Régis Gasper
Infrared spectroscopy as a new tool for the screening of antitumoral agents inducing original therapeutic action.
Service de Structure et Fonction des Membranes Biologiques.
Le moment des remerciements est toujours un peu particulier. Il me faut résumer plusieurs années de bonheur en quelques lignes.
A tout seigneur tout honneur, mes premières pensées vont à Erik. Tu as su imposer un élan scientifique au présent travail. Ta rigueur et ton positivisme m’ont servi de modèle. Je voudrais te remercier pour ton soutien sans failles au cours de ces années.
Je tiens aussi à souligner tout particulièrement toute l’aide que j’ai pu recevoir de Robert Kiss qui a toujours répondu présent pour m’apporter son savoir scientifique. A chaque occasion il a su hisser ma motivation au plus niveau. Ce travail ne serait certainement pas le même sans lui. Merci à Tanja également d’avoir comblé mes lacunes en biologie lors de l’écriture des papiers.
Le moment est venu à présent de remercier mes deux « parrains de science ».
JM, sans qui je n’aurais même pas mis le pied dans une carrière scientifique.
Anthoula qui m’a initiée au joyeux monde de la spectroscopie infrarouge de cellules et de son corollaire : une playlist conséquente dans son disque dur, histoire de décompresser.
Pour finir avec ce petit tour des pontes, un grand merci à Guy, Fabrice, Michel et Vincent pour leurs conseils éclairés et le temps qu’ils ont passé (malgré un horaire parfois rikrak) à partager leur connaissances avec moi.
Je ne pourrais écrire ces lignes sans citer les joyeux membres du cinéclub : Adelin (avec qui tout à commencé), Matthieu (pour sa gentillesse toujours au top), Fab I (pour son intégrité), Fab II (pour la qualité de son amitié… et de ces films). A ce noyau dur ce sont greffés « les petits jeunes » les 2 Nico’s et Ben. Merci à vous pour ces précieux moments de détente mais également, thèse oblige, pour les discussions scientifiques autour d’un verre. On ne travaillait pas sur le même sujet mais c’est justement ce recul qui m’aura permis de progresser.
Les joyeux membres du SFMB : Anastassia, Boris, Cédric, Caroline, Chantal, Emilie(s), JP, Moussa, Pamela, Rosie, Sajid … et les autres qui sont passés en coup de vent (c’est là que j’espère n’oublier personne... ). Les années passées à vos côtés ont été véritablement agréables. Je pense que les week- ends labo resteront dans ma mémoire de longue années encore. Merci à tous.
Un petit mot tout particulier pour Audrey et Allison. Cela aura été très agréable de travailler avec vous. Bonne continuation.
Et enfin, Rabia qui aura partagé le même bureau que moi pendant 5 ans. Entre éclats de rire et de joie, crises de larmes et moments de confidence (bon j’avoue là c’est la Méditerranée qui parle), elle fait partie de la famille maintenant. Donc je m’en vais mais à bientôt.
Je tenais également à remercier le Mathias. Il fut mon premier voisin de labo, pendant mon mémoire.
Depuis nous avons tissé une amitié qui nous emmène chaque année en pèlerinage à Londres.
Mais également Laurent, dit le Broh. On se connaît depuis 10 ans maintenant. Ton apport à cette thèse n’aura pas été scientifique et pourtant ce travail ne serait pas le même si nous n’avions pas passé tout ce temps ensemble.
Avant de finir, ceux sans qui je ne saurais pas le même sans leur conseils, leur encouragement et l’éducation qu’il m’ont apporté : mes parents. Vous avez été parfait. Et toi aussi frérot.
Mes dernières pensées vont à celle avec qui je partage ma vie depuis plus de 4 ans maintenant, Kheiro- Mouna. Les mots sont trop faibles pour exprimer mes sentiments mais ils sont tout à toi.
Merci à tous.
ABBREVIATION LIST 5 CHAPTER 1: GENERAL INTRODUCTION 7
1.1CANCER 7
1.2DRUG SCREENING IN ONCOLOGY 10
1.2.1HISTORIC 10
1.2.2MODERN SCREENING 10
1.2.3HIGH THROUGHPUT SCREENING 13
1.3INFRARED SPECTROSCOPY 16
1.3.1FOURIER TRANSFORM INFRARED TECHNOLOGY 17
1.3.2INFRARED SPECTROSCOPY OF MICROORGANISMS 19
1.3.3INFRARED SPECTROSCOPY ON CELLS AND TISSUES 20
1.3.4ATTENUATED TOTAL REFLECTION TECHNOLOGY 26
1.4MASS SPECTROMETRY 29
1.5CARDIAC GLYCOSIDES AS ANTI-CANCER DRUGS 31
1.5.1GENERAL STRUCTURE 31
1.5.2THE NA(+)/K(+)ATPASE RELATIONSHIP 31
1.5.3THE INOTROPIC EFFECT 34
1.5.4TOXIC AND ANTITUMORAL EFFECT 35
1.6CELLULAR LIPIDS 39
1.6.1GLYCEROPHOSPHOLIPIDS 39
1.6.2SHINGOLIPIDS 42
1.7DATA ANALYSIS 44
1.7.1PRE-PROCESSING OF THE DATA 44
1.7.2STATISTICAL ANALYSIS 46
1.7.2.1PRINCIPAL COMPONENT ANALYSIS 46
1.7.2.2WARD’S CLUSTERING METHOD 49
1.7.3TWO-DIMENSIONAL CORRELATION ANALYSIS 51
CHAPTER 2: AIM OF THE WORK 55 CHAPTER 3: IR SPECTROSCOPY AS A NEW TOOL FOR EVIDENCING ANTITUMOR DRUG SIGNATURES 57
Table of content
2
3.2.2CELL CULTURE 61
3.2.3IN VITRO OVERALL GROWTH DETERMINATION 61
3.2.4QUANTITATIVE VIDEOMICROSCOPY FOR CELLULAR IMAGING 62
3.2.5FTIR SPECTROSCOPY 62
3.2.6LIPID EXTRACTION 63
3.2.7DATA ANALYSIS. 63
3.3RESULTS 64
3.3.1OUABAIN-INDUCED EFFECTS ON THE GROWTH OF HUMAN PROSTATE CANCER
PC-3 CELLS 64
3.3.2EVALUATION OF THE POTENTIAL OF INFRARED SPECTROSCOPY TO YIELD A
SIGNATURE FOR OUABAIN ACTION ON CELLS 66
