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Zellen aus Karzinomen sind erwiesenermaßen weicher als Epithelzellen ihres Ursprungsgewebes. Es wurde vermutet, dass dieses Weicherwerden Zellen dabei hilft, aus dem Primärtumor auszubrechen und Metastasen zu bilden, was allerdings erst von wenigen Belegen bestärkt wird. Weiterhin wird die Entwicklung von Karzinomen allgemein als von einer epithelial-mesenchymalen Transition (EMT) angetrieben angesehen, ein Prozess, der die Umformung von Epithelgeweben steuert und stark in das Zytoskelett eingreift. Ich habe daher die Hypothese aufgestellt, dass EMT Karzinomzellen weicher macht und somit aggressive und invasive Tumore erzeugt. In der vorgelegten Arbeit gehe ich dem Nachweis dieser Hypothese nach. Ich habe den Einfluss der EMT auf Zellweichheit in vitro untersucht, allerdings kein gerichtetes Weicherwerden mit Fortschritt der EMT feststellen können. Mit vitalen Einzelzellen, die ich aus Operationsresektaten isoliert habe, verglich ich die mechanischen Eigenschaften von invasiven und nicht-invasiven Tumoren ex vivo und konnte eine klare Korrelation von Aggressivität mit Zellweichheit in vier verschiedenen Arten von Karzinomen aufzeigen. Membrangebundenes E-cadherin, das mir als Marker für den Fortschritt der EMT diente, war jedoch weder mit der Aggressivität der Karzinome noch mit der Weichheit derer Zellen korreliert. Ich benutzte maschinelles Lernen (ML), um Krebs-zellen in silico auf Basis ihrer mechanischer Eigenschaften zu klassifizieren, stieß aber auf klare Grenzen. In dieser Arbeit habe ich zum ersten Mal ex vivo gezeigt, dass das Weicherwerden von Krebszellen ein kontinuierlicher Prozess in Karzinomen ist, und dass erhöhte Aggressivität mit erhöhter Zellweichheit einhergeht. Ich habe außerdem EMT, die lange Zeit als entscheidend für Zellinvasion galt, als mögliche Ursache für dieses Weicherwerden ausgeschlossen. Zusammengenommen mit meinen Resultaten der ML Klassifikation deutet dies darauf hin, dass eine erhöhte Heterogenität von mechanischen Eigenschaften von Krebszellen, ausgelöst von allgemeiner Deregulation, die Invasion von Karzinomen antreibt.:1 Introduction 1 2 Background 11 2.1 The cytoskeleton of eukaryotic cells 12 2.2 The actin-E-cadherin-complex 17 2.2.1 E-cadherin 17 2.2.2 The Wnt/β-catenin pathway 18 2.2.3 Actin-E-cadherin dynamics 19 2.3 The epithelial to mesenchymal transition (EMT) 21 2.3.1 Epithelial and mesenchymal cells 21 2.3.2 Classical EMT 22 2.3.3 EMT in carcinoma development 23 2.4 Carcinoma development 25 2.4.1 Growth and spread 25 2.4.2 Tumor grading and staging 26 2.4.3 Carcinoma development outside of EMT 29 2.5 Cell mechanics in migration and invasion 31 3 Materials & methods 37 3.1 The Optical Stretcher as a main measurement device for cellular softness and E-cadherin level 38 3.1.1 Deformation by radiation pressure 39 3.1.2 Viability in an OS 43 3.1.3 Data acquisition and evaluation 46 3.2 Kelvin Voigt (KV) modeling 50 3.3 Machine learning 53 3.3.1 Interpreting and evaluating classications 54 3.3.2 Data preparation 58 3.3.3 Support vector machines (SVM) 58 3.3.4 Random forest (RF) 64 3.3.5 Permutation importance 67 3.4 Statistical analysis 68 3.4.1 Two one-sided tests (TOST) as a statistical test for equivalence 69 3.5 In vitro model systems for eukaryotic cells, their culture, and preparation 71 3.5.1 Cell lines 71 3.5.2 Cell culture 73 3.5.3 Fluorescent labeling of E-cadherin 73 3.6 Isolation of cancer cells from primary samples 75 3.6.1 Isolation of cancer cells from blood samples 75 3.6.2 Isolation of cancer cells from surgical resections 77 4 Results & discussion 79 4.1 In vitro growth factor induced EMT 81 4.1.1 EGF induced EMT is not correlated to cell softening in MCF 10A epithelial cells 82 4.1.2 TGFβ1 induced EMT is not correlated to cell