Bcl-xL et Mcl-1 sont deux protéines anti-apoptotiques de la famille Bcl-2 dont dépendent les cancers de l’ovaire pour leur survie, leur inhibition semble donc être une stratégie pertinente. La molécule BH3-mimétique ABT 737 (ou son analogue oral, l’ABT-263), est un puissant inhibiteur de Bcl-xL mais l’inhibition de Mcl-1 reste problématique. Les voies de signalisation PI3K/Akt/mTOR et MAPK/ERK régulent l’expression et l’activité de cette dernière protéine et de ses partenaires BH3-only (Bim, Puma, Noxa). Nous nous sommes donc intéressés à l’intérêt de leur inhibition pour sensibiliser les cellules cancéreuses ovariennes à l’ABT-737. La première étude menée avec le BEZ235, double inhibiteur PI3K/mTOR développé par le laboratoire Novartis, montre qu’il inhibe l’expression de Mcl-1 et induit celle de Puma, et qu’il sensibilise les cellules cancéreuses ovariennes à l’ABT-737 à condition que l’expression de Bim soit également induite. La deuxième étude a évalué les effets de l’AZD8055, inhibiteur du site actif de mTOR développé par le laboratoire AstraZeneca, et du trametinib, inhibiteur allostérique de MEK développé par le laboratoire GlaxoSmithKline et actuellement en clinique, sur trois lignées cancéreuses ovariennes. L’inhibition de l’expression de Mcl-1 et l’induction de celle de Puma par l’AZD8055 ne permettent pas de diminuer suffisamment le ratio [Mcl-1/protéines BH3-only] pour sensibiliser les cellules à l’ABT-737. En revanche, la forte induction de Bim sous forme active déphosphorylée par le trametinib permet de diminuer suffisamment ce ratio pour sensibiliser deux des trois lignées testées à l’ABT-737. C’est cependant la triple combinaison AZD8055/trametinib/ABT-737 qui est la plus efficace pour induire une apoptose massive dans les trois lignées. Par ailleurs, de façon intéressante, l’association de l’AZD8055 et du trametinib est cytotoxique sans ABT 737 dans une des lignées testées. Ces résultats mettent en évidence l’efficacité de différentes stratégies thérapeutiques multi-cibles et la nécessité de définir des marqueurs prédictifs de la réponse afin d’évoluer vers un traitement personnalisé pour améliorer la prise en charge des cancers de l’ovaire. / Ovarian cancers depend on Bcl-xL and Mcl-1, two anti-apoptotic protein of the Bcl-2 family, for their survival and their inhibition seems to by a relevant strategy. The BH3-mimetic molecule ABT-737 (or its oral form, ABT-263), is a strong Bcl-xL inhibitor, but Mcl-1 inhibition remains problematic. Signaling pathways PI3K/Akt/mTOR and MAPK/ERK regulate expression and activity of Mcl-1 and its BH3-only partners (Bim, Puma, Noxa). We focused on the interest of their inhibition to sensitize ovarian cancer cells to ABT-737. The first study with BEZ235, a PI3K/mTOR dual inhibitor developed by Novartis, inhibits Mcl-1 expression and induces the one of Puma, and sensitizes ovarian cancer cells to ABT-737 provided that Bim expression is induced. The second study evaluated the effects of AZD8055, mTOR active site inhibitor developed by AstraZeneca, and of trametinib, MEK allosteric inhibitor developed by GlaxoSmithKline and currently in clinic, on three ovarian cancer cell lines. Mcl-1 expression inhibition and Puma expression induction by AZD8055 does not sufficiently reduce [Mcl-1/BH3-only proteins] ratio to sensitize cells to ABT-737. On the other hand, strong Bim induction in its active dephosphorylated form by trametinib sufficiently reduce this ratio to sensitize two of the three cell lines tested to ABT-737. Nevertheless, the triple combination AZD8055/trametinib/ABT-737 is the most efficient to induce massive apoptosis in the three cell lines. Besides, interestingly, AZD8055 and trametinib association is cytotoxic without ABT-737 in one of the tested cell lines. These results highlight the efficacy of different multi-targets therapeutic strategies and the need of predictive marker definition of the response to develop personalized treatment and to improve ovarian cancer management.

