FTIR SPECTRA OF CANCER CELLS EXPOSED  TO ANTICANCER DRUGS REFLECT THEIR 

FTIR SPECTRA OF CANCER CELLS EXPOSED  TO ANTICANCER DRUGS REFLECT THEIR 

CELLULAR MODE OF ACTION  

Allison DERENNE  

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

Université libre de Bruxelles – Ecole Interfacultaire de Bioingénieurs   

Service de Structure et Fonction des membranes biologiques  Centre de Biologie structurale et de Bioinformatique 

Promoteur : 

Prof. Erik GOORMAGHTIGH 

Mai 2013

La première personne que je voudrais remercier est, bien entendu, Erik, sans qui cette thèse n’aurait pas pu être réalisée. Merci pour ton soutien, tes idées, tes conseils et ta disponibilité malgré ton programme surchargé. Merci de m’avoir accordé ta confiance, d’avoir cru en moi et de m’avoir donné des responsabilités. Je suis consciente de t’en avoir demandé beaucoup durant ces années. Pour moi, cette collaboration a été très fructueuse, tant d’un point de vue scientifique que d’un point de vue personnel. Pour toutes ces raisons, encore mille fois merci ! J’ai eu beaucoup de chance que tu sois le promoteur de ma thèse. Je suis ravie que notre collaboration ne s’arrête pas là et que de nouvelles aventures soient déjà en route.

Je voudrais ensuite remercier le jury pour l’ensemble de ses conseils, idées et questions tout au long de ce travail et notamment, lors des séminaires. J’aimerais aussi les remercier d’avoir accepté d’être lecteurs de cette thèse.

Un élément indispensable est bien entendu les financements qui ont permis la réalisation de mes travaux durant ces 4 ans. Pour cela, je tiens à remercier particulièrement le FRIA et le FNRS, ainsi que les autres financements facilitant l’achat de matériel et la participation à différents congrès.

Lorsque je suis arrivée au laboratoire SFMB, l’implication de deux personnes a été très importante dans la formation que j’ai reçue et dans le démarrage de cette grande aventure doctorale: Régis et Audrey. Merci Régis pour ton temps et ta patience et pour toutes les explications pendant mon mémoire. Merci de m’avoir donné l’envie de commencer cette thèse. Audrey, je suis consciente d’être arrivée au moment où tu parvenais enfin à t’en sortir avec ce microscope qui a hanté nos nuits de nombreuses fois. Je tiens donc à te remercier vivement de m’avoir fait profiter de ton travail et d’avoir partagé ton expérience. Merci aussi pour les sympathiques moments à Porquerolles, Coimbra, Manchester, etc…

Je voudrais ensuite remercier le laboratoire de toxicologie (Robert, Véronique, Delphine,…) pour notre collaboration et pour votre disponibilité. Votre aide a été très précieuse à plusieurs reprises pendant ma thèse.

Quatre personnes ont également eu une contribution significative (comme des étoiles sur les spectres… ) pendant cette thèse. Il s’agit de Magali, Alix, Vincent et Olivier qui ont tous réalisé un mémoire sur le sujet de cette thèse. Je tiens à vous remercier de tout cœur pour ces belles

Remerciements 

collaborations, le travail et l’aide que vous m’avez apportée. Tout cela a été très riche pour moi et travailler avec vous a rendu ma thèse agréable et passionnante. J’ai tenté de partager avec vous mon expérience et mon enthousiasme ; j’espère avoir réussi ?

Un petit mot particulier pour Noémie et Magali : le congrès et voyage en Thaïlande resteront à jamais gravés dans ma mémoire. Merci à vous pour ces beaux moments… (Super-IR, Tony et son Banjo, les cocktails à la piscine du Méridien,…)

J’aimerais ensuite remercier toutes les personnes qui ont participé au dénommé, groupe IR. Merci à Andréa, Julie, Margarita, Philippe, Thomas, Greg. Je n’oublie pas Caroline Conus et Sanjica qui ont fait un passage de quelques mois chez nous et avec qui j’ai aussi travaillé plus directement !

Ce labo rassemblant de nombreux groupes, pour le meilleur et pour le pire, il me reste encore de nombreuses personnes à remercier. Un petit mot particulier à Rosie pour tous les petits et grands conseils scientifiques, pour les délires dans le bureau, pour nos discussions sur les hommes et la vie,…! En parlant de délires dans le bureau, la vie au labo ne serait pas la même sans toi, Nico ! Merci de m’avoir fait rire tous les jours même quand je n’étais pas du tout de bonne humeur ou

« scandalisée », merci d’avoir rendu ces années agréables en assurant l’ambiance de notre bureau ! Merci à Nancy pour toutes les petites pauses sportives qui nous permettaient de nous défouler et de décompresser. Merci à Anastassia, Magda, Mouna et Boris pour les confidences, le partage de ce grand bureau, merci de m’avoir supporté dans les bons et les mauvais jours ! Merci aussi à Jean-Marie pour ses apparitions inopinées dans notre bureau et les discussions philosophiques mais sympathiques qui en découlaient.

En termes de conseils scientifiques, je voudrais témoigner une reconnaissance particulière à Caroline pour tous ses conseils sur la culture cellulaire et à Rabia pour ses conseils sur les lipides et sur beaucoup d’autres choses! Comme je le disais plus haut, la force de ce labo (qui, comme souvent, peut s’avérer une faiblesse dans certains cas), est de rassembler de nombreuses personnes, chacune avec une expérience et des connaissances scientifiques différentes. Je voudrais donc ici remercier tous les membres du SFMB qui à tout moment sont disponibles pour aider ou répondre à une question. Je ne pourrais pas citer chacun de ces échanges mais il est certain qu’ils ont permis de faire avancer mon travail !

L’organisation d’évènements comme le « research day » ou la journée du SFMBBM constitue aussi des moments marquants pendant ces années. Merci à Emilie, Matt et Fabien pour cette journée SFMBBM et merci à Noémie, Magali, Fred, Thomas, Marie, Lauranne, Jief et Emilie pour les

« Research Day ». Ce sont des supers expériences et cela a été particulièrement agréable de partager tout ça avec vous !

Comme vous l’aurez compris, au SFMB, on fait beaucoup de sciences mais aussi de belles rencontres ! Parmi les personnes qui n’ont pas encore été citées plus haut, je pense à Emilie C, Adelin, Chantal… Merci à tous pour les sympathiques moments que nous avons partagés (Palerme, week-end labo, nettoyage ou peintures labo et tout le reste en dehors…)

Parce que, pendant une thèse, il y a aussi une vie à l’extérieur du labo (si, si, je vous le jure !!), j’aimerais également remercier une série de personnes qui ne sont pas du SFMB mais qui ont fait partie de ma vie et m’ont soutenu pendant ces années.

Je commencerai par « les filles » (Laurence, Adeline, Justine et Savitri), merci pour votre soutien et pour les petites soirées confidences, papotes et resto! Je ne sais pas si vous vous en êtes rendu compte mais elles étaient vraiment nécessaires à mon équilibre et mon bien-être .

Merci à tous mes amis d’où que vous soyez et peu importe où je vous ai rencontré (Lycée, Bioingénieur ou Canada), vous avez tous contribué en m’encourageant ou en me demandant des nouvelles !

