infiltrating lymphocytes in human breast cancer

Thèse présentée en vue de l’obtention du grade de Docteur en Sciences Agronomiques et Ingénierie Biologique

FTIR imaging : A potential new tool to characterize cancer cells and tumor

infiltrating lymphocytes in human breast cancer

Magali Verdonck

Laboratoire de Structure et Fonction des Membranes Biologiques Ecole Interfacultaire de Bioingénieurs - Université Libre de Bruxelles

JURY

Promoteur : Prof. Erik Goormaghtigh (SFMB, ULB, Belgique) Co-promoteur : Dr. Christos Sotiriou (BCTL, IJB, Belgique) Président : Prof. Vincent Raussens (SFMB, ULB, Belgique) Secrétaire : Prof. Michel Vandenbranden (SFMB, ULB, Belgique)

Dr. Karen Willard-Gallo (MIU, IJB, Belgique)

Prof. Bayden Wood (Chem., Monash, Australia)

Juin 2015 Prof. Philip Heraud (MISCL, Monash, Australia)

“If we knew what it was we were doing, it would not be called

research, would it?”

R EMERCIEMENTS

Probablement la partie la plus lue d’un manuscrit… J

La première personne que je voudrais remercier est mon promoteur de thèse, Erik. On peut dire que pour cette thèse, tu m’as vraiment laissé carte blanche. Je voudrais tout particulièrement te remercier pour la totale liberté que tu m’as laissée dans cette thèse, autant pour le choix du projet que dans la manière de le mener. Merci également de m’avoir donné de nombreuses responsabilités et de m’avoir fait confiance pour l’encadrement de plusieurs mémoires, ce sont des expériences extrêmement enrichissantes. Je voudrais également en profiter pour te remercier d’être un chef scientifiquement brillant tout en étant résolument humain.

I would also like to thank the members of my jury for taking the time to read this manuscript. Thank you for your advice and the interesting discussions we have had and will certainly have about this project. I would also like to thank the jury coming from far away and for taking the time to attend this thesis defense during their visit of Brussels.

De manière générale, je voudrais remercier les patientes, anonymes, qui ont été intégrées dans cette étude. Sans leur générosité et leur volonté de faire avancer la recherche, aucune étude n’aurait été possible.

Même si aujourd’hui c’est moi qui signe cette thèse, je voudrais préciser qu’il s’agit d’un travail d’équipe. Au cours de ces 4 années plusieurs personnes se sont investies dans ce travail. Je pense notamment à Julie, Amandine et Benjamin. Vous avez activement contribué à cette thèse en y mettant votre énergie et votre réflexion et cela a été un réel plaisir pour moi de partager ce projet avec vous. J’espère que vous garderez également un bon souvenir de votre passage au SFMB et de son ambiance légendaire.

Je voudrais également profiter de cette occasion pour remercier ma famille, qui m’a

toujours soutenue dans tous les projets que j’ai entrepris sur le plan privé et

professionnel. Maman, j’admire particulièrement ton esprit indépendant, ton amour pour

la liberté et ta passion dévorante pour la Science. Ce sont des valeurs que tu m’as

transmises et qui m’ont souvent aidée dans mes choix d’études et dans l’achèvement de

cette thèse. La Science s’est souvent invitée à notre table (pas toujours au plus grand

plaisir des convives à cause des détails peu ragoutants) et je suis contente que mon

parcours scientifique m’ait permis de mieux comprendre les discussions entre papa et toi

(bien qu’on compte encore les morts ;) ).

Marraine, ta force de caractère m’a toujours impressionnée, ta confiance et ton amour à toute épreuve m’ont souvent redonné la force d’entreprendre des projets et de les finaliser. En plus de m’avoir appris comment faire de belles présentations orales depuis les

‘persoonlijk project’ de ma 1

primaire (et oui, je lui dois tout) tu m’as aussi appris qu’il ne faut pas rêver mais vivre ses rêves. Tu es une oreille attentive, toujours à l’écoute pour partager mes petites découvertes, joies et déceptions parfois. Et même quand plus personne n’a le courage, que tout le monde a décroché de mes « lymphocytes tumoraux » tu restes toujours à mon écoute. De manière générale je voudrais vous remercier de votre soutien inconditionnel qui m’a permis d’avoir confiance en moi et grâce à cela, je ne crains pas d’entreprendre le moindre projet.

Je voudrais aussi particulièrement remercier ma sœur, Louis, Laura et Alexis, vos petits messages de soutien, repas-détente et (surtout) vos ‘grigris’ sans lesquels je ne serais jamais arrivée au bout de ma thèse m’ont toujours redonné sourire et courage. Merci Sœur pour tes innombrables conseils et maximes scientifiques (applicables dans la vie privée également) tels que ‘le mieux est l’ennemi du bien’ (toujours à acquérir), ‘la réflexion prime sur l’agitation’, ‘rien ne change tant qu’on ne change rien’, ‘ne jamais faire confiance’ (à la qualité de la solution de DMSO qui traîne sous la hotte par exemple), ‘un jour n’est pas l’autre’ (pour les problèmes de reproductibilités), ‘ne jamais désespérer’ (le plus important) et surtout : ‘la mer est bonne’ J. Merci pour votre soutien à toute épreuve et qui m’accompagne depuis les études dans tous les projets de ma vie.

Bien qu’une thèse puisse paraître un travail solitaire parfois, elle m’a cependant permis de

croiser le chemin de personnes exceptionnelles tant du point de vue scientifique

qu’humain. En poussant la porte du laboratoire de ‘Structure et Fonction des Membranes

Biologiques’, je ne m’attendais pas à y trouver une petite communauté pleine de vie,

vivant au rythme de la réussite de manips (et de petits soucis parfois) que seul un labo (de

l’ULB ?) peut rencontrer. Allison, tu fais partie sans nulle doute de ces belles découvertes,

en plus de tes conseils scientifiques toujours judicieux, je ne compte même plus le nombre

de papotes passionnantes que nous avons eu en Belgique et ailleurs. Je vous souhaite

beaucoup de bonheur à Jérôme et à toi pour la grande aventure qui vous attend. Merci

aussi pour ces nombreux petits repas à 6 sur le plat pays ou en Thaïlande avec Jérôme et

Alex, ce sont vraiment des souvenirs inoubliables. En parlant d’inoubliables, je me dois de

citer les nombreux congrès auxquels la bande infrarouge (IR) : Allison, Noémie, Alix,

Margarita, Marie, Joelle et Erik (et les nombreux autres personnes ‘de passage’) ont pris

part.

