Arginase 2 as a metabolic immune checkpoint in anti-tumor immunity

Thesis

Reference

Arginase 2 as a metabolic immune checkpoint in anti-tumor immunity

MARTI LINDEZ, Adria-Arnau

Abstract

Arginine depletion, an essential amino acid for T cells, is a major immunosuppressive mechanism for anti-tumoral T cells. Despite extensive characterisation of extracellular arginine depletion by the arginase enzyme Arg1, the role of the more ancestral Arg2 isoform in immunity, and especially in anti-tumor immunity, remained unaddressed. Preclinical murine melanoma and colorectal carcinoma models showed that, while Arg2-overexpression in tumor cells impaired adaptive anti-tumor responses, germ-line and CD8+ T cell-specific Arg2 deletion enhanced anti-tumor immune responses, reducing tumor growth. Notably, combination of Arg2 deletion and PD-1 blockade synergistically improved single-immunotherapy effects. Concomitantly, we also engineered a new mouse strain (Arg2em1Wreith), a tool for further comprehension of Arg2 post-transcriptional regulation by the immunorelevant microRNA-155. In conjunction with incipient data on human ARG2 inhibition in T cells, this thesis proposes Arg2 as a new molecular target for the improvement of T cell-based immunotherapies, at the forefront of cancer treatments in modern medicine.

MARTI LINDEZ, Adria-Arnau. Arginase 2 as a metabolic immune checkpoint in anti-tumor immunity. Thèse de doctorat : Univ. Genève, 2019, no. Sc. Vie - Bioméd. 11

DOI : 10.13097/archive-ouverte/unige:118259 URN : urn:nbn:ch:unige-1182598

Available at:

http://archive-ouverte.unige.ch/unige:118259

Disclaimer: layout of this document may differ from the published version.

UNIVERSITÉ DE GENÈVE FACULTÉ DES SCIENCES Section de médecine fondamentale

Département de Pathologie et Immunologie Professeur Walter Reith

Arginase 2 as a Metabolic Immune Checkpoint in Anti-tumor Immunity

THÈSE

présentée aux Facultés de médecine et des sciences de l’Université de Genève pour obtenir le grade de Docteur ès sciences en sciences de la vie,

mention Sciences biomédicales par

Adrià-Arnau Martí i Líndez

de

Reus (Catalunya) Thèse N

11

GENÈVE

2019

A ma chère ISA

i. Acknowledgements

My most sincere, most profound and joyful thanks are for Isa. Gifting me this opportunity, celebrating the joy of life at every second, embracing me as her pupil, shining her strength everywhere, radiating an incommensurable courage, all these will always be precious memories in me. Your admirable fight against this fate serves to spark the seek for cures against this ignominious illness. Merci beaucoup, Isa. T’enyoro.

To Walter, my most sincere thanks. I am deeply grateful for this opportunity, for your increasing involvement after hard times, for your mentoring and, most importantly, for always being extremely helpful and positive when fostering this research. Thanks for being the cornerstone of this work.

Ah, sacré, Grégory! If you had a fan club, I would be its president! I am extremely grateful for all the wisdom you emanate, for the unlimited patience you had with me and for all the hilarious moments! I finally admit it, you were the best teacher.

Mark, it is now my turn to wholeheartedly thank you back! My applause still echoes since you graduated from your Master thesis: bravo Mark!

Queralt, Sylvian, Daichi, I would like to thank you from the bottom of my heart; starting a life in the lab and in Geneva was much funnier with you in our side: the lab misses your

“pitchiouness” a lot! Florian and Vishal, thank you guys for all those funny times in the lab.

Emmanuèlle, Ilke, Kerstin, Thibaut, Aurélie, Deborah, Laurent, Ilke, Louise thank you all for your individual grains of sand that made this pile bigger.

I would also like to especially thank Cécile and Jean-Pierre; thanks for the ginormous patience you had, for your excellent teaching of flow cytometry and for making me feel the platform like a second lab! Naturally, I need to thank all the invisible work the animal caretakers perform tirelessly every single day: thank you Anthony, Jenny, Laure, Sidonie, Pascale, Mylène, Séverine who are inadvertently at the basis of this research.

I would also like to thank Professor Jean-Claude Martinou and Professor Cristoph Hess for becoming part of my thesis advisory committee. I want to thank Professor Pedro Romero as well for becoming, together with the thesis advisory committee, part of this thesis’ jury.

Naturally, I would like to express my gratitude with our fantastic collaborators, Thomas, Roger, Nicolás; from whom I learnt really a lot; and also Pierre-Mehdi, Alessandra and Kerstin, and Professor Burkhard Becher for their excellent contributions. Last but not least, I would like to thank as well Professor Stéphanie Hugues and all her lab members,

especially Juan, Carla, Dale and Marion; thank you!

També voldria agraïr al Prof. Joven, especialment a en Raúl, a l’Anna i a l’Esther.

This adventure in Geneva also came with new friends and great PhD colleagues (like the magnificent “Team Awesome” with whom we organised a terrific PhD retreat in the Swiss alps), always keeping close to my mind the good old and missed friends in Catalunya; thank you all, Nico, Marion, Amy, Claire, Marta, Sunil, Byung Ho, Alex, Lingzi, Daniele, Hafner, Soner, Ebru, thank you for the mutual support!

Finalment resta agraïr als que sempre hi són, als de veritat. A l’Ausi, al meu germà més crack i admirat. A la millor i més sàvia àvia del món, la iaia que fa honor al seu nom, na Pilar.

I, pare, mare, us n’adoneu que tot això es irremeiable i imprescendiblement gràcies a vosaltres?

I bé, Núria a tu t’ho he d’agraïr absolutament tot i principalment, per ser l’alegria en la meva vida. Feliç de poder seguir admirant-te cada dia, creu-t’ho: aquesta tesi és també un xic teva.

ii. Abstract

Tumor-infiltrating lymphocytes (TILs) entering the hostile tumor microenvironment (TME) face numerous immunosuppressive barriers that help tumors to escape from immune control. Amongst different immunomodulatory mechanisms, tumors often exert strong competitive pressure for molecular nutrients, hence restricting available resources for TILs.

Amino acids are essential nutrients for lymphocytes, and their availability is more and more being regarded as a node of immunological control. In previous studies, we and others have demonstrated that L-Arginine is an essential amino acid for T cell responses and that repression of the arginine-metabolising enzyme Arginase 2 (Arg2) in dendritic cells has a critical role in establishing an arginine-rich microenvironment permissive for proliferation after T cell priming. However, the role of Arg2 in the context of anti-tumor immune responses has been largely unaddressed.