Cette thèse n’aurait pas non plus été la même sans toi, Jérôme… A vrai dire, je ne sais même pas si j’en aurais commencé une. Je voudrais vraiment te dire merci aujourd’hui pour ton soutien inconditionnel, pour la confiance que tu m’as donnée presque quotidiennement pendant ces quatre ans. Merci de m’avoir motivée même les jours les plus difficiles, merci pour tes relectures exigeantes et ton discernement qui m’a beaucoup aidé dans tous les choix que j’ai faits. Et puis, merci pour tout le reste, toutes les petites choses qui ont rendu ma vie agréable pendant ces 4 ans. Je suis très heureuse et j’ai eu beaucoup de chance d’avoir pu partager tous ces moments (agréables comme difficiles) avec toi en espérant que cela continue encore très longtemps…

Enfin, je terminerai en remerciant ma famille. Mes parents pour m’avoir donné toutes les armes pour en arriver là et tout particulièrement, le courage et la passion. Merci aussi à Papy pomme, comme on t’appelle ici, pour l’optimisme que tu m’as transmis ! Et merci à toute ma famille et belle famille (vous comprendrez de qui je parle même si nous ne sommes pas mariés !!) pour tout votre soutien pendant cette thèse.

Chapter I:  General introduction ___________________________________________________ 1  1.  Hallmarks of cancer _________________________________________________________ 1  2.  Anticancer drugs ____________________________________________________________ 5  3.  Preclinical anticancer drug development ________________________________________ 13  4.  Infrared spectroscopy _______________________________________________________ 21  Chapter II:  Aim of the thesis _____________________________________________________ 31  Chapter III:  The FTIR spectrum of prostate cancer cells allows the classification of anticancer drugs according to their mode of action. _______________________________________________ 33 

1.  Introduction _______________________________________________________________ 34  2.  Materials and Methods ______________________________________________________ 36  3.  Results ___________________________________________________________________ 38  4.  Discussion ________________________________________________________________ 45  Chapter IV:  The effect of anticancer drugs on seven cell lines monitored by FTIR spectroscopy _ 47  1.  Introduction _______________________________________________________________ 48  2.  Materials and Methods ______________________________________________________ 50  3.  Results ___________________________________________________________________ 53  4.  Discussion ________________________________________________________________ 61  5.  Appendix: Drug contribution to difference spectra ________________________________ 65  Chapter V:  FTIR spectral signature of anticancer drug effects on PC-3 cancer cells – is there any influence of the cell cycle? _________________________________________________________ 67  1.  Introduction _______________________________________________________________ 68  2.  Materials and Methods ______________________________________________________ 70  3.  Results ___________________________________________________________________ 74  4.  Discussion ________________________________________________________________ 79  Supplementary data _____________________________________________________________ 81 

Table of contents 

Chapter VI:  Infrared spectroscopy of membrane lipids _________________________________ 85  1.  Introduction _______________________________________________________________ 86  2.  ATR-FTIR spectroscopy of lipids ______________________________________________ 86  3.  Lipid polar head groups _____________________________________________________ 87  4.  Lipid hydrocarbon chains ____________________________________________________ 88  5.  Lipid phase transition _______________________________________________________ 90  6.  Lipid orientation ___________________________________________________________ 92  7.  Lipids in cells _____________________________________________________________ 93  Chapter VII:  Lipids quantification method using FTIR spectroscopy applied on cancer cell extracts _________________________________________________________________ 95 

1.  Introduction _______________________________________________________________ 96  2.  Materials and Methods ______________________________________________________ 99  3.  Results __________________________________________________________________ 103  4.  Discussion _______________________________________________________________ 113  5.  Annex __________________________________________________________________ 116  Chapter VIII:  FTIR spectroscopy – A new valuable tool to classify the effects of polyphenolic compounds on cancer cells. _______________________________________________________ 119 

1.  Introduction ______________________________________________________________ 120  2.  Materials and Methods _____________________________________________________ 123  3.  Results __________________________________________________________________ 127  4.  Discussion _______________________________________________________________ 133  Supplementary data ____________________________________________________________ 136  Chapter IX:  General conclusions _________________________________________________ 139  Bibliography ___________________________________________________________________ 143  Publications ____________________________________________________________________ 157 

| Abbreviation list ix ATR: Attenuated total reflection

CH: Cholesterol CL: Cardiolipin

DOPE: 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine DTP: Developmental therapeutics program

EGCG: Epigallocatechin-3-gallate ESS: Error sum of square

FDA: Food and drug administration FPA: Focal plane array

FTIR: Fourier transform infrared GEM: Genetically engineered models GI: Growth inhibition

Hrs: Hours

HPLC: High performance liquid chromatography

IC50: Inhibitory concentration that reduces cell growth by 50%

IR: Infrared

IRE: Internal reflection element LC: Lethal concentration

MANOVA : Multivariate analysis of variance

MTT: 3-[4,5-dimethylthiazol-2yl]-diphenyltetrazolium bromide

Abbreviation list 

x Abbreviation list | NCI: National cancer institute NMR: Nuclear magnetic resonance S/N: Signal to noise

SD: Standard deviation PC: phosphatidylcholine

PCA: Principal component analysis PE: Phosphatidylethanolamine PI: Phosphatidylinositol PLS: Partial least square PS: Phosphatidylserine

RMSECV: Root mean square error of cross validation RMSEP: Root mean square error of prediction

SM: Sphingomyelin

TLC: Thin layer chromatography TGI: Total growth inhibition

| Abstract xi There is an urgent need to develop reliable and cost-saving methods to select pre-clinically new drug candidates with original mechanism for cancer therapy. Previous results have shown that IR spectra of cancer cells exposed to various drugs provided a global signature of all the metabolic changes induced by the treatments. In this thesis, we attempted to develop a selection criterion – based on FTIR spectroscopy – for potential antitumor compounds according to their mechanism of action.

In chapter III, it was demonstrated that spectral variations in IR spectra of cancer cells induced by a treatment can be correlated to the mechanism of the drug. Human prostate cancer PC-3 cells were exposed to 7 well-described anticancer drugs belonging to 3 distinct classes. Each class is characterized by a unique mode of action. Drugs known to induce similar types of metabolic disturbances appear to cluster when spectrum shapes are analyzed. Chapter IV generalized the results obtained on PC-3 cells with six other cell lines. We showed that the spectral signatures of drug effects are mainly independent of the cell line. Chapter V indicated that, while the cell cycle phase influence IR spectra of cells, the drug spectral signature was dominated by global metabolic modifications and not much by the cell cycle perturbations due to this drug.

Chapter VI and VII focused on lipids. While the precise identification of particular molecules is particularly complex with IR spectroscopy, we attempted to extract more precise information and to assign spectral variations to specific changes in lipids. IR spectra of lipids contain very interesting details on their nature and structure. We achieved to build a tool which quantifies five major lipid classes in complex mixtures such as total lipid cell extracts. However, based on this tool, the treatments used do not induce any variation in the lipid cell composition (for five classes).

Finally, in chapter VIII, we applied the method developed previously on a new potential class of anticancer molecules: the polyphenols. A global method was particularly interesting as the development of therapy using these compounds is hampered by the complexity of the multiple anticarcinogenic mechanisms of these molecules. We have noticed the similarities and discrepancies among 3 very close synthetic molecules and the observations were coherent with previous biological data. We also compared them with 3 natural molecules already in clinical phase for treatment of various cancers.

