Model Systems Of Ovarian Cancer Research Articles

Abstract 3909: PARG inhibitor sensitivity is correlated with accumulation of single strand DNA gaps in preclinical models of ovarian cancer

Abstract Poly (ADP-ribose) glycohydrolase (PARG) is a dePARylating enzyme which promotes DNA repair in conjunction with PARP1 by removal of poly (ADP-ribose) (PAR). Loss or inhibition of PARG results in replication stress and sensitizes cancer cells to DNA damaging agents, suggesting it is a potential therapeutic target for cancer therapy. Indeed, PARG inhibitors are now undergoing clinical development for patients having tumors with homologous recombination deficiency (HRD), such as ovarian and breast cancer patients with BRCA1/2-mutation. In this study, we investigated PARG inhibitor (PARGi)-PDD00017273 activity in preclinical models of ovarian cancer cell lines and primary patient-derived organoids. PARGi exhibited sensitivity in a subset of ovarian cancer cell lines that was distinct from PARP inhibitor sensitivity. Initially, we evaluated a PARGi-sensitive cell line, RMUGS. By gradually increasing the concentration of PARGi, we generated drug resistant cells. PARGi treatment resulted in increased S phase specific PAR, DNA-PARylation, DNA damage, and replication stress in the sensitive cells but not in cells with de novo or acquired resistance. In the sensitive cells, PARGi exposure also increased accumulation of PAR at the replication fork resulting from unligated Okazaki fragment processing. More importantly, PARGi treatment or PARG loss caused accumulation of single strand DNA (ssDNA) gaps in sensitive cells, as detected by the DNA fiber assays combined with S1 nuclease treatment. Regardless of the BRCA-status, the induction of ssDNA gaps in ovarian cancer cells correlated with PARGi sensitivity. Consistent with an increase in ssDNA gaps, PARGi exposure increased p-RPA, a ssDNA surrogate, at the replication fork in sensitive cells. p-RPA sites also colocalized with PAR suggesting that accumulation of PAR occurs at the ssDNA sites, perhaps, leading to the ssDNA gaps. Collectively, these results suggested that toxic accumulation of PAR at the replication fork leads to accumulation of ssDNA gaps due to Okazaki fragment processing defects and ovarian cancer cell killing after PARG inhibition. We further assessed PARG inhibition in patient-derived organoids (PDOs) and patient-derived xenograft (PDX)-derived organoids (PDXOs) as model systems of ovarian cancer. PARGi exhibited monotherapy activity in specific HR-deficient PDOs and PDXOs with BRCA1 or RAD51C mutation and in a HR-proficient PDXO model. Importantly, PARGi exposure resulted in accumulation of ssDNA gaps in organoids of ovarian cancer and this phenotype directly correlated with drug sensitivity. PDOs can therefore be a useful model system for testing PARGi sensitivity. The detection of ssDNA gaps in PDOs may provide a functional biomarker to predict the response to PARG inhibitors in clinical trials. Citation Format: Ramya Ravindranathan, Ozge Somuncu, Yuqing Jiao, Alexandre André B A da Costa, Benjamin P Lamarre, David B Martignetti, Gabriella A Zambrano, Sirisha Mukkavalli, Joyce Liu, Bose Kochupurakkal, Jean-Bernard Lazaro, Kalindi Parmar, Geoffrey I Shapiro, Alan D. D'Andrea. PARG inhibitor sensitivity is correlated with accumulation of single strand DNA gaps in preclinical models of ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3909.

Multifunctional APJ Pathway Promotes Ovarian Cancer Progression and Metastasis.