softening in MCF 10A epithelial cells 87 4.1.3 Summary 91 4.2 Ex vivo vital tumor cells from liquid biopsies and surgical resections 94 4.2.1 Database analysis reveals that there is no systematic change of EMT related markers over the course of carcinoma progression 96 4.2.2 Vital single cells isolated from liquid biopsies of breast cancer patients can be distinguished from healthy cells of their natural surrounding 99 4.2.3 Cell softening is correlated to aggressiveness in tumor cells isolated from surgical resections 110 4.2.4 EMT progression is connected to neither cell softening nor aggressiveness in tumor cells isolated from surgical resections 120 4.2.5 Summary 123 4.3 In silico Machine learning as means to assess the predictive power of cell mechanics 127 4.3.1 Parameters from OS measurements 128 4.3.2 In vitro discrimination of cell types in a breast cancer cell line panel 129 4.3.3 Ex vivo discrimination of breast cancer cells and PBMC isolated from liquid biopsies 136 4.3.4 Summary 143 5 Conclusion & outlook 147 A Additional data and information 161 A.1 Optimization of support vector machines (SVM) and random forest (RF) machine learning approaches 161 A.1.1 Optimization of the training set size in SVM and RF machine learning approaches 161 A.1.2 Optimization of the SVM machine learning algorithm 161 A.1.3 Optimization of the RF machine learning algorithm 163 A.2 List of features for machine learning based classication 164 A.2.1 List of features used for classication of my in vitro cell line panel 164 A.2.2 List of features for classication of circulating tumor cells isolated from the blood of patients with mamma carcinoma 166 A.3 Activity parameter A of cells isolated from the blood samples of breast cancer patients 170 B Materials and reagents 171 B.1 Cell culture media 171 B.1.1 Medium for MCF 10A cells 171 B.1.2 Medium for MDA-MB-436 and MDA-MB-231 cells 171 B.1.3 Medium for NIH/3T3 cells 172 B.2 Ringer lactate buer for tissue transport and storage 172 B.3 MACS buffer 172 C Protocols 173 C.1 In vitro culture of cell lines 173 C.1.1 Passage of cell lines cultured in vitro 173 C.1.2 Cryogenic storage and thawing of cell lines 174 C.2 Immunouorescent labeling of E-cadherin 174 C.3 Growth factor treatment of MCF 10A epithelial cells 175 C.3.1 Treatment with increasing concentrations of epidermal growth factor (EGF) 175 C.3.2 Treatment with constant concentration of epidermal growth factor (EGF) 176 C.3.3 Treatment with transforming growth factor β1 (TGFβ1) 177 C.4 Isolation of vital cells from patient samples 178 C.4.1 Negative depletion of specic populations from cell suspensions by magnetic bead sorting 178 C.4.2 Isolation of vital circulating tumor cells (CTC) from the blood of patients with mamma carcinoma 179 C.4.3 Isolation of healthy peripheral blood mononuclear cells (PBMC) from the blood of patients and donors 179 C.4.4 Isolation of vital cancer cells from tumor samples of surgical resections of various carcinomas 180 C.5 Immunohistochemical staining of paranized tissue slices of tumor tissue 82 Bibliography 186 / Carcinoma cells have been shown to be softer than cells from their tissue of origin, healthy epithelia. This softening effect has been predicted to drive tumor cell migration and ergo metastases, but only circumstantial evidence exists for this. Carcinoma development is also generally viewed as driven by an epithelial to mesenchymal transition (EMT), a process that governs epithelial restructuring and heavily interferes with the cytoskeleton. I therefore hypothesized that EMT drives cell softening in carcinomas, which in turn leads to aggressive and invasive tumors. In the presented work, I pursue the verification of this hypothesis. I investigated the influence of EMT on cell softening in vitro, yet found no directed