We therefore sought to determine whether Arg2-mediated L-arginine depletion has a relevant impact on anti-tumor immune responses. Using two murine cancer models of melanoma and colorectal carcinoma, we observed that Arg2-overexpressing tumors impair adaptive anti-tumor responses and present increased tumor growth. In contrast, Arg2^-/- hosts challenged with the same murine cancer models presented enhanced anti-tumor responses. In vivo killing assays, bone marrow transplantation and antibody-mediated depletion

experiments showed that CD8⁺ T cells are critical for the enhanced anti-tumor responses in Arg2^-/- mice. Moreover, adoptive transfer experiments of Arg2^-/- CD8⁺ T cells into tumor- bearing mice revealed that Arg2-deletion in T cells is a cell-intrinsic factor sufficient to enhance CD8⁺ T cell cytotoxic function in the tumor context. In vivo murine cancer models have further shown that upon anti-PD-1 treatment, the reinvigoration of adoptively-transferred Arg2-deficient CD8⁺ T cells rescues a highly efficient immune response and synergistically improves the effects of anti-PD-1 immunotherapy. These results suggest that Arg2 deletion in CD8⁺ T cells leads to redistribution of the metabolic flux of L-arginine away from Arg2 pathway, thereby allowing the arginine-dependent cytotoxic CD8⁺ T cells to become more efficient killers in the highly-demanding tumor microenvironment. This notion is further supported by additional results demonstrating that ARG2 inhibition in human T cells enhances their activation in vitro.

In parallel, we also describe the generation of a new Mus musculus strain named

Arg2^em1Wreith, a valuable tool for future studies aimed at a more precise comprehension of the regulation of Arg2 expression by the master regulator microRNA of the immune response, namely microRNA-155 (miR-155).

Finally, this work provides several lines of evidence supporting the potential role of Arginase 2 as a previously unsuspected molecular target of interest for the improvement of T cell-based immunotherapies, which are at the forefront of cancer treatments in modern medicine.

iii. Résumé

Les lymphocytes antitumoraux qui pénètrent dans l’hostile microenvironnement tumoral font face à de nombreux signaux immunosuppresseurs qui aident les tumeurs à échapper au contrôle immunitaire. Parmi les nombreux mécanismes immunomodulateurs, souvent les tumeurs exercent une forte pression sur les nutriments moléculaires, limitant ainsi les ressources disponibles pour les lymphocytes antitumoraux. Les acides aminés sont des nutriments essentiels pour les lymphocytes et leur disponibilité est de plus en plus considérée comme un nœud de contrôle immunologique. Dans des études précédentes, nous et d’autres auteurs avons démontré que la L-arginine est un acide aminé essentiel pour les réponses des cellules T et, que dans le cas des cellules dendritiques, la répression de l’enzyme métabolisant l’arginine, l’Arginase 2 (Arg2), joue un rôle essentiel dans l’établissement d’un

microenvironnement riche en arginine permissif pour la prolifération des lymphocytes T.

Cependant, le rôle de l’Arg2 dans le contexte des réponses immunitaires antitumorales n’a pas été formellement abordé.

Notre objectif était donc de déterminer si la déplétion en L-Arginine médiée par l’Arg2 avait un impact significatif sur les réponses immunitaires antitumorales. En utilisant des modèles murins de mélanome et de carcinome colorectal, nous avons observé que les tumeurs qui surexpriment Arg2 diminuaient les réponses antitumorales adaptatives et présentaient une croissance tumorale accrue. Au contraire, les hôtes Arg2^-/- injectés avec les mêmes modèles de cancer murin présentaient une réponse antitumorale améliorée. Des essais « in vivo killing » ultérieurs, des expériences de transplantation de moelle osseuse et de déplétion médié par des anticorps ont démontré que chez les souris Arg2^-/- les cellules T CD8⁺ jouent un rôle essentiel pour l'amélioration des réponses antitumorales. De plus, le transfert adoptif de lymphocytes T CD8⁺ Arg2^-/- chez des souris porteuses de tumeurs a révélé que la délétion de l’Arg2 dans les lymphocytes T CD8⁺ est un facteur intrinsèque et suffisant pour améliorer la fonction cytotoxique des lymphocytes T CD8⁺ dans le contexte antitumoral. D’autre part, des modèles murins in vivo de cancer ont aussi montré que, après traitement anti-PD-1, la

revigoration des lymphocytes T CD8⁺ déficients en Arg2 transférés par adoption est capable de sauver une réponse immunitaire très efficace et d'améliorer de manière synergique les effets de l'immunothérapie anti-PD-1 en monothérapie. Ces résultats suggèrent que la suppression de l'Arg2 dans les cellules T CD8⁺ entraîne une redistribution du flux

métabolique de la L-arginine, loin d’Arg2, permettant ainsi aux cellules T CD8⁺ cytotoxiques

(dépendantes de l'arginine) de devenir des tueurs plus efficaces dans le micro-environnement tumoral très immunosuppressif. Cette notion est également corroborée par des résultats supplémentaires qui démontrent que l'inhibition de l'ARG2 dans les cellules T humaines peut améliorer leur profil d'activation in vitro.

En parallèle, nous décrivons également la génération d’une nouvelle souche de Mus musculus appelée Arg2^em1Wreith, un outil précieux pour des études futures visant à une compréhension plus précise de la régulation de l’expression d’Arg2 par le microARN miR-155, le « master regulator » de la réponse immunitaire.

En autre, ce travail apporte des arguments en faveur de la notion que l’Arginase 2 peut devenir une cible moléculaire, jusque-là insoupçonnée, pour l’évolution des immunothérapies à base de cellules T, qui sont à la pointe des traitements anticancéreux en médecine moderne.

iv. Abbreviations

Å angstrom(s) ABH 2(S)-amino-6- boronohexanoic acid ADI arginine deiminase ADI-Peg pegylated ADI ANOVA analysis of variance APC antigen-presenting cell Arcsinh arc sinus data transformation

Arg1 arginase 1

Arg1-Peg pegylated Arg1 Arg2 arginase 2

Ass1 argininosuccinate synthase

ATP adenosine 5’-triphosphate B16-OVA chicken ovalbumin- expressing B16 cells

B6D2F1 first generation hybrid of a C57BL6/J and a DBA/2J crossing

Bcl‐2 B cell lymphoma 2 BEC S-(2-boronoethyl)-l- cysteine

BM bone marrow bp base pair(s)

BSA bovine serum albumin cAMP cyclic adenosine 5’- monophosphate

CAR T chimeric antigen receptor (T cell receptor) CAT cationic amino acid transporter

CBP CREB binding protein CD cluster of differentiation CD40L CD40 ligand CD62L CD62 ligand

cDC conventional dendritic cell CDK4 cyclin-dependent kinase 4

CDK6cyclin-dependent kinase 6

cDNA complementary DNA CFSE Carboxyfluorescein succinimidyl ester

cGy centigray

CRE cAMP response element CREB CRE binding protein CRISPR clustered regularly interspaced short palindromic repeats

crRNA CRISPR-targeting sequence

CTL cytotoxic T lymphocytes CTLA-4 cytotoxic T

Lymphocyte Antigen 4 CTV CellTrace^TM Violet DAMP danger-associated molecular patter

DC²¹¹⁴ dendritic cell line 2114 DCs dendritic cells

DFMO D,L-alpha- difluoromethylornithine dLN draining Lymph Node DMEM Dulbecco Modified Eagle’s Medium