L’adénocarcinome épithélial de l’ovaire (CEO) est le cancer gynécologique le plus mortel. La recherche de nouvelles thérapies repose principalement sur des modèles précliniques 2D et in vivo avec des lignées cellulaires (LC) pour générer les évidences nécessaires à l’initiation d’essais cliniques. Ce processus requiert des fonds substantiels en recherche/santé qui est associé à un taux d’attrition élevé laissant supposer des lacunes dans le modèle actuel. Nos publications antérieures suggèrent que la sensibilité in vitro de nos LC du CEO à la chimiothérapie carboplatin varie en 2D ou 3D. Il reste à élucider lequel de ces modèles est le plus représentatif de la réponse in vivo. De ce fait, nous avons émis l’hypothèse que le modèle 3D refléterait plus étroitement la sensibilité in vivo. L’objectif de cette étude était de caractériser la réponse au carboplatin de nos LC du CEO en monocouches et en sphéroïdes (3D), puis de les comparer à leur réponse in vivo (xénogreffes). Un total de 6 LC du CEO a été injecté dans des souris qui ont reçues trois différentes concentrations de carboplatin. Leurs réponses ont été évaluées/classées selon leurs mesures de volume tumoral et l’immunofluorescence. Ces mêmes LC ont été ensemencées dans des plaques à très faible adhérence pour former des sphéroïdes et les traiter. Des analyses de cytométrie en flux ont été effectuées afin de classer les LC selon leur concentration inhibitrice médiane (CI50). Nous avons comparé le tout aux résultats 2D (CI50) précédemment publiés. Nos résultats montrent que le système 3D démontre la meilleure concordance avec le modèle in vivo. Notamment, notre LC ultra-résistance en 2D devient plus sensible en modèle murin ou encore en 3D. Inversement, une LC ultra-sensible en 2D est plus résistante en xénogreffe et en sphéroïde. Les résultats découlant de notre étude sont importants à considérer lors d’investissement de temps et de fonds dans les études de criblage et de prédiction de réponses thérapeutiques. / Epithelial ovarian adenocarcinoma (EOC) is the most lethal gynecological cancer. The drug discovery pipeline is heavily based on preclinical models. Typically, 2D cell line (CL)-based models are used to screen compounds followed by validation in animal models to generate the evidence needed to design clinical trials. This process incurs a high cost to the research pipeline and still results in high drug attrition rates. This may in part reflect the poor translation of preclinical to clinical results and points to deficiencies in modeling. Previous work from our laboratory shows that the sensitivity of our EOC CLs to carboplatin therapy varies between 2D and 3D in vitro models, however it is unclear how these differences align with the in vivo response. We hypothesize that 3D models will more closely reflect therapeutic in vivo response. The objective of this study was to characterize the carboplatin sensitivity of EOC CLs in 2D and 3D-spheroids and compare them to in vivo response using mouse xenografts. We injected mice with 6 different EOC CLs that were treated with 3 different carboplatin concentrations. Tumor volume measurements and immunofluorescence viability stains were used to categorize CLs by their sensitivity. The same CLs were seeded in low attachment plates to form, and thereafter treat, spheroids. Flow cytometry analysis was used to classify CLs by their 50% inhibitory response (IC50). The 2D response (IC50) for these CLs has previously been published. Our results show that therapeutic response changes significantly for a single CL between different systems, and the 3D model was most concordant with the in vivo model. Our ultra-resistant CL in 2D became more sensitive in 3D/mouse models. In contrast, the highly 2D sensitive CL became more resistant in our xenograft/spheroid models. The results are important to consider when investing time/funds in drug screening and therapeutic response prediction studies.

Das Ovarialkarzinom ist eines der tödlichsten Malignome in der Gynäkologie und birgt eine große therapeutische Herausforderung. Trotz Platin und Taxan haltiger Chemotherapie liegt die Rezidivrate des Ovarialkarzinoms bei 70%. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) gilt aufgrund seiner Eigenschaft spezifisch in Krebszellen Apoptose zu induzieren ohne normalen Körperzellen zu schaden in der Krebsforschung als vielversprechendes Therapeutikum. Seit einiger Zeit ist jedoch ersichtlich, dass 50% der Zelllinien und die Mehrheit aller primären humanen Krebszellen resistent für TRAIL induzierte Apoptose sind (Koschny, Walczak et al. 2007) und zunächst sensitiviert werden müssen. In dieser Studie konnte gezeigt werden, dass primäre Ovarialkarzinomzellen die mit Hilfe von EpCAM Dynabeads aus der Aszites von Krebspatientinnen isoliert wurden, sowohl mit Bortezomib (Proteasominhibitor) als auch mit PIK75 (PI3K- Inhibitor)spezifisch für TRAIL induzierte Apoptose sensitiviert werden konnten. Desweiteren konnte gezeigt werden, dass diese Kombinationstherapie normale hämatopoietische Zellen nicht beschädigt. Dies bekräftigt vor allem die Eigenschaft von TRAIL, krebszellspezifisch Apoptose zu induzieren. Wichtig ist vor allem, dass diese Kombinationstherapie sogar Chemotherapie resistente primäre Ovarialkarzinomzellen in Apoptose führen konnte.

