNF-α production (Wu et

Introduction

11

al. 2014). Our laboratory has recently demonstrated that γδ17 T cells mobilize small peritoneal

macrophages that are pro-inflammatory, pro-angiogenic and induce tumour proliferation, in a

mouse model of ovarian cancer (Rei et al. 2014).

Figure 4: Mechanisms of γδ T cell pro-tumour roles. Adapted from Rei, Pennington, and Silva-Santos

2015

Likewise, type II NKT, when activated, produce IL-13 that induces TGF-β expression by

suppressive myeloid cells. In turn, this leads to suppression of CD8 T cell anti-tumour response.

Besides lymphocytes, myeloid cells can also display potent immunosuppressive or tumour-

promoting features.

M2 macrophages promote immune suppression through production of IL-10 and TGF-β and

recruitment of Tregs via CCL22. Moreover, M2 produce angiogenic drivers, such as vascular

endothelial growth factor (VEGF) and platelet-derived growth factor (PDGF) and proteases

such as cathepsins and metalloproteases, which are involved in metastasis formation. Thus,

M2 macrophages promote tumour evasion through several distinct mechanisms.

Equivalently, N2 neutrophils promote carcinogenesis through the production of matrix

metallopeptidase-9 (MMP-9) that is involved in regulation of oncogene-induced keratinocyte

hyperproliferation and confers resistance to apoptosis in lung tumour cells (Coussens,

Fingleton, and Matrisian 2002). Besides its role in promoting carcinogenesis, MMP-9 leads to

enhanced bioavailability of matrix-sequestred VEGF, thus contributing to angiogenesis

(Nozawa, Chiu, and Hanahan 2006). Moreover, N2 TANs secrete high levels of collagenase-IV

and heparanase which are basement membrane-degrading enzymes, hence assisting tumour

cell extravasion (Welch et al. 1989). Another effect of neutrophils in tumour growth is linked

GATA-3+

Introduction

12

with neutrophil elastase secretion that enters tumour cells, binds to insulin receptor substrate

1 (IRS-1) and increases Akt activation (Houghton et al. 2010). High levels of neutrophil elastase

are also associated with invasion and metastasis promotion due to its extracellular matrix

degrading functions (Sun and Yang 2004). Finally, neutrophil depletion in tumour-bearing mice

led to increased activation of CD8 T cells (Fridlender et al. 2009). Such inhibition has recently

been associated with increased breast cancer metastasis (Coffelt et al. 2015) supporting the

idea that N2 display immunosupressive functions.

Myeloid-derived suppressor cells (MDSC), are a heterogeneous mixture of myeloid composed

by immature and mature cells of polymorphonuclear and monocytic origin. MDSCs are defined

by the expression of CD11b and Gr-1 and ability to suppress T cell responses. Immature cells

with the same phenotype as MDSC are present in the bone marrow of healthy individuals and

differentiate into mature cells without causing detectable immunosuppression (Gabrilovich,

Ostrand-Rosenberg, and Bronte 2012). However, under tumour conditions these cells are

diverted from their normal differentiation pathway and accumulate in high numbers. Factors

that induce MDSCs expansion include prostaglandins, M-CSF (macrophage colony-stimulating

factor), GM-CSF, IL-16 and VEGF. Most of these factors trigger signaling pathways that

converge to STAT3. MDSCs from tumour-bearing mice have increased levels of phosphorylated

STAT3 compared to immature myeloid cells from tumour-free mice and MDSCs expansion is

abrogated when STAT3 expression is inhibited (Nefedova, Nagaraj, et al. 2005; Nefedova,

Cheng, et al. 2005). Hence, STAT3 abnormal activation in myeloid progenitors prevents their

differentiation into mature cells and promotes MDSCs expansion (Gabrilovich and Nagaraj

2009). MDSC suppressive activity is an active process that is promoted by factors such as IFN-γ,

IL-4, IL-13 and TGF-β that are produced by activated T cells and tumour stromal cells

(Gabrilovich and Nagaraj 2009).

Based on mouse models, MDSC are currently divided into two main subsets: monocytic MDSC

(Mo-MDSC) described as CD11b+Gr-1intLy6G-Ly6C+ with low side-scatter (SSC) properties; and

polymorphonuclear (PMN-MDSC) also known as granulocytic, which are CD11b+Gr-

1highLy6G+Ly6Cint with high SSC features (Peranzoni et al. 2010).

MDSC suppressive features can be mediated by a plethora of mechanisms, represented in

Figure 4, that include: depletion of amino acids required by lymphocytes; generation of

oxidative stress; impairment of lymphocyte migration and viability; and induction of Tregs. The

first type of mechanism includes arginase-1 (Arg1) dependent L-arginine consumption

(Rodriguez et al. 2004) and L-cysteine deprivation (Srivastava et al. 2010). The depletion of

Introduction

13

these amino acids leads to downregulation of ζ-chain of the TCR complex and proliferative

arrest of antigen-activated T cells. Secondly, MDSCs are able to generate oxidative stress

through production of reactive oxygen and nitrogen species (ROS and RNS) via NADPH oxidase,

Arg1 and inducible nitric oxide synthase (iNOS). These reactive species lead to loss of TCR ζ-

chain expression (Schmielau and Finn 2001), nitration of the TCR (Nagaraj et al. 2007) and

interference with IL-2 signalling (Mazzoni et al. 2002). The third type of mechanisms employed

by MDSC includes cell-cell interaction with surface expression of inhibitory molecules. These

include ADAM17, that causes CD62L downregulation and consequently limits naïve CD4 and

CD8 T cell homing to peripheral lymph nodes and inflammatory sites, such as tumours (Hanson

et al. 2009). Moreover, peroxynitrite secretion leads to CCL2 modification and impaired T cell

recruitment (Molon et al. 2011). Additionally, interaction of galectin 9 expressed by MDSCs

and T cell immunoglobulin and mucin domain-containing protein 3 (TIM3) induces T cell

apoptosis (Sakuishi et al. 2011). Finally, through mechanisms that are not yet completely

understood, but that may involve CD40-CD40L interactions and expression of IFN-γ, IL-10, TGF-

β and Arg1 by MDSC, these cells are able to promote expansion of natural Tregs and

differentiation of iTregs (Pan et al. 2010; Huang et al. 2006; Serafini et al. 2008).

N2 neutrophils are pro-tumour effectors mainly because they modulate tumour invasion,

metastasis and angiogenesis, while evidence for a similar function of MDSCs is only beginning

to emerge. Conversely, several mechanisms of MDSC immunosuppression are well

characterized, whereas the features of immunosuppressive neutrophils are beginning to be

established. It is clear that there is a significant overlap between surface markers, functions

and mechanisms employed by N2 neutrophils and PMN-MDSC, which questions their

relationship (Brandau, Moses, and Lang 2013).

All these leukocytes display pro-tumour functions, which encompass changes in the

microenvironment that favour tumour growth, as well as immunosuppressive activities. Th17

CD4 T cells and γδ17 T cells can provide large amounts of IL-17, which besides inducing the

infiltration of pro-tumour cells, has been directly implicated in promotion of tumour cell

proliferation. Furthermore, IL-17 can promote angiogenesis which consists in de novo

formation of blood vessels and is a crucial process for the sustained growth of solid tumours. A

tumour mass without new blood supply is deprived from oxygen and nutrients and thus

becomes unable to proliferate.

Introduction

14

Figure 5: Mechanisms of lymphocyte inhibition by MDSCs. From Gabrilovich, Ostrand-Rosenberg, and

Bronte 2012

Besides microenvironment changes, immunosuppressive functions, that can be exerted by the

tumour cells or by the immune cells themselves, are also key for tumour development.

Tumour cells upregulate molecules from the B7 family, such as B7.1, B7.2 and B7-H1. B7.1 and

B7.2 bind to the inhibitory coreceptor which is expressed by T cells. This ligation leads to

decreased IL-2 production, impaired TCR signaling and cell cycle arrest. Similarly, B7-H1 binds

to PD-1 expressed by activated T cells and leads to TCR/CD28 signaling disruption. These

mechanisms empower tumour cells with the ability to cause T cell anergy. Besides tumour

cells, immune cells, such as Tregs and MDSCs, are important mediators of immunosuppression.

These cells can directly target anti-tumour subsets by inhibiting their activation, proliferation

and differentiation through the mechanisms already described. All these strategies used by the

tumour and tumour-infiltrating immune cells lead to tumour escape.

5. Cancer immunotherapy

Immunotherapies have been proposed for cancer over a century but it was not until recent

years that their clinical value has been appreciated (Restifo, Dudley, and Rosenberg 2012).