DNA deoxyribonucleic acid DNaseI deoxyribonuclease I EDTA

ethylenediaminetetraacetic acid eIF2 eukaryotic Initiation Factor 2

eIF2 eIF2 alpha subunit ELISA enzyme-linked immunosorbent assay ERK5 extracellular-signal- regulated kinase 5

FACS fluorescence-activated cell sorting

FBS foetal bovine serum Fc receptor for Fc portion of immunoglobulins

FCS foetal calf serum FDR false discovery rate

g gram(s) G418 geneticin

GAPDH glyceraldehyde-3- phosphate dehydrogenase GCN2 general control nonderepressible 2

G-CSF granulocyte-colony stimulating factor

GEO Gene Expression Omnibus

GFP green fluorescent protein GM-CSF granulocyte

macrophage-colony stimulating factor

GO gene ontology

GSEAGene Set Enrichment Analysis

GZM granzyme

HBSS Hank's Balanced Salt SolutionHCC hepatocellular carcinoma

HDAC histone deacetylase HDR homology directed repair

HEV high endothelial venule HFFshuman foreskin

fibroblasts

HIF-2 hypoxia-inducible factor 2

HPLC high performance liquid chromatography

i.p. intraperitoneal i.v. intravenous

IC50 half maximal inhibitory concentration

IDO indoleamine 2,3- dioxygenase

IED immune-enhancing diet IFN interferon

IFN interferon alpha IFN interferon beta IFN interferon gamma

IgG immunoglobulin G IL interleukin

ILR interleukin receptor IRF-3 interferon regulatory factor 3

ITAM immunoreceptor tyrosine-based activation motif IUPAC International Union of Pure and Applied Chemistry kDa kiloDalton(s)

KEGG Kyoto Encyclopedia of Genes and Genomes

Ki inhibition constant L litre(s)

LFQ label-free quantification LN lymph node

LPS lipopolysaccharide mArg2 mouse Arg2 MDSC myeloid-derived suppressor cells

mg milligram MHC I major

histocompatibility complex class I

MHC II major

histocompatibility complex class II

MHC major histocompatibility complex

miR-155 microRNA-155 ml millilitre

mM millimolar

mRNA messenger RNA MS mass spectrometry mTOR mechanistic Target of Rapamycin

NaOH sodium hydroxide ND not determined

ndLN non-draining Lymph Node

NES normalised enrichment score

NFκB nuclear factor kappa- light-chain-enhancer of activated B cells

NK natural killer nm nanometer(s) nM nanomolar NO nitric oxide

NOHANω-hydroxy-l-arginine nor-NOHA Nω-hydroxy-nor- Arginine

Nos2 nitric oxide synthase 2 or iNOS

Nos3 nitric oxide synthase 3 or eNOS

nt nucleotide(s) OAT ornithine aminotransferase OD optical density

ODC ornithine decarboxylase ODN oligodeoxynucleotide OFP orange fluorescent protein OT encoding a TCR specific against an OVA peptide OT^tg carrier of the OVA peptide-specific TCR transgenic allele

OT-I TCR allele specific for OVA257-264

OT-II TCR allele specific for OVA323 339

OVA chicken ovalbumin OVA257-264 peptide derived from residues 257 to 264 of OVA OVA323 339 peptide derived from residues 323 to 339 of OVA OXPHOS oxidative

phosphorylation

PBMC peripheral blood mononuclear cell

PBS phosphate buffered saline PCR polymerase chain reaction PD-1 programmed cell death protein 1

pDC plasmacytoid dendritic cell

PD-L1 programmed death- ligand 1

PHA phytohaemagglutinin PMA phorbol myristate acetate

PPAR peroxisome proliferator- activated receptor

PRF1 perforin 1 PRR patter-recognition receptor

qRT-PCR quantitative real- time PCR

R receptor (e.g IL-2R)

Rag2recombination activating gene 2

RNA ribonucleic acid RPKMReads Per Kilobase Million

RPMI tissue culture medium developed in the Roswell Park Memorial Institute

rRNA ribosomal RNA RT room temperature s.c. subcutaneous SD standard deviation

SDS lauryl sulphate sodium salt SDS-PAGE SDS-

polyacrylamide gel electrophoresis

SEM standard error of the mean

sgRNA single-guide RNA SILAC Stable Isotope

Labelling by/with Amino acids in Cell culture

Slc7a5 Solute Carrier Family 7 Member 5

SLO secondary lymphoid organ

ssDNA single-strand DNA ssODN single-strand ODN Stat6 Signal transducer and activator of transcription 6 TAMs tumor-associated macrophages

TCR T cell receptor Tcm central memory T cell TE Tris-EDTA buffer Tem effector memory T cell TGFβ transforming growth factor beta

Th1 T helper 1 type Th2 T helper 2 type TILs tumor-infiltrating lymphocytes

TLR Toll-Like Receptor TME tumor microenvironment TNF tumor necrosis factor TNF tumor necrosis factor alpha

tracrRNA trans-activating crRNA

Treg regulatory T cell Tris tris(hydroxy- methyl)aminomethane tRNA transfer RNA

tSNE t-Distributed Stochastic Neighbor Embedding

U unit of catalytic activity UTR untranslated region

WT wildtype

y+ transporter solute carrier family 7 member 6 protein

 anti (as a prefix)

2m β2-microglobulin

g microgram(s)

l microlitre(s)

M micromolar

v. Contents

i. Acknowledgements ... i

ii. Abstract ... iii

iii. Résumé ... v

iv. Abbreviations ... vii

Chapter I - Introduction ... 14

1.1 The anti-tumor immune response ... 15

1.2 Arginine and arginases ... 26

1.3 Arginine and Arginase 2 in anti-tumor immunometabolism ... 40

1.4 New immunotherapeutic agents in cancer treatments ... 43

Chapter II - Results ... 46

2.1 Introduction ... 47

2.2 Arginase-2 serves as an immunometabolic checkpoint regulator for anti- tumor CD8⁺ T cells ... 48

Chapter III - Additional Results ... 85

3.1 Arginase 2 overexpression in DCs represses CD4⁺ and CD8⁺ T cell proliferation ... 87

3.2 Arg2 overexpression in melanoma dampens adaptive anti-tumor immune responses ... 88

3.3 In vivo priming of Arg2^-/- CD8⁺ T recapitulates their enhanced in vitro activation ... 93

3.4 Arg2 deletion does not confer protection against Toxoplasma gondii ... 94

3.5 Pharmacologic inhibition of Arginase 2 enhances in vitro human T cell activation ... 96

3.6 Generation of mice mutant for miR-155 seed sequence in Arg2 by CRISPR/Cas9 ... 97

Chapter IV - Materials and methods ... 100

Chapter V - Discussion ... 106

4.1 Arginase 2 expression during the priming phase limits T cell expansion ... 107

4.2 Overexpression of Arginase 2 promotes tumor growth ... 108

4.3 Arginase 2 deletion enhances CD8⁺ T cell function ... 109

4.4 Perspectives ... 114

Chapter VI - References ... 115

vi. List of Figures

Figure I-1. The cancer-immunity cyclic model depicting the major

steps on T cell-mediated anti-tumor immunity. ... 17 Figure I-2. T cell recirculation patterns throughout the organism. ... 18 Figure I-3. Classical cross-priming of a CD8⁺ T cell priming mediated