In conclusion, we developed an objective classifier for potential anticancer drugs based on their global effects on cancer cells. Applied to a larger scale, this method could constitute a first step in the screening method to select drugs with original mode of action.

Abstract 

| General Introduction 1

1. Hallmarks of cancer 

Cancer remains a leading cause of death worldwide and accounts for 7.6 millions of death (13% of all death). In 2008, 12.7 millions of cancer cases were diagnosed. These rates are predicted to further increased [1].

Cancer is a multistep process involving several sequential mutations. These diverse genetic alterations progressively turn normal human cells into highly malignant derivatives [2]. To rationalize the complexities of neoplastic disease, Hanahan and Weinberg suggested in 2000 that hallmarks of cancer comprise six acquired capabilities.

Sustaining Proliferative Signaling: The proliferation of normal cells is known to strongly depend on the presence of growth factors. Cancer cells become masters of their own destinies by deregulating these growth-promoting signals that instruct entry into and progression through the cell cycle. Various disturbances have been observed. Somatic mutations cause constitutive activation of the pathway generally triggered by growth factors. The negative feedback loops which attenuate proliferative signals are down-regulated. Moreover, high concentrations of oncoproteins such as growth factor induce senescence in normal cells. Therefore, the relative intensity of oncogenic signaling in cancer cells may represent compromises between maximal mitogenic stimulation and avoidance of these antiproliferative defenses. Alternatively, some cancer cells may adapt to high levels of oncogenic signaling by disabling the senescence or apoptosis program [2,3].

Evading growth suppressors: cancer cells must also bypass the tumor suppressor genes which negatively regulate the proliferation. RB and TP53 are two central nodes that govern the decisions of cells to proliferate or to activate the senescence- or apoptosis-inducing circuitry. Moreover, the mechanism of “contact inhibition” which suppress the proliferation in case of cell to cell contacts in dense population of normal cells, is abolished in cancer cells [2–4].

Resisting cell death: Apoptosis is recognized as a natural barrier against cancer development. It is the most common programmed cell death and a physiological “cell-suicide”, essential for example in embryonic development or for immune-system function. Apoptosis pathways can be triggered by

Chapter I: General introduction 

2 General Introduction |

various intrinsic and extrinsic stresses such as hypoxia, DNA damage, oncongene induction. Tumor cells acquire mutations allowing them to avoid death stimuli. The loss of the already mentioned TP53 tumor suppressor function eliminates the critical damage sensor from the apoptosis-inducing circuitry.

Defects in non apoptotic cell-death (autophagy, necrosis, senescence, mitotic catastrophe) pathways have also been linked to cancer [3,5].

Enabling replicative immortality: The three characteristics described above lead to an uncoupling of cell’s growth from signal in its environment but cannot fully explain immortality. Most normal cells in the body are able to pass through a limited number of successive divisions. This is mainly due to the loss of about 100 base pairs of telomeric DNA from the end of every chromosome at each doubling. The ongoing maintenance of telomeres thus appears as a prerequisite for the indefinite proliferation of cells. Telomerase, the specialized DNA polymerase that adds telomere segments at the ends of telomeric DNA is almost absent in nonimmortalized cells but expressed at functionally significant levels in the vast majority of immortalized cancer cells [2–4].

Inducing and sustaining angiogenesis: Angiogenesis is the neovascularisation associated with a tumor. It allows cancer cells the access to the circulatory system. Like normal tissue, tumors require nutrients and oxygen as well as an ability to evacuate metabolic wastes and carbon dioxide. During tumor development, an alteration of gene transcription changes the balance of angiogenesis inducers and inhibitors. This induces an “angiogenic switch” that causes chronic activation of angiogenesis in the blood vessels within tumors [3,4,6].

Activating Invasion and Metastasis: The invasion-metastasis process by tumor cells includes the invasion of the local microenvironment facilitated by the alterations in cell-to-cell adhesion, their intravasation into the blood and lymphatic vessels and their subsequent extravasation into the distant tissues parenchyma. The last step of the metastasis process is the successful colonization of these malignant cells escaped from the primary tumor site which requires the adaptation of the tumour cells to their new tissue microenvironment. The loss of E-cadherin, a key molecule involved in cell-to-cell adhesion is one of the best characterized event enabling local invasion and subsequent metastasis.

In 2011, Hanahan and Weinberg suggested to add two emerging hallmarks in the set of genetic and biochemical rules that apply to most and perhaps all types of tumors.

Reprogramming energy metabolism: Adjustments of energy metabolism are required in cancer cells to fuel the chronic and uncontrolled cell growth. One well-known example is the Warburg effect. Even in the presence of oxygen, cancer cells can reprogram their glucose metabolism to behave as in anaerobic condition. This increased glycolysis activates other biosynthetic pathways generating

| General Introduction 3 nucleosides and amino acids required for assembling new cells. Moreover, some tumors have been found to contain two subpopulations with a different energy metabolism. One population uses mainly the glucose dependent pathway (Warbug effect) and secretes lactate. The second utilizes lactate as the principal source of energy.

Evading immune destruction: The second new issue concerns the role that the immune system plays in resisting or eradicating formation and progression of tumors. The dual host-protective and tumor- promoting role of the immune system during the tumorigenesis forces the scientific community to revisit the initial immune surveillance theory [3,7].

The acquisition of the functional capabilities described above is made possible by two enabling characteristics:

Genomic instability: In cancer cells, various random mutations are generated including chromosomal rearrangement and rare genetic changes that can orchestrate hallmark capabilities [3].

Tumor-promoting inflammation: Premalignant and malignant neoplastic lesions are infiltrated by cells from both the adaptive and innate immune system at various densities. This inflammatory state of the tumor can promote tumor progression through various mean [3,8].

In turn, it is now recognized that the biology of tumor can only be understood by considering also the

“tumor microenvironment” and not simply by studying the individual specialized cell types within it [3].

4 General Introduction |

Figure I.1: The hallmarks of cancer and therapeutic targeting [3]

These 8 hallmarks capabilities as well as the two enabling characteristics (Figure I.1) enhance the understanding of the complex mechanisms driving tumor initiation and progression. Moreover, the description of these characteristics allows initiating a new approach to develop cancer therapies. In addition to regular treatments (chemotherapy, radiotherapy and surgery), new therapy were established against cellular targets specific of cancer cells. The high specificity of these new anticancer medicines was firstly considered as very interesting because of weak secondary effects and low toxicity. However, as it will be described in the next section, the clinical responses to these therapies were generally transitory and followed by relapses due to the development of cellular resistance mechanisms. In turn, new treatments attempt to target multiple hallmarks capabilities of cancer cells. It is now obvious that the combination of numerous anticancer drugs with various mode of action is necessary to obtain more efficient and sustainable therapy [3,9].

| General Introduction 5

2. Anticancer drugs 

2.1. Drugs used in clinics 

Five of the most important classes of anticancer drugs are described here. One of two examples are depicted for each group and all the molecules used further in this thesis are detailed. It was not the aim of this work to provide an exhaustive list of chemotherapy drugs.