Introduction

15

However, there are still several hurdles to overcome, such as the constant ability of the

tumour to create an immunosuppressive environment and to convert the immune response to

its own benefit. Here we briefly review the main cancer immunotherapy strategies that are

currently available.

Cytokines, such as IL-2 and IFNs, have been approved by the Food and Drug Administration

(FDA) for treatment of some kinds of tumours. IL-2 can promote T cell and NK cell cytotoxicity

and modulate T cell differentiation, promoting CD4 differentiation into Th1 (and Th2) while

inhibiting Th17 (Paul, Zhu, and Yamane 2010; Littman and Rudensky 2010). However, IL-2 is

also essential for development and maintenance of Tregs, thus mediating immune tolerance

(Sakaguchi et al. 2008). IL-2 immunotherapy can result in complete remission of 5-10% of

patients with metastatic melanoma and renal cell carcinoma (Rosenberg 2012). A limitation of

IL-2 is its high-dose toxicity, which includes severe capillary leak syndrome. All types of IFNs

can induce tumour cell apoptosis. IFNα2b was the first shown to be beneficial in melanoma

and was approved by FDA as an adjuvant therapy. Although IFN immunotherapy has produced

some positive results, it is also associated with high toxicity (Kirkwood et al. 1996).

Tumour immunologists have developed therapeutical anti-cancer vaccines in an attempt to

produce an immune response that eliminates cancer cells and produces a long-lasting

memory. Currently, most cancer vaccine approaches use a specific target antigen expressed

only in cancer. One antigen-specific vaccine that resorts on melanoma-associated antigen A-3

has showed promising results in a non-small-cell lung clinical study (Vansteenkiste et al. 2013).

Cimavax, a vaccine developed for non-small-cell lung cancer, stimulates endogenous

production of antibodies against a well-known oncogene - epidermal growth factor. This

vaccine has led to a 4 to 6 months improvement in patients’ survival (Rodríguez et al. 2010).

Another vaccine approach relies on dendritic cells which are key immune cells that process and

present antigens to naïve T cells. These vaccines rely on the administration of antigen-loaded

dendritic cells that are then able to generate an adaptive immune response. Sipuleucel-T is so

far the only DC-based vaccine approved by FDA (2010) for treatment of hormone-treatment-

refractory prostate cancer. It prolongs patients’ survival in 4-6 months (Kantoff et al. 2010).

Another strategy for cancer immunotherapy relies on the blockade of immune checkpoints.

When an antigen is presented by a DC to a T cell, the B7 molecules on DCs bind to the co-

stimulatory molecule CD28 on T cells leading to their activation. However, B7 molecules can

also bind to CTLA-4 which generates inhibitory signals. Monoclonal antibodies (mAb) that bind

to CTLA-4 and prevent their interaction with B7 lead to reduction of T cell inhibition and

Introduction

16

accelerate immune responses to tumours. Ipilimumab, an anti-CTLA-4 monoclonal antibody,

has been approved for melanoma (2011) and is currently on clinical trials for non-small-cell

lung cancer, prostate cancer and renal cell carcinoma (Lynch et al. 2012; Small et al. 2007).

Similarly, PD-1 receptor is expressed on lymphocytes and binds to PD-L1 and PD-L2. Often,

tumour-infiltrating lymphocytes upregulate PD-1 while tumour cells increase PD-L1 expression.

The interaction between these two molecules results in T cell anergy. Thus, strategies to block

PD-1 and PD-L1 using monoclonal antibodies have been proven efficient in clinical trials of

melanoma (>50% response rate), non-small-cell lung cancer, renal cell carcinoma and ovarian

cancer (Brahmer et al. 2012; Topalian et al. 2012), and two anti-PD1 monoclonal antibodies,

Pembrolizumab and Nivolumab, have been approved (2014-2015) for melanoma treatment.

Adoptive T cell therapy have been showing encouraging results since overall clinical response

rate is 51% and complete regression over 5 years is 13% (Jiang and Zhou 2015). This strategy

includes adoptive cell transfer of antigen-specific T cells which consists on infusion of

autologous or allogeneic ex vivo expanded T cells. T cells used for adoptive cell transfer can be

either naturally occurring T cells or engineered chimeric antigen receptor T cells (CAR-T). CARs

comprise an extracellular domain which is composed by variable regions of antibody genes,

and intracellular TCR signalling domain. Hence CAR-Ts are able to recognize MHC-unrestricted

structures. Clinical trials in haematological cancers have shown very positive results (Davila et

al. 2014; Porter et al. 2011). Furthermore, γδ T cell-based immunotherapy is becoming more

and more promising. Nonetheless, the recent discoveries of pro-tumour roles of these cells

may create new challenges for this therapeutic approach. It is important to ensure the stable

polarization of γδ T cells, maximizing IFN-γ production and minimizing IL-17 secretion. For

adoptive γδ T cell transfer, it is crucial to differentiate IFN-γ+ IL17- effector cells, devoid of

immunosuppressive features. In line with this, Vγ9Vδ2 human γδ T cells activated with

pyrophophate agonists and IL-12 display strong IFN-γ production but no IL-17 (deBarros et al.

2011). Moreover, our laboratory has identified a population of Vδ1 T cells that express natural

cytotoxicity receptors (such as NKp30), produces abundant IFN-γ but no IL-17 and displays high

anti-leukemia cytotoxicity (Correia et al. 2011), all promising features for cancer

immunotherapy. It is worth mentioning that γδ T cell-based immunotherapy likely depends on

avoiding activation-induced cell death, exhaustion and inhibitory mechanisms such as those

caused by PD-1 expression (Iwasaki et al. 2011), suppressive functions of regulatory T cells

(Kunzmann et al. 2009; Gonçalves-Sousa et al. 2010) or, potentially, of MDSC – which will be

the focus of this thesis.

Hypothesis and objectives

17

HYPOTHESIS AND OBJECTIVES OF THIS THESIS

Previous studies from our laboratory and others had shown that γδ T cells can play different

roles in tumour growth. On one hand, they can be protective, as in subcutaneous B16

melanoma model, where they provide large amounts of IFN-γ (Gao et al. 2003; Lança et al.

2013). On the other hand, they can contribute to ID8 ovarian cancer progression by providing

IL-17 that mobilizes pro-tumour small peritoneal macrophages (Rei et al. 2014). While

dissecting whether this difference was due to the tumour type (melanoma vs ovarian cancer)

or to the site of tumour injection (subcutaneous vs intraperitoneal), we came across a model

(intraperitoneal B16 injection) where γδ T cells play a neutral role, i.e., they fail to respond to

tumour challenge.

We hypothesized that the γδ T cell response to the tumour challenge was impeded due to a

suppressive mechanism, likely mediated by an infiltrating immune cell population.

Building on this, the main objectives of this thesis were:

1. To dissect the cellular and molecular mediators of γδ T cell suppression in the

intraperitoneal B16 model;

2. To characterize the phenotype and determine the function of tumour-associated γδ T

cells upon ablation of the immunosuppressive mediator;

3. To determine the consequences of ablation of the immunosuppressive mediator on

tumour growth in the peritoneal cavity.

18

Methods

19

METHODS

1. Mice

C57Bl/6J wild type (WT) mice were purchased from Charles River Laboratories. B6.TCRδ-/- mice

were purchased from The Jackson Laboratory. B6.IL17-/- mice were kindly provided by Dr. Fiona

Powrie (University of Oxford, UK) with permission from Dr. Yoichiro Iwakura (Tokyo University

of Science, Chiba, Japan). All animals were females with 5 to 16 weeks of age, which were age-

matched within 2 weeks. Mice were maintained in a specific pathogen-free facility at Instituto

de Medicina Molecular (Lisboa, Portugal). All experimental procedures were performed

according to guidelines approved by the local ethics committee.

2. Cell culture

B16-F0 melanoma cell line was purchased from ATCC. Cells were maintained in Dulbecco’s

modified Eagles’ medium (DMEM; Life Technologies) with glutamine, sodium pyruvate, 10%

fetal calf serum (FCS; Life Technologies) and 1% penicillin-streptomycin (P/S), at 37ºC and 5%

CO2. When around 90% confluency was reached cells were washed with phosphate buffer

saline (PBS; Life Technologies), incubated with Triple Express (Life Technologies) for 2 min at

37ºC and ressuspended in 3 times the volume of complete media. Cells were split in a

proportion of 1:20 every 2 to 3 days. For long term storage, cells were ressuspended in FCS

with 10% dimethyl sulfoxide (DMSO).