by an activated dendritic. ... 19 Figure I-4. Summary of events occurring during the CD8⁺ T cell

cytotoxic killing of a cognate target cell. ... 21 Figure I-5. Arginine frequency in proteins differs from the expected

random incorporation model. Arginine molecule

representation ... 28 Figure I-6. Projection of the three-dimensional surface structure of the

human Arginase 2 protein ... 30 Figure I-7. Schematic representation of the strategy used for the

generation of Arg2 knockout mice ... 31 Figure I-8. Schematic overview of the arginine metabolism mediated

by arginases and nitric oxide synthases. ... 32 Figure I-9. Summary of the competition between tumor and T cells

within the tumor. ... 44

Figure II-1. Deletion of Arg2 reduces tumor growth and increases

systemic arginine concentrations. ... 51 Figure II-2. Arg2^-/- mice control tumor growth more efficiently via

enhanced cytotoxic CD8⁺ T cell function. ... 53 Figure II-3. Arg2^-/- CD8⁺ T cells exhibit enhanced activation dynamics

and cytokine production. ... 56 Figure II-4. Activated Arg2^-/- CD8⁺ T cells exhibit faster and stronger

upregulation of key genes implicated in CD8⁺ T cell

function. ... 58 Figure II-5. Arg2 deletion in CD8⁺ T cells enhances their anti-tumor

function by increasing their persistence within tumors and

reducing exhaustion. ... 60 Figure II-6. Arg2^-/- CD8⁺ T cells are partially protected against an

immunosuppressive TME induced by overexpression of

Arginase 2 in tumor cells. ... 63 Figure II-7. Tumor growth is inhibited synergistically by PD-1

blockade and either germ-line or CD8⁺ T cell-intrinsic

deletion of Arg2. ... 65

Supplementary Figure II-1. Additional characterization of Arg2^-/-

mice. ... 77 Supplementary Figure II-2. Efficacy of T cell depletion in tumor-

bearing Arg2^-/- mice. ... 78 Supplementary Figure II-3. Deletion of Arg2 does not affect in vitro

proliferation of CD8⁺ T cells. ... 78 Supplementary Figure II-4. Transcriptome analysis of in vitro

activated WT and Arg2^-/- CD8⁺ T cells. ... 79 Supplementary Figure II-5. Analysis of mixed bone marrow chimeras

used as donors of WT and Arg2^-/- OT-I CD8⁺ T cells. ... 80 Supplementary Figure II-6. High-dimensional flow cytometry analysis

of lymphocyte populations in tumor-bearing mice. ... 81 Supplementary Table II-1. Histopathologic analyses of young and

aged Arg2-deficient mice. ... 82 Supplementary Table II-2. List of primers used for PCR or qRT-PCR. ... 83 Supplementary Table II-3. List of anti-mouse monoclonal antibodies

used for FACS analysis. ... 84

Figure III-1. Arginase 2 overexpression in dendritic cells represses

CD4⁺ and CD8⁺ T cell proliferation. ... 88 Figure III-2. Arginase 2 overexpression in tumor cells promotes tumor

growth by dampening adaptive anti-tumor immunity. ... 90 Figure III-3. Generation of Arg2^-/- B16-OVA cell lines by

CRISPR/Cas9 gene editing. ... 91 Figure III-4. Constitutive Arg2 expression is not essential for B16

tumor cells and does not confer them any growth. ... 92 Figure III-5. Cell-intrinsic deletion of Arg2 alters activated CD8⁺ T

cell phenotype in vivo. ... 93 Figure III-6. Arg2 deficiency does not protect C57BL6 mice against

virulent Toxoplasma gondii infections. ... 95 Figure III-7. Arginase inhibitors enhance the in vitro activation

responses of human CD4⁺ and CD8⁺ T cells. ... 97 Figure III-8. Generation of a new 3’ Arg2 UTR mutant mouse strain

bearing an irrelevant substitution of the miR-155 seed

sequence. ... 99

vii. List of Tables

Supplementary Table II-1. Histopathologic analyses of young and aged Arg2-

deficient mice. ... 82 Supplementary Table II-2. List of primers used for PCR or qRT-PCR. ... 83 Supplementary Table II-3. List of anti-mouse monoclonal antibodies used for

FACS analysis. ... 84

Chapter I - Introduction

1.1 The anti-tumor immune response

Framework

Mammals possess efficient and versatile immune systems that protect them against a wide range of insults, including viral and intracellular pathogen infections, as well as extracellular bacterial, fungal and parasitic infections. The functions of the immune system extend beyond mere clearance of infectious agents and, amongst others, also plays key roles in the control of aberrant cells, e.g. senescent cells or cancer cells. The incorporation of new functions into the immune system has required profound innovation in new cell lineages and molecular

mechanisms, to finally be able to adapt to, virtually, all possible insults. In such systems, both cellular and molecular components act in an orchestrated manner. Mirroring other essential systems, like morphogenesis, evolutionary forces have shaped mammalian immunity as a result of progressive accumulation of new components and refinement of existing ones.

In opposition to the homeostatic role of immunity, cancer is primarily defined as an aberrant and uncontrolled cell proliferation in neoplastic lesions. A capital effort to rationalise the

definition of the vast concept of cancer identified a finite number of properties which, combined, support the pathogenesis of this often-fatal disease. Namely, these signatures are: unremitting proliferative signalling, evasion from growth-supressing stimuli, resistance to programmed death pathways, telomeric immortality, angiogenesis induction, active stromal invasion and metastatic migration, metabolism derangements, and the most recently catalogued property, and focus of this research project, escape from immune control and the establishment of a cellular and humoral tumor-supportive microenvironment¹. The major driving force that sustains the genetic diversity underlying the appearance of these functions is genomic instability.

As a consequence of both the accumulation of different genetic alterations and the corruption of normal cellular regulatory processes², cancer cells frequently express neoantigens,

differentiation antigens or cancer testis antigens. These antigens constitute a body of molecules that significantly differ in quality and quantity from those antigens normally expressed in the healthy tissue. The dysregulated expression of these frequently abnormal proteins is generally followed by the loading of peptide sequences from protein antigens onto major

histocompatibility (MHC) class I (MHC I) molecules expressed at the surface of cancer cells.

Therefore, these cancer-specific peptide-MHC I complexes serve as a platform allowing CD8⁺ T cells to recognise and discriminate cancers cells³.