High mortality rates in ovarian cancer are due to late-stage diagnosis when extensive metastases are present, coupled with the eventual development of resistance to standard chemotherapy. There is, thus, an urgent need to identify targetable pathways to curtail this deadly disease. In this study, we show that the apelin receptor, APJ, is a viable target that promotes tumor progression of high-grade serous ovarian cancer (HGSOC). APJ is specifically overexpressed in tumor tissue, and is elevated in metastatic tissues compared with primary tumors. Importantly, increased APJ expression significantly correlates with decreased median overall survival (OS) by 14.7 months in patients with HGSOC. Using various ovarian cancer model systems, we demonstrate that APJ expression in cancer cells is both necessary and sufficient to increase prometastatic phenotypes in vitro, including proliferation, cell adhesion to various molecules of the extracellular matrix (ECM), anoikis resistance, migration, and invasion; and these phenotypes are efficiently inhibited by the APJ inhibitor, ML221. Overexpression of APJ also increases metastasis of ovarian cancer cells in vivo. Mechanistically, the prometastatic STAT3 pathway is activated downstream of APJ, and in addition to the ERK and AKT pathways, contributes to its aggressive phenotypes. Our findings suggest that the APJ pathway is a novel and viable target, with potential to curb ovarian cancer progression and metastasis. IMPLICATIONS: The APJ pathway is a viable target in HGSOC.

Antitumor and Antiangiogenic Effects of Aspirin-PC in Ovarian Cancer.

To determine the efficacy of a novel and safer (for gastrointestinal tract) aspirin (aspirin-PC) in preclinical models of ovarian cancer, in vitro dose-response studies were performed to compare the growth-inhibitory effect of aspirin-PC versus aspirin on three human (A2780, SKOV3ip1, and HeyA8) and a mouse (ID8) ovarian cancer cell line over an 8-day culture period. In the in vivo studies, the aspirin test drugs were studied alone and in the presence of a VEGF-A inhibitor (bevacizumab or B20), due to an emerging role for platelets in tumor growth following antiangiogenic therapy, and we examined their underlying mechanisms. Aspirin-PC was more potent (vs. aspirin) in blocking the growth of both human and mouse ovarian cancer cells in monolayer culture. Using in vivo model systems of ovarian cancer, we found that aspirin-PC significantly reduced ovarian cancer growth by 50% to 90% (depending on the ovarian cell line). The efficacy was further enhanced in combination with Bevacizumab or B20. The growth-inhibitory effect on ovarian tumor mass and number of tumor nodules was evident, but less pronounced for aspirin and the VEGF inhibitors alone. There was no detectable gastrointestinal toxicity. Both aspirin and aspirin-PC also inhibited cell proliferation, angiogenesis, and increased apoptosis of ovarian cancer cells. In conclusion, PC-associated aspirin markedly inhibits the growth of ovarian cancer cells, which exceeds that of the parent drug, in both cell culture and in mouse model systems. We also found that both aspirin-PC and aspirin have robust antineoplastic action in the presence of VEGF-blocking drugs. Mol Cancer Ther; 15(12); 2894-904. ©2016 AACR.

Active FOXO1 Is a Key Determinant of Isoform-Specific Progesterone Receptor Transactivation and Senescence Programming.

Progesterone promotes differentiation coupled to proliferation and prosurvival in the breast, but inhibits estrogen-driven growth in the reproductive tract and ovaries. Herein, it is demonstrated, using progesterone receptor (PR) isoform-specific ovarian cancer model systems, that PR-A and PR-B promote distinct gene expression profiles that differ from PR-driven genes in breast cancer cells. In ovarian cancer models, PR-A primarily regulates genes independently of progestin, while PR-B is the dominant ligand-dependent isoform. Notably, FOXO1 and the PR/FOXO1 target gene p21 (CDKN1A) are repressed by PR-A, but induced by PR-B. In the presence of progestin, PR-B, but not PR-A, robustly induced cellular senescence via FOXO1-dependent induction of p21 and p15 (CDKN2B). Chromatin immunoprecipitation (ChIP) assays performed on PR isoform-specific cells demonstrated that while each isoform is recruited to the same PRE-containing region of the p21 promoter in response to progestin, only PR-B elicits active chromatin marks. Overexpression of constitutively active FOXO1 in PR-A-expressing cells conferred robust ligand-dependent upregulation of the PR-B target genes GZMA, IGFBP1, and p21, and induced cellular senescence. In the presence of endogenous active FOXO1, PR-A was phosphorylated on Ser294 and transactivated PR-B at PR-B target genes; these events were blocked by the FOXO1 inhibitor (AS1842856). PR isoform-specific regulation of the FOXO1/p21 axis recapitulated in human primary ovarian tumor explants treated with progestin; loss of progestin sensitivity correlated with high AKT activity. This study indicates FOXO1 as a critical component for progesterone signaling to promote cellular senescence and reveals a novel mechanism for transcription factor control of hormone sensitivity.