Merci Erik de m’avoir permis de participer à tous ces congrès extraordinaires. En plus de discussions scientifiques passionnantes, rythmées par des présentations de poster ou speech (pour la dose d’adrénaline) nous eûmes l’occasion de visiter des contrées lointaines et même exotiques. L’ambiance était à chaque fois au rendez-vous : rencontre avec Super Infrarouge, banquet de noces et paysages époustouflants en Thailande, visite de Berlin, le

‘drapeau’ d’Ali à Oxford, présentations de poster à Liège et à Namur avec une représentation en force du SFMB pour les journées doctorales, l’organisation des Bioengineer Research Days, la Floride et ses dessins animés en plein air (Let it go, let it gooo) et le moins exotique mais tout aussi sympathique IMPAKT à Bruxelles. Avec la bande IR, c’est certain, on en a fait des envieux ! Je suis certaine qu’il y en a même qui pensent qu’on a fait QUE ça. Heureusement, ce petit tas de feuilles est là pour leur prouver que, entre les congrès, on a quand même un peu bossé. Merci à tous les membres du SFMB pour ces magnifiques souvenirs et pour votre contribution à la bonne ambiance (de travail) !

Merci également à Alix, Caroline, Margarita, (et avant elles) Audrey et Emilie pour la bonne ambiance de bureau. En plus de votre bonne humeur, je retiendrai principalement les ‘tea-times’, décorations de Noël, Escherichou et les nombreux passages de Jean-Marie.

Je voudrais aussi réserver une place de choix dans ces remerciements à Noémie, binôme de toujours (9 ans d’études communes quand même). Nos thèses ‘jumelles’ n’ont pas toujours été faciles à gérer mais c’était bon d’avoir quelqu’un avec qui partager ses joies et ses peines. Je veux bien sur parler des manips, qui d’autre peut aussi bien comprendre comment ce modèle statistique, le microscope, le scanner, les marquages qui déconnent, les coupes histologiques qui se décollent, les mauvaises conversions PDF (et j’arrête ici la liste peu glorieuse des soucis rencontrés lors d’une thèse) puissent me mettre dans un état d’énervement tout à fait disproportionné pour ‘les autres’. Mais je fais aussi référence aux vacances au ski par exemple, aux autres moments de détente et aux congrès. Et pour clore en beauté, le dernier congrès en date : la Floride (même si on n’a pas pu aller voir les alligators ensemble). Un petit congrès juste pour nous deux avec plein d’hamburger et des soirées spéciales projection Disney…

Lors de cette thèse j’ai également eu l’occasion de rencontrer un autre univers

laborantin : le Molecular Immunology Unit (MIU) de Bordet qui a beaucoup contribué à ce

projet.

Merci Karen de m’avoir accueilli dans ton service les bras ouverts, de m’avoir permis de travailler dans ton labo et de m’avoir même prévu un bureau. Tu m’as vraiment intégré dans ton équipe, m’offrant même, comme à tout le service, un délicieux ‘home-made speculoos’ pour Noël. Merci pour tes judicieux conseils scientifiques et pour ton aide lors des nombreux labmeetings et présentations que j’ai faites à Bordet, elles ont énormément contribué à voir plus clair dans mon projet.

Une autre belle rencontre de cette thèse est sans nul doute Soizic. Je ne compte même plus tout ce que tu m’as appris : les manips (encore mille merci pour la fluo d’ailleurs), les conseils, les astuces, ton aide inconditionnelle tant dans mon projet que pour faire fonctionner ce Nanozoomer. Merci aussi à Ligia qui m’a toujours fermement défendue quand on m’a parfois accusée de ses maux ;). En plus d’être une scientifique redoutable avec le cœur sur la main, toujours prête à rendre service ou à essayer de trouver une solution pour ce projet qui n’était cependant pas le tien, j’ai eu l’occasion de faire la rencontre d’une personne vraiment exceptionnelle. Le souvenir de Jean-Marie et toi comme dernières personnes à ma pendaison de crémaillère restera dans ma mémoire ainsi que les repas, le petit ciné, etc. Je vous souhaite beaucoup de bonheur dans votre nouvelle maison !

Je tiens également à remercier tous les membres du MIU. Hugues, merci pour les longues journées passées au trieur (de cellules) et pour les nombreuses discussions passionnantes autour de la science, de l’éthique, des jeux de société ainsi qu’au sujet de systèmes d’étalement de cellules sur lames et la mise au point de divers prototypes de cytospin…

affaire à suivre. Merci aussi à Laurence, au Canada en ce moment, pour ton dynamisme et

pour m’avoir aidée dans la sélection des patientes. Je tiens également à remercier Anaïs

pour l’aide dans la recherche de blocs anapath’ et les marquages. Merci également à

Cinzia, Edoardo, Pushpamali, Jean-Nicolas, Céline, Luan, Laurence et Sylvia. Merci pour

votre aide, vos conseils, vos petits cadeaux et votre intérêt dans mon projet. Grâce à votre

implication dans votre travail, chacun de mes passages à Bordet me redonnait un coup de

motivation. Merci également à Christine qui m’a conseillé d’intégrer ce projet d’immuno

et à Ghizlane pour son aide précieuse au début de ce projet.

Je voudrais également remercier tous ceux qui n’arpentent pas les couloirs du labo mais qui ont énormément compté (peut-être plus qu’ils ne le croient) dans l’aboutissement de cette thèse. Je veux parler d’Olivia, Sven, Cécile (mes Nusseults d'amour), Marine, Furet (comprenez Hervé), Vanessa, Urocyon (et ici Alexis), Sandrine, Fred, Thomas, Geoff, Astrid, et encore bien d’autres. Les repas, soirées, sorties, apéros, ballades,… que vous avez partagés avec moi m’ont vraiment permis de continuer à rester motivée jusqu’au bout. Olivia, la figure du chapitre VI t’est tout spécialement dédiée, encore merci pour ton photo-merge-aide ! Je voudrais aussi remercier tous les membres de l’équipe de volley UAAE, votre participation à ma défense de thèse me touche beaucoup ainsi que vos messages, les innombrables fou-rires et l’ambiance inégalable que vous mettez m’ont vraiment énormément aidée. Seb je voudrais tout particulièrement te remercier pour toutes tes astuces et en profiter pour te nommer conseiller officiel de cette thèse. Merci à tous pour votre belle énergie communicative.

Merci aussi à toutes les personnes qui seront présentes lors de ma défense publique. Cela me touche énormément que vous ayez tous répondu présents à cette invitation et je sais déjà que je serai particulièrement émue de vous voir tous réunis pour me soutenir dans cette épreuve.