Even though spontaneous T cell responses are frequent in cancer patients and in animal models of cancer, these immune responses only provide protective immunity in an extremely rare number of patients. Nevertheless, it has also been proposed that immune surveillance, in conjunction with stromal factors, controls benign precursor lesions that appear to be extremely common⁴, thus expanding the vision that malignant lesions can be recognised by the immune response. Malignant cancers tend to clonally evolve and develop mechanisms that co-opt immune responses and subvert otherwise anti-tumor responses into pro-tumoral responses, ultimately allowing cancers to escape from immune surveillance and immune control. The work reported in this thesis is aimed at better understanding the involvement of the Arginase 2 protein in the subversion of anti-tumor immune responses.

An overview on anti-tumor immune responses

Our modern comprehension of cancer biology and immunobiology, coupled to milestone advances in oncology, have inspired efforts to rationalise the anti-tumor immune response as well. The following lines will describe a revised version of a commonly accepted model⁵,

proposed in 2013, that encompasses most of the events that are relevant to frame this dissertation (Figure I-1). The described model proposes a series of stepwise events that have to be initiated upon cancer recognition by the immune system, and allowed to proceed in a cyclic manner to iteratively expand in order to achieve cancer clearance.

In an initial step, proteins from cancer cells are released after tumor cell death (step 1) and, in a process known as immunogenic cell death, the immunogenic peptides released are captured by local dendritic cells (DCs) in an adjuvant context⁶. At this stage, the presence of signalling molecules like danger-associated molecular patterns (DAMPs) and inflammatory cytokines is essential to activate immunity. The uptake of immunogenic antigens is also crucial to bypass posterior mechanisms of peripheral tolerance. Therefore, adjuvant-activated DCs process the captured antigens and present, or cross-present, these cancer-specific peptides to CD8⁺ or CD4⁺ T cells, within the context of MHC I or MHC II (MHC class II) molecules, respectively (step 2).

After migrating to secondary and tertiary lymphoid structures, the antigen-loaded activated dendritic cells prime T cells and induce their activation, thus generating effector T cell responses against the presented cancer-specific antigens (step 3). In a series of molecular events described later, the activated T cells traffic to the tumor (step 4) and infiltrate the effector site, i.e. the tumor (step 5). Once in the effector site, cancer-specific T cells precisely recognise cancer cells via the specific interaction between their T cell receptor (TCR) and the cognate peptide-MHC I complex (step 6). After TCR-MHC I interaction, cytotoxic CD8⁺ T cells form polarised cytolytic

Figure I-1. The cancer-immunity cyclic model depicting the major steps on T cell-mediated anti-tumor immunity. The generation of immune responses against cancer cells can be regarded as a cyclic process which would ideally be self-propagating. Instead, tumors can interrupt this virtuous cycle at different steps, thus halting anti-tumor immunity. This cycle comprises seven major steps and each step is briefly described in the text.

In the experiments reported here, we have exploited the recognition of cancer cells by T cells thanks to forced expression of the chicken ovalbumin (OVA) protein as a surrogate cancer marker and the subsequent presentation of its derived OVA257–264 and OVA323-339 peptides by MHC I and MHC II molecules, respectively. Additionally, T cell responses were adjuvanted by supplementation in cell cultures or by in vivo injection of CpG-B 1826, a potent TLR9 agonist.

Complementarily, antigen-specific responses have been studied thanks to the use of the OVA peptide-specific OT-I and OT-II TCR alleles, whose protein products bind to OVA-derived peptides presented in the context of MHC I or MHC II molecules, respectively.

T cell recirculation, activation, migration and cytotoxicity

Adult mice contain billions of T cells, but it is estimated that as little as only a hundred of the pre-existing naïve T cells are specific for a given peptide–MHC complex^7,8. However, the immune synapses with their target and, in a series of molecular events, focus and activate their cytotoxic machinery towards the cancer cell (step 7). To reinitiate the cycle, the death of killed cells releases a new wave of tumor-associated antigens (step 1) and subsequent iterations of this cycle expand the anti-tumor response in intensity and breadth.

evolution of the immune system has developed secondary lymphoid organs (SLOs), such as the lymph nodes and spleen, that act both as antigen collecting organs and selective migration platforms that increase the likelihood of DC-T cell contact. This system is remarkably efficient, as it is estimated that the activation of virtually all naïve cognate T cells takes place within 3 days⁷. Underlying this efficient system, there is the unceasing recirculation of lymphocytes: in rats, it has been demonstrated that the entire replacement of all blood-borne lymphocytes that enter the subclavian vein can take place up to 11 times per day⁹.

Naïve T cells incessantly recirculate between the blood, SLOs and lymph¹⁰ (Figure I-2a).

Three main molecules control the rolling, activation and arrest mechanism that allow the selective entry of recirculating T cells into lymph nodes via the high endothelial venules:

CD62L, CCR7 and LFA1. Once in the lymphatic system, naïve T cells can recirculate to downstream lymph nodes via the central hierarchical architecture of the afferent-efferent lymphatic system (Figure I-2n). In the SLOs, T cells scan antigen-presenting cells (APCs), like dendritic cells, seeking their cognate antigen and, in the most likely case of not finding their cognate antigen, they egress via the efferent lymphatics until the thoracic duct, where they finally return to the blood ∼10–20 h later to begin a new recirculation cycle^11,12.

Figure I-2. T cell recirculation patterns throughout the organism. a. T cells generally recirculate through different tissues in the direction depicted here: circulating naïve T cells enter lymph nodes from the blood, circulate through the lymphatic system using efferent ducts to finally arrive to thoracic duct, where they return to the bloodstream. b. Blood-borne T cells access the lymphatic system nodes via the high endothelial venules (HEVs) thanks to the expression of homing molecules, like CD62L, that allow rolling, activation and arrest. Besides the entry via the HEV, T cells can also reach the lymph from non-lymphoid organs or after migration from afferent, more peripheral lymph nodes. Independently from the mode of lymph node entry used, the migration into the T cell zone is CCR7 dependent. Adapted¹⁸.

As mentioned above, the lymph nodes also serve as platforms to maximise cell-to-cell interactions. After entry into lymph nodes, T cells migrate to the T cell zone using chemotactic gradients dependent on CCR7 and its ligands CCL21 and CCL19. This compartmentalisation, together with an increase in T cell motility¹³, facilitates DC-T cell encounters, estimated to occur at a frequency of up to 500 T cell encounters per hour per DC¹⁴.

During the DC-T cell contact (Figure I-1), ligation of the peptide-MHC I complex with the TCR does not suffice to trigger immunogenic T cell activation¹⁵. In this way, T cells require not only information about the identity of the immunogenic signal (the antigen) but also require co- stimulatory signals that confirm the danger and the type of pathogen that the antigen represents.

Thus, besides the MHC I-TCR interaction that provides what is known as “signal 1”, the transmission of danger information, known as “signal 2” or co-stimulation, is also essential for mounting effective T cell responses (Figure I-3). Co-stimulatory signalling is mediated by the interaction of B7-1 and B7-2 proteins (also named CD80 and CD86), expressed by the APCs, with the CD28 protein, expressed by the T cells¹⁶. Importantly, CD28 co-stimulation provides additional signals required to avoid the entry of T cells into a non-functional state known as anergy, which is transcriptionally and metabolically stable and maintains T cell

hyporesponsiveness despite secondary ligations of the TCR in the presence of CD28 co- stimulation¹⁷.