2.1.1. Antimicrotubules 

The effect of these drugs is mainly mediated by their interaction with microtubules. They are divided in two categories: stabilizers (taxanes) and destabilizers (Vinca alkaloids).

Microtubules are fibrillar structures playing a key role in various cellular processes such as transport, signaling and mitosis. They are made up with a protein called tubulin which is a dimer containing one α-subunit and one β-subunit. Microtubules are constantly undergoing rearrangements and exist in a dynamic equilibrium. During mitosis, they form the mitotic spindle responsible for the separation of chromosomes into two daughter cells [10,11].

2.1.1.1. Taxanes 

Taxanes are natural compounds derived from trees of the family Taxoidacae. Paclitaxel was the first taxane discovered for cancer therapy and was isolated from the bark of the Western Yew, Taxus brevifolia. Initially, the development of this molecule was limited due to the low content of paclitaxel in Taxus. It was then found that paclitaxel could be produced from 10-deacetyl-baccatin III which is abundantly present in the leaves of Taxus baccata. The cellular target of these compounds is the β- subunit of tubulin. Taxanes bind microtubules and stabilize them by inhibiting their depolymerization.

This subsequently disrupts the normal dynamic reorganization of the microtubules network during the mitosis and causes cell arrest in G2-M phase of the cell cycle. Paclitaxel is notably used for the treatment of ovarian, breast and non-small cell lung cancer [10,12].

2.1.1.2. Vinca Alkaloids 

These antimicrotubule agents were discovered by chance in the plant Catharanthus roseus (Madagascar periwinkle). This species was historically used in traditional medicine to treat diabetes and high blood pressure. This plant was thus studied by the pharmaceutical industry and more than 70 alkaloids of interest were evidenced in the sap of C. roseus. Among them, vinblastine and vincristine were selected for their antitumor properties. Like taxanes, they bind to the the β-subunit of tubulin but, at a distinct region and prevent polymerization of microtubules. The primary mechanism of

6 General Introduction |

action of vinca alkaloids is the alteration of microtubules dynamics. However, they are also presumed to act on other cellular process such as RNA, DNA, and lipid synthesis. They are used to treat several types of cancer including leukemia, lymphoma, melanoma, breast and lung cancer [10–12].

2.1.2. Topoisomerases inhibitors 

Topoisomerases are a family of enzymes involved in the regulation of DNA supercoiling. DNA is normally present in cells as a supercoiled double helix. Since polymerases need a single strand DNA as a template, it must be unwound during transcription or replication. This induces torsional stress due to unwinding of the duplex, ahead of the replication fork. Topoisomerase activity is thus crucial to relieve these constraints. These enzymes are separated in two classes: topoisomerase I and topoisomerase II. Relaxation of supercoiled DNA involves a transient single strand cleavage (for topoisomerase I) or a double strand cleavage (for topoisomerase II). These breaks allow the passing of the intact single or double strands through the gap. The helix integrity must be restored by posterior relegation of cleaved strands. Before religation, the intermediate usually called “the cleavable complex” can be stabilized by DNA intercalating drugs. The primary target of anthracycline, campothecin and podophyllotoxin families of anticancer drugs is considered to be the topoisomerase- DNA complex. These compounds are only active if DNA synthesis is initiated when the fork is formed by the two DNA strands and coiling strains must be relieved. Topoisomerases inhibitors are subsequently very specific to the S phase of the cell cycle [12–14].

2.1.2.1. Anthracyclines 

These molecules are characterized by a tetracyclic chromophore that contains an anthraquinone motif.

They present a wide range of biological activity: antibacterial, immunosuppressants, antiparasitics and antitumor. Doxorubicin and daunorubicin are two anthracyclines used clinically for the last four decades. Doxorubicin was isolated from Streptomyces peucetius and is extensively used to treat a wide spectrum of solid tumours (breast, ovarian, lung, thyroid,…). Daunorubicin is produced by S.

coeruleorubidus and S. peucetius and has a narrower spectrum of clinical treatments. They present a similar mode of action. Their biological effect is mainly mediated by an inhibition of topoisomerase II as they bind strongly to duplex DNA. The anthracyclines chromophore is selectively intercalated in GC sequences. This prevents the cleavable complex from religation [13,15].

2.1.2.2. Camptothecins 

Camptothecin was isolated from alkaloid extracts of the tree Camptotheca acuminata present in Tibet and China. It binds and stabilizes the binary complex DNA-topoisomerase I, resulting in the inhibition of the religation of the cleaved strand and eventually of the DNA synthesis and cell viability.

| General Introduction 7 Camptothecin has been modified chemically to reduce its toxicity and two derivatives were commercialized: irinotecan and topotecan [12–14].

2.1.2.3. Podophyllotoxins 

Podophyllotoxin was first isolated from the plant Podophyllum peltatum and presented a broad variety of pharmacological properties (antiviral, immunostimulatory, used in dermatology and for the treatment of rheumatoid arthritis). It was also recognized to have strong antitumoral activity but was never used in clinic due to the severity of its side effect. Two clinically relevant analogues were discovered: etoposide and teniposide. Interestingly, the derived molecules present a divergent mode of action from the original compound. Podophyllotoxin exerts its biological effect by binding tubulin while the molecular target of etoposide and teniposide is the topoisomerase II-DNA covalent complex [12–14].

2.1.3. Antimetabolites  

Metabolite is a general term to refer to organic compounds necessary for the biochemical pathways in cells. An antimetabolite is defined as a molecule with a structure similar to a metabolite structure, yet different enough to disturb the normal function of cells including cell division. These compounds may be integrated into a DNA or RNA molecule during synthesis or may directly interfere with key enzymes [16].

2.1.3.1. Folic acid antagonists: 

Folic acid is a growth factor that provides single carbons to the precursors of nucleotides in DNA or RNA synthesis. These antagonists inhibit one or more enzymes involved in the folic acid cycle illustrated in figure I.2. It results in a decreased DNA, RNA and protein synthesis. Methotrexate inhibits the enzyme dihydrofolate reductase (DHFR) which reduces dihydrofolate, coming from folic acid, to active tetrahydrofolate. These active folates are required co-enzymes for the synthesis of purine nucleotides and thymine. Methotrexate thus prevents DNA and RNA synthesis and is used alone or in combination with other cytotoxics in the treatment of a wide range of cancers including leukaemias, lymphomas, osteosarcomas, breast cancer, lung cancer, bladder cancer,… [16].

8 General Introduction |

Figure I.2: Folic acid cycle 2.1.3.2. Pyrimidine antagonists: 

Molecules such as 5-Fluorouracil or gemcitabine act to block the synthesis of nucleotides containing cytosine and thymine in DNA and cytosine and uracile in RNA.

2.1.3.3. Purine antagonists: 

These compounds inhibit the production of adenine and guanine found in DNA and RNA.

Mercaptopurine is an analogue of the purine bases adenine and hypoxanthine. It is metabolized by hypoxanthine-guanine phosphoribosyltransferase (HGPRT) in various ribonucleotides which inhibit the conversion of inosinic acid (IMP) to adenylic acid (AMP) and guanylic acid (GMP). The nucleotides derived from mercaptopurine also interact with enzymes necessary for the de novo pathway for purine ribonucleotide synthesis. Mercaptopurine is also incorporated into the DNA and interferes with DNA replication. It is currently not defined which mechanisms are predominantly responsible for cell death [16].