Abstract POSTER-BIOL-1320: Rho-family GTPases as therapeutic targets in ovarian cancer

Abstract Purpose of the study: Although Rac1 and Cdc42 are considered attractive therapeutic targets, no selective inhibitors of these GTPases are in clinical trials. The Ras-homologous (Rho) family GTPases Rac1 and Cdc42 contribute to metastatic dissemination through regulation of actin reorganization, cell motility, cell-cell and cell-extracellular matrix adhesion. Using high throughput screening and cheminformatics, we identified the R-enantiomer of ketorolac as a novel inhibitor of Rac1 and Cdc42. R-enantiomers of nonsteroidal anti-inflammatory drugs are poor inhibitors of cyclooxygenase (COX) activity, yet little is known about the pharmacologic activities or targets of the R-enantiomers. The purpose of this study was to investigate the effects of R-ketorolac on ovarian cancer. Experimental procedures: GTPase target expression and activity was determined by immunohistochemistry, RT-PCR and enzymatic assays. The effects of racemic, R- and S-ketorolac on proliferation, adhesion and migration were investigated using human ovarian tumor cells (OvCA 429 and SKOV3ip). In vivo effect of ketorolac treatments was determined in a xenograft model using SKOV3ip cells. Pharmacokinetic and pharmacodynamic assessments of racemic R/S-ketorolac (Toradol®) in patients were conducted in women with suspected advanced stage ovarian, fallopian tube or primary peritoneal cancer with planned optimal cytoreductive surgery. Ascites samples were obtained for measurement of cell adhesion and drug inhibition of GTPase activity. After placement of an IP port the recommended dose of IV racemic ketorolac was administered and blood and peritoneal fluid were obtained at T=0, 1h, 6h and 24h. R- and S-ketorolac concentrations in serum and peritoneal fluid were measured by HPLC. GTPase inhibitory activity of ketorolac was assessed in peritoneal tumor cells. Summary of the data: Elevation of Cdc42 protein and expression of the constitutively active Rac1b splice variant of Rac1 were detected in ovarian cancer specimens providing the first evidence for dysregulation of these GTPase targets in ovarian cancer. R-ketorolac, and not S-ketorolac, inhibits Rac1 and Cdc42 activity demonstrating an unexpected pharmacologic activity for the R-enantiomer. R-ketorolac, but not S-ketorolac, inhibits cell adhesion and migration, and reduced peritoneal tumor implantation in a mouse xenograft model. In the clinical studies using R/S-ketorolac for post-operative pain management, we found that ketorolac distributed to peritoneal fluids within 6 hours and fluids were highly enriched in the R-enantiomer compared to the S-enantiomer. Rac1 and Cdc42 activity was inhibited in ovarian tumor cells retrieved from the peritoneal cavity post-ketorolac administration. Cell adhesion was decreased by R-ketorolac in patient-derived ovarian tumor cells. Conclusions: The findings show R-ketorolac is a novel inhibitor of Rac1 and/or Cdc42, and active in ovarian cancer model systems. The favorable distribution of R-ketorolac in the peritoneal cavity coupled with GTPase inhibition in cells retrieved from the intraperitoneal compartment support the potential benefit of R-ketorolac for ovarian cancer patients. Citation Format: Hudson LG, Kenney SR, Guo Y, Adams S, Rutledge T, Muller CY, Wandinger-Ness A. Rho-family GTPases as therapeutic targets in ovarian cancer [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr POSTER-BIOL-1320.