3.3.3PCA SPECTRAL ANALYSIS 68
3.3.4STUDENT T-TESTS 69
3.3.5OUABAIN TREATMENT OF PC-3 CELLS AFFECTS LIPID CONTENT AND/OR
LIPID TYPE 71
3.4DISCUSSION 73
CHAPTER 4: FTIR SPECTROSCOPY REVEALS THE CONCENTRATION DEPENDENCE OF CELLULAR MODIFICATIONS INDUCED BY
ANTICANCER DRUGS 79
4.1INTRODUCTION 81
4.2MATERIALS AND METHODS 82
4.2.1CELL CULTURE AND TREATMENT. 82
4.2.2FTIR SPECTROSCOPY. 82
4.2.3DATA ANALYSIS. 83
4.3RESULTS AND DISCUSSION 84
CHAPTER 5: EFFECTS OF THE CONFLUENCE RATE ON THE FTIR SPECTRUM OF PC-3 PROSTATE CANCER CELLS IN CULTURE 87
5.1INTRODUCTION 89
5.2MATERIALS AND METHODS 90
CELL CULTURE AND TREATMENT. 90
FTIR SPECTROSCOPY. 91
DATA ANALYSIS. 91
5.3RESULTS 93
5.4DISCUSSION 97
CHAPTER 6: FTIR SPECTRAL SIGNATURE OF CARDIOTONIC STEROIDS WITH ANTITUMORAL PROPERTIES ON A PROSTATE
CANCER CELL LINE 99
6.1INTRODUCTION 101
6.2.MATERIALS AND METHODS 104
6.2.1.COMPOUNDS 104
6.2.2.CELL CULTURE 105
6.2.3.IN VITRO OVERALL GROWTH DETERMINATION 105
6.2.4.FTIR SPECTROSCOPY 105
6.2.5.DATA ANALYSIS 106
6.3.RESULTS 108
6.3.1.PC-3 CELL SPECTRA TREATED WITH DIFFERENT CARDIOTONIC STEROIDS.108
6.3.2.PCA ANALYSIS 109
6.3.3.INCREMENTAL STUDENT T-TESTS 114
6.3.4.COMPARISON OF SPECTRAL MODIFICATIONS INDUCED ON PC-3 CELLS BY
CARDIOTONIC STEROIDS AND DOXORUBICIN. 115
6.4.DISCUSSION 117
CHAPTER 7: TIME DEPENDENCE OF CELLULAR CHEMICAL CHANGES INDUCED IN PROSTATE PC-3 CANCER CELLS BY TWO
STRUCTURALLY RELATED CARDENOLIDES MONITORED BY FTIR SPECTROSCOPY 121
7.1INTRODUCTION 122
7.2MATERIALS AND METHODS 124
7.2.1COMPOUNDS 124
7.2.2CELL CULTURE AND DRUG TREATMENT. 124
7.2.3FTIR SPECTROSCOPY 124
7.2.4DATA ANALYSIS 125
7.2.5TIME DEPENDENCE 125
7.2.62D SPECTROSCOPY 126
7.2.6.1GENERALIZED 2D CORRELATION SPECTROSCOPY 126
7.2.6.2NORMALIZED 2D MAPS. 127
7.3RESULTS 128
7.3.1TIME DEPENDENCE 129
7.3.2STUDENT TESTS 130
7.3.32D CORRELATION ANALYSIS 131
7.3.3.12D SYNCHRONOUS MAPS 132
7.3.3.22D ASYNCHRONOUS MAPS. 136
7.4DISCUSSION 140
CHAPTER 8: OUABAIN-INDUCED MODIFICATIONS OF PROSTATE CANCER CELL LIPIDOME INVESTIGATED WITH MASS
SPECTROMETRY AND FTIR SPECTROSCOPY 143
8.1INTRODUCTION 145
8.2MATERIALS AND METHODS 146
8.2.1COMPOUNDS 146
Table of content
4
8.2.3LIPID EXTRACTION 147
8.2.4MASS SPECTROMETRY 147
8.2.5FTIR SPECTROSCOPY 147
8.2.6DATA ANALYSIS. 148
8.2.6.1PRE-TREATMENT OF THE SPECTRA 148 8.2.6.2UNSUPERVISED STATISTICAL ANALYSIS 148 8.2.6.32D HETERO-SPECTRAL CORRELATION ANALYSIS 149
8.3RESULTS 150
8.3.1MASS SPECTROMETRY 150
8.3.2FTIR SPECTROSCOPY 154
8.3.32D HETERO-SPECTRAL CORRELATION ANALYSIS 156
8.3.4QUANTITATIVE ANALYSIS OF LIPID MODIFICATIONS 158
8.4DISCUSSION 159
CHAPTER 9: GENERAL CONCLUSIONS 161 REFERENCES 165 PUBLICATIONS 182
Abbreviation list
2D: Two Dimensional
ATP: Adenosine-5'-triphosphate ATR: Attenuated Total Reflexion CCD: Charge Coupled Device CID: Collision-Induced Dissociation CS: Cardiotonic Steroid
CYP: Cytochrome P450 DNA: Deoxyribonucleic Acid
EGFR: Epidermal Growth Factor Receptor ERK: Extracellular Signal-Regulated Kinases ESS: Error Sum of Square
FDA: Food and Drug Administration FTIR: Fourier Transform infrared CG: Cardiac Glycosides
GGR: Global Growth Ratio h: Hours
H/D: Hydrogen/Deuterium HFA: Hollow Fibre Assay
HTS: High Throughput Screening IR: Infrared
IRE: Internal Reflection Element
MAPK: Mitogen-Activated Protein Kinases MCT: Mercury Cadmium Telluride
MS: Mass spectrometry
NF-kB: Nuclear Factor kappa-light-chain-enhancer of activated B cells MIR: Mid-Infrared
NIR: Near-Infrared
NCI: National Cancer Institute
Abbreviation list
6 PCA: Principal Component Analysis
PE: Phosphatidylethanolamine PG: phosphatidylglycerol pRB: Retinoblastoma protein PS: Phosphatidylserine RNA: Ribonucleic Acid
ROS: Reactive Oxygen Species RyR2: Ryanodine receptor SM: Sphingomyelin
PI3K: phosphatidylinositol-3 kinase SR: Sarcoplasmic reticulum
UV: Ultraviolet
Chapter 1: General introduction
1.1 Cancer
Tumorigenesis, or tumor development, occurs as a multistep process that reflects the genetic alterations, each conferring one or another type of growth advantage, that drive the progressive transformation of human cells into highly malignant derivatives (Hanahan and Weinberg, 2000). Cancer cells share the common defects in regulatory circuits that govern normal cell proliferation and homeostasis. More than hundred types of cancer have already been highlighted and, with them, a high number of disrupted regulatory circuits. Despite this complexity, there are 6 essential acquired capabilities in cell physiology that together seem necessary to induce malignant growth (Figure 1.1):
Introduction
8 Self sufficiency in growth signal: The Ras/MAPK kinase is one of the most important pathways that transmit signals from cell membrane to nucleus. Activated by diverse stimuli such as Epithelial Growth Factor, this pathway is known to regulate various cellular responses. In particular, its role in cell cycle progression in G1 phase and cell proliferation is well established (Torii et al., 2006). The proliferation of normal cells is known to strongly depend on the presence of these growth factors. Mutation of the ras oncogene, present in about one quarter of all the tumors, encodes for proteins that release continuous stream of mitogenic signals into the cells, making the cells free from their regulated growth signal dependence (Hanahan and Weinberg, 2000).