development of cell body softness with EMT progression. With vital single cancer cells that I isolated from surgical resections, I explored the mechanics of invasive, and non-invasive tumors ex vivo and saw a clear correlation of tumor aggressiveness with cell softness in four different types of carcinomas. There was however no correlation between E-cadherin in the cell membrane of isolated cancer cells, which I used as a marker for EMT progression, and the aggressiveness of the respective carcinomas or the softness of their cells. I employed machine learning (ML) to classify cancer cells based on their mechanical properties in silico, but found clear limits to that approach. In this work, I have shown for the very first time ex vivo how cell softening is an ongoing process during carcinoma development and increased aggressiveness is linked to increased softness. I also excluded EMT, which has long been deemed a driver of cell invasion, as a possible origin for cell softening. Together with results from ML classification, this points to increased heterogeneity in mechanical properties of cancer cells by deregulation as a main contributor to carcinoma invasion.:1 Introduction 1 2 Background 11 2.1 The cytoskeleton of eukaryotic cells 12 2.2 The actin-E-cadherin-complex 17 2.2.1 E-cadherin 17 2.2.2 The Wnt/β-catenin pathway 18 2.2.3 Actin-E-cadherin dynamics 19 2.3 The epithelial to mesenchymal transition (EMT) 21 2.3.1 Epithelial and mesenchymal cells 21 2.3.2 Classical EMT 22 2.3.3 EMT in carcinoma development 23 2.4 Carcinoma development 25 2.4.1 Growth and spread 25 2.4.2 Tumor grading and staging 26 2.4.3 Carcinoma development outside of EMT 29 2.5 Cell mechanics in migration and invasion 31 3 Materials & methods 37 3.1 The Optical Stretcher as a main measurement device for cellular softness and E-cadherin level 38 3.1.1 Deformation by radiation pressure 39 3.1.2 Viability in an OS 43 3.1.3 Data acquisition and evaluation 46 3.2 Kelvin Voigt (KV) modeling 50 3.3 Machine learning 53 3.3.1 Interpreting and evaluating classications 54 3.3.2 Data preparation 58 3.3.3 Support vector machines (SVM) 58 3.3.4 Random forest (RF) 64 3.3.5 Permutation importance 67 3.4 Statistical analysis 68 3.4.1 Two one-sided tests (TOST) as a statistical test for equivalence 69 3.5 In vitro model systems for eukaryotic cells, their culture, and preparation 71 3.5.1 Cell lines 71 3.5.2 Cell culture 73 3.5.3 Fluorescent labeling of E-cadherin 73 3.6 Isolation of cancer cells from primary samples 75 3.6.1 Isolation of cancer cells from blood samples 75 3.6.2 Isolation of cancer cells from surgical resections 77 4 Results & discussion 79 4.1 In vitro growth factor induced EMT 81 4.1.1 EGF induced EMT is not correlated to cell softening in MCF 10A epithelial cells 82 4.1.2 TGFβ1 induced EMT is not correlated to cell softening in MCF 10A epithelial cells 87 4.1.3 Summary 91 4.2 Ex vivo vital tumor cells from liquid biopsies and surgical resections 94 4.2.1 Database analysis reveals that there is no systematic change of EMT related markers over the course of carcinoma progression 96 4.2.2 Vital single cells isolated from liquid biopsies of breast cancer patients can be distinguished from healthy cells of their natural surrounding 99 4.2.3 Cell softening is correlated to aggressiveness in tumor cells isolated from surgical resections 110 4.2.4 EMT progression is connected to neither cell softening nor aggressiveness in tumor cells isolated from surgical resections 120 4.2.5 Summary 123 4.3 In silico Machine learning as means to assess the predictive power of cell mechanics 127 4.3.1 Parameters from OS measurements 128 4.3.2 In vitro discrimination of cell types in a breast cancer cell line panel 129 4.3.3 Ex vivo discrimination of breast cancer cells and PBMC isolated from