Enfin, et ne garde-t-on pas le meilleur pour la fin (?), je voudrais remercier celui avec lequel je partage ma vie depuis plus de 10 ans maintenant, c’est bien toi Ivan. Étant totalement passionnée et impliquée dans ma thèse, je me rends compte que cela n’a pas toujours dû être simple pour toi de t’adapter à mon humeur, fluctuante en fonction des manips. Les derniers mois de rédaction ont particulièrement dû être compliqués, mon humeur joviale et mon calme olympien n’étant pas vraiment au rendez-vous…mais tu m’as toujours soutenue, aidée, redonné le sourire, confiance, fait des petits plats pour me redonner de l’énergie … et ce depuis 10 ans maintenant. Cette période de thèse a aussi été pleine d’aventures pour nous deux, 2 déménagements, (2 dos cassés aussi), l’achat d’une maison, les magnifiques combo congrès-vacances, les superbes vacances tout court ! Et j’espère que beaucoup d’autres aventures nous attendent encore… Merci de toujours croire en moi, même dans les périodes de doutes et de me redonner confiance afin que je puisse toujours donner le meilleur de moi-même. Tu peux compter sur moi pour te rendre la pareille ;)

Pour mes parents, Pour ma famille,

Pour mes amis,

Pour mon amoureux

…Par amour pour la Science

Table of content

T ABLE OF CONTENTS

xxxx

C

I ...

G

... 1

1. Breast cancer ... 1

2. Tumor microenvironment ... 14

3. Infrared spectroscopy ... 21

R

... 32

C

II ... Aim of the thesis ... 39

C

III: ... Breast cancer and melanoma cell line identification by FTIR imaging after formalin-fixation and paraffin-embedding ... 41

Abstract ... 43

Introduction ... 44

Materials and methods ... 45

Results ... 48

Discussion ... 56

References ... 59

C

IV: ... Characterization of human breast cancer tissues by infrared imaging ... 63

Abstract ... 65

Introduction ... 66

Materials and methods ... 67

Results ... 70

Discussion ... 85

References ... 88

Supplemental data ... 92

Perspectives ... 94

Table of content

C

V: ...

Label-free phenotyping of peripheral blood lymphocytes by infrared imaging ... 103

Abstract ... 105

Introduction ... 106

Materials and Methods ... 107

Results ... 110

Discussion ... 119

References ... 122

Supplemental data ... 126

C

VI: ... Identification and characterization of lymphocyte subpopulations in secondary lymphoid organs by infrared imaging ... 127

Introduction ... 129

Materials and methods ... 130

Results ... 133

Discussion ... 142

References ... 145

Supplemental data ... 148

C

VII: ... Identification and characterization of tumor infiltrating lymphocytes in breast cancer tissue by infrared imaging ... 149

Abstract ... 151

Introduction ... 152

Materials and methods ... 153

Results ... 156

Discussion ... 166

References ... 171

Perspectives ... 174

References ... 177

C

VIII: ... G

,

... 179

References ... 184

Abbreviations

A BBREVIATION LIST

xxxx

BC Breast Cancer

DCIS Ductal Carcinoma In Situ HCA Hierarchical Cluster Analysis ECM ExtraCellular Matrix

EMT Epithelial-Mesenchymal Transition

ER Estrogen Receptor

FFPE Formalin-Fixed/ation Paraffin-Embedded/ing FPA Focal Plane Array

FTIR Fourier Transform InfraRed

GGI Genomic Grade Index

HER2 Human Epidermal Growth Factor Receptor 2

IF ImmunoFluorescence

IR InfraRed

LOOCV Leave-One-Out Cross-Validation (M)ANOVA (Multivariate) ANalysis Of VAriance MMP Matrix MetalloProteinase

NANT Non-Adjacent Non-Tumor PBL Peripheral Blood Lymphocyte PCA Principal Component Analysis

PLS-DA Partial Least Square Discriminant Analysis PR Progesterone Receptor

S/N Signal-to-Noise ratio

SLO Secondary Lymphoid Organ

TDLU Terminal Duct Lobular Unit

TIL Tumor Infiltrating Lymphocytes

TLS Tertiary Lymphoid Structure

TNBC Triple Negative Breast Cancer

Abstract

A BSTRACT

xxxx Breast cancer is the most common cancer in women. It is a highly heterogeneous disease in terms of histology, therapeutic response and patient outcomes. Early and accurate detection of breast cancer is crucial as the patient prognosis varies greatly depending on the diagnosis of the disease. Nonetheless current breast cancer classification methods fail to precisely sub-classify the disease, resulting in potential inadequate therapeutic management of patients and subsequent poor clinical outcomes. Substantial effort is therefore put in cancer research to develop methods and find new biomarkers efficiently identifying and characterizing breast tumor cells. Moreover it is now well-recognized that the intensive cross-talk between cancer cells and their microenvironment (including non- tumor cells) highly influences cancer progression. Recently, a growing body of clinical evidence reported the prognostic and predictive value associated with the presence of tumor infiltrating lymphocytes (TILs) in the microenvironment of breast tumors. Although the evaluation of TILs would be of great value for the management of patients and the development of new immunotherapies, it is currently not assessed in routine practice.

Furthermore Fourier transform infrared (FTIR) imaging has shown its usefulness to study a panel of human cancers. Infrared (IR) spectroscopy coupled to microscopy provides images composed of multiple spectra reflecting the biochemical composition and subtle modifications within biological samples. IR imaging therefore provides useful information to improve breast cancer identification and characterization. The ultimate aim of this thesis is to improve breast cancer diagnosis using FTIR imaging to better identify and characterize cancer cells and the tumor microenvironment of breast cancers. In a first step we carried out a feasibility study aiming at evaluating the impact of the sample fixation process on IR spectra. While spectra were undeniably influenced by this biochemical alteration, our results indicated that closely-related cell types were influenced similarly and could still be discriminated on the basis of their spectral features. We then demonstrated the capability of IR imaging to discriminate a tumor from a normal tissue environment based on the spectral features of tumor cells and the surrounding extracellular matrix. A particular focus was placed on the identification of lymphocyte spectral signatures of cells isolated from blood or present within secondary lymphoid organs such as tonsils. Our results revealed that IR imaging was sensitive enough to discriminate lymphocyte subpopulations and to identify a particular spectral signature that we assigned to lymphocyte activation. Finally we highlighted the potential value of IR imaging as complementary tool to identify and characterize TILs in breast tumor samples.

Altogether, our results suggest that IR imaging provides interesting and reliable

information to improve breast cancer characterization and to assess the immune

microenvironment of breast tumors.

Chapter I – Introduction 1

C ^HAPTER I

G ENERAL INTRODUCTION

xxxx

1. BREAST CANCER

1.1. Epidemiology, etiology and clinical aspects: general overview

Invasive breast carcinoma is the most common cancer in women worldwide.

According to

the latest available report of the World Health Organization,

breast cancer (BC) is the

second most frequently diagnosed cancer, with nearly 1.7 million new cases diagnosed in

2012 and contributes for more than 25% of the total number of new cancer cases diagnosed

in women.