Insensitivity to growth-inhibitory signal: Access to the G1 phase of the cell cycle is largely dependant of the pathway governed by the retinoblastoma protein (pRB). This control circuit can be disturbed by several genetic and biochemical alterations present in tumor cells. If these alterations depend on the tumor type, several evidences suggest they all converge to the loss of growth suppression by pRB in a majority of human cancer (Hahn and Weinberg, 2002).
Evasion of programmed cell death: The p53 gene represents one of the most studied tumor suppressor genes in biology (Pietsch et al., 2006). When p53 functions normally as a regulator of apoptosis, the response to cellular stresses causing hypoxia, oncogene activation and DNA damage, is the induction of apoptosis through the p53 pathway (Okada and Mak, 2004). The pathway controlled by p53 tumor suppressor protein is altered in most, if not all, cancers in human. Elimination of functional p53 appears to be sufficient to inactivate the apoptotic machinery in many types of cancer (Shen and White, 2001;Hahn and Weinberg, 2002).
Limitless replicative potential: About 50 years ago, Hayflick’s work pointed out the finite replicative potential of normal cell lines After about 50 cells generation, human cultured cells enter a non growing but viable state called senescence (Hayflick and Moorhead, 1961). Cancer cells, in contrast, proliferate indefinitely and are therefore considered to be immortal. The three acquired capabilities named above lead to an uncoupling of cell’s growth from signal in its environment but cannot entirely explain immortality. Telomeres attrition (loss of about 100 base pair of telomeric DNA from the end of every chromosome at each population doubling) present in normal cells is
responsible for senescence process (Stewart and Weinberg, 2002). Their maintenance appears to be one of the important event in the tumor phenotype establishment (Stewart and Weinberg, 2000;Hahn and Weinberg, 2002).
Sustained angiogenesis: Angiogenesis is defined as the growth of new blood vessel.
The oxygen and nutrients cell needs require at least 100 µm capillary vessels. The ability of tumor cells to induce and sustain angiogenesis seems to be acquired during tumor development by an alteration of gene transcription that changes the balance of angiogenesis inducers and inhibitors (Hanahan and Weinberg, 2000).
Tissue invasion and metastasis: Metastasis is defined as the spread of diseased cells from one organ to another. Only tumor cells possess this capability. This process includes the loss of cell-to-cell adhesion, invasion into the local microenvironment, intravasation1 into the blood and lymphatic vasculature, and extravasation2 into the parenchyma of distant tissues (Hanahan and Weinberg, 2000).
Understanding of biochemical process underlying tumor development is essential to design pharmaceutical compounds that will efficiently fight the disease. Yet, the large variability of activated pathways among all cancer types makes this task a real challenge. So far comprehensive and rationale design of drug turns out to be infeasible and antitumoral drugs are discovered by the mean of intensive screening.
1 In medicine, intravasation refers to the entrance of externally formed matter (i.e. invasion of cancer) into vessels.
2 In the case of maligniant cancer metastasis, it describes the movement of cells out of a blood vessel
Introduction
10
1.2 Drug Screening in Oncology
1.2.1 Historic
Pharmaceutical compounds screening has undergone many modifications since the beginning of the concept, almost five decades ago. In 1955, some studies noticed that the use of transplanted tumor on animal model for drugs potential evaluation offered a better correlation between compound efficacy observed in vitro and their real clinical activity (Suggitt and Bibby, 2005). A panel of three mouse models (sarcoma3, leukemia4, and carcinoma5) was selected for a large scale anticancer drug testing initiated by the National Cancer Institute (NCI). Over time only leukemia tumor was kept for screening. Later it was realizes that a major problem was the fast growth of this tumor. Indeed drug selection essentially resulted in preferential identification of drugs that were active against rapidly growing tumors. 20 years later, the discovery of the nude athymic (nu/nu) mouse and the successful growth of human xenografts allowed the use of a new panel of solid transplantable human tumors. This new panel highlighted antitumoral agents that would have been missed with previous strategy (e.g., taxol). In 1982, NCI established a new cost effective strategy based on a progressive selection. The first step involves a leukemia “prescreen” tumor (P388 model) which is found to be remarkably sensitive to most class of clinically effective drugs.