Abstract POSTER-TECH-1111: High-throughput drug sensitivity and resistance testing of ovarian cancer cell lines provides useful strategy for assessing drug repositioning and therapeutic possibilities of emerging drugs

Abstract As almost all therapeutic approaches for ovarian cancer (OC) are organ-based therapies that have been tested in large-scale clinical studies, no precision medicine approach to OC currently exists. There is an urgent need to develop a better understanding of the drug responsiveness in OC, particularly in the clear cell and mucinous subtypes, which tend to be resistant to the commonly used platinum-based regimens. This would help to improve survival and facilitate precision medicine therapy approaches. In order to discover previously unsuspected anti-cancer effects of approved and emerging drugs, we applied Drug Sensitivity and Resistance Testing (DSRT) technology (Pemovska et al., Cancer Discovery, 2013) to determine detailed dose-response effects of 306 drugs in 29 established OC cell lines (12 clear cell, 6 mucinous, 1 endometrioid, and 10 serous and other OC cell lines). The panel covered 137 approved drugs as well as emerging, investigational and pre-clinical oncology compounds such as kinase and non-kinase inhibitors. All drugs were tested at 5 different concentrations, covering a 10,000-fold concentration range by using Labcyte nano-dispensing technology, in order to generate detailed dose-response curves for each drug in each cell line. The area under the curve was estimated from the dose-response curve to obtain the drug sensitivity score. Bioinformatic processing of the drug response data from OC cell lines resulted in several key observations. First, the clusters did not depend on the histological origin of the OC cell lines but were clustered according to drug categories. Second, our result showed that many emerging or non-approved drugs were sensitive in subgroups of OC cell lines. For example, MEK inhibitors and mTOR inhibitors show high sensitivity in many OC cell lines. They can be candidates for drug repositioning. Third, we confirmed reproducibility of our findings. In summary, as per the data from direct testing of drug efficacy, several emerging anti-cancer drugs show potential responses in subsets of OC cell lines. DSRT technology provides a powerful strategy for assessing drug response in OC cell models, and it could also help asses drug responses in patient-derived ex vivo model systems of OC. Analysis of correlations of DSRT data with genomic data of the cell lines is underway and will yield new translational and pharmacogenomic opportunities for treating OC. Citation Format: Akira Hirasawa, Astrid Murumägi, Mariliina Arjama, Bhagwan Yadav, John Patrick Mpindi, Krister Wennerberg, Tero Aittokallio, Daisuke Aoki, Olli Kallioniemi. High-throughput drug sensitivity and resistance testing of ovarian cancer cell lines provides useful strategy for assessing drug repositioning and therapeutic possibilities of emerging drugs [abstract]. In: Proceedings of the 10th Biennial Ovarian Cancer Research Symposium; Sep 8-9, 2014; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(16 Suppl):Abstract nr POSTER-TECH-1111.

Abstract B33: Understanding resistance mechanisms to PI3K/mTOR inhibitors in ovarian cancer model systems