The disease is most frequently detected in wealthy nations including

Australia, North America and Europe (Figure I.1A). The increasing risk of developing breast

cancer in more developed countries suggests an important role of the environment and

lifestyle as detailed further, but may also reflect aggressive screening programs.

Breast

cancer is the fifth most common cause of cancer death worldwide. Mortality rates vary

greatly across the world and, in contrary to incidence rates, are particularly high in low-

income countries in Africa and Latin America (Figure I.1B).

2 Chapter I - Introduction

Figure I.1: Breast cancer incidence (A) and mortality (B) worldwide. Cancer statistics provided in

the map come from GLOBOCAN, 2008.

Breast cancer mortality can be reduced if cases are detected and treated early.

Indeed prognosis for breast cancer patients is very good if the disease is detected at an early stage.

Since the 1990s, dramatic improvements in survival have been recorded in high- income countries, associated with the combined effect of massive mammography screening, adjuvant hormonal treatment and chemotherapy.

Because every breast cancer type requires a specific treatment regimen, a correct diagnosis is essential for providing adequate and effective therapy.

Breast cancer treatment encompasses multiple modalities such as surgery, radiotherapy and systemic therapy including hormone therapy, chemotherapy and immunotherapy.

Surgery is usually the first step in treating breast cancer. Excision of the entire tumor is essential since margin involvement is one of the strongest risk factors for local cancer recurrence.

In some cases, preoperative (neoadjuvant) systemic therapy may be used to reduce tumor size. Hormone therapy is effective only in estrogen receptor-positive (ER+) breast cancer and consists in tamoxifen or aromatase inhibitors (AIs) preferentially prescribed to pre- and postmenopausal women respectively. Chemotherapy has a greater role in hormone negative tumors and consists in a combination of drugs. Approximately 15%

of breast tumors show an amplification of the human epidermal growth factor receptor 2

(HER2 or ERBB2) gene.

For those specific cancers, monoclonal antibody therapy targeting

the HER2 receptor (Herceptin or trastuzumab) is prescribed.

Chapter I – Introduction 3 The origin of breast cancer is multifactorial and not totally elucidated. The most relevant risk factors involve predisposing genetic mutation, family history, atypical hyperplasia, reproductive factors, exposure to hormones, diet and age.

Breast cancer is a disease of affluent societies that have acquired the “Western lifestyle”, characterized by a high- calorie diet, rich in animal fat and proteins, combined to a lack of physical exercise.

Women with an early menarche, who remain nulliparous or have children with a late age at first delivery, are more likely to develop breast cancer. The lack of breast-feeding and infertility also appear as risk factors. Endogeneous and exogeneous hormones in particular patient subgroups were also related to a higher risk of developing breast cancer. Finally genetic factors such as mutations in suppressor genes including TP53 (Tumor suppressor Protein 53), BRCA1 and BRCA2 (Breast Cancer) increase the risk of developing the disease.

As will be pointed out throughout this thesis, breast cancer is a heterogeneous disease both biologically and clinically. This disease should be considered as a generic term for a group of diseases that affect the same organ and originate for the vast majority from the same anatomy structure, the terminal duct-lobular unit.

1.2. Breast anatomy

Breast tissue is a heterogeneous tissue that associates glandular and connective structures, as illustrated in Figure I.2A. This organ shows phenotypic plasticity, growing and changing cyclically under hormonal regulation.

The glandular tissue is composed of a network of ducts, allowing the transport of milk from

the acini to the nipple. From the nipple to the acini, 15 to 20 large ducts divide into

smaller ducts that end in mammary lobules. Each lobule is composed of approximately 20

small acini. Like ducts, each acinus is double layered; the internal part comprises a single

layer of cuboidal epithelial cells that lines the lumen and ensures the synthesis and

secretion of milk; more deeply, an external layer of myoepithelial cells lines the basal

membrane. The association of the terminal duct with the lobule is called terminal duct

lobular unit (TDLU, Figure I.2B).

4 Chapter I - Introduction

Ductal carcinoma in situ (DCIS), the major precursor to invasive breast carcinoma as detailed further, originates from the terminal duct lobular unit.

Figure I.2: Normal breast anatomy. A. Breast cross-section of the mammary gland depicting the

mammary gland; chestwall (1), pectoralis muscle (2), lobules (3), nipple (4), areola (5), milk duct (6), fatty tissue (7) and skin (8).

duct lobular unit (TDLU), Magnitude 50x.

Glandular structures are surrounded by connective tissue, mainly composed of fibrous and

adipose tissues, as well as nerves, lymphatic and blood vessels which supply nutrition and

provide support. The fibrous tissue is mainly composed of extracellular matrix (ECM),

mostly constituted of collagen, elastin and proteoglycans. The ECM is synthesized by

fibroblasts.

The inner part of blood vessels, called intima, is composed of an endothelial

cell monolayer lining a thin connective tissue layer. The intima is surrounded by the

media, composed of muscle fibers and extracellular compounds such as elastin and

collagen fibrils.

The blood vessel and lymphatic networks play an important role in the

metastatic process.

The connective tissue also hosts some exogenous elements that are

part of the immune system, such as lymphocytes.

Chapter I – Introduction 5

1.3. Breast cancer development: from in situ to invasive carcinoma

During the development of tumors, cells acquire a multitude of biological capabilities that drive their progression from a normal to a cancer state. In order to set up an organizing principle for rationalizing the complexity of tumors, Hanahan and Weinberg listed six hallmarks of tumor cells. These hallmarks include sustaining proliferative signaling, evading growth suppressors, resisting cell death, enabling replicative immortality, inducing angiogenesis, and activating invasion and metastasis.

The acquisition of those capabilities requires two additional hallmarks including genome instability and tumor-promoting inflammation. Recently, two emerging hallmarks have been added to the list, namely reprogramming cellular metabolism and escaping immune destruction.

For the vast majority of breast cancers, the capabilities listed above are acquired by the epithelial cells of the TDLU. About 95% of malignant breast tumors are therefore called

‘carcinomas’, indicating that the tumor originates from the epithelial surface of ducts and lobules. Sarcomas, originating in the connective tissue, account for fewer than 1% of all breast cancers.

The development of breast cancer includes two consecutive phases; the in situ and invasive phase (Figure I.3). The former is a malignant proliferation of epithelial cells originating from the TDLU within the duct system without evidence of stromal invasion.

Depending on the cytology and location of the proliferation, two types of in situ

carcinomas are distinguished: lobular carcinoma in situ (LCIS) and ductal carcinoma in situ

(DCIS).

The vast majority of in situ carcinomas are DCIS which is currently

considered as a biologically and genetically heterogeneous group of lesions.