1.2.2 Modern Screening
Meanwhile the feasibility of using human tumor cell lines for large scale drug screening was investigated. A study on about hundred cell lines showed evidences for a correlation between drug sensitivity measured in vitro and in vivo (Alley et al.,
3 Sarcoma: cancer of the bone, cartilage, fat, muscle, blood vessels, or other connective or supportive tissue.
4 Leukemia: cancer that starts in blood-forming tissue such as the bone marrow and induces production of a large numbers of blood cells that enter the bloodstream. Leukemia is a broad term covering a spectrum of diseases.
5 Carcinoma: any malignant cancer that arises from epithelial cells. This type of cancer can invade surrounding tissue and may spread to other sites.
1988). It opened the door for a new large-scale screening approach, initiated in 1990, when the NCI strategy switched from being “compound oriented” to “disease oriented” with an initial panel exhibiting a total of 60 different human tumor cell lines from diverse histologies derived from seven types of cancer. 2 years later 10 of the original cell lines were replaced by a selection of cell lines arising from 2 new types of cancer (Suggitt and Bibby, 2005). Presently each new compound is tested, over a concentration range, against each of the 60 cell lines, or against cell lines arising from other specific type of cancer. The data are presented in the form of a dose-response curve for every compound on each cell lines. These curves represent the cell line viability against a tested compound as a function of drug concentration. As an example, Figure 1 displays a simplified dose-response curve showing the response of two cell lines to doxorubicin. These curves derived from the cellular response to the drug can be considered as the compound fingerprint. A pattern recognition algorithm (COMPARE) was used in order to determine the degree of similarity between mean profiles generated by similar or different compounds (Paull et al., 1989). Two compounds inducing similar metabolic changes to the cell will tend to have the same cytotoxic pattern along the 60 cell lines, i.e. the same subsets are more or less sensitive for both compounds. Compounds producing a different cytotoxicity fingerprint are called “COMPARE-negative” and are considered to have a unique mechanism of action. Three end points are finally taken into account to determine whether a compound must be considered for further evaluation (Figure 1.2) (Holbeck, 2004):
- GI50 known as the concentration required to inhibit 50% of cell growth.
- LC50 defined as the concentration required to kill 50% of cells.
- TGI50 Total growth inhibition: inhibit 100% of cell growth.
Introduction
12 Figure 1.2: simplified dose-response curve showing the response of two cell lines to an antitumoral agent. 100% represent the normal growth, for a non treated cell line. 0%
represents the growth state at the moment of drug incubation. -100% is the point where no cell left in the culture box (from Holbeck, 2004).
As for the tumors, 3 highly sensitive cell lines were selected for an additional
“prescreen” in 99, i.e. MCF-7 (breast carcinoma), NCI-H460 (lung carcinoma), and SF-268 (glioma). The reason is these three cell lines were shown to efficiently highlight compounds that showed no evidence of antiproliferative activity and can thus reasonably be used to remove inefficient agents from an unnecessary and costly full scale evaluation in the 60-line panel.
Screening with cell lines offers many advantages such as easy and fast handling, low cost, and reproducible data which are indicative of mechanistic activity. The first proposal of the NCI with cell line project was to design a high-throughput in vitro screen able to select a relatively few number of compounds for further evaluation on human tumor xenograft model. Yet, the intrinsic nature of in vitro testing can induce false-positive or false-negative results because of all the lacking in vivo factors (pharmacokinetics, tumor microregions/pH and so on…) able to influence the inherent chemosensitivity of tumor cells. Since 1995, to face the insufficient selection of a unique in vitro testing, in vivo hollow fiber assay (HFA) was implemented on
compounds that successfully passed through the first screen to help reduce the number of agents to be tested on human xenografts (Suggitt and Bibby, 2005). The technique is based on cell line encapsulation in a porous fiber with high molecular cut-off (5 105 Da) allowing the passage of molecules such as growth factor, hormones as well as most proteins. The “loaded” fibers are implanted in a mouse and, once treatment administered (4 days), the fiber is excised for cell viability analysis (Hollingshead et al., 1995). This technique was shown to give results relatively close to in vivo testing.
Final screen selection is performed on human xenografts model in nude athymic mice.
All these studies aim at obtaining preliminary efficacy, toxicity and pharmacokinetic information and to assist pharmaceutical companies in deciding whether it is worthwhile to go ahead with further clinical testing on humans.
1.2.3 High Throughput Screening
Problem with traditional screening lies mainly with the inability to identify mechanisms of toxicity using whole animal assay as a “black box” as well as toxicity assessment on human body. Covering all chemicals available would require billions of euros. The increased emphasis placed by the Food and Drug Administration (FDA) on understanding the mechanisms of action of any new chemical entity encouraged the development of a low-cost screening providing mechanistic information (Pereira and Williams, 2007;Houck and Kavlock, 2008).
High throughput screening (HTS) is presently used on one or several biological pathways. The results of these experiments provide starting points for drug design and for understanding the role of a particular biochemical process. The application of HTS in toxicology are twofold: either a single or small number of chemicals are tested against a wide array of different targets to isolate a toxicity pathway, or a large number of chemicals are analyzed against a small number of key targets (Houck and Kavlock, 2008). Targets can take different shape, from animals to key protein of metabolism. Due to automation and robotic development, throughput from hundred to thousands samples tests (resumed on Figure 1.3) can be achieved.
Introduction
14 Assays aiming at proteins are mainly focused on drug metabolizing enzymes and receptor-binding. Cytochromes P450 (CYP) are one of the most important class of enzymes involved in degradation of exogenous chemicals. Two goals must be achieved by testing activity of this protein against new chemical molecules (Shimada, 2006):
- First, check if molecule degradation does not lead to any toxic metabolites or to deactivation of the molecule therapeutic properties. For further investigation it is important to determine whether active agents are stable enough to reach the aimed target.