Ovarian cancer is a disease with a high rate of mortality where the need for novel treatments will increase in the near future as older and populous generations reach the age where the cancer is usually diagnosed. Once treated, ovarian cancer tends to recur and display a newfound resistance against the platinum-based chemotherapeutic drugs that are used to treat the disease. Therefore, devising new methods of treatment is of utmost importance. Treatment with oncolytic viruses like LOAd703 offers an alternative treatment option that is more specific, causes immunogenic cell death in tumor cells, can stimulate the patient’s own immune system into fighting the cancer, and also has the potential to induce long term immune memory. In this project, the oncolytic and immunogenic capacity of LOAd703 in three different ovarian cancer cell lines was tested in conjunction with the standard-of-care chemotherapeutical drugs paclitaxel, cisplatin and carboplatin. The chemotherapy did not inhibit the replication, transgene expression or oncolysis of the LOAd703 virus. LOAd703 was able to effectively induce oncolysis in all three cell lines. The oncolytic capacity was generally increased when combined with chemotherapeutics. In cells resistant to chemotherapeutics, combination therapy with LOAd703 increased the killing capacity. While combination therapy proved effective, it did leave behind a small population of tumor cells that appeared to be resistant to both chemotherapy and viral oncolysis but longer culturing times may be tested to evaluate if complete killing will occur or if it is a primary resistance to these treatments in the cell lines. Further, if there is resistance to oncolysis or chemotherapy-mediated killing, employing tumor-immune cell co-cultures or in vivo studies might be necessary in order to assess whether the immunostimulatory effects of LOAd703 will lead to a complete eradication of the remaining tumor cells. The treatments also caused an increase in the expression of certain cell surface markers, like PD-L1 and CD262, which might open the door for future trials combining chemotherapy and LOAd703 with anti-PD-L1 inhibitors or soluble TRAIL.

Proteomics as a modern comprehensive approach to the analysis of proteomes was applied in three projects aimed at diagnosis and therapy of cancer. The aim of the first the project was to find a new diagnostic biomarker for ovarian cancer. Two different comparative proteomic approaches were used for comparative analysis of sera from patients diagnosed with ovarian cancer and from healthy age-matched women. We identified -1-antitrypsin with increased concentration in patien sera, and apolipoprotein A4 and retinol-binding protein 4 (RBP4) with significantly decreased concentration in patients. The significantly decerased concentration of RBP4 in patients is a new observation. We propose that RBP4 is either decreased in ovarian cancer patients as a result of its reduced production by ovary or it may reflect less specific systemic changes, for instance early onset of cancer cachexia. The second project was focused on gaining insight into the molecular mechanism of cytarabine resistance in mantle cell lymphoma (MCL). Proteomic and transcriptomic analyses of cytarabine-resistant cells revealed marked downregulation of deoxycytidine kinase (DCK) - a protein essential to intracellular activation of purine and pyrimidine nucleosides and their analogues including cytarabine. The cytarabine-resistant MCL...

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome cansignificantly vary among patients within the same stage. Data collected from largecohorts of human cancers has demonstrated the impact of immune-classification, which has a prognostic value that may add largely to the significance of the AJCC/UICC TNM-classification. In our study we examined the immune cells that infiltrated the tumor tissues of colorectal and ovarian cancer patients. In a cohort of newly diagnosed colorectal cancer patients we examined the correlations between the KRAS mutational status, patterns of tumor-infiltrating immune cells and the presence of tumor recurrence. Our data suggest that colorectal cancer patients with low levels of tumor-infiltrating lymphocytes, a high CD1a/DC-LAMP tumor-infiltrating dendritic cells ratio, and a KRAS mutation in codon 13 are at a high risk of disease recurrence. In ovarian cancer patients we focused on the dynamics of the tumor-infiltrating...

Ovarian cancer is serious and one of the most common gynecologic cancers. Carboplatin is the therapeutic agent of the first choice in the ovarian cancer therapy. However, after the primary therapeutic response to carboplatin, the relapse of the disease may occur with developed resistance to carboplatin. Chemoresistance and insufficient therapy response are considered to be the reason of the high mortality rate of ovarian cancer. The DNA damage response pathways play an important role in the therapeutic response and chemoresistance development. Restoration of homologous recombination function in cancers is the key mechanism of resistance development to platinum agents. Based on this knowledge, we formed our hypothesis, that the inhibition of homologous recombination could increase the sensibility to carboplatin. The main goal of this thesis was to define the role of double-strand breaks repair in response to chemotherapy of ovarian cancer. Protein MRE11 is part of the MRN complex, that participates in double-strand breaks repair. Using mirin as a pharmaceutic inhibitor of MRE11 we were aiming to determine the impact of homologous recombination on the effect of carboplatin and its role in resistant development to carboplatin. In the practical part of the thesis, we described the association between...