Abstract The combined use of computational models and experimental data is an emerging tool in systems biology to help explain the mechanism of resistance to various protein inhibitors in oncological medicine. Improved understanding of the signaling network dynamics may offer novel approaches to overcoming drug resistance. The aim of this study was to analyze the signaling dynamics of the PI3K/Akt/mTOR pathway in ovarian cancer cells after treatment with different PI3K/mTOR inhibitors. Systems computational approach was applied to unwind the role of multiple feedbacks in PI3K/Akt/mTOR pathway in the responses of cancer cells bearing mutations in PTEN, PIK3CA and HER2 overexpression. In this study, a set of PI3K (LY294002), mTOR (Rapamycin) and dual PI3K/mTOR (BEZ235) inhibitors were applied to a panel of ovarian cancer cell lines under heregulin driven conditions over 10 point time-course treatment, in order to assess the association of growth inhibition with pathway activation. The evaluation of expression levels of various proteins and phospho-proteins was assessed using reverse phase protein array (RPPA) as a high throughput proteomic analysis to investigate the dynamic changes in response to the inhibitors. In part, PTEN expression status was analyzed as biomarker of the feedback-dependent pAkt activation in response to mTOR inhibition by rapamycin in different cell lines. The three inhibitors displayed a significant inhibition in cell proliferation on all the ovarian cancer cell lines following a 5-day treatment. Our results have shown a significant positive correlation between the signaling dynamics of phosphorylated Src (Tyr527) and phosphorylated PTEN (Ser380/Thr382/383) upon treatment with the drugs, consistent with the role of Src in the inactivation of PTEN. Additionally, we demonstrate that PI3K plays a role in the activation of RAS pathway, as phosphorylated cRaf (Ser259 and Ser338) and phosphorylated mTOR (Ser2481) were upregulated and showed a significant positive correlation in their signaling dynamics. Although, all the cell lines have shown a significant inhibition to cell proliferation following a 5-day treatment with the inhibitors, the signaling expression of 12 different phospho-proteins within the PI3K/mTOR and MAPK pathways differ. Rapamycin has been shown to downregulate the expression of phospho-mTOR (Ser2448) and its substrates, phospho-4E-BP1 and phospho-S6K1 but has shown an upregulation in phospho-Akt (Ser473), confirming the existence of the negative feedback loop, S6K1-Akt, upon treatment. BEZ235 presented the highest efficacy in inhibiting cell proliferation in all the ovarian cancer cell lines but failed to downregulate the phosphorylation of ERK. Due to the high overexpression of erbB2 that may cause HER2 homodimerization, the signaling expression of the ovarian cancer cell line, SKOV3, showed upregulation in all the measured phospho-proteins. We propose an extended model of PI3K/Akt/mTOR pathway in ovarian cancer, based on theoretical modeling and experimental data, highlighting possible resistance compensatory mechanisms within the pathway and with its parallel cross-talk pathway MAPK. The model highlights potential novel protein interactions and feedback loops, offering strategies for combinatorial anti-cancer therapy. Citation Format: Ghassan Tashkandi, Alexey Goltsov, Peter Mullen, Jim Bown, David Harrison, Simon Langdon. Understanding resistance mechanisms to PI3K/mTOR inhibitors in ovarian cancer model systems. [abstract]. In: Proceedings of the AACR Special Conference: Targeting the PI3K-mTOR Network in Cancer; Sep 14-17, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(7 Suppl):Abstract nr B33.

Abstract 5384: Systematic high-throughput drug sensitivity and resistance testing (DSRT) of ovarian cancer cell lines indicates novel therapeutic possibilities with existing and emerging drugs