3. Lentiviral transduction for luciferase expression

For viral production 293 Hek cells (ATCC) were cultured for 32h in the presence of 1μg of

packaging plasmids (RSV-Rev, VSV-g and pDMLg), 2μg of GFP-luciferase-encoding plasmid and

Lipofectamine2000. In the last 8h of incubation 10mM of Sodium Butyrate was added. After

the incubation period cells were washed 3 times with complete medium and 24h later viral

supernatant was harvested.

For viral transduction 75.000 B16-F0 cells were cultured in a 24-well plate with 500μL of viral

supernatant and 500μL of complete media. The transduction was performed with 8μg/ml of

polybrene during a 90min centrifugation at 32ºC, 1500g. 72h later GFP+ cells were sorted.

4. In vivo transplantable B16 tumour model

5x104 viable B16-F0 cells were injected intraperitoneal (i.p.) or subcutaneously (s.c.) in 100μL

of PBS, for establishment of tumour.

Methods

20

For tumour growth experiments 5x104 viable B16-GFP-luc cells (B16 cells expressing GFP and

luciferase) were injected intraperitoneally in 100μL of PBS. Mice were injected i.p. with 3mg D-

luciferin in PBS and anesthetized 4min after with 75mg/Kg body weight of ketamine and 1

mg/KgBW of Medetomidine. Images were acquired using a charge-coupled device camera

(IVIS, Xenogen, Cliper, LifeSciences), with a 12.5cm X 12.5cm field of view, factor 16 of

resolution, with a lens aperture of f/1 and an imaging time of 5min. Images were taken after

10min of D-luciferin injection. Anesthesia was reversed by i.p. injection of 1mg/KgBW of

Atipamezole. Data were analysed in the Living Image 3.0 software (Xenogen) and presented as

total flux (photons/s). Tumour burden assessment was performed every 2 to 3 days.

For in vivo proliferation assays mice were injected i.p. with 1.5mg of bromodeoxyuridine

(BrdU, Sigma) 9 days post-tumour inoculation and fed with 0.8mg/mL in the drinking water

until the end of the experiment. BrdU solution was changed every other day and protected

from light.

For PMN-MDSC depletion 70μg of monoclonal antibody anti-Gr-1 (Clone RB6-8C5; BioXCell)

was injected i.p. at days 4, 8 and 12 post-tumour inoculation and analysis performed at day 13.

For tumour growth experiments, from day 12 on αGr-1 mAb was also inoculated every time

tumour burden was assessed.

5. Flow cytometry analysis and cell sorting

Peritoneal exudate cells were obtained from the lavage of the peritoneal cavity with 5mL of

DMEM with 10% FCS. Erythrocytes were osmotically lysed using Red Blood Cell Lysis Buffer

(Biolegend). In this model, we have faced a technical difficulty in the determination of cell

numbers. The lavage of the peritoneal cavity does not allow constant efficacy and

reproducibility in retrieving cells or constant volume of cell suspension. In addition, besides

immune infiltrates, B16 cells are also retrieved and, many times, in the form of clumps that do

not dissociate easily and thus compromise the accurate count of cell numbers. Thus, we have

presented the results as frequency within hematopoietic cells, defined as CD45+. For analysis

of tumour infiltrates the tumour was harvested and cut into small pieces. 100μg/mL of DNAse I

(Roche), 1mg/mL of collagenase D (Roche) and 200 U/ml of collagenase (IV) were used to

digest the tumour for 30 min at 37ºC. After that time 5mM of EDTA was added, the digested

sample was filtered through a 100μm cell strainer and stained.

For surface staining cells were incubated with anti-CD16/32 (clone 93, eBioscience), 2% of

mouse serum and the respective antibodies in complete RPMI medium, for 1h at room

Methods

21

temperature. Antibodies were purchased from eBioscience and Biolegend, as summarized in

Table 1. Anti-TCRVγ5Vδ1 (17D1) was provided by Prof. Adrian Hayday (King’s College London).

TCRVγ6 detection was performed by incubation with anti-TCRδ (GL3) for 30 min, followed by

incubation with 17D1 at room temperature. After two washes, anti-rat IgM labeled with

phycoerythin was added for 30 min at 4ºC.

Marker Clone Manufacturer

CD45 30-F11 Biolegend

CD3 145-2C11; 17A2 eBioscience

TCRδ GL3 Biolegend

Vγ1 2.11 Biolegend

Vγ4 UC3-10A6 eBioscience

CD27 LG.7F9 eBioscience

CD4 RM4-5 Biolegend

CD8 53-6.7 Biolegend

NK1.1 PK136 Biolegend

CD11b M1/70 eBioscience

Gr-1 RB6-8C5 Biolegend

Ly6C HK1.4 eBioscience

Ly6G 1A8 Biolegend

F4/80 BM8 eBioscience

MHC II M5/114.15.2 eBioscience

IL-17 TC11-18H10.1 Biolegend

IFNγ XMG1.2 eBioscience

Table 1 – List of antibody clones used in flow cytometry and manufacturers.

Methods

22

For intracellular cytokine staining, cells were stimulated with 50ng/mL of phorbol 12-myristate

13-acetate (PMA; Sigma) and 1μg/mL ionomycin (Ionon; Sigma) for 4h at 37ºC. 10μg/mL of

brefeldin-A (Sigma) were added during the last 2h. Cells were stained for surface markers,

fixed and permeabilized using BD Pharmingen cytofix/cytoperm kit, following the

manufacturer’s instructions, and then incubated for 1h with monoclonal antibodies to detect

cytokine production.

For BrdU staining, fluorescein isothiocyanate BrdU Flow Kit (BD Pharmingen) was used

following the manufacturer’s instructions.

Cells were either analysed on LSRFortessa (BD Bioscience) or sorted on Aria I (BD Bioscience)

for posterior mRNA extraction. Compensation was performed using single-stained samples.

Data was analysed using FACSDiva and FlowJo software (TreeStar). Cell gating strategy was

performed as described in Supplementary Figure 3.

6. Gene expression analysis

RNA was extracted from sorted cells using High Pure RNA Isolation Kit (Roche) following

manufacturer’s instructions. RNA was reverse-transcribed into cDNA using random

oligonucleotides (Invitrogen) and MMLV reverse transcriptase (Promega). Quantification of

specific cDNA species was assessed by real-time-PCR on ViiA7 Real-Time PCR System (Applied

Biosystems) with SYBR, relatively to endogenous references (β2-microglobulin, HPRT or β-

actin). Target gene CT was subtracted from CT of the endogenous reference and the relative

amount calculated as 2-ΔCT.

7. Statistical Analysis

In tumour growth graphs means and standard error of mean are plotted, in all other graphs

presented in this thesis each individual value is plotted as well as the mean of each group.

GraphPad Prism software was used to perform statistical analysis. Shapiro-Wilk test was

performed to assess if the samples followed a normal distribution. If so, the parametric

student t test was performed to assess differences between groups’ means. When samples did

not follow a normal distribution or were too small to test it, the non-parametric Mann-

Whitney test was performed to assess differences between groups’ medians. Results are

presented as p-values: * p≤0.05, ** p≤0.01, ***p≤0.001

Results

23

RESULTS

1. Role of γδ T cells in intraperitoneal B16 melanoma growth in vivo

It had been shown that γδ T cells inhibit the growth of the B16 melanoma cell line, when

injected subcutaneously, by providing large amounts of IFN-γ(Lança et al. 2013; Gao et al.

2003). To understand the role of γδ T cells in the intraperitoneal B16 melanoma model

established in our laboratory, we compared the tumour growth kinetics in WT and γδ T cell-

deficient mice (TCRδ-/-). Contrary to what we reported in the subcutaneous site

(Supplementary Figure 1), in the peritoneal cavity the kinetics of B16 tumour growth was

similar between the two mouse strains (Figure 6), indicating that γδ T cells play a neutral role

in this model. The lack of an active role for γδ T cells in tumour growth could be due to: i)

absence of this population in the anatomical location of tumour transplantation; ii) paucity of

tumour-derived stimuli to this particular lymphocyte subset; or iii) a suppressive mechanism

that would affect their accumulation and/or function. Given that γδ T cells are present in the

peritoneal cavity (Shibata et al. 2007; Rei et al. 2014), and that they readily responded to

subcutaneous B16 melanoma, it is more likely that an immunosuppressive mechanism

inhibited their response in the peritoneal cavity, which would explain the lack of phenotype in

TCRδ-/- mice (Figure 6B).

Figure 6: γδ T cells play a neutral role in the intraperitoneal B16 melanoma model. A – Representative

images from IVIS lumina analysis at day 14 post-tumour inoculation. B – Intraperitoneal B16 tumour

growth in C56BL/6 WT (n=5) and TCRδ-/- (n=5) mice, quantified by bioluminescence. Mean and Standard

Error of Mean (SEM) are plotted.