If

untreated, 40% of these in situ lesions progress into invasive disease.

Invasive breast

carcinoma is defined as a malignant invasive epithelial lesion of the breast, derived from

the TDLU.

Progression from the in situ to the invasive state is histologically characterized

by a disruption of the basal membrane allowing tumor cells to spread out into the stromal

environment. Basal membrane deterioration and subsequent disruption results from

complex phenotypic alterations and interactions involving tumor cells, myoepithelial cells

and the tumor microenvironment, including fibroblasts, stromal ECM, blood vessels and

immune cells.

The tumor microenvironment plays an important role in the

progression of cancer, as explained in further sections.

6 Chapter I - Introduction

Figure I.3:

Breast cancer development: progression from in situ to invasive breast cancer.

Schematic (top) and H&E stained tissue sections (bottom) illustrating the different stages in cancer

progression. A. Phenotypically normal milk duct. B. Ductal carcinoma in situ showing an intraductal

neoplastic proliferation of epithelial cells, separated from the breast stroma by an intact layer of

basement membrane.

into the vascular system causing metastasis. Figure adapted from Cichon et al., 2010

(top)

associated with tissue scans recorded during the thesis (bottom).

Chapter I – Introduction 7

1.4. Breast cancer classification and related challenges

The current breast tumor classification methods attempt to reflect the complexity and heterogeneity of breast cancer. Breast cancer classification aims at determining the prognostic and selecting the most suitable treatment for each patient. The present section indicates the most frequently used prognostic and predictive factors for breast cancer and indicates some emerging trends. The disease is classified on the basis of a combination of those factors rather than on a single feature to provide the best patient management.

One of the prognostic factors used in clinical practice is the Nottingham Prognostic Index (NPI). The clinical value of prognostic factors is mainly to identify patients with a poor prognosis that should therefore benefit from aggressive therapies and patients who should not undergo aggressive adjuvant treatments (Figure I.4). The NPI is based on three strong and independent prognostic factors: tumor size, stage and histological grade using the following formula: NPI score = Stage + Histological grade + (Tumor size x 0.2). Other prognostic indexes have emerged to further assist physicians in the treatment decision- making process, such as Adjuvant! Online, the most widely used tool nowadays.

Figure I.4: Relationship between the Nottingham Prognostic Index (NPI) and the overall survival in

3731 patients. EPG, Excellent Prognostic Group; GPG, Good Prognostic Group; MPGI and MPGII,

Moderate Prognostic Group 1 and 2 respectively; PPG, Poor Prognostic Group.

8 Chapter I - Introduction 1.4.1. Tumor size

In the NPI, the tumor size is not the most powerful parameter in estimating the patient prognosis. Although tumor size is not the most important prognostic factor, this parameter is clearly associated with a lower survival rate, as illustrated in Figure I.5.

Figure I.5: Relationship between tumor size and overall survival in 3731 patients.²⁹

1.4.2. Stage

The most widely used system for staging breast tumors is the TNM system, published by the

American Joint Committee on Cancer (AJCC)/Union for International Cancer Control

(UICC). This system takes into account the extent of the primary tumor (T) and the

invasion of the regional lymph nodes (N) and distant metastatic sites (M). The TNM scores

are combined to create five stages: 0, I, II, III and IV that summarize the extent of the

disease. The status of the axillary lymph node is the most important single prognostic

factor for almost all breast carcinomas.

Chapter I – Introduction 9 1.4.3. Histological grade

Invasive carcinomas are routinely classified according to histological grade, which reflects the degree of differentiation of tumor tissue. The histological grade assessment, called Nottingham Grading System (NGS), relies on three tumor characteristics: glandular/tubular differentiation, nuclear pleomorphism and mitotic counts. Practically, on the basis of visual inspection of an H&E stained tissue section, pathologists assign a score between 1 and 3 to each of the three components, as indicated in Table I.1. Values are then added together to obtain a final overall score that is assigned to a grade (bottom, Table I.1).

Numerous studies have demonstrated a significant association between histological grade and overall patient survival, underlining the relevance of this powerful prognostic factor.

Table I.1: Semi-quantitative method for assessing histological grade in breast tumors. Adapted

from Ellis et al., 2012 in WHO Classification of Tumours of the Breast.

Due to important improvement of the histological grading method, incorrect classification

and confusion between grade 1 and 3 is very rare. However categorization of grade 2

tumors, representing a substantial percentage of all tumors (about 42%), has the lowest

degree of concordance and is not informative for making clinical-decision.

Recent

molecular profiling studies gave new insights into histological grading. Numerous studies

suggested that grade 1 and 3 breast tumors are probably different diseases characterized

by distinct molecular origins, pathogenesis and behavior.

10 Chapter I - Introduction

The Genomic Grade Index (GGI) is a prognostic signature, introduced by Sotiriou et al. in 2006,

that classifies histological grade 1 and 3 tumors into Gene expression Grade (GG) 1 and 3 respectively, but interestingly also histological grade 2 tumors into GG1-like and GG3-like tumors according to the expression profile of 97 genes.

Analysis of patients with histological grade (HG) 2 by GGI revealed the co-existence of two patient subsets within the group; GG1-like patients, associated with a low-recurrence risk and GG3-like patients, associated with a high-recurrence risk, as illustrated in Figure I.6.

Recent studies suggest that the GGI prognostic signature, besides assessing breast cancer histological grade, also indicates favorable response to tamoxifen treatment in the case of ER+ tumors.

Figure I.6: Analysis of patients with HG2 tumors by gene expression grade (GG). The 217 patients

with HG2 were separated into low- and high-recurrence risk subsets by GG as GG1 (green) and GG3

(red) respectively. Figure from Sotiriou et al. 2006

Chapter I – Introduction 11 1.4.4. Hormone receptors

Three hormonal molecular biomarkers are used in routine practice to classify invasive breast cancer: estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2 (HER2). Those three receptors are prognostic and predictive biomarkers, being targets and/or indicators of effective therapies against breast cancer.

ER is a nuclear transcription factor that stimulates the growth and proliferation of normal breast epithelial cells when activated by the hormone estrogen. A majority of breast tumors, about 80%, express the nuclear ER with a range of <1% to 100%. Numerous studies including large randomized trials have demonstrated that ER is a strong predictive factor for response to hormonal therapies which target directly (tamoxifen) or indirectly (aromatase inhibitors) the receptor. The former binds to the receptor, blocking estrogen- stimulated growth, while the latter suppresses the production of estrogen.

PR expression is also assessed routinely in invasive breast cancer. Expression of PR is regulated by the ER expression. An overexpression of PR thus indicates that the estrogen- ER pathway is intact and functional. High expression levels of PR are directly correlated with high expression levels of ER and suggest an increased response rate to hormonal therapy.