Figure I-3. Classical cross-priming of a CD8⁺ T cell priming mediated by an activated dendritic. After immunogenic cell death of tumor cells, DAMPs released by tumor cells are detected by pattern-recognition receptors (PRRs) expressed by local dendritic cells, like Toll-like receptors (TLR). TLR ligands further activate DCs and stimulating their antigen presentation function by upregulating the expression of MHC molecules and co-stimulatory receptors like CD80 and CD86. In parallel, DCs capture extracellular antigens by distinct endocytic mechanisms not depicted here, and present antigen-derived in their MHC I complex. After migrating to the lymph node, DCs cross-present the MHC I-bound antigen to naïve CD8⁺ T cells along with co-stimulatory signals. Adapted^18,19.

Additional studies have demonstrated that other secondary co-stimulatory molecules can be expressed, like CD40L, as well as the existence and expression of other receptors-ligand pairs that counteract co-stimulation and dampen T cell activity, e.g. PD-1, Lag3, Tim3 and BTLA.

These receptors are known as co-inhibitory receptors or immune checkpoints. The Cytotoxic T Lymphocyte Antigen 4 (CTLA-4) is one the first discovered co-inhibitory receptors²⁰. CTLA-4 competitively binds to B 7‐1 a nd B7‐2 and thus displaces CD28 ligation, inhibiting IL‐2

production and cell cycle progression. Nowadays, CTLA-4 is regarded as an immune checkpoint intimately associated with the T cell activation phase occurring in the SLOs, where this co- inhibitory receptor has a crucial role in dampening unwanted T cell proliferation. In fact, the genetic deletion of Ctla4 in mice causes exacerbated lymphoproliferation and lethal autoimmune diseases^21,22.

In opposition to the lack of CD28 co-stimulation, certain immunologic contexts result in robust and sustained TCR, co-stimulatory and cytokine signaling²³. Pioneering work

demonstrated that in unresolving viral infections, T cells responding to antigens from chronic viral infections are significantly hyporesponsive. It was later hypothesised that the functional impairment was caused by the chronic stimulation, resulting in a hyporesponsive phenotype now termed “T cell exhaustion”²⁴. Exhausted T cells fail to proliferate efficiently, are not capable of secreting cytokines, nor to lyse target cells²⁵, and are characterized by the increased expression of co-inhibitory receptors like PD-1, LAG-3, Tim-3, and 2B4, which ultimately reinforce the dysfunctional phenotype and further suppress T cell activity²⁵.

In the case of productive TCR stimulation, the T cell engages into an activation process within minutes. T cell activation results in a transient upregulation of CCR7 and CD69 expression, a mechanism that serves to increase the dwell time within the supportive SLO

niches. This environment normally provides instructional cues, co-stimulation and cytokines that support extensive T cell proliferation²⁶. After a marked increase in size, T cells undergo rapid rounds of division that last for a few days. Two to three days later, a major proportion of the expanded population egresses from the SLOs to migrate to effector sites, via the lymphatics and ultimately the blood. Unlike plasma cells that can exert their effector functions distally, T cells, and especially CD8⁺ T cells, need to engage in direct contact with the cognate antigen-bearing cells in order to exert their pathogen or tumor control effector functions. In order to egress from the SLOs, effector T cells downregulate the expression of CD62L and CCR7 and upregulate the expression of non-lymphoid homing molecules. This ultimately results in the redirection of T cells towards non-lymphoid tissues instead of their re-entry into SLOs.

As CD8⁺ T cells are the main focus of this thesis, the following section will focus on the cytotoxic mechanisms that anti-tumoral CD8⁺ T cells use to kill cancer cells. Once in the tumor,

+

thanks to specific interactions between the TCR and peptide-loaded MHC I complexes, with the enhancing support of the CD8 co-receptor. TCR stimulation triggers a cascade of molecular events that result in the formation of a special surface of contact between the T cell and the cancer cell known as the cytolytic synapse (Figure I-4). Amongst these events, the CD8⁺ T cell polarises and recruits more TCRs into the cytolytic synapsee, to where it also directs the cytotoxicmolecular machinery employed to kill the target cell. The two main cytotoxic mechanisms include the expression of death ligands, like Fas ligand (FasL) and TNF-related apoptosis-inducing ligand (TRAIL)^27–29, and the granule exocytosis pathway^30,31.

Figure I-4. Summary of events occurring during the CD8⁺ T cell cytotoxic killing of a cognate target cell. Recognition of the target cell induces the formation of a transient conjugate between the CD8⁺ T cell and the target cell (a tumor cell in this case), followed by rapid polarisation and of its cytoskeleton of the T cell cytolytic synapse. Within a matter of minutes, the T cell moves both cytotoxic granules and TCR-transporting vesicles along the microtubules and delivers them to the plasma membrane at the synapse, and the cytotoxic granules are released into the secretory cleft formed between the two cells. Finally, the perforin and granzymes execute the death of the target cell. The cytotoxic CD8⁺ T cells only secretes a minority of the cytotoxic granules, being able to repeat multiple cycles of recognition, polarisation and cytolysis. Adapted^31,32.

The granule exocytosis pathway is rapidly executed and involves the directional mobilisation and release of specialized preformed granules towards the cytolytic synapse^30,31. The dominant constituents of such granules are the pore forming protein, perforin 1³³ (PRF1) and

granzymes^34,35 (GZMs). Once released in the synapse, PRF1 acts as a vehicle for the delivery of GZMs³³, either by forming pores in the target cell membrane^36,37 or by other mechanisms still under debate³⁸. Once released into the target cell cytosol, GZMs execute the killing of target cells by cleaving critical intracellular factors that control cell death and survival. Additionally, the death ligand pathway involves proteins expressed by the cytotoxic CD8⁺ T cell, like TNFα, FasL, and TRAIL, which can be either displayed at the T cell membrane or secreted. In the targetcell, these proteins bind to TNF superfamily receptors which are capable of triggering the apoptotic death of the target cell³⁹.

After the culmination of the expansion phase and resolution of inflammatory state, most activated T cells undergo a controlled death pathway of apoptosis that is programmed early on during the initial steps of activation, and demonstrated to be independent from antigen

clearance^40,41. Even so, a subset of T cells persists and differentiates into a memory T cell phenotype by downregulating much of the transcriptional programme of effector T cells, yet maintaining a remarkable ability to rapidly respond upon antigen re-encounter and to reactivate effector functions¹⁸. Memory T cells also survive in vivo for extremely long periods of time. This increased persistence is achieved thanks to an antigen-independent self-renewal stem cell-like slow division that is driven by the homeostatic cytokines IL-7 and IL-15⁴², as well as the

expression of different transcription factors such as Eomes^43–45, Id3^46,47, Runx3⁴⁸ and Runx2^49,50. In 1999, a pivotal study delineated memory T cells into two compartments: central and

effector memory T cells (Tcm cells and Tem cells, respectively)⁵¹. As differential characteristics, Tcm cells express lymphnode-homing molecules like CD62L and CCR7 and thus recirculate through SLOs, synthesise considerable amounts of IL-2 upon TCR stimulation and abundantly proliferate and differentiate into new effector T cells^52,53. In contrast, Tem cells express low or no levels of SLO-homing molecules and thus recirculate through non-lymphoid tissues,while maintaining heightened effector-like functions, i.e. superior cytolytic activity in CD8⁺ Tem cells, which allow a more rapid reaction and bypass the requirement of a period of re-differentiation.