To dissect the immune response to B16 tumour challenge, we analysed by flow cytometry the

peritoneal exudates of B16-bearing mice and PBS controls. Kinetics analysis of several immune

subsets was performed between day 0 and day 13 post-tumour transplantation

A

WT

TCR-/-

Day 14 B

Results

24

(Supplementary Figure 2). The gating strategy for lymphocyte analysis is presented in

Supplementary Figure 3A. Since an active immune response was clearly observed at week 2 as

revealed by the significant accumulation of CD4, CD8 T cells and NK cells (Figure 7), we decided

to further analyze peritoneal γδ T cells at this timepoint.

Figure 7: CD8, CD4 T cells and NK cells accumulate in response to intraperitoneal B16 tumour

challenge. A - Representative FACS plots in peritoneal exudates from PBS controls or B16-injected mice

2 weeks post tumour inoculation. Pre-gated on CD45+ cells and lymphocytes (based on side

scatter/forward scatter analysis). B – Frequency of each subset in peritoneal exudates from tumour-free

and tumour-bearing mice, at week 2, post-tumour inoculation. Data are representative of at least 3

independent experiments.

In steady state, γδ T cells accounted for less than 1% of total lymphocytes (Figure 8). In

agreement with the results from Figure 6 that suggest a lack of γδ T cell response, 2 weeks

after tumour challenge, γδ T cells still accounted for similar percentages of lymphocytes

***

A B

PBS B16

*

*

CD8

CD

3

NK1.1

CD

3

CD4

CD

3

Results

25

B

IL-17A

IFN

-

PBS B16 A

(Figure 8). To understand whether this phenomenon is specific to peritoneal exudates, we

analysed tumour infiltrates and compared them to those from subcutaneous B16 melanoma

model. We found that, at the same timepoint of tumour development, γδ T cells are 3 times

more frequent in the subcutaneous site (Figure 8C). Taken together, these findings suggest

that the B16 peritoneal environment is selectively unfavourable for the accumulation of γδ T

cells, but not for other lymphocyte subsets, such as CD8, CD4 T cells and NK cells.

Figure 8: γδ T cells do not accumulate in response to intraperitoneal B16 tumour challenge. A –

Representative FACS plots for γδ T cells in peritoneal exudates from PBS controls or B16-injected mice, 2

weeks post-tumour inoculation. Pre-gated on CD45+ cells and lymphocytes (based on side

scatter/forward scatter analysis). B – Frequency of γδ T cells in peritoneal exudates from tumour-free

and tumour-bearing mice, at week 2 post-tumour inoculation. Data are representative of at least 3

independent experiments. C – Frequency of γδ T cells in tumour infiltrates of intraperitoneal (i.p.) and

subcutenous (s.c.) B16 melanoma models, at week 2 post-tumour inoculation.

Although γδ T cells did not accumulate in the presence of the tumour, they could still respond

by increasing cytokine or cytotoxic molecule production. Hence, we next addressed γδ T cell

function in the tumour environment. γδ T cells are important producers of IL-17 and IFN-γ in

various settings (Sheridan et al. 2013; D’Ombrain et al. 2007; Pantelyushin et al. 2012), but also

in the tumour context (Lança et al. 2013;,Rei et al. 2014). Thus, we examined the production of

these two cytokines in the peritoneal exudates by intracellular cytokine staining, after four

hours of re-stimulation with PMA and ionomycin, in the presence of brefeldin A, for the last

two hours.

TCR

CD

3

PBS B16 A

n.s.

B C

**

T cells

n.s. n.s.

Results

26

Figure 9: γδ T cells do not increase pro-inflammatory cytokine production in response to

intraperitoneal B16 tumour challenge. A – Representative FACS plot for cytokine production by γδ T

cells in peritoneal exudates from PBS controls or B16-injected mice, 2 weeks post-tumour inoculation. B

– Frequency of IFN-γ and IL-17A γδ T cell producers in peritoneal exudates from tumour-free and

tumour-bearing mice, at week 2 post-tumour inoculation. Data are representative of 2 independent

experiments.

We observed no significant increase in the frequency of IL-17 or IFN-γ γδ T cell producers,

upon tumour challenge (Figure 9). However, within the CD8 T cell compartment IFN-γ

producers were increased, in the same tumour environment (Supplementary Figure 5).

γδ T cells, along with NK cells, have also been shown to be efficient tumour killers, through the

production of cytolytic molecules, such as perforin and granzymes. Therefore, we determined

perforin and granzyme b mRNA expression in NK and γδ T cells, by real-time quantitative PCR.

Figure 10: γδ T cells do not upregulate cytotoxic molecules in response to intraperitoneal B16 tumour

challenge. Relative mRNA expression of GranzymeB (Gzmb) and Perforin (Prf1) in FACS-sorted NK and γδ

T cells from peritoneal exudates from PBS control or B16-injected mice, 2 weeks post tumour

inoculation. Results were normalized to the housekeeping gene b2microglobulin (b2m).

As shown in Figure 10, NK cells upregulated granzyme b (Gzmb) and perforin (Prf1) mRNA, in

response to the tumour, which reveals an effector phenotype. By contrast, the expression of

Gzmb and Prf1 mRNA was not increased in γδ T cells isolated from B16 tumour-bearing mice

when compared to PBS controls.

Collectively, these data suggest that γδ T cells are unresponsive to intraperitoneal B16 tumour

challenge, since they do not accumulate and do not increase cytokine or cytotoxic molecule

production. Therefore, γδ T cells are functionally impaired in this model, which led us to

hypothesize that they are inhibited by an immune suppressive population present in the B16

tumour-bearing peritoneal cavity.

** n.s.

Results

27

CD25

CD

3

A PBS B16

B

**

2. Assessing the presence of suppressive subsets in the tumour environment

To fully understand if, in this model, γδ T cell unresponsiveness is caused by an immune

modulatory mechanism, we assessed the presence of suppressive subsets in the tumour

environment. It is well known that regulatory T cells favour a tolerogenic environment, which

facilitates tumour immune escape. That, added to the fact that Treg cells have already been

shown to suppress γδ T cell responses (Gonçalves-Sousa et al. 2010), led us to investigate the

presence of this subset in the peritoneal exudates of tumour-free and tumour-bearing mice.

Figure 11: Decreased accumulation of regulatory T cells in the intraperitoneal B16 tumour-bearing

mice. A – Representative FACS plots of Treg cells, defined as CD4+CD25

+ (pre-gated on CD4

+), in

peritoneal exudates from PBS controls or B16-injected mice 2 weeks post-tumour inoculation. B –

Frequency of Treg cells in peritoneal exudates from tumour-free and tumour-bearing mice, at week 2

post-tumour inoculation. Data are representative of at least 3 independent experiments.

As seen in Figure 11, Tregs did not accumulate but were instead reduced (in frequency) in B16-

bearing mice. This renders Tregs unlikely candidates for mediation of γδ T cell suppression in

this model.

We next explored myeloid-derived suppressor cells. This heterogeneous population is defined

as Gr-1+CD11b+ and can be divided in two main subsets: polymorphonuclear (PMN) and

monocytic (Mo). The gating strategy for MDSC analysis is presented in Suplemmentary Figure

3B. These two subtypes are distinguished by the differential expression of the surface markers

Ly6C and Ly6G as well as by different side-scatter properties, since the polymorphonuclear

subset is more granular (Figure 12A).

CD4T cells

Results

28

Figure 12: Myeloid-derived suppressor cells accumulate in the peritoneal cavity of B16 tumour-

bearing mice. A – Phenotypic characterization of polymorphonuclear (PMN) and monocytic (Mo) MDSC.

B – Representative FACS plots of PMN and Mo-MDSCs, in peritoneal exudates from PBS controls or B16-

injected mice 2 weeks post-tumour inoculation. Pre-gated on CD45+ myeloid cells (based on side

scatter/forward scatter analysis) CD11b+. C – Frequency of PMN and Mo-MDSCs in peritoneal exudates

from tumour-free and tumour-bearing mice, at week 2 post-tumour inoculation. Data are representative

of at least 3 independent experiments.

Interestingly, the frequency of Mo- and PMN-MDSCs increased by 20-fold and 2000-fold,

respectively. These results are in agreement with the fact that these cells have been described

to massively accumulate in the tumour context (Gabrilovich and Nagaraj 2009). Therefore

MDSC are likely candidates to mediate suppression of the γδ T cell response in the

intraperitoneal B16 tumour model.