The HER2 gene (standard nomenclature, ERBB2) is located on the chromosome 17 and encodes a growth factor receptor on the surface of breast epithelial cells. The gene and associated protein expression is amplified in approximately 15% of breast cancers. Recent studies have demonstrated that patients with HER2-positive tumors respond better to therapies targeting specifically the HER2 protein, such as trastuzumab and lapatinib.

Nowadays receptor status is mainly assessed by immunohistochemistry performed on formalin-fixed paraffin-embedded (FFPE) histological sections. Stained slides are evaluated microscopically to determine the proportion and intensity of positive cells.

Immunohistochemistry techniques induce irreversible alterations of the biological tissue

and the number of receptors detected can vary depending on the tissue fixation procedure

and delay.

12 Chapter I - Introduction 1.4.5. Histological type

Unlike histological grade, histological type is based on the morphological appearance of the tumor growth pattern. According to the World Health Organization (WHO), invasive breast carcinomas comprise 20 distinct histological types. Prognosis and treatment vary widely among histological types.

Invasive breast carcinoma of no special type (NST), also called invasive carcinoma not otherwise specified (NOS), represents the vast majority of invasive breast carcinomas (between 60 and 75% of cases). It is a particularly heterogeneous group of tumors that fail to exhibit sufficient characteristics to achieve classification as a specific histological type. The role of histological typing is therefore limited in the clinical management of breast cancer.

1.4.6. Molecular subtypes and gene expression profiling: new classification trends

There is a growing interest in the utilization of novel classification methods allowing simultaneously analyzing multiple gene or protein expression profiles. This new approach allows to sub-classify breast cancer and establish molecular-based prognostic and predictive “signatures”.

Gene expression array analyses combined to hierarchical cluster analyses revealed the existence of distinct “intrinsic” molecular subtypes of breast cancer. The development of PAM 50 (Prediction Analysis of Microarray 50-gene set) a 50-gene set allows classifying the 20 breast cancer histological types in 4 intrinsic molecular subtypes: luminal A, luminal B, HER2-enriched and basal-like, characterized by different gene expression profiles. Table I.2 indicates the main features of each molecular subtype.

Table I.2: Common characteristics of breast cancer molecular subtypes. Summarized from Weigelt

et al. 2010,

Prat and Perou 2011

and Ades et al. 2014.

Chapter I – Introduction 13 Molecular subtypes vary according to their genetic properties but show also distinct clinical characteristics as illustrated in the Kaplan-Meier curves in Figure I.7.

Figure I.7: Relationship between breast cancer molecular subtypes and patient survival (relapse-

free survival and overall survival). Claudin-low is an emerging molecular subtype. Figure from Prat and Perou, 2011.

Other gene signatures were also recently set up to improve breast cancer classification. A 70-gene prognosis signature, requiring fresh or frozen samples including > 30% of tumor- cell content, classifies tumors into ‘good’ or ‘poor’ prognosis. A 21-gene recurrence score, that can be applied on RNA extracted from FFPE tissue samples, classifies tumors into three categories: low, intermediate and high relapse risk at 10 years.

Recently a myriad of multi-gene classifiers were developed including EndoPredict (EP), Breast Cancer Index (BCI), MammaPrint, Oncotype DX and PAM 50 which have shown to be effective prognostic and predictive tools in breast cancer. More precisely those genomic expression tests are effective in predicting post-surgery local recurrence-free survival and/or determining the benefits of adjuvant endocrine therapy and chemotherapy.

Ongoing studies attempt to set up breast cancer classification methods that allow early

and accurate diagnosis of this heterogeneous disease, a cornerstone to achieve adequate

and personalized patient management. Next generation breast cancer classification will

thus probably rely on more global methods, assessing the genome and proteome of tumor

cells. As detailed further, infrared spectroscopy could therefore provide interesting

information to contribute to the improvement of breast cancer classifications.

14 Chapter I - Introduction

2. TUMOR MICROENVIRONMENT 2.1. General overview

Although breast cancer is currently exclusively characterized on the basis of tumor epithelial cell features, it is now well recognized that the tumor microenvironment plays an important role in cancer progression. As mentioned previously, an intense cross-talk between tumor cells and the surrounding cell types takes place at the tumor site; tumors can therefore be considered as complex tissues of interacting cells. The tumor microenvironment undergoes dramatic and complex changes due to and responsible of cancer progression; affecting cancer cells, cancer-associated fibroblasts, immune cells, endothelial cells (angiogenesis) and the stromal extracellular matrix (ECM). In this thesis we focused on the immune microenvironment of breast cancer and, to a lesser extent, on the stromal ECM of tumors. This section will therefore introduce only those two aspects of the tumor microenvironment, which includes a huge number of cell interactions. Figure I.8 illustrates a schematic overview of the tumor microenvironment and the associated signaling pathways.

Figure I.8: The tumor microenvironment. A. Schematic representation of the tumor

microenvironment depicting the distinct cell types contributing to tumor growth and progression.

B. Illustration of some signaling interactions in the tumor microenvironment during cancer

progression. Figure adapted from Hanahan and Weinberg, 2011.

Chapter I – Introduction 15 The stroma includes extracellular and cellular tissue network which interact with cancer cells.

The stroma undergoes important modifications in the presence of cancer cells to become the so-called ‘reactive’ stroma, different from the normal stroma.

An obvious influence of the stroma on the tumor during tumorigenesis is the induction of epithelial-mesenchymal transition (EMT) in cancer cells. During EMT, epithelial cell-cell contact characteristics are lost and the mesenchymal phenotype is acquired, allowing cancer cells to invade the stroma and to disseminate leading towards metastasis. Yet the underlying phenomena that are responsible of the EMT transformation are still not fully understood. A growing body of evidence suggests that cancer-associated fibroblasts (CAFs), also called myofibroblasts and identifiable by their high expression of α-smooth muscle actin stress fibers (α-SMA), initiate and enhance invasiveness by secretion of several pro- carcinogenic growth factors such as transforming growth factor β (TGF β), hepatocyte growth factor (HGF), platelet-derived growth factor (PDGF), insulin-like growth factors and granulocyte macrophage-colony stimulating factors (GM-CSF) to name but some of them and matrix metalloproteinases (MMP) such as MT1-MMP and MMP-11. The latter are proteolytic enzymes that degrade laminin, collagen, gelatin and other protein components of the ECM. In the case of breast cancer, those secretions are responsible of the degradation of the basement membrane, resulting in the DCIS to invasive carcinoma transition.