Abstract There is an urgent need to develop better understanding of the drug responsivenes in ovarian cancer (OC), particularly in the clear cell and mucinous subtypes, which tend to be resistant to the commonly used platinum-based regimens. This would help to improve survival and facilitate precision medicine approaches to therapy. In order to discover previously unsuspected anti-cancer effects with approved and emerging drugs, we applied Drug Sensitivity and Resistance Testing (DSRT) technology (Pemovska et al., Cancer Discovery, 2013) to determine detailed dose-response effects of 300 drugs in 25 established OC cell lines (10 serous, 10 clear cell and 5 mucinous ovarian cancer cell lines). The panel covered 160 approved drugs as well as 162 emerging, investigational and pre-clinical oncology compounds such as kinase and non-kinase inhibitors. All drugs were tested in 5 different concentrations covering a 10,000-fold concentration range using Labcyte nano-dispensing technology, in order to generate detailed dose-response curves for each drug in each cell line. The area under the curve was estimated from the dose-response curve to obtain the drug sensitivity score. Bioinformatic processing of the drug response data from OC cell lines resulted in several key observations. First, the DSRT data made it possible to classify OC cell lines into four functional taxonomic subtypes based on comprehensive drug responses. Interestingly, these clusters did not depend on the histological origin of the OC cell lines. Second, the 322 drugs were clustered into functional subsets based on the response data across the 25 OC cell lines. Most of this clustering followed the expected chemical similarity and target space of the drugs, such as topoisomerase II inhibitors, MEK inhibitors, mTOR inhibitors and Taxanes each clustering in their own subgroups. Third, we found that many emerging, currently not-yet-approved drugs were active in subgroups of OC cell lines, including both kinase as well as non-kinase drugs, such as HDAC inhibitors Entinostat and Belinostat. DSRT technology provides a powerful strategy for assessing drug response in OC cell models, and it could also help to asses drug responses in patient-derived ex vivo model systems of OC. Analysis of correlations of DSRT data with genomic data of the cell lines is underway and will yield new translational and pharmacogenomic opportunities for OC. Citation Format: Akira Hirasawa, Astrid Murumägi, Mariliina Arjama, Bhagwan Yadav, John Patrick Mpindi, Krister Wennerberg, Tero Aittokallio, Daisuke Aoki, Olli Kallioniemi. Systematic high-throughput drug sensitivity and resistance testing (DSRT) of ovarian cancer cell lines indicates novel therapeutic possibilities with existing and emerging drugs. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5384. doi:10.1158/1538-7445.AM2014-5384

Differential expression patterns of histone modifying enzymes in ovarian cancer in response to estradiol and bisphenol A (942.3)

Ovarian cancer is the ninth most common cancer but the fifth leading cause of cancer death for women. It has long been known that ovarian cancer growth and development is dependent upon estrogen. Conversely there is less known about how environmental estrogens influence ovarian cancer development. Estrogenic compounds have been shown to affect the epigenome, yet little is known about the specific mechanisms by which these changes occur. This work focused on the effects of both estradiol and the endocrine disruptor bisphenol A (BPA) on the expression of histone modifying enzymes (HMEs) in two different human ovarian cancer model systems, SKOV3 and OVCAR3. Specifically, the expression of Set8, a histone methyl transferase, and Sirt1, a histone deacetylase, was examined in response to physiological doses of either estrogen or BPA. In addition, the experiments were carried out using physiological conditions. There are differences in the expression pattern of these genes between the two compounds and also between the two model systems. These results imply that environmental estrogens potentially impact global gene expression by changing the expression of HMEs. Furthermore these changes are different depending on the model system analyzed demonstrating a complex effect of these compounds in human ovarian cancer.

Preclinical antitumor activity of a nanoparticulate SN38

The present studies were carried out to examine the efficacy of a nanoparticulate formulation of SN38, the potent topoisomerase I inhibitor and active metabolite of irinotecan. Metabolism of irinotecan to SN38 is inefficient and subject to considerable patient-to-patient variability. One approach to more controlled administration of the anticancer agent is direct administration of the active SN38. A nanoparticulate formulation of SN38 was prepared by a method of precipitation with compressed antisolvent. Nanoparticulate SN38 efficiently inhibited the proliferation of colorectal, ovarian, and mesothelial cancer cell lines in vitro. Concentrations resulting in 50% inhibition of proliferation were approximately 1000 fold lower for nanoparticulate SN38 compared to irinotecan. In vivo effects were examined using colorectal and ovarian mouse model systems. In a mouse model of peritoneally disseminated ovarian cancer intraperitoneal administration of irinotecan was favorable to intravenous delivery however intraperitoneal delivery of nanoparticulate SN38 was significantly more effective than intraperitoneal irinotecan. In addition, in a mouse colorectal cancer model administration of nanoparticulate SN38 once weekly exhibited greater activity compared to daily or weekly administration of irinotecan. Additional studies demonstrated nanoparticulate SN38 administered as a combination therapy with mitomycin C was more effective than the combination of irinotecan and mitomycin C. Results from the present studies using preclinical colorectal and ovarian cancer model systems demonstrate the efficacy of nanoparticulate SN38 and substantiate continued development.