- Second, check the possible inhibition of CYP proteins by the chemical tested.
If CYP protein activity is inhibited, another drug administered at the same time could see its toxicity increased.
HTS assays are also often run against ion channels or against a large number of therapeutic candidates (Houck and Kavlock, 2008). For example, functional biochemical assays have been developed to classify unknown chemical agents as agonists, antagonists or partial modulators of estrogen receptor using Förster resonance energy transfer 6 (Liu et al., 2003a) or small fluorescent labeled peptides (Ozers et al., 2005).
Technical development in fluorescent microscopy allowed cell imaging to enter among the screening process techniques. Beyond the speed of the technique, compounds screening can be performed at two levels. At low resolution, tumor cell
6 Förster resonance energy transfer (FRET) describes an energy transfer mechanism between two chromophores.
Figure 1.3: Definitions of screening modes (Houck and Kavlock, 2008)
proliferation can be monitored. At high resolution the population of cell in each cell cycle stage is determined (Gasparri et al., 2004). General development of fluorescent dye also permits the use of high resolution mode to follow and quantify subcellular changes and hence, follow which pathway is activated (Lang et al., 2006).
The use of biomarkers to early drug development is promising as they might aid in preclinical and early clinical decisions such as dose ranging, definition of treatment regimen, or even a preview of efficacy and so improve and shorten the process.
Although the number of publications on experimental biomarkers extends into several thousands each year, only a small number of these will ever achieve approval by FDA for clinical trials (Cummings et al., 2008).
Computational structure-activity relationship between ligand and receptor (Lill, 2007) as well as de novo drug design techniques (Schneider and Fechner, 2005), offer complementary techniques to more cost effective high throughput screening. Yet, considering the large number of potential chemicals as novel anticancer agents (in the order of 1060-10100), even HTS is though to fail in achieving the identification of most promising candidates.
Overall, despite all these outstanding advances, most of the authors agree to say that little positive effects have been seen on the drug discovery industry over the last few decades (Duyk, 2003). Only 68 new oncology drugs were approved for marketing in the United States from 1990 to 2005 (Dimasi and Grabowski, 2007) and it reaches an average of 12 years and $800 million per therapeutic entity to bring a new drug from discovery step to market (Dimasi, 2002;Dimasi et al., 2003). In addition among the 750 000 molecules tested from NCI program, none of these show a potent antitumoral effect, indicating drug screening process needs further improvements. In this context, IR spectroscopy might be particularly useful, as it could bring an specific signature of metabolic modifications induced by any molecule tested.
Introduction
16
1.3 Infrared Spectroscopy
The electromagnetic spectrum is defined as the range of all possible electromagnetic radiation (Figure 1.4). The spectrum covers the electromagnetic wave energies having wavelengths from thousands of meters, such as the radio waves, down to size lower than the angstrom for the gamma rays. In this work, only the infrared part of this spectrum will be of interest. The infrared light, found by Herschel in 1800, covers the wavelengths range from approximately 0.7 m to 1 mm, and can be divided in three regions: the near-, mid- and far- infrared, named after their relation to the visible spectrum. For historical reasons, the unit used to characterize radiations in infrared spectroscopy is the wavenumber, which is the number of waves per centimeter and corresponds to the inverse of the wavelength (1/λ). The spectral window corresponding to mid-infrared light, from 4000 to 200 cm-1, fits the vibrational and rotational frequencies of organic molecules characterizing biological samples. When
Figure 1.4: The spectrum of electromagnetic waves ranges from low-frequency radio waves to high-frequency gamma rays. Only a small portion of the spectrum, representing wavelengths of roughly 400–700 nanometers, is visible to the human eye.
infrared light interacts with a molecular bond, the energy of the light that will be absorbed is the one matching the vibrational transition energy. The absorption wavenumber of a chemical bond depends on the relative masses and the geometry of the atoms. For example, there are 6 theoretical modes of vibrations associated with
the atoms found in a CH2 group: asymmetrical and symmetrical stretching, scissoring, wagging, twisting and rocking (Figure 1.5).
Figure 1.5: Vibrational modes for a CH2 group. + and – indicate movement perpendicular to the plane of the page. The carbon atom is designed by the white circle, hydrogen ones are in blue (adapted from (Silverstein et al., 1991)).
In addition, the coupling between vibrations strongly influence the absorption frequency. In most case the absorbance is used in place of transmittance to represent the intensity as the absorbance at a given wavelength is directly proportional to the concentration in the sample according to Beer’s law.
1.3.1 Fourier Transform Infrared Technology
The first paper that investigated tissue in search for a disease marker with the use of IR spectroscopy was published in Science in 1949 by Blout and Mellors. The experiments required a large amount of materials and spectra were recorded using a
+
+ -
-
Out-of-plane bending or wagging
(ω CH2) In-plane bending
or scissoring (δs CH2) Asymmetrical
stretching (υas CH2)
Symmetrical stretching
(υs CH2)
Out-of-plane bending or twisting
(τ CH2)
In-plane bending or rocking
(ρs CH2)
+
Introduction
18 single beam, manually scanned instruments. Because of the poor quality of the spectra, the field was abandoned (Diem et al., 2004). Things changed with the huge technological advances in the 70’s in spectrometric instrumentation and the use of Michelson interferometer (Figure 1.6) combined with Fourier transform. This enabled the development of Fourier Transform infrared (FTIR) spectrophotometer able to convert all the frequencies emitted by a polychromatic source in an oscillatory signal.
Sum of all the oscillations leads to an interferogram. After its interaction with the sample, an IR spectrum can be reconstructed using a Fourier transform.
Figure 1.6: Basic principles of an FTIR spectrophotometer.
The source emits all the wavelengths of the IR window. IR beam is split in two equal parts by a KBr beam splitter coated with germanium film. One half is directed to a fixed mirror, the other one to a movable one. For rapid scanning interferometers liquid nitrogen cooled mercury cadmium telluride (MCT) detectors are used. The moving mirror yields a sinusoidal signal at the detector for each frequency. The interferogram arises from the superimposition of all the resulted sine curves. The most important feature about interferogram is that every individual point of this signal contains information on the entire IR region. The Fourier Transform is simply a mathematical way to sort out the individual frequencies for a final representation of an IR spectrum.