2.1.4. Alkylating agents 

This is another major class of anticancer drugs approved by the national agencies and used in clinics.

Cyclophosphamide is representative of this group and is one of the most successful anticancer agents ever synthesized. This compound was developed by modifying the chemical structure of nitrogen mustard to achieve greater selectivity for cancer cells. The design of cyclophosphamide is based on the rationale that some cancer cells contain high level of phosphamidase able to cleave the phosphorus-nitrogen (P-N) bond and to release nitrogen mustard. Cyclophosphamide is thus a prodrug that requires metabolic activation. As illustrated on the following figure, the cytotoxic action of nitrogen mustard is closely related to the reactivity of the 2-chloroethyl groups attached to the central nitrogen atom. Under physiological condition, a highly unstable cation is formed by intramolecular

| General Introduction 9 cyclization through the elimination of one chloride. This cation is easily attacked by various nucleophiles such as DNA guanine residues. As a covalent linkage is formed with a DNA nucleobase, a second cyclic aziridinium cation is available to be attacked by another nucleophile. This results in the formation of intrastrand and interstrand DNA crosslinks, interfering with DNA replication [17].

Figure I.3 Cytotoxic action of nitrogen mustard [17]

Another example of alkylating agent is temozolomide which is approved for the treatment of newly diagnosed glioblastoma in combination with radiotherapy. It is also under clinical investigation for brain metastasis from solid tumors and refractory leukemias. Temozolomide leads to cell death by methylation of guanine and subsequent disturbance of DNA replication [18,19].

2.1.5. Platinum drugs 

Platinum drugs constitute the last major class of anticancer compounds. Three platinum complexes (cisplatin, carboplatin and oxaliplatin) are marketed for oncological purposes. They act similarly as the previous class but, without alkyl group. They covalently bind to DNA and form DNA adducts which induce the activation of various signal pathways such as DNA-damage recognition and repair, cell-cycle arrest and programmed cell death/apoptosis [20,21].

2.2. Polyphenols 

Polyphenolic compounds constitute one of the most widespread and ubiquitous groups of plant secondary metabolites. Somewhere between 100 000 and 200 000 of polyphenolic metabolites are believed to exist in nature. They are produced to protect the plants from photosynthetic stress, reactive oxygen species, UV radiation, wounds and herbivores. They are extremely structurally diverse and more than 8000 compounds can be divided in at least ten different classes based on their general chemical structure. Phenolic acids, flavonoids, stilbenes and lignans are the most abundantly occurring families of polyphenols in plants. Despite the diversity of their structure, most of these metabolites arise from common intermediates, the amino acids phenylalanine and tyrosine [22–24].

10 General Introduction |

Polyphenols are also an important part of human diet; they are present in fruits, vegetables, seeds and drinks such as tea and wine. The initial interest for these compounds was related to their antinutritional effects particularly due to their ability to reduce absorption and digestibility of food as they bind to protein and minerals. Indeed, the precipitation of salivary proteins with plant polyphenols is responsible for the astringency of many fruits. More recently, new attention were attached to these molecules due to their antioxydative, anti-inflammatory and anticarcinogenic activities [22,24].

Bioavailability is still an issue with polyphenolic compounds and an important determinant in understanding their biological activities. The bioavailability of many dietary polyphenols is rather low and their tissue concentration may not be sufficient to exert the effects observed in vitro. For example, high doses of tea polyphenols are necessary to produce a cancer-preventive effect in animal models.

However, the bioavailability varies greatly according to the molecules. Different factor may influence including the chemical properties of the compounds, the intestinal absorption, the enzymes available for metabolism, … [24,25].

Various epidemiological studies have pointed out the association between a polyphenol-rich diet and a reduced risk of chronic disease, including cancer [26]. Numerous studies have also assessed the chemopreventive activity of polyphenols in various animal models. Anticarcinogenic properties were notably evidenced for quercetin present i.e. in apple and onion, green tea polyphenols and curcumin for specific cancers [23]. Although results obtained on cultured cells cannot be applied directly in clinics, it constitutes a valuable tool to elucidate the multiple pathways involved in the chemopreventive properties [26].

Dietary polyphenols can affect the overall process of carcinogenesis by several molecular mechanisms rather than by a single receptor or molecular target. Different pathways involved are described here under:

The antioxidant and pro‐oxidant activities: 

Reactive oxygen species (ROS) production occurs naturally in aerobic organisms. ROS can damage proteins, DNA and RNA as well as oxidize fatty acids in cell membranes which generally increase the risk of mutations. The level of ROS is usually controlled by antioxydants such as gluthatione or enzymes and most of the damages caused by ROS are restored by internal surveillance and repair systems. As their aromatic ring give rise to electron delocalization properties, polyphenolic compounds can prevent these damages caused by free radicals. Many mechanisms of prevention have been proposed. Firstly, they can directly quench free radicals and interrupt radical chain propagation by lipid peroxydation. Secondly, they are able to chelate divalent cations involved in Fenton reaction

| General Introduction 11 which also induce the production of very oxydant species. Finally, they modulate enzymes related to oxidative stress [23,27–29].

Conversely, dietary polyphenols can act as pro-oxidants depending on cell types, dose and time of treatment. Some of the anticarcinogenic effects of these compounds would be thus related to induction of oxidative stress. As polyphenols have entered the cells, ROS production is induced by unknown mechanisms. The role of theses ROS in cancer prevention is still under investigation but is probably responsible for the induction of apoptosis of tumor cells [23,25,27].

Cell cycle arrest 

Perturbations of the cell cycle generally affect or block the proliferation of cancer cells. It is demonstrated that several polyphenols inhibit cells at different cycle phases through down-regulation of cyclins or cyclins-dependent kinases [23,29].

Induction of apoptosis 

This chemopreventive mechanism is subsequent to the two described here above. Apoptosis is considered as an important target in preventive approach against cancer. Many dietary polyphenols including quercetin, tea polyphenol, curcumin, resveratrol provoke their inhibitory effect on carcinogenesis through the induction of apoptosis. It has been shown that various pathways triggering programmed cell death are affected by these compounds. The regulation of crucial proteins such as caspases or Bcl-2 is disrupted [23,29,30].

Modulation of growth promoting signals 

Polyphenolic compounds can suppress in vitro the signals that regulate cell proliferation and survivals. Many pathways are involved in this signaling: PI3K/ protein kinase B (AKT), GFR/RAS/MAPK and nuclear factor κ B (NF- κB). Epigallocatechin-3-gallate (EGCG), the main polyhenol in tea is also recognized to block the binding of growth factor to their receptor such as the epidermal growth factor receptor (EGFR) [23,29].

Inhibition of Angiogenesis and Metastasis 

Phenolic compounds possess antiangiogenic effects, antiinvasive and antimetastatic properties but their molecular mechanisms are not clear yet and they might diverge according to the molecule and the dose used. These effects could be mediated by various targets such as the vascular endothelial growth factor (VEGF) or by the platelet derived growth factor (PDGF) and their receptors or also by the matrix metalloproteases (MMPs). Dietary polyphenols might also disrupt the adhesion and migration processes of cancer cells through multiple mechanisms [23,25,29].