2.2. Cancer and immunity

Immune cells are present in the microenvironment of numerous cancers. Very soon,

researchers suggested a potential implication and possible manipulation of the immune

system in and/or to avoid the progression of tumors, respectively. Recently the study of

the immune microenvironment has become an exciting field in cancer research leading to

the advent of cancer immunotherapy. Cancer immunotherapy is defined as the deliberate

use of the adaptive immune system to reject tumors or prevent their recurrence.

Three

main axes of therapeutic strategies can be pointed out: immunostimulatory antibodies,

vaccination and adoptive transfer. The first modality is preferred when an immune

response is already present at the tumor site but too weak to be efficient and consist in

inhibiting immune checkpoints, also called checkpoint blockade, to boost the immunity

response. The concept of those promising therapies is to ‘take off the brake’ that inhibits

lymphocyte activation, by addition of anti-CTLA-4, anti-PD1 or anti-PDL1 antibodies to

reactivate lymphocytes and thus the immune response against tumor cells.

Currently,

those immune checkpoint therapies are entering clinical practice to treat melanoma and

lung cancer.

The first vaccine against prostate cancer (sipuleucel-T) has also just been

approved.

16 Chapter I - Introduction

The interaction between immune cells and cancer cells at the tumor site has been conceptualized by a process called immunoediting. Immunoediting defines cancer progression on the basis of tumor and immune cell interaction in three steps; elimination, during which the immune system eradicates the tumor cells; equilibrium, during which the immune system controls tumor expansion and metastasis and escape, during which tumor cells develop immune resistance and escape immunosurveillance.

Accumulating evidence indicates that the immune system plays a dual and antagonist role in cancer progression either promoting tumor growth and progression through generation of chronic inflammation or inhibiting tumor progression.

A review by Pagès et al. in 2010

lists a series of cancers associated either with chronic inflammatory diseases or favorable clinical outcome (Table I.3).

Table I.3: Dual role of the immune system in cancer progression. A. Cancers associated with

chronic inflammatory diseases. B. Cancers associated with a favorable prognosis. Table from Pagès

et al. 2010.

Chapter I – Introduction 17 More detailed analyses in cancer immune infiltrates revealed that distinct immune cell subsets have distinct prognostic and predictive clinical significances. Immune cell subsets recruited at the tumor site are either involved in anti- or pro-tumor immunity as indicated in Figure I.9.

Interestingly some subsets among the same immune cell population have an opposite impact on the tumor. As an example, type 1 CD4

helper T cells (Th1) are anti- tumorigenic whereas type 2 CD4

helper T cells (Th2) induce tumor progression. Such differences indicate the crucial need to subtype immune cells infiltrating tumors.

Figure I.9: Immune cell subsets associated with pro- (right) and anti- (left) tumorigenic properties.

The role of B cells and Th17 cells remains to be elucidated. Figure from Salgado et al. 2015.

18 Chapter I - Introduction

2.3. The immune microenvironment of tumors 2.3.1. Tumor infiltrating lymphocytes (TILs)

Although breast cancer is not classified as an immunogenic cancer, accumulating evidence indicates that the presence of tumor infiltrating lymphocytes (TILs) at the tumor site is highly associated with prognostic and predictive value.

Interestingly, an extended lymphocytic infiltration has been associated with a favorable clinical outcome and enhanced treatment response in two particularly aggressive breast cancer types: HER2+

and triple negative breast cancer (TNBC) (Figure I.10).

Figure I.10: Kaplan-Meier curves illustrating the prognosis and predictive value of TILs in breast cancer among different studies. A. Prognosis value of TILs in all cancer types (1), Disease-free survival (DFS) in HER2+

patients (2) and Triple negative breast cancer (TNBC) patients (3).⁶⁷ B. Predictive value of TILs in HER2+

patients treated with trastuzumab associated with high (1) and low (2) immune infiltrates.⁶⁸ C. Predictive value of TILs in HER2+ patients treated with anthracyclins: DFS (1) and overall survival (2).⁶⁷ D. Predictive value of TILs in patients treated with paclitaxel and doxorubicin (PM) alone or combined with carboplatin (Cb).⁶⁹

Abbreviations:  

BC:  Breast  Cancer  

LPBC  :  Lymphocyte  Predominant  Breast  Cancer   TNBC:  Triple  Negative  Breast  Cancer  

pCR:  pathologic  Complete  Response  

Chapter I – Introduction 19 A growing body of clinical evidence thus points out that TILs are a critical prognostic and predictive immunological biomarker that could have an impact on the clinical management of patients with HER2+ and TNBC diseases. Nonetheless routine assessment of immune cells at the tumor site is not carried out yet. In order to address the challenge of TIL quantification, an international working group recently set up a standardized approach to evaluate the degree of TIL in breast tumors. The procedure is based on the visual assessment of H&E tissue sections.

2.3.2. Tertiary lymphoid structures (TLS)

Accumulating evidence suggests that adaptive immunity, mediated by T and B lymphocytes, is required to provide an effective and sustained antitumor response.

In numerous cancers, the presence of particular spatially organized aggregates of lymphocyte subsets in the tumor microenvironment, called tertiary lymphoid structures (TLS), has been noted. The presence of TLS at the tumor periphery has been associated with increased survival in patients with cancer such as oral squamous cell carcinoma (Figure I.11).

Figure I.11: Kaplan-Meier analysis of 5 year disease-specific survival for 80 patients with oral

squamous cell carcinoma with and without TLS. The Kaplan-Meier curve shows a 5 year disease-

specific survival rate of 88.2% for TLS-positive patients and 60.3% for TLS-negative patients.

20 Chapter I - Introduction

TLS are defined as transient ectopic lymphoid structures and mimic the organization and functionality of secondary lymphoid organs (SLOs) (Figure I.12). In both structures, T-cell- rich areas surround B-cell-rich areas that are the site of differentiation of effector and memory T and B cells.

Although not much about the induction of TLS is currently understood, many of the processes that occur during the formation of SLOs (lymph nodes, tonsils, etc.) are mirrored in the development of TLS and the presence of those structures is believed to be vital in anti-tumor immunity.

Figure I.12: Similarities between lymph nodes, secondary lymphoid organs (SLOs), and tertiary

lymphoid structures (TLS). A. Schematic representation of a lymph node with the main immune cell subsets indicated.

organization. Figure from Pimenta 2014.

tumor microenvironment of a breast tumor, B cells appear in green and T cells appear in red.

Immunofluorescence image recorded during this thesis.

In the long term, understanding precisely how tumor cells trigger immune cell recruitment

and activation and induce or inhibit the formation of TLS will allow researchers to develop

specific immunotherapies that not only will spare patients the side effects of non-specific

chemotherapies but also provide them a long term anti-tumor immunity.

Chapter I – Introduction 21

3. INFRARED SPECTROSCOPY

3.1. General principle: IR radiation and molecular vibrations

The infrared (IR) region of the electromagnetic spectrum, ranges between the red end of the visible region (λ ~ 780 nm) and overlaps the microwaves region (λ ~ 1 mm).