liquid biopsies 136 4.3.4 Summary 143 5 Conclusion & outlook 147 A Additional data and information 161 A.1 Optimization of support vector machines (SVM) and random forest (RF) machine learning approaches 161 A.1.1 Optimization of the training set size in SVM and RF machine learning approaches 161 A.1.2 Optimization of the SVM machine learning algorithm 161 A.1.3 Optimization of the RF machine learning algorithm 163 A.2 List of features for machine learning based classication 164 A.2.1 List of features used for classication of my in vitro cell line panel 164 A.2.2 List of features for classication of circulating tumor cells isolated from the blood of patients with mamma carcinoma 166 A.3 Activity parameter A of cells isolated from the blood samples of breast cancer patients 170 B Materials and reagents 171 B.1 Cell culture media 171 B.1.1 Medium for MCF 10A cells 171 B.1.2 Medium for MDA-MB-436 and MDA-MB-231 cells 171 B.1.3 Medium for NIH/3T3 cells 172 B.2 Ringer lactate buer for tissue transport and storage 172 B.3 MACS buffer 172 C Protocols 173 C.1 In vitro culture of cell lines 173 C.1.1 Passage of cell lines cultured in vitro 173 C.1.2 Cryogenic storage and thawing of cell lines 174 C.2 Immunouorescent labeling of E-cadherin 174 C.3 Growth factor treatment of MCF 10A epithelial cells 175 C.3.1 Treatment with increasing concentrations of epidermal growth factor (EGF) 175 C.3.2 Treatment with constant concentration of epidermal growth factor (EGF) 176 C.3.3 Treatment with transforming growth factor β1 (TGFβ1) 177 C.4 Isolation of vital cells from patient samples 178 C.4.1 Negative depletion of specic populations from cell suspensions by magnetic bead sorting 178 C.4.2 Isolation of vital circulating tumor cells (CTC) from the blood of patients with mamma carcinoma 179 C.4.3 Isolation of healthy peripheral blood mononuclear cells (PBMC) from the blood of patients and donors 179 C.4.4 Isolation of vital cancer cells from tumor samples of surgical resections of various carcinomas 180 C.5 Immunohistochemical staining of paranized tissue slices of tumor tissue 82 Bibliography 186

Cancer is one of the leading causes of death in the world, often due to failed treatments because of drug resistance. Treatment is difficult as resistance is hard to detect before treatment and can develop during treatment. The fluorometric microculture cytotoxicity assay (FMCA) is a reliable, rapid method for testing drug cytotoxicity but requires large cell samples, which can be challenging to obtain. Patient-derived cancer cells (PDC) have proven challenging to culture in monolayer models, but recent studies have shown the possibility of using tumoroids. Tumoroids are three-dimensional models where cells are grown in basement membrane matrix hydrogel, allowing scaffold growth like in vivo tumors. This study aimed to culture colorectal PDC in the form of tumoroids, transfecting them, and examine cell cycle and tumor resistance for 5-Fluorouracil, Oxaliplatin and Irinotecan. Cells were deposited in gels with medium mimicking in vivo conditions, supporting growth and allowing extracellular signaling. The study succeeded in culturing both untransfected and transfected cells, resulting in cells expanding 48 and 42 times, respectively. Cell cycle remained unchanged. No changes were observed in 5-Fluorouracil, but a change was seen in transfected cells at passage 3 with oxaliplatin. The cells showed a 22% difference in survival indexes compared to naïve cells. Changes were seen in Irinotecan’s half maximal inhibitory concentration (IC50); all cell passage IC50 values differed >15.17 µM (p-value 0.0184). In conclusion, PDC can be cultured as tumoroids, but more studies are needed to determine if the model can generate reliable results representing PDC regarding tumor resistance.