3. PMN-MDSC inhibit Vγ6 T cell accumulation

Aiming at testing our hypothesis that MDSCs inhibit γδ T cell responses, we designed an

experiment to deplete the former. It is well established that injection of monoclonal antibody

anti-Gr-1 leads to MDSC depletion. As such, we injected this antibody at days 4, 8 and 12 post

tumour inoculation, and one day after the last injection we analysed the peritoneal exudates

by flow cytometry.

PMN-MDSC

Mo-MDSC

Ly6C

Ly6

G

FSC-A

SSC

-A

CD11b

GR

-1

A

MoB16 1

Gate %

Mo 16.8

PMN 13.3

0 50K 100K 150K 200K 250K

FSC-A

0

50K

100K

150K

200K

250K

SS

C-A

PMN-MDSC

Mo-MDSC

Ly6C

Ly6

G

PBS B16 B

*** ***

C

Results

29

Ly6C

Ly6

G

A B16 + Gr-1 B16 + PBS

Figure 13: Monoclonal antibody Gr-1 injection leads to efficient depletion of PMN-MDSCs, but not

Mo-MDSCs in the peritoneal cavity of B16 tumour-bearing mice. A – Representative FACS plots of

PMN- and Mo-MDSCs in peritoneal exudates from B16-injected mice treated with Gr-1 mAb (or PBS), 2

weeks post-tumour inoculation. Pre-gated on CD45+ myeloid cells (based on side scatter/forward scatter

analysis) CD11b+. B – Frequency of PMN- and Mo-MDSCs in peritoneal exudates from tumour-bearing

mice with Gr-1 mAb treatment (or PBS). Data are representative of at least 3 independent

experiments.

Consistent with the observation that Mo-MDSCs express lower levels of Gr-1 on their surface

(Figure 12A), anti-Gr-1 mAb injection failed to deplete this subpopulation of MDSCs. By

contrast, PMN-MDSCs were efficiently reduced from the peritoneal cavity of B16 tumour-

bearing mice upon anti-Gr-1 mAb treatment (Figure 13).

A

n.s.

n.s.

n.s.

CD8

CD

3

NK1.1

CD

3

CD4

CD

3

B16 + Gr-1 B16 + PBS B

*** n.s.

B

Results

30

Figure 14: GR-1 mAb treatment does not affect CD8, CD4 T cells or NK cells in intraperitoneal B16

tumour-bearing mice. A – Representative FACS plots in peritoneal exudates from B16-injected mice

treated with Gr-1 mAb (or PBS), 2 weeks post-tumour inoculation. Pre-gated on CD45+ cells and

lymphocytes (based on side scatter/forward scatter analysis). B – Frequency of each subset in peritoneal

exudates from tumour-bearing mice treated with Gr-1 mAb (or PBS), at week 2 post-tumour

inoculation. Data are representative of at least 3 independent experiments.

The frequency of CD8, CD4 T cells and NK cells in the peritoneal exudates was not affected by

PMN-MDSC depletion (Figure 14). This suggests that, in this model, such immune subsets are

not PMN-MDSC targets. By contrast, γδ T cells accumulated massively in anti-Gr-1 mAb-treated

mice, suggesting that PMN-MDSC play an active role in restraining γδ T cell responses in the

B16 tumour-bearing peritoneal cavity (Figure 15).

Figure 15: Gr-1 mAb treatment leads to accumulation of γδ T cells in the peritoneal cavity of B16

tumour-bearing mice. A – Representative FACS plots in peritoneal exudates from B16-injected mice

treated with Gr-1 mAb (or PBS), 2 weeks post-tumour inoculation. Pre-gated on CD45+ cells and

lymphocytes (based on side scatter/forward scatter analysis). B – Frequency of γδ T cells in peritoneal

exudates from tumour-bearing mice treated with Gr-1 mAb (or PBS), at week 2 post-tumour

inoculation. Data are representative of at least 3 independent experiments.

γδ T cell subsets are commonly defined based on cell surface CD27 expression (Ribot et al.

2009) and TCRγ variable (Vγ) chain usage (Carding and Egan 2002). To characterize the

accumulated γδ T cells, upon PMN-MDSC depletion, we assessed those parameters. In the

absence of PMN-MDSCs, the vast majority of γδ T cells were negative for Vγ1 or Vγ4 chains

(Figure 16A) and for CD27 expression (Figure 16B), compared to PBS-treated mice. We

reasoned that Vγ1-Vγ4- cells would express Vγ6, since these cells populate the peritoneal cavity

(Prinz, Silva-Santos, and Pennington 2013) where they were shown to respond to ovarian

tumours (Rei et al. 2014). As there is no available commercial antibody for Vγ6, we used the

reactivity of the 17D1 antibody, which typically identifies Vγ5 T cells, but has the property to

bind to Vγ6 T cells when used after pre-incubation with the pan-TCR--specific mAb GL3

A B

***

TCR

CD

3

B16 + Gr-1 B16 + PBS

Results

31

B16 + PBS

T cells

B16 +

Gr-1

V1

V4

A

V6

TCR

T cells T cells

CD27

TCR

B C

D

(Roark et al. 2004). This protocol revealed that in anti-Gr-1 mAb-treated mice, the majority of

γδ T cells (over 80%) were indeed Vγ6+, as opposed to around 20% in PBS-treated controls

(Figure 16C).

Figure 16: Characterization of accumulated γδ T cells after PMN-MDSC depletion in the intraperitoneal

B16 tumour model. Representative FACS plots of: A, Vγ1 and Vγ4 expression; B, CD27 expression; and C,

Vγ6 expression by γδ T cells in peritoneal exudates from tumour-bearing mice treated with Gr-1 mAb

(or PBS), 2 weeks post-tumour inoculation. D – Percentage of γδ T cells expressing Vγ4, Vγ1 or other

(mostly Vγ6) TCRγ chain variable regions. Data are representative of 2 independent experiments.

As observed in Figure 16D, in the absence of tumour Vγ1-Vγ4- cells (Vγ6 cells) account for

almost 40% of total γδ T cells. Of note, there is no PMN-MDSCs in peritoneal exudates at

steady state, in absence of tumour. Then, when the tumour grows there is a concomitant

increase in PMN-MDSC frequency (Figure 12C) and decrease in Vγ1-Vγ4- cells (Figure 16D).

Upon treatment with Gr-1 mAb, Vγ6 cells overtake the other subsets, leading not only to a

substantial increase in their proportion within γδ T cells but also to an increase in total γδ T

cells that infiltrate the tumour and peritoneal cavity (Figure 15B).

Results

32

Given that the frequency of T cells was increased by PMN-MDSC depletion we tested if

there was an acquisition of functionality. To do so, we assessed cytokine production in the

accumulated γδ T cells by intracellular staining after stimulation with PMA/iono. We observed

a decrease in the percentage of IFN-γ producers (Figure 17), which is consistent with the

reduced proportion of CD27+ γδ T cells (~15%) of total γδ T cells (Figure 16B) upon anti-Gr-1

mAb treatment. By contrast, PMN-MDSC depletion led to a marked increase in the frequency

of IL-17 producers (Figure 17), which agrees with the accumulation of Vγ6+ and CD27- cells

(Figure 16).

Figure 17: Accumulated peritoneal γδ T cells are functionally restored, following Gr-1 mAb

treatment. A – Representative FACS plots of IFN-γ/IL-17A production by γδ T cells in peritoneal exudates

from B16-injected mice treated with Gr-1 mAb (or PBS), 2 weeks post-tumour inoculation. B –

Frequency of IFN-γ/IL-17A γδ T cell producers in peritoneal exudates from tumour-bearing mice treated

with Gr-1 mAb (or PBS), at week 2 post-tumour inoculation.

Collectively, these findings demonstrate that PMN-MDSC impair the accumulation of a specific

γδ T cell subset characterized by lack of CD27, expression of Vγ6, and IL-17 production, in the

intraperitoneal B16 model.

4. Dissecting the mechanism of inhibition of Vγ6 T cell accumulation by PMN-MDSC

Next we attempted to decipher the mechanism(s) by which PMN-MDSC prevented Vγ6 T cell

accumulation in the peritoneal cavity of B16 tumour bearing mice. We considered three main

possibilities: PMN-MDSC could provoke γδ T cell death, inhibit their proliferation in situ or

prevent their recruitment to the tumour site.

A T cells

IL17A

IFN

-

B16 + PBS

B16 +

Gr-1

B

Results

33

To track cell division we combined PMN-depletion with provision of the thymidine analogue

BrdU, which incorporates into the DNA during its synthesis, thus allowing tracking of cells that

have been through the S phase of the cell cycle. In addition to αGr-1 mAb injection at days 4, 8

and 12 post tumour inoculation, BrdU was given intraperitoneally at day 9 and in the water,

from that day until the end of the experiment. Furthermore, to address γδ T cell death, we

stained with Annexin-V, a phospholipid-binding protein that binds to phosphatidylserine. In

healthy cells, this phospholipid is predominantly located in the cytoplasmic side of the plasma

membrane but it becomes exposed upon initiation of apoptosis. Therefore, Annexin-V+ cells

can be detected by flow cytometry to quantify apoptosis.