Development of FTIR has considerably enhanced the quality of IR spectra. First, the method is way faster because it records the IR beam absorption by the sample at all frequencies emitted by the polychromatic source in a single measurement, while each
1
2 Fourier Transform
spectrum
1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 0.05
0.1 0.15 0.2 0.25 0.3 0.35
cm-1
Absorbance
1’
2’
interferogram
IR spectrum Fourier Transform
wavenumber required an independent measure with old (prism or grating based) spectrometers. The spectrum acquisition time fell thereby from hours down to few milliseconds, allowing many scans to be averaged, and in turn the increase of the Signal/Noise ratio leading to better quality spectra. Second, the interferometer contains no more slits that limit considerably the energy that reaches to the detector.
Theoretically, the resolution of FTIR spectrometer is not restricted anymore because it is only related to the distance covered by the movable mirror of the Michelson interferometer. Physically, it is limited by the ability to obtain a perfectly stable speed for the mirror (Naumann, 2000). Nevertheless the wavelength precision and resulting spectrum resolution obtained with modern FTIR spectrophotometer is much higher than for dispersive spectrometers. This allows the subtraction of spectral contaminant such as water, a strong infrared absorber (Chittur, 1998). Third, an internal reference laser checks the position of the movable mirror and the internal wavelength calibration. It allows the wavelength accuracy of most of the FTIR spectrophotometer to lie within 0.01 cm-1. The increase of both the sensitivity and resolution has led to higher quality spectra. In addition, personal computers coupled with interferometer allowed the digitalization of spectral data that can now be easily stored and manipulated (Naumann, 2000). The development of methods for interpreting biological data has led, in the 70 and 80’s, to a growing interest; establishing vibrational spectroscopy as a sensitive method to probe protein secondary structure, dynamics and solvation of biomolecules, and the interactions among them. All together Fourier Transform infrared spectroscopy became a sensitive and powerful tool to record fingerprints of complex mixtures such as biological samples.
1.3.2 Infrared Spectroscopy of Microorganisms
In 1911 W.W. Coblentz was probably the first scientist to put forward the use of IR spectroscopy for analyzing biological sample. Its use to identify and discriminate bacteria was reported as soon as in the 50’ and 60’s (Naumann, 2000). As explained the development of modern interferometric IR spectroscopy and powerful algorithm of multivariate analysis largely contributed to the revival of infrared spectroscopy as a diagnostic tool. 20 years ago, a project aiming at a large scale identification of intact bacteria (Naumann et al., 1991) was started. Once again, technological developments
Introduction
20 microspectroscopy (Essendoubi et al., 2005) allowed fast and large scale studies on microcolonies of bacteria. With the use of IR microscopes biomass requirement for analysis can be scale down to single colony as small as 20 µm in diameter, corresponding to few hundred cells. In addition, the specificity of the method is very high and bacteria classification can be performed at subspecies level (Sandt et al., 2006). These advantages led this technique to be used for the screening of pathogens in several domains such as food industry (Wenning et al., 2002;Rebuffo et al., 2006;Erukhimovitch et al., 2007) or clinical environnement (Goodacre et al., 1998;Kirschner et al., 2001;Winder et al., 2004;Sandt et al., 2006).
1.3.3 Infrared Spectroscopy on Cells and Tissues
Presently, one of the most interesting emerging fields in which infrared spectroscopy is becoming an important tool is medical diagnostic of disease. The two biggest advantages of IR spectroscopy are the absence of any staining procedure and the possibility to record spectra both in vitro and in vivo (Meier, 2005). Yet, if IR spectroscopy can provide a specific fingerprint of any sample, even the most complex ones such as those from biological origin, precise identification of the molecule responsible for specific spectral features cannot be expected. Some IR absorptions bands observed in the mid-infrared (MIR) region between 4000 and 800 cm-1 can be still assigned roughly to the major components of the cells:
- Between 4000 and 3100 cm-1, the IR spectrum is dominated by absorption arising from –OH and N-H stretching mode. In practice this area is often overlapped by liquid water absorption.
- The area between 3100 and 2800 cm-1 shows absorptions derived from C-H vibrations which, in a biological sample, come largely from lipids.
- Between 2800 and 1800 cm-1, there is no absorption due to any biological molecule. Yet in practice, a double peak between 2450 and 2250 cm-1 is observable and can be assigned to atmospheric CO2 absorption.
- Between 1700 and 1500 cm-1, IR radiations are essentially absorbed by proteins and are sensitive to protein conformation in the amide I and II.
- Many absorption bands arising from carbohydrates, nucleic acids or phospholipids are superimposed in the region between 1400 and 900 cm-1.
Figure 1.7 shows a cell spectrum and the related major cell pure component spectra:
lipid (DMPC), DNA, RNA, and proteins. The 3 proteins displayed in Figure 1.7 have three characteristic spectral shapes. Compared to the other components, lipids have a strong absorption between 3000 and 2800 cm-1. Contribution in this region in a cell spectrum derives thus essentially from lipids. Nucleic acids (DNA, RNA) bases absorb mainly between 1740 and 1550 cm-1 and PO2- vibrations between 1300 and 1000 cm-1. Mucin is a highly glycosylated protein. It is characterized by peaks between 1200 and 1000 cm-1 arising from carbohydrates vibrations. Myoglobin is a protein predominantly folded in α helix (73,9 %) while xynalase is a β-sheet folded protein (61,6 %) (Oberg et al., 2003). A zoom on the amide I region shows the conformational differences between the two protein spectra. Finally, an IR cell spectrum represents the sum of all the individual component spectra, weighted with respect to their abundance in the cell. All together, IR cell spectrum gives a unique and very precise fingerprint of the sample studied.