12 General Introduction |

These chemopreventive effects might also be exploited for therapeutic purposes. Clinical trials have already been started on quercetin, curcumin and polyphenols from green tea [23]. For this group of compounds with multiple targets and pathways involved in the anticarcinogenic mechanism, a metabolomic approach with a global overview of all the effect would be of particular interest to classify and select active molecules.

| General Introduction 13

3. Preclinical anticancer drug development 

3.1. Overview and concerns 

As described previously, spectacular advances in our understanding of the molecular and cellular biology of cancer have been seen in the last decades. However, this knowledge has so far not been translated into major improvements in therapy and long-term survival for many cancers [31]. In turn, the number of new agents for the treatment of cancer approved by the Food and Drug Administration (FDA) has steadily decreased over the past decade and one single compound was approved in 2008 [32]. In addition, only 5% of cancer drugs entering clinical trials reach marketing approval and the failure often occurs very late in the clinical development process. The cost of bringing a new anticancer drug to market is thus over US$ 1 billion [31,33]. Given the cost due to failure at the clinical stages, it is imperative to develop more robust approaches that combine high predictive ability with simplicity and low cost [34].

The successful identification of novel effective anticancer drugs is largely dependent on the use of appropriate preclinical experimental models. Two main approaches can be followed for preclinical development: either, it is based on a library of compounds with unknown mechanism of action or the molecules are designed to hit a cancer specific molecular target. The figure I.4 overviews the typical development plan for a new anticancer agent. Sequential steps are required before a compound enter in clinical phase. In vitro assays allow the selection of active compounds (cell-based or molecular target driven). The selected molecules called the “leads” must go through an optimization step to find an acceptable profile across the whole range of properties needed for an effective drug (solubility, cell membrane permeability, kinetics of metabolization,…). The compound can then be experimented in vivo to evaluate the potential antitumor activities. The pharmacological studies assess drug absorption, metabolism and elimination and finally toxicological studies define the safe dose to give to humans and to develop a formulation. Pharmacological and toxicological studies are also carried out on in vivo models [34,35].

14 General Introduction |

3.2. Approaches and models for preclinical development: 

3.2.1. Cultured cells  

In 1990, the US National Cancer Institute (NCI) introduced the Developmental Therapeutics Programs (DTP). A new screening system was established to replace the method using mouse tumor models. This new approach was based on a panel of 60 cell lines derived from all the major human neoplasms representing the heterogeneity of human tumors. Compounds were tested over a 5-log concentration range against each cell line for their ability to inhibit the growth of, or to kill the cells in a 48 hours assay. 60 dose-response curves were thus obtained. As presented on figure I.5, to facilitate the analysis of the curves, three end-points were calculated for each cell line. The GI50 (growth inhibition) is the negative log10 value required to inhibit the growth of that cell line by 50%. The TGI (total growth inhibition) is the negative log₁₀ minimum concentration that yields no net growth over the course of the assay. The LC50 (lethal concentration) reflects the negative log10 value needed to kill 50% of the cells present at the time of drug addition [36–38].

Figure I.4: overview of the preclinical development steps in the evaluation of new compounds. (Adapted from [35])

| General Introduction 15 These data generates characterized fingerprints profiling the sensitivity/resistance of compounds on all the cell lines, called Mean Graphs. Compounds with similar mechanisms of action tend to present similar patterns of growth inhibition in the 60 cell lines screen and then comparable Mean Graphs [37,39]. An example of Mean Graph for 27 cell lines is presented in figure I.6. The bars depict the deviation of individual tumor cell lines from the overall mean value of GI50 for all the cells tested [36].

Figure I.5: Three endpoints (GI50, TGI and LC50) calculated from 5-log dose response curves for compounds tested in the NCI 60 human tumor cell line screen. In this graph, cell line A is more sensitive than cell line B.

Even at the maximum concentration tested, cell line B did not reach the TGI or LC50. [37]

Figure I.6: Mean graph or profile of 27 cell lines response for two test compounds. For each cell line, the deviation from the mean value of GI50 is represented by the bars. [36]

16 General Introduction |

Paul and colleagues developed a computerized pattern recognition algorithm named COMPARE. It calculates the linear correlation coefficient between the data over all cell lines for the pattern of interest and the thousands of other compounds in the database. Then, it returns a list with the highest correlations. Thus, it can be determined whether a molecule with an unknown mechanism behaves similarly to drugs of defined mechanism previously screened [37,39]. The resulting “matrix COMPARE” correlations among all the approved drugs can be hierarchically clustered; the dendrogram is shown in figure I.7.

Figure I.7: Clustering of all drugs tested on the NCI60 cell lines.

Correlation coefficients comparing the GI50 patterns of each drug with all other drugs were hierarchically clustered using Ward algorithm. The color is attributed according to the mechanism:

purple for signaling agents; blue for alkylating and other DNA damaging agents; turquoise for tubulin binders; orange for topoisomerases poisons; green for antimetabolites and nucleosides; red for hormonal agents and gray for all others. [38]

| General Introduction 17 Some compounds produced remarkably different fingerprints. These COMPARE negative compounds indicate a unique mechanism of action. A program was also initiated to characterize “Molecular targets” within the 60 cell lines panel. Molecular targets in this context denote measurable entities in the cell lines and are for example, the mutation status of important genes in cancer (p53, Ras,…) or the quantification of protein such as cyclins, the RNA levels for tyrosine kinases or phosphatases,…

These molecular target data can also be visualized in Mean Graphs and COMPARE can be used to identify positive correlations, where cell lines with higher levels of a target tend to be more sensitive to a compound [35,37,40]. 85% of the compounds screened had shown no evidence of anti- proliferative activity and a pre-screen was thus introduced in 1999. The synthetic compounds were firstly screened in three highly sensitive cell lines: MCF-7 breast cancer, NCI-H460 large cell lung cancer and SF-268 glioblastoma cell lines. This step has avoided the unnecessary and costly full scale evaluation in the 60 lines panel of many inactive compounds [35,36,40]. Finally, the NCI screening program is technically simple, relatively fast, cheap, reproducible and provides indicative data of mechanistic and target interactions. Yet, it is not without limitation. In vitro methods are always susceptible to false-positive and false-negative results. Moreover, the selection is only based on cytostatic and cytotoxic properties of the compounds.

3.2.2. Target­oriented approach 

This approach is also called the gene to drug approach. The target is defined here as a molecular characteristic of the tumor recognized to play a key role in its development and progression. The improvements in the understanding of the biological principles underlying the genesis and progression of cancer lead to the identification of various molecular anomalies required for the malignancy transformation of a normal cells and the maintenance of cancer cells. Therapy targeting these molecular abnormalities was the subsequent step and generates the so-called targeted agents. These molecules are divided in two main classes: small molecules inhibitors and monoclonal antibodies. The perspectives to guide the preclinical and clinical development of this new type of targeted anticancer agents change in comparison to molecules with unknown mechanism of action. A biochemical assay is required to validate the functional inhibition of the target in different cellular context. The choice of the models is also crucial; it must be characterized for the relevant mutation or expression of the target protein or at least express the target of interest [33,35].