Cytochrome P450 enzymes (P450s) are involved in cancer development and treatment due to their roles in the oxidative metabolism of various endogenous (e.g. oestrogen) and exogenous (e.g. tamoxifen) compounds. It is well-known that intermediate P450 metabolites derived from oestrogen metabolism are associated with breast carcinogenesis. The main aim of this project was to profile the cytochrome P450 and P450-regulatory nuclear receptor mRNAs in a series of breast cancer cell lines (BCCs) and compare this profile with normal breast cells. This study used the qualitative reverse transcriptasepolymerase chain reaction (RT-PCR) to detect mRNA expression of target genes. Results showed CYP1B1, CYP2D6, CYP2J2, CYP2R1, CYP2U1 and CYP4X1 mRNA to be present in all cell lines. CYP2A6, CYP2C8, CYP2C18, CYP2F1 and CYP4Z1 mRNA were expressed in oestrogen receptor (ER)-positiveCaucasian and ER-negative Afro- Caribbean BCCs. Although no differences in P450 mRNA were observed between the different ethnic groups, these preliminary findings suggest potential similarities in the ERpositive Caucasian and ER-negative Afro-Caribbean BCCs which warrant further investigation The CYP4Z1 PCR product was identified as two distinct bands. Specific primer sets were used to demonstrate potential intron retention in CYP4Z1. Using established in vitro models for the study of regulatory mechanisms of CYP4Z1, T47D and ZR-75-1 breast cancer cell lines were used to determine the appropriate nuclear receptors (i.e. progesterone receptor, glucocorticoid receptor or peroxisome proliferator-activated receptor alpha ). These findings suggest that there may be an alternative receptor mechanism involved in CYP4Z1 mRNA induction in these cells. In conjunction, pre-treatment of these two cell lines with the RNA synthesis inhibitor actinomycin D followed by the agonists showed a significant reduction (p < 0.05) of CYP4Z1 mRNA levels and inhibited CYP4Z1 induction by either progesterone, dexamethasone or pirinixic acid, indicating that these agonists have effects on CYP4Z1 mRNA transcription or stability. In contrast, cycloheximide differentially affected the level of CYP4Z1 mRNA induction by these agonists. Taken together, these results suggest that CYP4Z1 mRNA induction in T47D and ZR-75-1 is mediated through differential cell type specific regulatory mechanisms and there is evidence for differential regulation of the splice variants.

Regulatory T cells (Treg) play a key role in maintaining the immune tolerance. They suppress development of autoimmune diseases and contribute to maintaining the homeostasis of the immune system. Expansion and excessive ability of regulatory T cells to suppress the immune response is increasingly observed also at many types of cancer. Due to the active inhibition of the antitumor immune response Treg contribute to tumor progression. Specific phenotype based detection and analysis of Treg functional properties may contribute to the successful monitoring of Treg accounts and to the effective cancer immunotherapy itself. Tumor cells express high amounts of so-called tumor antigens, which may play a key role in the antitumor immune response. Expression level of the tumor antigens gives the evidence about relevancy of each antigen in the specific immune response and efficiency of cancer immunotherapy. These data are obviously important to be obtained from the tumor cell lines as well as primary tumor cells. In the first part of the thesis I was focusing on the quantitative analysis of regulatory T cells in tumor tissue and peripheral blood of patients with ovarian cancer. For this purpose I used the newly introduced methyl-sensitive quantitative PCR (MS-qPCR) method and compare the data with the widely...