Indiana University-Purdue University Indianapolis (IUPUI) / Ovarian cancer (OC) is a lethal disease due to metastasis and chemoresistance. Our laboratory previously reported that tissue transglutaminase (TG2) is overexpressed in OC and enhances OC peritoneal metastasis. TG2 is a multifunctional protein which catalyzes Ca2+-dependent cross-linking of proteins. The purpose of this study was to explore the mechanism by which TG2 is upregulated in OC and its role in OC progression. We demonstrated that transforming growth factor (TGF)-β1 is secreted in the OC milieu and regulates the expression and function of TG2 primarily through the canonical Smad signaling pathway. Increased TG2 expression level correlates with a mesenchymal phenotype of OC cells, suggesting that TGF-β1 induced TG2 promotes epithelial-to-mesenchymal transition (EMT). TG2 induces EMT by negatively regulating E-cadherin expression. TG2 modulates E-cadherin transcriptional suppressor Zeb1 expression by activating NF-κB complex, which leads to increased cell invasiveness in vitro and tumor metastasis in vivo. The N-terminal fibronectin (FN) binding domain of TG2 (tTG 1-140), lacking both enzymatic and GTPase function, induced EMT in OC cells, suggesting the interaction with FN involved in EMT induction. A TGF-β receptor kinase inhibitor, SD-208, blocked TGF-β1 induced TG2 upregulation and EMT in vitro and tumor dissemination in vivo, which confirms the link between TGF-β1 and TG2 in EMT and tumor metastasis. TG2 expression was correlated with the number and size of self-renewing spheroids, the percentage of CD44+CD117+ ovarian cancer stem cells (CSCs) and with the expression level of stem cell specific transcriptional factors Nanog, Oct3/4, and Sox2. These data suggest that TG2 is an important player in the homeostasis of ovarian CSCs, which are critical for OC peritoneal metastasis and chemoresistance. TG2 expression was also increased in CSCs isolated from human ovarian tumors, confirming the implication of TG2 in CSCs homeostasis. Further, we demonstrated that TG2 protects OC cells from cisplatin-induced apoptosis by regulating NF-κB activity. We proposed a model whereby TGF-β-inducible TG2 modulates EMT, metastasis, CSC homeostasis and chemoresistance in OC. These findings contribute to a better understanding of the mechanisms of OC metastasis modulated by TG2.

Mass spectrometry has been used extensively in recent years as a valuable tool in the study of proteomics. However, the data thus produced exhibits hyper-dimensionality. Reducing the dimensionality of the data often requires the imposition of many assumptions which can be harmful to subsequent analysis. The IP algorithm is a dimension reduction algorithm, similar in purpose to latent variable analysis. It is based on the principle of maximum entropy and therefore imposes a minimum number of assumptions on the data. Partial Least Squares (PLS) is an algorithm commonly used with proteomics data from mass spectrometry in order to reduce the dimension of the data. The IP algorithm and a PLS algorithm were applied to proteomics data from mass spectrometry to reduce the dimension of the data. The data came from three groups of patients, those with no tumors, malignant or benign tumors. Reduced data sets were produced from the IP algorithm and the PLS algorithm. Logistic regression models were constructed using predictor variables extracted from these data sets. The response was threefold and indicated which tumor classifications each patient belonged. Misclassification rates were determined for the IP algorithm and the PLS algorithm. The rates correct classification associated with the IP algorithm were equal or better than those rates associated with the PLS algorithm.

Mutations in the BRCA1 and BRCA2 genes are known risk factors and drivers of breast and ovarian cancers. So far, few studies have been focused on understanding the differences in transcriptome and functional landscapes associated with the disease (breast vs. ovarian cancers), gene (BRCA1 vs. BRCA2), and mutation type (germline vs. somatic). In this study, we were aimed at systemic evaluation of the association of BRCA1 and BRCA2 germline and somatic mutations with gene expression, disease clinical features, outcome, and treatment. We performed BRCA1/2 mutation centered RNA-seq data analysis of breast and ovarian cancers from the TCGA repository using transcriptome and phenotype 'portrayal' with multi-layer self-organizing maps and functional annotation. The results revealed considerable differences in BRCA1- and BRCA2-dependent transcriptome landscapes in the studied cancers. Furthermore, our data indicated that somatic and germline mutations for both genes are characterized by deregulation of different biological functions and differential associations with phenotype characteristics and poly(ADP-ribose) polymerase (PARP)-inhibitor gene signatures. Overall, this study demonstrates considerable variation in transcriptomic landscapes of breast and ovarian cancers associated with the affected gene (BRCA1 vs. BRCA2), as well as the mutation type (somatic vs. germline). These results warrant further investigations with larger groups of mutation carriers aimed at refining the understanding of molecular mechanisms of breast and ovarian cancers.