Imatinib represents the best example of a drug that specifically targets the pathogenic lesion of a human tumor. It was shown to suppress the proliferation of brc-abl-expressing cells with minimal effect on normal cells. Brc-abl kinase is a product of chromosomal translocation that occurs in more than 90% of the chronic myeloid leukemia (CML) and is demonstrated to have a causative role in the development of CML. Trastuzumab is another example of targeted agent and is directed against the HER2 receptor. It is mostly used for the treatment of HER2 positive metastasized breast cancer. The

18 General Introduction |

binding of trastuzumab to HER2 results in attenuation of aberrant HER2 kinase-associate signal transduction, with changes in cell cycle distribution [35].

The inhibition of pathways that are the hallmarks of cancer appear initially as an efficient strategy.

However, selective inhibition of an enzymatic target have unexpected consequences. Mechanisms of resistance are rapidly set up and this is more likely with highly selective targeted agents. Even Imatinib becomes ineffective after prolonged used. Two of the most studied targets relate to the inhibition of angiogenesis. Preventing the remodeling of the extracellular matrix is likely to result in tumors becoming more dense with increased hypoxia, decreased responsiveness to anticancer treatments and increased development of aggressive phenotypes including metastases. As described in the first part of the introduction, cancer cells can exist in a variety of states, even within the same tumor. It is thus unlikely that all will be equally responsive to any one class of highly targeted anticancer agents [32].

3.2.3. Animal models 

3.2.3.1. Hollow Fiber assay 

This assay was developed at the NCI to fill the gap between the in vitro cell-based assay and human xenograft model in immune-deficient mice. It constitutes a relatively rapid and cost-effective demonstration of in vivo activity and better predicts which compounds found active in the 60 cell lines panel would be active in the subsequent xenograft model. This selection was required due to the high cost, the number of animals and the time associated with test on in vivo models [35,41].

Human cancer cells are grown in biocompatible hollow fibers for 24 to 48 hours. These fibers are then implanted in nude mice. They contain small pores that retain cells but permit the entry of anticancer molecules. Mice are treated with compounds at two doses for up to 4 days, fibers excised and analyzed for cell viability [35,40].

3.2.3.2. Human tumor xenograft 

Establishment of human tumors in nude mice which are immune-deficient can be obtained both by inoculating human cancer cells cultured in vitro or by direct implantation of patients tumor or biopsy derived fragments or cells. Morphological and molecular properties of the original tumor are better retained with xenografts derived from patient biopsies while those derived from cultured cells show a more homogeneous and undifferentiated histology. However, a high transplantation failure rate is observed for xenografts obtained directly with patient biopsies [35,40].

| General Introduction 19 Compounds of interest are administered and various parameters are measured. The activity of a molecule is defined as the tumor growth delay when treated and untreated mice are compared.

Toxicity can be evaluated by monitoring body-weight loss and drug-related death. The value of the predictions obtained with this kind of models is controversial, especially for targeted therapy. For targeted agent, it is now necessary to molecularly characterize the different xenograft models to ensure the expression of the drug target [34,35,40].

3.2.3.3. Orthopic tumor models 

These models better mimic the physiology, the morphology and the growth characteristic of clinical disease because tumor cells are implanted into the organs from which they are derived. The metastatic process has been demonstrated to be more efficient in these conditions. Despite the obvious clinical relevance of orthopic models, they are accompanied by several limitations including technical skills (complex surgical procedure is required), time and costs [35,40].

3.2.3.4. Genetically engineered cancer models (GEM) 

GEM have meaningfully contributed to our understanding of the molecular pathways responsible for the initiation and progression of tumors but have also highlighted the importance of several genes in carcinogenesis. With an intact immune system, GEM closely reflect the complex interaction of tumors with their microenvironment, an aspect of carcinogenesis missing in xenograft models. However, GEM are not frequently used at the preclinical level because they are very expensive and time- consuming and their use are often restricted by intellectual properties rights of patents [34,35,40].

3.3. Metabolomic as a new tool for preclinical screening 

Despite the use of various preclinical models and the development of molecular targeted therapeutics, the attrition rate of new anticancer drugs in clinical trials is disappointingly high. The decreasing number of novel drugs every year makes for a renewed interest to develop novel approaches. One of the promising tools for new strategies is the use of metabolomics [42]. Metabolomics is the study of global metabolites profiles in a system (cell, tissue or organism) under a given set of conditions.

Metabolites are the end product of gene expression and enzyme activity of organisms. The metabolome indicates the state of an ongoing biological situation, and the changes in metabolite concentration and/or composition may describe this situation better than genomics or proteomics [42,43]. Various techniques can be exploited for metabolic profiling. Mass spectrometry coupled with liquid or gas chromatography is the analytical method presenting the highest sensitivity. NMR spectroscopy is also a method of choice to measure the metabolites because of its reproducibility, its short measurement time, the ease of quantification and mainly the straightforward metabolite identification [42–44].

20 General Introduction |

Metabolomics has been used in a wide range of applications such as the detection of biomarkers in biofluids (urine, blood), the identification of active compounds in plants or for the quality control of phytomedicines,… [45]. This technique was also applied for cancer research in many different fields.

Monitoring chemical components in malignant cells provides a metabolic snapshot clearly different from that of normal cells as cancer cells undergo significant changes in their metabolism including a redistribution of metabolic networks. Various studies have demonstrated that the level of several metabolites appears to be important quantitative biomarkers to distinguish normal and diseased conditions [42]. One of the more relevant examples in cancer diagnosis was realized in breast cancer cells. Compared to benign tumor or healthy tissue, the level of total choline containing compounds increased while the level of glycerophosphocholine and glucose decreased [46,47]. Metabolomics can be used in cancer diagnosis, to assess the response to a therapy but also contributes to the search for an anticancer lead [42,44].

This technology provides a view of all metabolic changes occurring after exposure to a certain anticancer agent and is thus a mean to monitor the effects of drugs. Measuring all interconnected cellular network gives more information than the use of single molecular markers. As an example, a study of neuroblastoma cell lines based on NMR spectroscopy evidence the possibility to predict the response of the resistance of the cells to cytotoxic drugs (i.e. cisplatin, irinotecan, etoposide) [48].

Several anticancer drugs were tested on the breast cancer cell lines showing different hormonal response and metastatic potential. NMR spectroscopy on treated cells revealed a correlation between the mode of action of anticancer drug and the observed changes in cell metabolic profiles. Briefly, cells exposed to antimicrotubules (paclitaxel, vincristine, colchicine) show a significant increase in intracellular glycerophosphorylcholine (GPC) while it was not observed with other drugs (methotrexate or doxorubicin). Several studies suggest that tumor metabolic profile changes could be exploited to predict the response to anticancer treatment faster than current method [42,49].

| General Introduction 21

4. Infrared spectroscopy 

4.1. General principles 

Infrared spectroscopy is a relatively old analytical technique with a wide range of applications. This technique is based on the vibrations of the atoms of a molecule. Every atom within a molecule oscillates around an equilibrium position. This induces changes in bond length and bond angles. The frequency of these motions is within the IR region of the electromagnetic spectrum [50,51]. As shown on figure I.8, the IR region of the spectrum extends from the visible region until it overlaps the microwave [52]. For historical reason, the unit preferentially used to characterize radiations in IR spectroscopy is the wavenumber ν which is the number of waves per centimeter and corresponds to the reciprocal of the wavelength. The range of the infrared region goes from 10 to about 10 000 cm^-1. The IR window can be divided in three regions: near-, mid- and far-infrared. In most infrared spectroscopic analyses, the mid-infrared region (4000-400 cm^-1) is used and especially on biological samples as it fits the vibrational and rotational frequencies of organic molecules characterizing these samples [51].