L'objectif de cette thèse est d'étudier la sensibilité des lignes cellulaires du cancer du sein BTCL aux agents stabilisants des microtubules (taxanes et ixabépilone) afin de: 1 - identifier la pharmaco-génomique prédictif de la réponse (résistance / sensibilité) comme une signature moleculaire, et de valider cette signature sur d'autres études dont les données génomiques sont disponibles en ligne, donc mis l'expression des gènes prédictifs de GES pour Tax- sensibilité (333 gènes ) et Ixa-sensibilité (79 gènes) ont été définis, et les Taxanes prédicateurs GES a considérablement prédit Pac-sensibilité dans BTCL, et pathologiques réponse complète à base de Pac-chimiothérapie néoadjuvante chez les patients du cancer du sein. 2 - étudier le rôle des cellules souches du cancer (ALDH +) sur la réponse thérapeutique aux Taxanes et donc, Nous identifions quatre lignes BTCL qui présentent un enrichissement significative dans le pourcentage et le nombre absolu de ALDELFUOR cellules positives dans chacun de ces quatre BTCLs après 5 jours de traitement par le paclitaxel, en contraste avec les résultats précédents, nous avons constaté que dans ces autres 3 BTCLs le phénomène est inversé avec la diminution significative du pourcentage et le nombre absolu de cellules positives ALDELFUOR trouve dans chacun de ces trois BTCLs après 5 jours du traitement par le paclitaxel. Une signature moléculaire de SCC résistant / sensible de 243 pb avec 179 gènes dont 152 gènes sont régulés à la hausse et 27 gènes régulés à la baisse au CSC résistantes au paclitaxel, une sorte prédicteurs génomiques pour Tax - sensibilité au CSC résistantes au paclitaxel peut être dérivée à partir BTCL et peut être utile pour mieux comprendre les mécanismes de résistance aux taxanes et de l'implication de la CSC dans cette résistance, afin de mieux sélectionner des traitements cytotoxiques chez les patients du cancer du sein et l'identification des d'autres marqueurs potentiels de thérapies ciblées dans l'avenir. 3 - Nous avons testé l'impact de l'altération des paramètres génomiques et protéiques ou les mutations de certains gènes comme tau (MAPT), K-alpha tubuline (TUB A1B) tubuline alpha-6 (A1C TUB) tubuline beta 3 (TUBB3) et stathmine (STMN1), malheureusement nous n'avions jamais identifier une mutation pour être corrélée à la réponse des BTCL aux Taxanes. 4 - Nous essayons d'étudier au niveau de protéines par immunohistochimie sur le tissu de micro-array et cyto-micro-array pour certains paramètres qui ont été déjà prouvé (in vitro) pour être corrélée à la réponse aux Taxanes, (cette partie est en fait en cours). / The aim of this thesis is to study the sensitivity of breast cancer cell lines BTCL to microtubule-stabilizing agents (Taxanes and ixabepilone) in order to:1- identify pharmaco-genomic predictor of response (resistance /sensitivity) as a molecular signature, and to validate this signature on others studies of which the genomic data are available on line, so gene expression set GES predictors for Tax-sensitivity (333 genes) and Ixa-sensitivity (79 genes) were defined, and the Taxanes GES predictors has significantly predicted Pac-sensitivity in BTCL, and pathological complete response to Pac-based neo-adjuvant chemotherapy in BC patients.2- study the role of cancer stem cell (ALDH+) on the therapeutic response to Taxanes and their we identify 4 BTCLs which present a significant enrichment in the percentage and the absolute numbers of ALDELFUOR-positive cells found in each of these 4 BTCLs after 5 days of treatment by Paclitaxel , In contrast to the previous results we found that in others 3 BTCLs these phenomenon is inversed with the significant decrease of the percentage, and the absolute numbers of ALDELFUOR-positive cells found in each of these 3 BTCLs after 5 days of treatment by Paclitaxel.A molecular signature of CSC resistant /sensitive of 243 pb with 179 genes of which 152 genes are up- regulated and 27 genes down-regulated in CSC resistant to Paclitaxel, so a genomic predictors for Tax-sensitivity in CSC resistant to Paclitaxel can be derived from BTCL and may be helpful for better understanding the mechanisms of resistance to Taxanes and the implication of CSC in this resistance in order to better select of cytotoxic treatment in breast cancer patients and identification of others potential markers for targeted therapies in the future .3- we tested the impact of the alteration of genomic and proteic parameters or the mutations of some genes like tau (MAPT),Tubulin K- ALPHA (TUB A1B) Tubulin alpha-6 (TUB A1C) Tubulin beta 3 (TUBB3) and Stathmin (STMN1), unfortunately we did'nt identify a mutations to be correlated to BTCL response to Taxanes .4- we try to study at the level of proteins by immunohistochemistry on the tissue micro- array and cyto-micro-array for some parameters which have been already proved (in vitro) to be correlated with response to Taxanes , ( this part is actually ongoing).