Characteristic
α helix peak Characteristic β-sheet peak
RNA
lipids DNA mucin myoglobin xylanase PC-3 cells
Figure 1.7 : Human prostate cancer cells spectrum (black spectrum above) and main cell components pure spectra.
Introduction
22 Table 1.1 displays more precisely some characteristic bands found in the literature.
These band assignments are obtained from original absorbance or more often, from second derivative of original absorbance spectra.
Table 1.1: frequencies and assignments of absorption peaks in the IR spectra of cells and cell fractions. Asym= asymmetric; sym= symmetric; str= stretching
wavenumber assignment references
~3500 O-H stretching of hydroxyl group (Naumann, 2000)
~3300 N-H str of proteins (amide A) (Goormaghtigh et al., 1994a;Naumann, 2000)
~3030 N-H str of proteins (amide B) (Naumann, 2000)
2959 C-H str (asym) of CH3 (Mantsch and Jackson,
1995;Naumann, 2000)
2934 C-H str (asym) of CH3 (Mantsch and Jackson,
1995;Naumann, 2000)
2921 C-H str (asym) of CH2 in fatty acid (Mantsch and Jackson, 1995;Naumann, 2000;Lasch et al., 2002a)
2872 C-H str (sym) of CH3 (Mantsch and Jackson,
1995;Naumann, 2000)
2852 C-H str (sym) of CH2 (Naumann, 2000;Lasch et al., 2002a)
~1741 C=O str of ester
(Mantsch and Jackson, 1995;Naumann, 2000;Lasch et al., 2002a)
1715
- C=O str of ester - RNA/DNA - COOH
(Mantsch and Jackson, 1995;Naumann, 2000)
1690-1620 Amide I band components
~1685 antiparallel β-sheet of proteins (Naumann, 2000)
~1675 β-turn of proteins (Naumann, 2000)
~1655 α-helical structures (Goormaghtigh et al.,
1994a;Mantsch and Jackson, 1995;Naumann, 2000)
~1637 parallel β-sheet of proteins (Naumann, 2000) 1570- 1530 Amide II band components
1560 C-N str (Goormaghtigh et al., 1994a)
~1540 in plane N-H bending (Goormaghtigh et al.,
1994a;Mantsch and Jackson, 1995)
1515 "Tyrosine" band (Naumann, 2000)
1468 CH2 sym band (scissoring)
(Mantsch and Jackson, 1995;Naumann, 2000;Lasch et al., 2002a)
wavenumber assignment references 1455 various CH2/3 deformation mode
(protein) (Lasch et al., 2002a)
~1400 COO- sym str (Naumann, 2000;Lasch et al.,
2002a)
1379 CH3 sym bend (Lasch et al., 2002a)
1450, 1390, 1310 protein side chains vibration (Diem et al., 1999)
1337, 1282, 1236 CH2 wagging vibrations (Mantsch and Jackson, 1995)
~1240 PO2- asym str (phopholipids, nucleic acids)
(Mantsch and Jackson, 1995;Benedetti et al., 1997;Lasch et al., 2002a)
1155
- C-OH str mode from serine, threonine, tyrosine.
- C-O carbohydrates str+bending
(Wong et al., 1991;Lasch et al., 2002a)
1121 - RNA ribose (Andrus, 2006)
1151, 1078, 1028 glycogen triad of peaks (Diem et al., 1999) 1095, 1084, 1071 ribose triad of peaks from DNA (Diem et al., 1999)
~1085
- PO2- sym str (phospholipids, nucleic acids)
- C-O str (carbohydrates, glycoproteins)
(Mantsch and Jackson, 1995;Benedetti et al., 1997;Diem et al., 1999;Naumann, 2000;Lasch et al., 2002a)
1050 C-O str (carbohydrates) (Lasch et al., 2002a) 968
- C-O phosphodiester moiety (phospholipids, nucleic acids) - Choline vibrations (lipids)
(Fringeli and Günthard, 1981;Lasch et al., 2002a)
Many studies investigated the potential of IR spectroscopy as a tool for disease diagnostic. As all the diseases, without exception, are caused by changes in cellular and/or tissues biochemistry, IR spectroscopy could be applied to the study of disease states in humans. There are many advantages with respect to current diagnostic method (Mantsch and Jackson, 1995):
- There is no need for external perturbation or dependence upon physical state, which make IR spectroscopy a non destructive technique easy to handle.
- Changes in cells or tissue biochemistry precede the morphological alterations, allowing early disease diagnostic.
- Current diagnosis methods are often based upon physician background and his capability to detect tissue abnormalities correlated with a particular physical state, leading to highly subjective diagnosis. In comparison, IR spectroscopy is an instrumental method providing an objective result.
- A less scientific but important aspect is the low cost of this approach, allowing its access in developing countries.
Introduction
24 In modern spectroscopy, the first study on human cells date from 1984. Benedetti et al analyzed 2 series of normal and leukaemic lymphocytes and put forward bands only present in the leukaemic cells (Benedetti et al., 1984). One year later, they underlined that ratio between areas of amide II (~1540 cm-1) and phosphates from DNA (~1085 cm-1) bands has a systematically different value between normal and leukaemic cells, establishing the first known spectroscopic marker for early detection of the disease (Benedetti et al., 1985). A few years later, the group of Rigas with the help of two pathologists showed multiple infrared areas were modified in intensity and shape between human normal and cancer colorectal tissues extracted from the same patients.
They also pointed out differences between these colorectal cancer tissues and colorectal cancer cell lines (Rigas et al., 1990). One year later they evidenced the different grades of the cancer progression by IR spectroscopy from normal cervical tissue to malignant stage (Wong et al., 1991).