Figure 18: Assessing the role of proliferation and survival on γδ T cell accumulation, following αGr-1

mAb treatment. A – Representative FACS plots of BrdU incorporation and Annexin-V staining in γδ T

cells from peritoneal exudates from B16-injected mice treated with αGr-1 mAb (or PBS), 2 weeks post-

tumour inoculation. B – Frequency of BrdU+ and Annexin-V

+ γδ T cells in peritoneal exudates from

tumour-bearing mice treated with αGr-1 mAb (or PBS), at week 2 post-tumour inoculation. Data are

representative of 2 independent experiments.

We found no evidence for increased proliferation or survival upon αGr-1 mAb treatment

(Figure 18).

An alternative mechanism could be the prevention of Vγ6 T cell recruitment to the tumour

site. If that were the case, ablation of PMN-MDSC could potentially reduce Vγ6 T cell frequency

in other organs or tissues. To address this question, we analysed several lymphoid and non-

lymphoid organs, as well as the blood, for Vγ chain usage in tumour-free and PBS or αGr-1

mAb-treated tumour-bearing mice.

n.s.

n.s.

BrdU

TC

Annexin V

B16 +

Gr-1

B16 + PBS

T cells T cells A B

TCR

n.s.

n.s.

Results

34

Figure 19: Assessing the role of recruitment on γδ T cell accumulation following αGr-1 mAb treatment.

Representative FACS plots of Vγ chain usage by γδ T cells in secondary lymphoid organs, lung and blood

of tumour-free and tumour-bearing mice treated with αGr-1 mAb (or PBS), 2 weeks post-tumour

inoculation.

Contrary to our prediction, the frequency of Vγ1-Vγ4- cells (mostly Vγ6+ cells) remained

unchanged in all assessed organs between tumour-free controls and tumour-bearing mice

(Figure 19, top two rows). However, the αGr-1 mAb treatment in tumour-bearing mice induced

a drastic increase in the proportion of Vγ1-Vγ4- cells in all organs analysed, especially in blood,

lung and spleen (Figure 19 bottom row). These results suggest that αGr-1 mAb treatment

released a systemic inhibition targeting Vγ6 T cells. However, the mechanism regulating this

potential systemic crosstalk between PMN-MDSC and Vγ6 T cells remains to be elucidated.

5. Addressing the role of γδ T cells, IL-17 and PMN-MDSC in intraperitoneal B16 tumour

growth

We showed that PMN-MDSC inhibit γδ T cell responses in the intraperitoneal B16 tumour

model. Intertingly, the restored γδ T cells upon αGr-1 mAb treatment were Vγ6+ IL-17

producers, which led us to postulate that these cells may promote tumour growth, since γδ17

T cells have been shown to play pro-tumoural roles in several studies (Rei et al. 2014;,Wu et al.

2014; Wakita et al. 2010; Ma et al. 2014). Hence, we compared the tumour growth kinetics in

TCRδ-/-, IL-17-/- and WT mice upon anti-Gr-1 mAb treatment to clarify the role of γδ T cells and

B16 + PBS

B16 +

Gr-1

PBS

Spleen Mesenteric LN Brachial LN

V1

V4

γδ T cells

15.2 14.8 15.3

13.9 14.8

30.1 23.0 51.3

15.7

Blood Lung

15.5

19.9 11.1

9.29

71.8 53.7

Results

35

IL-17; and in WT mice with or without αGr-1 mAb treatment, to evaluate the function of PMN-

MDSC in this model.

Figure 20: γδ T cells and IL-17 play a pathogenic role in intraperitoneal B16 melanoma tumour growth,

following αGr-1 mAb treatment. A – Representative images from IVIS lumina analysis at day 15 post-

tumour inoculation. B – Intraperitoneal B16 tumour growth in C56BL/6 WT (n=5) and TCRδ-/-

(n=4) or IL-

17-/-

(n=5) mice, upon αGr-1 mAb treatment, quantified by bioluminescence. Mean and Standard Error

of Mean (SEM) are plotted.

Both TCRδ-/- and IL-17-/- mice displayed delayed tumour growth when compared to WT

controls, suggesting that the absence of these immune system elements protects from tumour

growth (Figure 20). However, in the case of IL-17-/- mice we can observe that in early stages the

tumour growth is higher than in WT controls, but that around day 12 there is a shift in this

tendency. This shift is probably due to the angiogenic switch, which is when the tumour

requires new blood vessels to grow further. As IL-17 is a crucial cytokine for angiogenesis

(Numasaki et al. 2003) it is reasonable to think that this event might be the angiogenic switch,

similarly to peritoneal ovarian (ID8) tumour model (Rei et al. 2014). If that is the case, then we

can speculate that, at later timepoints, γδ T cells play a detrimental role because they promote

angiogenesis through production of IL-17.

*

*

A B

N.D. TCR-/- +

Gr-1

WT +

Gr-1

IL17-/- +

Gr-1

Day 15

Results

36

Figure 21: Effect of αGr-1 mAb treatment on intraperitoneal B16 melanoma tumour growth. A –

Representative images from IVIS lumina analysis at day 15 post-tumour inoculation. B – Intraperitoneal

B16 tumour growth in C56BL/6 WT mice treated with αGr-1 mAb (or PBS, n=5 for each group),

quantified by bioluminescence. Mean and Standard Error of Mean (SEM) are plotted.

In agreement with the previous results, the αGr-1 mAb treatment led to a tendency of

increased tumour growth, when compared to PBS controls (Figure 21). This suggests, for the

first time, that in this specific context, ablation of PMN-MDSC may promote tumour growth.

These results are consistent with PMN-MDSC inhibiting γδ T cells and, concomitantly, their IL-

17 production. Since both γδ T cells and IL-17 are pro-tumour in this model, PMN-MDSCs can

play a host-protective role. Therefore, our data highlight a rare phenomenon where the

suppressive subset has an overt anti-tumour function because it inhibits a pro-tumour IL-17+

γδ T subset.

B

WT + PBS

Day 15

WT +

Gr-1

A

Supplementary Figures

37

SUPPLEMENTARY FIGURES

Supplementary Figure 1: Subcutaneous B16 melanoma growth in WT and TCR-/- mice as

measured with a caliper. Results obtained by Telma Lança. Published in Journal of Immunology

in 2013.

Supplementary Figure 2: Kinetics of lymphocyte subset frequencies in peritoneal exudates of

tumour-bearing mice, in intraperitoneal B16 tumour model.

CD45 FSC-A FSC-A

SSC

-A

SSC

-A

FSC

-W

CD4

CD

3

CD

3

CD25

CD

3

CD8

CD

3

NK1.1

CD

3

TCR

A

CD4 T cells Treg

CD8 T cells

NK cells

γδ T cells

Supplementary Figures

38

B

SSC

-A

CD45

SSC

-A

FSC-A

FSC

-W

FSC-A

SSC

-A

CD11b

Ly6

G

Ly6C

CD11b

F4/8

0

FSC

-W

FSC-A

FSC-A

SSC

-A

LPM

SPM

PMN-MDSC

Mo-

MDSC

PBS B16

CD8 T cells

IL17-A

IFN

-

Supplementary Figure 3: Gating strategies used for FACS analysis of A - lymphocytes and B -

myeloid-derived suppressor cell, small peritoneal macrophages (SPM) and large peritoneal

macrophages (LPM).

Supplementary Figure 4: Cytokine production by CD8 T cells in peritoneal exudates from

tumour-free and tumour-bearing mice, after 4h of stimulation with PMA/iono, in the presence

of Brefeldin A for the last 2h.

Supplementary Figure 5: A – Representative FACS plots in peritoneal exudates from B16-

injected mice treated with Gr-1 mAb (or PBS), 2 weeks post-tumour inoculation. Pre-gated on

CD45+ cells and macrophages (based on side scatter/forward scatter analysis). B – Frequency

of small peritoneal macrophages (SPM) in peritoneal exudates from tumour-bearing mice

treated with Gr-1 mAb (or PBS), at week 2 post-tumour inoculation.

A B

B16 αGr-1

CD11b

F4/8

0

B

Discussion

39

DISCUSSION

In this work we describe an inability of γδ T cells to accumulate and respond to intraperitoneal

B16 tumour due to a crosstalk between γδ T cells and a myeloid subset. We show, for the first

time, that this myeloid subset – polymorphonuclear myeloid derived suppressor cells (PMN-

MDSCs) - selectively suppresses a specific subset of γδ T cells: Vγ6+ IL-17 producers (Figure 22).