Chronic viral infections and cancer result in sustained antigen exposure and/or inflammation that profoundly alter the differentiation programmes of T cells, and especially of memory T cells.

These alterations result in what is defined as “exhausted T cells”, which are phenotypically similar to anergic T cells as their performance is of limited efficacy⁵⁴. Although T cell

exhaustion was first described in chronic viral infection in mice^55,56, it has also been observed in humans during HIV and hepatitis C virus infections, as well as in cancer patients, as tumor lesions are a long-term source of antigen and inflammatory signals^25,57. T cell exhaustion usually manifests as a reshaping of transcriptional programmes and the expression of key transcription factors, an upregulation of multiple co-inhibitory receptors like PD-1, a hierarchical and progressive loss of effector T cell functions, metabolic alterations⁵⁸, and the impossibility to readopt a quiescent and antigen-independent homeostatic responsive state, i.e. to become bona fide memory T cells^25,57,59. Importantly, T cell exhaustion is a major factor preventing optimal control of tumors. Therefore, the therapeutic modulation of pathways overexpressed in exhausted T cells, like blockade of the PD-1/PD-L1 and/or CTLA-4 co-inhibitory axes, has proven to be effective to reverse this dysfunctional state and reinvigorate immune responses25,57,60,61.

Basic concepts of T cell metabolism

Naïve T cells remain in a quiescent state for their entire lifetime and barely display any detectable metabolic activity: otherwise, preserving clonality throughout T cell ontogeny would represent a dramatic challenge for the organism⁶². Upon productive activation, T cells

considerably enlarge during the first 24 hours and later engage in rapid and repeated mitotic cell cycles, duplicating as quickly as every 2-4 hours^63,64. During this clonal expansion phase, T cells become heavily biosynthetic as their activity escalates: DNA replication, protein synthesis and membrane synthesis, all these activities require considerable biosynthetic anabolic efforts to produce intermediates for cell growth⁶⁵. Mirroring a process first described in cancer cells, rapidly dividing cells engage in complete glycolysis^66–68. Thus, activated proliferating T cells ferment glucose into lactate to generate ATP, in a process known as “aerobic glycolysis” or the

“Warburg effect”, despite oxygen availability, which would allow them to obtain more ATP from complete oxidation of the glucose molecule. Although aerobic glycolysis is not essential for T cell activation, it is required for T cell effector functions⁶⁹ because glucose uptake and metabolisation are coupled to effector responses such as calcium flux and maintenance of lineage stability^70,71. A paradigmatic example is that when glycolysis rates are low, the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase (GAPDH) acts as a

ribonucleoprotein that binds to the 3’UTR of Ifng mRNA, inhibiting its translation. Conversely, during active glycolytic metabolism, GAPDH is instead devoted to glucose metabolism and Ifng mRNA is released from this regulation. Thus, from a metabolic perspective, glucose and its availability can affect the effector T cell function, besides acting as a mere energy source.

Because T cell activation is a metabolically demanding process, T cells require mechanisms to sense nutrient availability in their microenvironment and ensure that the conditions required to engage highly biosynthetic processes are met. Nutrient sensing mechanisms involving Akt and mechanistic target of rapamycin (mTOR) signalling have been demonstrated to be crucial for metabolic reprogramming during T cell activation⁷². T cell co-stimulation is normally provided in the nutrient-rich and highly supportive microenvironment of the SLOs, being also essential for the metabolic reprogramming of the T cell. CD28 signalling, which is exerted in part through the mTOR pathway, drives upregulation of the glycolysis machinery as well as the induction of amino acid and glucose transporters⁷³. On the contrary, the lack of CD28 co-stimulation and the induction of T cell anergy not only impede upregulation of the glycolytic program, but also prevent its subsequent upregulation upon TCR and CD28 restimulation, suggesting that anergic T cells are also metabolically anergic⁷⁴. Importantly, blockade of glucose, amino acids or

energy-sensing mechanisms also results in durable anergy induction, indicating that nutrient sensing acts as a safety mechanism to prevent activation in unfavourable nutrient conditions⁷⁴.

Functionally-quiescent naïve T cells mainly obtain their energy using the oxidative

phosphorylation pathway (OXPHOS) as their biosynthetic needs are minimal⁶⁵. However, in the case of memory T cells, the duality of their quiescent-poised state requires a state of slow but efficient metabolism for long-term persistence while, at the same time, being energetically primed for vigorous reactivation upon antigen re-encounter. Thus, memory T cells abandon aerobic glycolysis programs and shift towards the more energetically-efficient OXPHOS, extracting the energy from the oxidation of fatty acids⁷⁵, paralleled with the maintenance of an increased mitochondrial reserve that confers the ability to be bioenergetically poised for reactivation⁷⁶. Interestingly, memory T cells also use a partially-futile cycle, hypothesised to maintain long-term mitochondrial health⁷⁷, in which they oxidise glucose to make ATP,

subsequently use this ATP energy for fatty acid synthesis and finally oxidise the fatty acids via β−oxidation⁷⁸.

Mitochondria also play a vital role during T cell activation. In T cells, mitochondria are quantitatively, qualitatively and spatially regulated via mitochondrial biogenesis^79,80, mitochondrial fission and fusion⁸¹, and cytoskeletal positing relative to the immunologic synapse^82,83. Besides the cytosolic metabolisation of glucose, activated T cells not only use mitochondrial OXPHOS to oxidise energetic intermediates coming from energy sources like amino acids and fatty acids, i.e. acetyl-coA, but also use mitochondrial metabolism for different biosynthetic pathways and for the generation of reactive oxygen species^73,84–86. Unlike activated T cells, memory T cells have fused mitochondria, increased mitochondrial mass and better- organized cristae, accompanied by a greater spare respiratory capacity (SRC) that reflects the increased mitochondrial reserve discussed above^76,81, the Tcm subpopulation being the one with the greater mitochondrial respiratory capacity⁸⁷.