Per convention, the IR region is subdivided into the near-IR (NIR, λ from ~ 780 nm to 2.5 µm ), mid-IR (MIR, λ from ~ 2.5 µm to 25 µm) and far-IR (FIR, 25 µm to 1 mm) regions (Figure I.13).

Figure I.13: The electromagnetic spectrum. Figure from Naumann, 2000.⁷⁴

Per convention also the spectroscopic unit used to characterize the IR radiation is the

wavenumber (1/ λ ), which is the number of waves per centimeter. Wavenumber ( ! , in cm

), wavelength ( λ , in µm) and frequency ( ν , in Hz) are related as follow:

! =   !

!   =   1

!

!

= 10  

× 1 !

In this thesis we investigated exclusively the absorbance of biological samples in the MIR region extending thus from 4000 to 400 cm

. The range of energy photons in the MIR region corresponds to the vibrational transitions of intra- and inter-molecular bonds.

Molecules that are in periodic (sinusoidal) motion absorb MIR photons only when the

frequency of the IR beam coincides exactly with the frequency allowing the change of

vibrational energy level (from the ground level to the first energy level) in the molecule.

22 Chapter I - Introduction

Fundamental vibrational modes detectable by MIR spectroscopy include bond stretching (either symmetric or anti-symmetric) and deformation (mainly symmetric and anti- symmetric bending); other vibrational modes are twisting, wagging, rocking and scissoring motions.

As an example, the vibrational modes of water molecule are shown in Figure I.14. They include antisymmetric and symmetric stretching vibrations and bending deformations, occurring at specific wavenumbers each.

Figure I.14: Principle of the IR vibrational absorbance spectroscopy. Illustration of the main

vibrational modes of a water molecule, detected at specific frequencies in the MIR region.

Chapter I – Introduction 23

3.2. Assignment of IR absorption peaks for molecular identification

The frequencies at which specific vibrations occur within the IR spectrum are specific for a given functional group. Each molecule has its own distinct pattern of absorption peaks, which can be used as a fingerprint for molecular identification.

Table I.4 summarizes the vibrational frequencies of some functional groups in molecules in the MIR region.

Table I.4: Summary of the vibrational frequencies of some functional groups in molecules within

the MIR region. Figure from Bellisola and Sorio, 2012.

24 Chapter I - Introduction

3.3. IR spectra of complex biological systems: the cell IR spectrum

An IR absorbance spectrum of a sample is obtained by recording the intensity of the IR radiation before (!

) and after (!

) the passage of the IR beam through the sample. The transmittance (T) corresponds to the ratio ! = !

!

and the absorbance is calculated as follow ! = − log

!. IR spectra are commonly plotted with the absorbance as a function of the wavenumbers since the absorbance at a given wavenumber is directly proportional to the concentration (C) of a sample, according to Beer-Lambert Law (! = !"#). The IR spectrum of a biological cell is a superimposition of spectra of all cellular constituents. It comprises absorption peaks and bands (Figure I.15) that are directly proportional to the concentration of cellular components, IR spectroscopy serves thus both as qualitative and quantitative spectroscopic tool.

A cell IR spectrum accounts not only for the chemical nature of cell molecules but also for their conformations, such as the protein secondary structure.

Figure I.15: Typical biological spectrum (human breast carcinoma) showing biomolecular peak

assignments from 3000 to 800 cm

. ν = stretching vibrations, δ = bending vibrations, s = symmetric

and as = antisymmetric vibrations.

Chapter I – Introduction 25

3.4. Infrared spectroscopy sampling modes

Acquisition of IR spectra can be performed by means of three sampling modes:

transmission, transflection and attenuated total reflection (ATR). Each sampling mode implies a different disposition of the following elements: IR source, sample and detector as illustrated in Figure I.16. The sampling mode is chosen to be the most suitable for the analyzed sample and depends on the signal intensity required by the user. In the present thesis all spectral acquisition were performed in the most frequently sampling mode, i.e.

transmission mode, allowing recording a signal of high intensity. The sample was deposited on a BaF

window, invisible for IR light, and the beam passed through the sample.

Figure I.16: Schematic illustration of the three main modes of IR spectroscopy sampling. In

transmission mode the beam passes linearly through the sample towards the detector. In

transflection mode the beam passes through the sample and is reflected on an IR reflecting surface

(a substrate such as a low-emissivity slide) towards the sample and finally reaches the detector. In

attenuated total reflectance (ATR) mode, the IR beam is directed towards an internal reflection

element (IRE) with a high refractive index (such as germanium or diamond), internal reflection

occur within the IRE creating an evanescent wave at the IRE surface-sample interface that

penetrates the sample. The beam then comes out the IRE and reaches the detector.

26 Chapter I - Introduction

3.5. Fourier transform Infrared technology

A major improvement in IR spectroscopy was achieved with the development of Fourier transform Infrared (FTIR) spectrometers. Previous dispersive IR spectroscopy techniques measured one wavelength after the other and/or were equipped with monochromators, which limited the IR light energy.

Unlike previous techniques, FTIR spectroscopy has the main advantage to measure the absorbance for all IR frequencies simultaneously.

The main element that composes an FTIR spectrometer is a Michelson-type interferometer, the component that allows signal modulation. The interferometer includes a white-light source (globar), a KBr beam splitter and two perpendicular mirrors (one fixed and one moving). The working principle is as follow; the beam splitter divides the IR beam into two parts, the first half is directed towards the fixed mirror and the second half towards the moving mirror. The two beams are then reflected towards the splitter and added together to pass through the sample (Figure I.17B, top). The addition of the two beams results in constructive and destructive interferences according to the position of the moving mirror, yielding a sinusoidal signal at the detector for each modulated frequency (Figure I.17B, center). All modulated signals of the white-light source superimpose to an interferogram (Figure I.17B, bottom). The interferogram is thus the intensity of the beam transmitted as a function of the position of the moving mirror; this signal contains information over the entire IR region. Finally the interferogram is amplified, digitalized and converted into a traditional IR spectrum by Fourier transformation, a mathematical means of sorting out the individual IR frequencies.

With the development of FTIR technology, spectral acquisition time significantly decreased

(from hours to seconds) and the quality of spectra was improved. The spectral resolution is

related to the distance covered by the moving mirror. The spectral resolution of the FTIR

spectrometer used to record all measurements in this thesis was of 8 cm

.

Chapter I – Introduction 27

spectrometer. B. Working principle of a Michelson interferometer. Top: main elements of an

interferometer. Center: a single frequency light source is modulated to a sinusoidal signal,

recorded by the detector. Bottom: a white-light source is transformed into an interferogram.