Furthermore, Vγ6 cells promote tumour growth, which unexpectedly reveals a beneficial effect

of PMN-MDSC in the tumour context. By contrast we showed that NK cells, CD8 and CD4 T

cells accumulate in response to B16 melanoma tumour challenge, and that NK and CD8 T cells

are able to upregulate cytotoxic molecules (perforin and granzyme B) and IFN-γ, respectively.

The mechanism that PMN-MDSC employ to selectively control the Vγ6 T cell response (but not

other lymphocyte subsets) to intraperitoneal B16 tumour is still to be determined.

Figure 22: Schematic representation of the proposed model in this thesis.

Here, we will first discuss the experimental limitations of this work. Secondly, the regulation of

γδ T cell responses will be addressed, as well as the role of the PMN-MDSC/ γδ T cell crosstalk

in tumour progression. Finally, the translation and implications of our findings, as well as

future perspectives, will be discussed.

CD8+

T cells

NK

cells

γδ T

cells

CD4+

T cells

CD8+

T cells

CD8+

T cells

CD4+

T cells

CD4+

T cells

NK

cells

NK

cells

GzmB Perforin

IFN

PMN

PMN PMN

PMN

PMN

PMN

PMN

Tumour

IL-17A

Discussion

40

1. Experimental limitations

The findings reported in this thesis were obtained by transplantation of a melanoma cell line

into the peritoneal cavity, which is a non-orthotopic and thus contrived model. Consequently,

we are currently investigating the possibility of validating the physiological relevance of the

PMN-MDSC/ γδ T cell crosstalk in an orthotopic model. Despite the striking physiological

differences between human cancers and transplantable, non-orthotopic mouse models used

to study them, studies in mice are often corroborated in humans. That is the case of Gao et al.

report in 2003, in which γδ T cells were shown to infiltrate subcutaneous B16 melanoma

lesions and provide large amounts of IFN-γ (Gao et al. 2003). Later, in 2012, a study in human

conducted by Cordova et al. reported that γδ T cells infiltrated malignant melanomas and

produced IFN-γ, as well as TNF- (Cordova et al. 2012). Also, Ma et al. showed that γδ17 T cells

induce the infiltration of MDSCs, in a transplantable hepatocellular carcinoma model (Ma et al.

2014). A few months later, Wu and colleagues showed a similar link between these

lymphocyte and myeloid subsets, in human colorectal cancer (Wu et al. 2014). So, although

transplantable tumour models are not ideal, their use is useful and some of the withdrawn

conclusions have been corroborated in studies conducted with human samples.

Besides the limitations of the in vivo model, we have faced other technical and feasibility

constrains. Performing in vitro assays with PMN-MDSCs and γδ T cells could be a valuable

approach to dissect the mechanism that the former employ to inhibit the latter. We have done

several attempts to perform these assays, in which we co-cultured γδ T cells with PMN-MDSCs

and evaluated proliferation, cell death and cytokine production. However, these assays have

never showed differences, which, we believe is due to the difficulty in working with MDSCs in

vitro. These immature and suppressive cells rapidly differentiate in vitro and lose their

suppressive features (Youn et al. 2012). To overcome this spontaneous maturation, we tried to

condition them with supernatant from B16 cell culture or tumour extract from the in vivo B16-

derived tumour. Still this was unable to keep MDSC suppressive/immature features, as we

observed major alterations in their shape, suggestive of maturation. Consequently, we decided

to concentrate our efforts on dissecting the in vivo dynamics of γδ T cell accumulation upon

PMN-MDSC ablation. While this suggested a systemic inhibition of Vγ6 T cells by PMN-MDSCs,

the underlying mechanism remains to be dissected.

On the other hand, we provided indirect evidence that IL-17-producing Vγ6 T cells display a

pro-tumour role in this model, given their selective accumulation and the similar phenotypes

of TCRδ-/- and IL-17-/- mice, upon anti-Gr-1 mAb treatment. Notwithstanding, to further

Discussion

41

demonstrate the role of IL-17+ Vγ6+ T cells the ideal approach would be to conditionally knock-

out IL-17 in γδ T cells, or to manipulate Vγ6+ T cells, either by depleting or adoptively

transferring them. However, it is not yet available a reliable mouse line expressing Cre

recombinase under the control of a γδ T cell specific promoter. Also, the lack of an antibody

that specifically recognizes Vγ6 TCR receptor chain prevents direct in vivo depletion of this

subset. We also envisaged a gain-of-function approach by adoptive transferring Vγ6 T cells and

assessing tumour growth. Several attempts have been made in our laboratory to adoptively

transfer these cells and even after in vitro activation/expansion they failed to engraft. This is

likely due to their very poor homeostatic expansion in vivo, a characteristic of CD27- γδ T cells

(Ribot et al. 2009).

The restricted development of Vγ6 T cells and γδ17 T cells to an embryonic wave (Haas et al.

2012) provides alternatives to generate mice that lack IL-17+ Vγ6 T cells. Bone marrow

chimeras, created with RAG-/- or TCRδ-/- recipient mice receiving bone marrow from IL-17-

sufficient (WT) donors would only be populated by γδ T cell subsets generated during adult life

(that is, Vγ1, Vγ4, and Vγ7 T cells). In addition, very few IL-17-producing γδ T cells would

emerge because these effector cells require the specification of an embryonic thymus to

develop (Haas et al. 2012). We plan to use this approach to elucidate the role of Vγ6+IL-17+ T

cells in the intraperitoneal B16 tumour model.

2. Regulation of γδ T cell responses

γδ T cells have been shown to be important contributors to tumour immunity (Girardi et al.

2001; Gao et al. 2003; Lança et al. 2013; Rei et al. 2014), responses to infection (D’Ombrain et

al. 2007; Sheridan et al. 2013) and autoimmunity (Cai et al. 2011; Sutton et al. 2009), however

regulation of γδ T cell responses is still a poorly understood process. This contrasts with the

large body of evidence for regulation of T cell responses, namely in the tumour context, by

MDSCs (Draghiciu et al. 2015) and Tregs (Nishikawa and Sakaguchi 2014).

Our laboratory has demonstrated that murine γδ T cells can be regulated by Tregs (Gonçalves-

Sousa et al. 2010). Tregs are able to suppress IFN-γ and IL-17 production and cytotoxicity in

vitro, as well as proliferation of naïve and malaria-activated γδ T cells in vivo. This inhibition

was shown to be partially dependent on GITR receptor signalling, as its blockade partially

recovered γδ T cell proliferation and cytokine production (Gonçalves-Sousa et al. 2010).

Additionally, human Tregs were also shown to control phosphoantigen-induced proliferation

of γδ T cells, but not other effector functions such as cytokine production or cytotoxicity

(Kunzmann et al. 2009).

Discussion

42

Moreover, mesenchymal stem cells were shown to be potent suppressors of in vitro Vγ9Vδ2 T

cell proliferation, cytokine production and cytolytic activity via prostaglandin E2 production

(Martinet et al. 2009; Martinet et al. 2010).

Effector γδ T cell responses, particularly against tumours, can also be controlled by γδ T cell

subsets that display regulatory features. In the mouse B16 melanoma model, Vγ1 T cells were

reported to suppress anti-tumour Vγ4 T cell responses (Hao et al. 2011). The protective role of

Vγ4 T cells was mediated by IFN-γ and perforin and promoted by the transcription factor

eomesodermin, whereas Vγ1 T cells were characterized by expression of GATA-3 and

production of IL-4. In fact, IL-4 production by Vγ1 T cells reduced the protective effect of Vγ4 T

cells via downregulation of IFN-γ, NKG2D and perforin (Hao et al. 2011). Furthermore, human

Vδ1+ T cells that infiltrated breast tumours were shown to inhibit proliferation of Vδ2+ T cells

(Peng et al. 2007), which could potentially mediate anti-tumour responses.

Furthermore, γδ T cell responses have been reported to be regulated by myeloid cells such as

monocytes and neutrophils, in humans. Neutrophil uptake of nitrogen-bisphosphonates, such

as zoledronate, was associated with suppression of Vγ9Vδ2 T cell proliferation, which was

overcome by targeting neutrophil-derived hydrogen peroxidase, serine proteases and arginase

activity (Kalyan et al. 2014). Also, ROS production by neutrophils was shown to inhibit (E)-1-

hydroxy-2-methylbut-2-enyl 4-diphosphate (HMBPP)-induced upregulation of CD25 and CD69,

production of IFN-γ and proliferation of Vγ9Vδ2 T cells (Sabbione et al. 2014).