Thesis (Ph.D. (Biochemistry)) --University of Limpopo, 2009 / Commelina benghalensis Linn is used in traditional medicine in several Asian and African countries for the treatment of various ailments such as stomach irritations, burns, sore throat and feet, diarrhoea and as an anti-inflammatory agent. Recently, our laboratory showed that the crude methanolic extract of Commelina benghalensis L (CMECB) exhibits growth inhibitory and proapoptotic effects in Jurkat T and Wil-2 NS cancer cell lines. In this study, the precise molecular mechanism(s) associated with CMECB-induced growth inhibitory and apoptosis inducing effects in Jurkat T and Wil-2 NS cell lines were investigated. This was achieved by investigating the effects of the extract on the cell division cycle distribution profile as well as its effects on various cell division cycle and apoptosis regulatory genes. Ground stems of C. benghalensis L were extracted with absolute methanol to obtain a crude extract. To assess the effect of CMECB on cancer cell growth, experimental cell cultures were exposed to various concentrations (0 to 600 μg/ml) of CMECB for up to 72 hours. The results demonstrated a significant reduction in cell viability and inhibition of proliferation of experimental cell cultures as determined by the trypan blue dye exclusion assay and the Coulter counter method, respectively. Analysis of nuclear morphological changes in cells stained with Hoechst 33258 confirmed apoptosis as the mode of cell death that is associated with the growth inhibitory effects of CMECB in both the Jurkat T and Wil-2 NS cell lines. This assertion was based on the observed presence of nuclear morphological changes such as chromatin condensation and fragmentation and apoptotic bodies in cells exposed to CMECB. In order to get an insight on the pro-apoptotic mechanisms of CMECB, Western blot xxi and quantitative real-time PCR (qrt-PCR) were used to investigate the expression profiles of various apoptosis and cell division cycle regulatory genes. Qrt-PCR results showed a lack of a clear up- and/or down-regulatory effects of CMECB on the mRNA expression levels of bax and bcl-2 in both Jurkat T and Wil-2 NS cells. Western blot analyses demonstrated that CMECB induced apoptosis by facilitating Bax protein translocation from the cytosol to the mitochondria in both Jurkat T and Wil-2 NS cells. In addition, CMECB down-regulated Bcl-2 protein expression which, as a result, led to the shift in the Bax/Bcl-2 protein ratio at certain time points and concentration in both Jurkat T and Wil-2 NS cells. The modulation of the Bcl-2 family members led to mitochondrial cytochrome c release into the cytosol and activation of caspases-9 and -3; this was also confirmed by caspase activity assays and eventual degradation of PARP. Furthermore, CMECB induced Jurkat T and Wil-2 NS cell division cycle arrest at the G2/M phase as determined by flow cytometric analysis. Western blot analyses of G2/M phase regulatory proteins demonstrated that the CMECB-induced cell division cycle arrest was associated with the downregulation of cyclin B1 and Cdc2 protein expression levels. Western blot analyses results further revealed that the arrest of Wil-2 NS cells at the G2/M phase was independent of p21 protein activity. However, Jurkat T cell division cycle arrest was found to be mediated, in part, by p21. Quantitative real-time PCR results did not show a clear trend in terms of the down- or up-regulatory effects of the extracts on the G2/M phase regulatory genes. The CMECBinduced apoptosis and G2/M arrest was found to occur in a p53-independent xxii manner due to the lack and down-regulation of p53 protein levels in both Jurkat T and Wil-2 NS cells, respectively. In conclusion, CMECB induces its anticancer activity by inducing G2/M phase arrest and mitochondrial-mediated apoptosis independent of p53 protein activity. Although the study did not perform in vivo experiments to ascertain the efficacy of extracts of CMECB against specific tumour types in animal models, the present findings somehow validate the traditional use of C. benghalensis L as an anticancer agent. A more definitive study needs to be done to ascertain this assertion. / National Research Foundation and the University of Limpopo research office

La matrice extracellulaire est un réseau enchevêtré de macromolécules variées, en étroite relation avec les cellules qu'elle environne. Les interactions bidirectionnelles qui s'établissent entre les cellules et leur microenvironnement matriciel régulent mutuellement leur comportement et devenir. La diversité biochimique des constituants moléculaires de la matrice, leurs propriétés biophysiques, leur architecture tout comme leur dynamique représentent autant de signaux régulateurs. Parmi les constituants de la matrice, la fibronectine (FN) est une glycoprotéine structurale et fonctionnelle majeure intervenant dans de nombreux processus physiologiques et pathologiques. Ces fonctions diverses sont directement liées à la dynamique structurale de cette protéine et à sa capacité à interagir avec les autres molécules