Metabolic immunosuppression in cancer

A growing body of evidence indicates that metabolic conditions in the tumor

microenvironment profoundly disturb the intracellular metabolism and function of tumor- infiltrating lymphocytes, thus playing a major role in shaping anticancer immune responses^88,89. The metabolic environment of the TME inhibits energetically-demanding functions crucial for infiltrating T cell function, such as cytokine production and cytotoxic activity⁷². Tumor cells are also avid consumers of glucose, the primary nutrient for effector T cells, resulting in limiting

concentrations of glucose in the TME⁷⁰. For instance, it has been demonstrated that limiting glucose prevents effective IFNγ production at the post-transcriptional level⁹⁰, converting

glucose competition into a major limiting factor for anti-tumor T cell function. Not only glucose is scarce; glutamine, arginine and tryptophan can be frequently found at limiting concentrations in

the TME. The scarcity of these metabolites driven, in part, by the prevailing tumor cell metabolism also limits T cell metabolism and consequently their effector functions^91–94. The specific role of arginine is extensively discussed below.

The availability of nutrients in the TME is not the only metabolic limiting factor for T cells.

Impairments in the cell-intrinsic metabolism and metabolic machinery can also repress tumor- infiltrating T cell function. For instance, tumor-infiltrating T cells display poor mitochondrial morphology, suppressed mitochondrial function, and decreased total mitochondrial mass⁹⁵. Remarkably, these mitochondrial impairments occur independently of the PD-1/PD-L1 suppressive axis, indicating a dependency on different mechanisms for this type of tumor-

induced immunosuppression. In parallel, defects in the nutrient sensing machinery itself can also be critical for tumor-infiltrating T cells: several groups have reported that the mTORC1 pathway is repressed in exhausted T cells, leading to glycolysis inhibition, autophagy induction,

decreased translation, as well as reduced mitochondrial activity^58,95.

Additionally, regulatory CD4⁺ T cells (Tregs) represent an outstanding example of cell- mediated immunosuppression within tumors, in conjunction with the inhibitory roles of

MDSCS and TAMs discussed below. In contrast to highly proliferative activated T cells, Tregs are less vulnerable to the scarcity and limited resources caused by metabolic competition within the TME. In contrast to effector CD8⁺ T cells, Tregs display some metabolic peculiarities that make the tumor microenvironment less stringent for them. Unlike for CD8⁺ T cells, limited glutamine and glucose availability favours Treg cell expansion, which fosters

immunosuppression^96,97. Another differential property of Tregs, unlike effector CD4⁺ T cells, is that they preferentially rely on lipid oxidation over glycolysis for their proliferation, thus circumventing the strong competition that tumors exert for glucose^98,99.

Many other metabolic pathways and metabolites have been reported to cause

immunosuppression in tumor-infiltrating T cells. In summary, increasing evidence underscores the notion that TIL hypometabolism and impaired TIL function is enforced either directly by metabolites or the lack thereof, or indirectly by the activity of other immunosuppressive cellular components of the TME that rely on distinct metabolic modules for their intratumoral survival.

1.2 Arginine and arginases Arginine

General introduction

As a chemical substance, arginine was first identified in 1886 in seedlings of etiolated lupine¹⁰⁰. It was later demonstrated to be a chemical constituent of proteins, being a product of casein hydrolysis¹⁰¹. Its amino acidic structure was determined in 1910 by Sørensen¹⁰². Only the L-arginine isomer is physiologically active, as is the case for most amino acids. For the sake of simplicity, laevorotatory amino acid isomers will be hereafter named without the L- prefix, e.g. arginine instead of L-arginine.

Arginine is one of the twenty proteinogenic α-amino acids that are encrypted in mRNA molecules, using the universal genetic code, for protein synthesis. As a free amino acid, arginine also serves as the substrate for different non-protein, nitrogen-containing compounds. In

ureotelic animals like mammals, a paramount biological function of free arginine is ammonia detoxification because arginine serves as a substrate for a key step in the urea cycle. Free arginine also serves as a substrate for non-protein biologically-active compounds such as nitric oxide (NO), polyamines, proline, glutamate, creatine and agmatine. As a consequence, arginine directly and indirectly participates in a plethora of biological processes such as vasodilation, calcium release, regeneration of adenosine triphosphate, neurotransmission, cell proliferation, and, most noticeably, immunity^103,104.

The molecular formula of arginine is C6H14N4O2 and the IUPAC nomenclature for arginine is (2~{S})-2-amino-5-(diaminomethylideneamino)pentanoic acid. Arginine has a molecular weight of 174.204 g/mol and at room temperature, purified arginine adopts an appearance of white odourless crystals, with a water solubility of 148.7 g/L. The pKa value of the guanidinium group in the arginine molecule is 13.8 ± 0.1¹⁰⁵, which implies that arginine side chains remain

protonated under near-neutral pH physiological conditions. Thus, in physiologic conditions the vast majority of arginine molecules are positively charged, acting as a basic amino acid.

Arginine endogenous synthesis

Arginine is classically classified as a semi-essential or conditionally-essential amino acid. In adult mammals, arginine is a non-essential amino acid as it can be synthesised endogenously in sufficient quantities^106–108. Nevertheless, in stress situations such as growth during infancy or during pregnancy, dietary arginine intake is required to fulfil organismal requirements103,109,110.

In mammals, the homeostasis of arginine concentrations in plasma is regulated by dietary arginine intake, protein turnover, arginine synthesis, metabolism and urea excretion.

The dietary arginine ingestion in typical Western diets is of 3-5 g/day and constitutes 5-7% of the total amino acid content^111,112. Orally-ingested arginine is absorbed in the jejunum and ileum of the small intestine via a specific amino acid transporter, the y⁺ transporter, which mediates uptake of the basic amino acids lysine, ornithine, histidine and arginine^113,114. However, only a fraction of the ingested arginine enters the systemic circulation in humans, pigs and rats:

approximately 40% of the dietary arginine is degraded in the small intestine during the first pass metabolism, or pre-systemic metabolism^115,116.

In contrast, endogenous arginine synthesis at the organismal level is greatly mediated by the intestinal-renal axis. In particular, citrulline is released into the blood from the small intestine, to be later converted into arginine in the proximal tubules of the kidney and finally excreted to the systemic circulation¹¹⁷. Although the liver also synthesises considerable amounts of arginine, the hepatic arginine synthesis contributes little or not at all to plasma arginine levels because the resulting arginine is completely dedicated to the urea cycle and ammonia detoxification¹¹⁸. Arginine as a regulation platform

Because the guanidinium group in the side chain of arginine displays a very high pKa, arginine probably is the only amino acid whose protonated nature can hardly be suppressed at physiological conditions. Hence, its side chain renders difficult the incorporation of this amino acid into the hydrophobic interior of proteins. It has therefore been hypothesised that this has resulted in an evolutionary selective pressure against the incorporation of arginine into proteins as proteins evolved into increasingly bigger and more complex proteins¹¹⁹.

In the genetic code, six codons dictate the incorporation of arginine into proteins. Although this relatively large number of codons would normally associate with a more frequent

incorporation of this amino acid into proteins, arginine is commonly found at a lower frequency than it might be expected according to the number codons coding for it in the genetic code¹²⁰. Noticeably, this discrepancy is the greatest amongst all proteinogenic amino acids (Figure I-5), whereas the expected frequency according to random distribution of codons in mRNAs and the frequency observed in mammalian protein sequences correlate quite well for all other

proteinogenic amino acids.