Figure I.8: The electromagnetic spectrum [52]

An infrared spectrum is obtained when measuring the intensity of an IR radiation at a particular energy before (IR) and after (IS) passing through a sample. The transmittance corresponds to the ratio and the absorbance is calculated as followed: log . An IR spectrum is commonly plotted with the absorbance as a function of the wavelength. It contains various absorption peaks which appear at wavenumbers corresponding to the frequencies of vibration of molecular bonds present in the sample. Actually, IR light interacts with a bond only if the energy of the radiation matches the vibrational transition energy of this bond. The absorption wavenumber of a chemical bond depends on the relative mass and the geometry of the atoms. For example, no FTIR spectrum of N2 can be obtained as no change in dipole moment occurs during the vibrational motions [51].

22 General Introduction |

4.2. Fourier transform infrared technology 

Traditionally, dispersive instruments were used to record IR spectra. They were equipped with a monochromator strongly limiting the light energy from IR source and measured one wavelength after the other. A huge progress was achieved with the development of Fourier transform infrared spectrometers. Collecting data for all the frequencies simultaneously constituted the greatest advantage of this new technology [53].

The principal component of these spectrometers is the Michelson interferometer illustrated on figure I.9. It consists of one source, two perpendicularly mirrors (one stationary and one moving) and a beamsplitter. The incident beam is divided in two in contact with the splitter: half is sent to the fixed mirror and half to the moving mirror. These two beams are then reflected toward the splitter and are gathered before crossing over the sample. The addition of the two beams results in constructive and destructive interferences according to the moving mirror position.

Figure I.9: Schematic of a Michelson Interferometer (Adapted from [53])

The measured interferogram is thus the intensity of the beam transmitted as a function of the position of the moving mirror. The IR spectrum can then be reconstructed using the Fourier transform.

The development of this new technology considerably improved the quality of the spectra. As all the frequencies are recorded in a single measurement, the acquisition time significantly decreased (from hours down to a few seconds). It thus allowed recording many scans of the same sample to be average and lead to enhance the signal to noise ratio. Another improvement is called the Jacquinot advantage.

As no slit is present in the interferometer, all the energy reaches the detector. The spectral resolution

| General Introduction 23 is only related to the distance covered by the moving mirror. An internal reference laser monitors the moving mirror position and is used as an internal wavelength calibration. Therefore, the wavelength accuracy reaches 0.01 cm^-1.

4.3. Infrared spectroscopy techniques 

4.3.1. Transmission spectroscopy 

This mode of measurements is the most frequently used IR method. It is simply based on the absorption of infrared beam at specific wavelength as it passes through a sample. The window used for the deposition of the sample must be transparent to IR light (e.g. Barium fluoride, calcium fluoride or zinc selenium). This technique provides good signal to noise ratios. However, as the signal crosses the entire thickness of the sample, it is limited to a few micrometer thick samples [53].

4.3.2. Attenuated total reflection technology 

In attenuated Total Reflection (ATR), the IR radiation is directed into the ATR crystal containing a high refractive index medium (germanium, diamond), called internal reflection element (IRE).

Several internal reflections occur within the ATR crystal, depending on its length, until the beam comes out and reach the detector. The absorption comes from the interaction between the sample and the electric part of the evanescent wave created by the internal reflections and present at the crystal- sample interface. The absorption arises only if the sample is in intimate contact with the IRE. The evanescent wave is characterized by its amplitude which falls down exponentially with the distance to the interface. In comparison with transmission mode, it avoids any problem of signal saturation (deviation of Beer Lambert law) related to the thickness of the sample [54].

Figure I.10: Comparison between Transmission Infrared Spectroscopy and Attenuated Total Reflection (ATR).

[55]

24 General Introduction |

4.3.3. FTIR micro­spectroscopy 

Coupling infrared spectroscopy with microscopy has led to the development of a new technology called infrared micro-spectroscopy. It combines high spatial resolution as obtained by microscopy and the chemical data from IR spectroscopy. This combination can be achieved by two optical configurations:

 Mapping: this technique is a microscopically point by point sequential analysis. It is based on the radiation restriction and light condensing at the sample plane. The aperture size of the microscope defines the sample area which is analyzed. By moving a XY stage, point measurements can be repeated at consecutive positions through a larger sample area. Imaging large area is rather slow [56,57].

 FPA Imaging: for this second approach, the entire field of view is illuminated in contrast with the mapping method in which a small sample region is considered. It involves the segmentation of the transmitted radiation beam at the detection plane. No aperture is required as the contributions from adjacent sample areas are directly segmented onto the detector array. The key element of this approach is the IR multichannel detector, termed focal plane array (FPA) detector. It is composed of thousands of individual detectors (pixels), each one collecting data from a specific area of the field. The actual spatial resolution highly depends on the diffraction limits of the spectral wavelength which ranges from 5.5 to 10 µm for IR light. The main advantage of the multichannel detectors is that it reduces dramatically the recording time [56].

4.4. FTIR spectroscopy of biological molecules 

For many years, FTIR spectroscopy has been intensively used to characterize organic compounds. It is actually applicable to a wide range of samples in a variety of physical states, liquid, solid or powders. FTIR spectroscopy has largely been employed to study membrane lipids. Spectra of lipids provide a unique signature of the lipid class and fine details of the structure (chain unsaturation and length). The structure and organization of biomembrane can also be studied. It allows the detection and characterization of lipid phase transition and the measurement of lipid orientation in monolayer/multilayer systems [58,59].

FTIR spectroscopy is also a method of choice for the experimental determination of protein secondary structure [60]. Amide vibrations are the largest bands in protein spectra and are based on the amide bond present in proteins. Nine characteristic amide bands have been identified but only three of them are usually used to investigate the secondary structure of protein. The exact frequencies of amide I (C=O stretching, 1700-1600 cm^-1) and amide II (N-H bending, 1600-1500 cm^-1) absorption is

| General Introduction 25 influenced by the strength of hydrogen bonds involving amide C=O and N-H groups and the geometry of the polypeptide chain. Each type of secondary structures is associated with specific frequencies at which amide I and II occur [51,61].

Malins and his colleague worked on the structure of the DNA. They recorded spectra of extracted DNA from normal and cancer cells. They evidenced spectral differences between DNA molecules from healthy and diseased tissue of various cancers (breast, prostate,…) [62]. More recently, they also treated mice with a carcinogen leading to the development of tumor. They noticed on IR spectra of the extracted DNA that a particular spectral profile appeared in cells turning into malignant cells. This phenotype was observed prior to any morphological change could be detected on a tissue section by a pathologist. Moreover, a simultaneous treatment with an antitumour drug, cyclophosphamide, inhibits the development of this cancer phenotype. They concluded that FTIR technique could be exploited to identify new agents that would delay or prevent carcinogenesis [63].

4.5. FTIR  spectroscopy  as  a  new  tool  to  study  complex  organism  

The numerous advantages of Fourier transform technology and the development of powerful computer lead this technique to become a sensitive and powerful tool to record fingerprints of complex mixtures such as biological samples.

Figure I.11 : Infrared spectra of cells and their main components.