matricielles, dont elle-même. Retrouvée sous forme soluble dans les fluides biologiques, la FN est incorporée dans les matrices insolubles sous forme d'assemblages supramoléculaires principalement fibrillaires mais aussi sous forme d'agrégats. Ces assemblages sembleraient être impliqués dans des processus physiologiques et pathologiques distincts.Si l'étude des assemblages de FN est rendue possible par l'élaboration de modèles in vitro, les mécanismes de polymérisation et l'effet d'assemblages de structures définies sur le comportement cellulaire restent cependant à mieux élucider et constituent le cœur de ce travail.Les travaux ont donc consisté à élaborer des assemblages de FN, à caractériser les mécanismes et structures impliqués dans leur polymérisation, et à étudier leur influence sur un modèle de cellules cancéreuses ovariennes. D'autre part, des études préliminaires comparatives ont été menées avec un analogue végétal de la FN.L'irréversibilité de la dénaturation thermique de la FN entraîne la formation d'agrégats de type amyloïde. Deux populations d'agrégats coexistent en solution. Cette agrégation est corrélée à une diminution de l'accessibilité des sites de liaison à la gélatine et des sites RGD, et à une diminution de l'incorporation dans les réseaux matriciels. De plus, si la FN sous sa forme agrégée n'est pas cytotoxique pour les cellules étudiées, la modification de la conformation de la FN favorise leur migration isolée et aléatoire.Ces résultats soulèvent la question de l'implication de ces agrégats de FN dans des processus pathologiques tels que le développement tumoral. / Extracellular matrix is a complex meshwork of various macromolecules that have a tight relationship with the surrounding cells. Bidirectional interactions between cells and the microenvironment control their respective behaviors and fate. The biochemical diversity of matrix molecular components, their biophysical properties, their architecture but also their dynamic represent as many regulator signals. Among the components of the matrix, fibronectin (FN) is a major structural and functional glycoprotein involved in numerous physiological and pathological processes. These various functions are directly linked to the structural dynamic of this protein and its ability to interact with others matrix components, in particular with itself. Found as a soluble protein in biological fluids, FN is also incorporated in insoluble matrix as supramolecular assemblies, mainly fibrils but also aggregates. These assemblies could be involved in distinct physiological and pathological processes.If the study of the assembly of the FN is possible with the help of in vitro models, the mechanism of polymerization and the effects of defined assemblies on the cell behavior still have to be better defined.Therefore, this work consisted in elaborating FN assemblies, in characterizing the mechanisms and structures involved in their polymerization and in studying their influence on behaviors of a model of ovarian cancer cells. Besides, preliminary comparative studies have been performed with a plant analogous of FN.We show that irreversible thermal unfolding of FN triggers amyloid-like aggregation. Two states of aggregates could coexist in solution. FN aggregation correlates with a decrease of gelatin-binding domain and RGD sequence accessibility, and a decrease of the incorporation in the matrix network. Moreover, if aggregates are not cytotoxic for the studied cells, conformation change of FN promotes their single-cell and random migration.These results raise questions about the role of FN aggregates in pathological processes like tumor development.

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Objectives: To investigate the effects of serotonin and melatonin (MLT) on the regulation of malignant growth and the activity of serotonin receptors (5HTR1a/-1b) in prostate cancer (PCa) cell lines. Materials and Methods: In four PCa cell lines (LNCaP, 22RV1, PC3, DU145) and two reference cell lines 5HTR1a and -1b, relative mRNA expression levels were assessed. Different serotonin and MLT receptor agonists and antagonists were used in stimulation and inhibition experiments. Results: mRNA expression of 5HTR1b was higher than that of 5HTR1a in all PCa cell lines. Serotonin showed a significant growth stimulatory effect in all PCa lines. The 5HTR1a and -1b agonists/antagonists did not significantly affect viability. MLT inhibited viability only in PC3 cells. Similarly, the 5HTR1a antagonist induced apoptotic changes in PC3 cells only at 10–4M, while the 5HTR1b antagonist induced necrosis at 10–4M in all cell lines. Cell cycle alterations were seen in PC3 and DU145 cells under the influence of the 5HTR1a antagonist. Conclusions: Serotonin receptor antagonists and agonists as well as MLT influence viability and apoptosis of PCa cell lines at supraphysiologic concentrations. In contrast to other reports, our results do not support a regulatory role of serotonin or MLT receptor activation or inhibition in PCa growth. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.