These promising advances stimulated many studies, investigating for spectroscopic marker to separate cells type (Chiriboga et al., 1997;Chiriboga et al., 1998a;Chiriboga et al., 1998b) or diagnose disease: differentiation of cancerous and normal esophagus tissues (Wang et al., 2003), grading of lymphoid tumor (Andrus and Strickland, 1998;Andrus, 2006) or human glioma (Steiner et al., 2003). Several studies have also tried to correlate spectral information with biological features. Our laboratory, for example, attempted with success to bridge over migrations properties of different glioma and pancreatic carcinomas cell lines with characteristic spectral wavenumbers (Gaigneaux et al., 2004). IR spectroscopy can also highlight changes occurring in a same cell line. Mourant put forward spectral differences in cells harvested at different growth stages (exponential or plateau) (Mourant et al., 2003). Even the different steps of cell division cycle in exponential phase can be followed by comparison of IR spectra recorded at each phase (Boydston-White et al., 1999). Modification of a cell line properties, such as multiresistance (Gaigneaux et al., 2002) or virus transformation (Salman et al., 2003) can also be evidenced. Detection of cell apoptosis induced by a drug can be achieved by IR spectroscopy (Liu and Mantsch, 2001;Gasparri and Muzio, 2003) and differences can even be detected as early as after 4 hours incubation time (for 6 hours by the use of flow cytometry) (Liu et al., 2001).
To get more insight the spectral investigations of a single cell, IR microspectroscopy can be used. An infrared microscope is composed of a microscope coupled with an IR spectrophotometer. 2 modes are available following the spectrophotometer type:
- The mapping mode: an area of the sample is divided into squares, each one scanned by a moving detector controlled by a computer. For each square, a spectrum is recorded.
- The focal plane array detectors technology: composed of an array of multiple detectors, each one able to record individual spectrum. This technology is much faster than mapping mode but more expensive.
From these two technologies an IR image can be recorded from a sample at a subcellular level. With these technologies, Lasch et al., investigated the spectral weight of each subcellular structure. Their conclusions support the old hypothesis of DNA that is barely detectable by infrared spectroscopy due to the tightly packed form of the double strand (Lasch et al., 2002b). A further study by the same group showed that this conclusion is particularly prevalent in metabolically inactive cells while dividing cells show larger signals attributable to nucleic acids (Diem et al., 2002).
Another interesting result available is the imaging of one HeLa cell suspended in an aqueous environment at a high spatial resolution (Miljkovic et al., 2004).
The recent development of IR imaging has mostly contributed to the rise of IR techniques in the field of medicinal diagnosis. Accuracy and rapidity of IR spectrum recording coupled with development of strong chemometric analyses have made IR spectroscopy a powerful tool for imaging. One of the critical measurement parameter is spatial resolution, normally limited to the order of the wavelength. Nevertheless some computational manipulations and the use of synchrotron light can decrease this restriction (Lasch and Naumann, 2006). Many articles point out the excellent agreement between infrared spectral mapping data and histopathological information (Romeo et al., 2002;Gazi et al., 2003;Lasch et al., 2004). As examples, attenuated total reflection Fourier transform infrared (ATR- FTIR) microspectroscopy with its powerful ability to target individual cells allowed to segregate different kind of cell types within a prostate tissue (German et al., 2006) as well as grades of exfoliative cervical cytology (Walsh et al., 2007). Recently, the benefits of ATR-FTIR imaging for kidney biopsy analysis were described. The authors showed that elimination of spectral artifacts induced by transflection or transmission measurements can be overcome with ATR. In particular, contributions from mineral inclusions present in kidney biopsies, which are strong reflectors with a transflection approach, were eliminate (Gulley-Stahl et al., 2010).
Introduction
26
1.3.4 Attenuated Total Reflection technology
Most of time, IR spectra are recorded with transmission mode, in which an incident IR beam (I0) passes through the sample and the transmitted beam (I) is analyzed (Figure 1.8a).
Figure 1.8: Comparison between Transmission Infrared spectroscopy and Attenuated Total Reflection (ATR)
In Attenuated Total Reflection (ATR), the IR beam is directed into a high refractive index medium, called internal reflection element (IRE), considered to be transparent for the IR radiation. Several internal total reflections occur within the IRE, depending on its length, until the beam comes out and reaches the detector. When the beam hits the surface of the IRE, the electric part of the electromagnetic beam gets out the bounds of the crystal. Absorbance arises from the interaction between the sample and the electric part of the beam, also known as the evanescent wave, present at the crystal–sample interface (Figure 1.8b). This evanescent wave is characterized by its amplitude which falls down exponentially with the distance to the interface (Goormaghtigh et al., 1999). As we have extensively used ATR-FTIR in the course of this work, it is of interest to highlight the advantages and disadvantages of this method.
a
b
Pros and cons of ATR-FTIR spectroscopy with respect to the transmission mode (Goormaghtigh et al., 1999)
- In transmission mode, IR beam reflections can occur between interfaces of plane parallel transmission set up (Figure 1.8) that can lead to energy loss and fringes generation while Total Attenuated Reflection spectroscopy stays clear from these troubles.
- In transmission mode band shapes, different kind of size and shape may be adopted by particles under study leading to artifact in the resulting absorbance spectrum. For example, one of the major problem actually encountered in microspectroscopy of cells derived from dispersion artifact, the so-called Mie Scattering (Mohlenhoff et al., 2005;Bassan et al., 2009;Bassan et al., 2010).
This dependency is not present in ATR experiments.
- As depth penetration of the beam in the sample is limited by evanescent wave, there is no problem derived from deviation of Beer-Lambert law with ATR spectroscopy.
- In spectroscopic analysis of solution, one of the most frequently cause of spectral problem comes from air bubbles which does not occur in ATR spectroscopy.
- Because of the exponential nature of the evanescent wave (Figure 8), there is not consistent beam absorption along the sample (i.e.: the first layer contributes more than the 10th). Experimenter must take care of this particularity when analyzing its data to avoid possible artifact.
- According to the refractive index of the crystal used and the penetration angle of the beam, ATR spectra can be shifted with respect to true absorbance.
- As the beam passes through the IRE, a part of the signal intensity is absorbed and the Signal/Noise ratio strongly diminishes. Yet with an appropriate choice
Introduction
28 of IRE, absorption occurring in the spectral area of interest is relatively weak and final spectra quality obtained remains quite good.