We show in this thesis that the neutral role of γδ T cell in the intraperitoneal B16 tumour

model is due to PMN-MDSCs that selectively suppress γδ T cell accumulation and effector

functions. Thus, our work adds another important player to the regulation of γδ T cell

responses, particularly in the tumour context. The mechanisms that underlie this inhibition are

yet to be elucidated; however, in light of factors previously described to regulate γδ T cell

responses, it is plausible that IL-4, ROS, arginase and/or PGE2 may be directly or indirectly

implicated in γδ T cell inhibition by PMN-MDSCs.

3. Role of PMN-MDSC/ γδ T cell crosstalk in tumour progression

We have shown that upon Gr-1 mAb treatment, γδ T cells display a pathogenic role and so

does IL-17, in the intraperitoneal B16 model. Because tumour-associated γδ T cells, which are

mainly Vγ6+ (80-90%), increase IL-17 production, we assume that IL-17+ Vγ6+ T cells are

responsible for the pathogenic role of γδ T cells. However, we did not dissect the mechanism

by which these cells or IL-17 lead to an increased tumour growth upon Gr-1 mAb treatment.

Discussion

43

Several mechanisms could potentially underlie this phenomenon. First, as shown by our

laboratory, in an ovarian ID8 model, IL-17+ Vγ6 γδ T cells can promote recruitment of small

peritoneal macrophages (SPM: CD11b+F4/80int) that, in turn, lead to increased tumour

proliferation (Rei et al. 2014). However, in our model we did not observe an accumulation of

SPM upon Vγ6 accumulation (Supplementary Figure 5). Second, in human colorectal cancer, γδ

T cells were proposed to induce PMN-MDSC recruitment, proliferation and survival through

the production of IL-8, GM-CSF, IL-17 and TNF-(Wu et al. 2014) and in a mouse

hepatocellular carcinoma model, Vy4 T cells were the major source of IL-17 leading to

increased CXCL5 production by tumour cells which increased CXCR2-dependent MDSC

infiltration (Ma et al. 2014). However, in the intraperitoneal B16 tumour model, we only

revealed the pathogenic γδ T cell role upon MDSC depletion, and therefore this suppressive

subset cannot be downstream of γδ T cells in this model. Thirdly IL-17+ Vγ6 T cells may support

tumour growth through induction of angiogenesis and/ or promotion of tumour proliferation.

IL-17 induces pro-angiogenic factors such as prostaglandin E1, E2, macrophage inflammatory

protein-2, vascular endothelial growth factor and nitric oxide, by both tumour cells and

fibroblasts present in the tumour microenvironment. Consequently, IL-17 enhances tumour

neovascularization, a critical process for the sustained growth of solid tumours (Numasaki et

al. 2003). Besides promotion of angiogenesis, IL-17 can also lead to direct enhancement of

tumour growth. Wang et al. have shown that IL-17 stimulates IL-6 production by B16 and

MB49 (bladder) tumour cells in vitro. IL-6 induction, in turn, activates signal transducer and

activator of transcription 3 (STAT3) in both tumour and non-transformed cells that compose

the tumour microenvironment (Wang et al. 2009). Activation of STAT3 leads to upregulation of

proliferation- and survival-associated genes, such as myc, cyclin D1/D2 and survivin.

Furthermore, the IL-17-IL-6-STAT3 axis is also involved in increased angiogenesis and

immunosuppression (Yu, Kortylewski, and Pardoll 2007). Whether these are the critical (pro-

tumour) IL-17-induced mechanisms suppressed by PMN-MDSC in our model remains to be

established.

Because PMN-MDSCs target a potentially pathogenic subset, their role in this intraperitoneal

B16 tumour model is unexpectedly protective. MDSC protective roles have been described in

transplantation (Adeegbe et al. 2011; Luan et al. 2013), autoimmunity (Yin et al. 2010) and

materno-fetal tolerance (Köstlin, Kugel, and Spring 2014). However, studies showing protective

roles of MDSCs in cancer are scarce. In fact, there is one report by Centuori et al. that shows a

peculiar ability of PMN-MDSCs, isolated from models of lung and mammary carcinoma, to

suppress in vitro TGF-1-induced iTreg generation and to impair nTreg proliferation (Centuori

Discussion

44

et al. 2012). Contrary to the well-known ability of MDSCs to promote Treg expansion, this

feature of PMN-MDSCs may render them a protective subset in the tumour environment.

However, the authors did not assess the role of PMN-MDSC role in tumour progression in vivo.

In line with Centuori’s report we also observed a decrease in Treg frequency that coincided

with PMN-MDSC accumulation. This opens the possibility for in vivo inhibition of

differentiation and/or accumulation of Treg by PMN-MDSC in the peritoneal B16 tumour

model.

In conclusion, our work describes, for the first time, a PMN-MDSC/ γδ T cell crosstalk that is

unexpectedly protective for the host, and which may have important implications for cancer

immunotherapy.

4. Translation and implications of our findings

MDSCs are known to contribute to tumour immune escape by influencing both innate and

adaptive anti-tumour immune responses through inhibition of proliferation, activation,

migration or induction of apoptosis (Gabrilovich, Ostrand-Rosenberg, and Bronte 2012).

Hence, those features render MDSCs an attractive target for cancer immunotherapy (Waldron

et al. 2013). There are several strategies to target these cells, which include: prevention of

MDSC development; induction of MDSC differentiation into mature cells; blockade of MDSC

expansion and activation; and blockade of MDSC suppressive activity (Draghiciu et al. 2015).

Our study highlights the fact that γδ T cells are potential targets of PMN-MDSCs. In the

particular case of our peritoneal B16 tumour model, the crosstalk between suppressive MDSCs

and pathogenic γδ17 T cells is beneficial for the host. Thus, our findings raise the concern that

in cancers in which γδ17 T cell responses may be dormant, ablation of MDSC (numbers and/or

functions) may be counter-productive.

However, it is also possible that the crosstalk between PMN-MDSCs and γδ T cells leads to

inhibition of anti-tumour γδ T cell responses. In that case, and because the adoptive transfer of

γδ T cells are a promising approach for patients with several types of cancers, PMN-MDSCs

may limit the efficacy of this immunotherapy strategy. Hence, we propose that it is important

to assess the presence of MDSCs in patients assigned for adoptive γδ T cell transfer and, if

appropriate, to combine the therapy with depletion of the suppressive subset, in order to

achieve better clinical results.

Discussion

45

5. Future perspectives

In order to further consolidate our work, some relevant aspects need to be elucidated. We

need to unravel the molecular mediator(s) responsible for the suppression of γδ T cells by

PMN-MDSCs. Furthermore, it is of key importance to understand if our findings can be

validated in other experimental models and in human samples. For validation in other

experimental settings we favor the use of genetic models, because, by specifically controlling

timing and location of mutations, these models resemble sporadic human cancers more

accurately (Walrath et al. 2010).

One big study conducted with 248 renal patients showed that percentages of intratumour γδ T

cells were very low and did not correlate with any prognostic factor or survival. The authors

concluded that the role of γδ T cells in renal cancer is questionable (Inman et al. 2008). In light

of our results, these findings might be explained by the presence of MDSC, specifically PMN-

MDSC, which might target γδ T cells. To validate our findings in a renal cancer mouse model

TRACK (transgenic model of cancer of the kidney) can be used. These mice express a mutated,

constitutively active HIF1form in kidney proximal tubule cells and develop renal cell

carcinoma, with histological features similar to human samples (Fu et al. 2011).

It may also be interesting to study if PMN-MDSC may be responsible for inhibition of anti-

tumour γδ T cell subsets in models were the overall γδ T cell response is reported as

pathogenic. In those cases, which comprise breast (Ma et al. 2012; Peng et al. 2007; Coffelt et

al. 2015) and colorectal cancer (Wu et al. 2014), ablation of PMN-MDSC might unleash an anti-

tumour effect of γδ T cells that could potentially override their pathogenic role. To understand

whether that phenomenon can occur a recently described mouse model of metastatic breast

cancer (Doornebal et al. 2013) may be of great interest. In this model γδ17 T cells lead to

accumulation of PMN-MDSCs that suppress the anti-metastatic function of CD8 T cells (Coffelt

et al. 2015). However, the reverse relationship of γδ1 T cell suppression by PMN-MDSCs was

not addressed in this study, which we think may be an important investigation to extend our

findings.

We expect future research to clarify the physiological relevance of the crosstalk between

MDSCs and γδ T cells, and the potential of manipulating it towards improving cancer

immunotherapy.

46

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47

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