Modeling High-Grade Serous Carcinoma: How Converging Insights into Pathogenesis and Genetics are Driving Better Experimental Platforms

Recent developments in the study of epithelial ovarian cancer have called into question the traditional views regarding the site of tumor initiation. Histopathologic studies and genomic analyses suggest that extra-ovarian sites, like the fallopian tube, may harbor the coveted cell of origin and could therefore contribute significantly to the development of high-grade serous ovarian carcinoma (HG-SOC). Our ability to validate these emerging genomic and pathologic observations and characterize the early transformation events of HG-SOC hinges on the development of novel model systems. Currently, there are only a handful of new model systems that are addressing these concerns. This review will chronicle the convergent evolution of these ovarian cancer model systems in the context of the changing pathologic and genomic understanding of HG-SOC.

Abstract 4289: Using the right tools: A catalog of ovarian cancer cell lines by subtype

Abstract Ovarian cancer cell lines provide an important tool in exploring disease phenotypes and biology. Within the spectrum of ovarian epithelial cancers at least five histologically distinguishable unique diseases exist: high-grade serous, clear cell, endometrioid, mucinous, and low-grade serous. While sharing a common site of presentation, these ovarian cancer types exhibit distinct genomic signatures, clinical characteristics and treatment responses. Thus, the critical interpretation of the results of cell based experiments performed in in-vitro and in-vivo model systems of ovarian cancer first requires characterization of the disease subtype each model represents. Our group has recently used a minimal panel of nine immunohistochemical (IHC) markers, termed “COSP” (Calculator for Ovarian carcinoma Subtype Prediction), to predict each ovarian cancer type. Application of COSP has suggested that as many as 19% of primary ovarian cancer samples may be misclassified prior to an expert review. Commonly used cell lines are rarely classified into ovarian cancer types, confounding interpretation of results and potentially delaying transition of basic research to clinically relevant application. We now apply COSP for typing commonly used ovarian cancer cell lines, as well as in-house derived xenografts, and primary culture models. The COSP immuno-predictive tool is combined with molecular and mutational data to support each cell line's subtype prediction while primary tumour types are compared to their derivative cell lines. We now present an extensive panel of accurately classified ovarian cancer cell lines to facilitate disease specific analysis of the biology of ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4289. doi:10.1158/1538-7445.AM2011-4289

Mechanisms of resistance to cisplatin and alkylating agents.

All too often, human solid tumors follow a pattern of initial sensitivity to chemotherapy manifested by a decrease of tumor burden followed by a loss of sensitivity to chemotherapy and by tumor regrowth [1]. This sequence of events is attributed to the presence of a subset of cells in the original tumor that are resistant at the onset of therapy and/or to the induction of resistance mechanisms through the exposure to drugs during treatment. Whatever the origin of the phenotype, this progression from sensitivity to resistance is often observed during the treatment of ovarian cancer, and thus we have chosen this tumor as a prototype in which to investigate the mechanisms operative in conferring the resistance phenotype. We would then hope to expand our findings to other relevant tumor classes and to determine ways in which the emergence of drug resistance could be prevented or reversed. In this review, we will summarize our findings in ovarian cancer model systems as regards resistance mechanisms and describe related work of other investigators. In addition, less studied mechanistic possibilities will be noted and experience in reversal of drug resistance will be described.KeywordsOvarian CancerAlkylating AgentOvarian Cancer Cell LineHuman Ovarian CancerParental Cell LineThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Experimental model systems of ovarian cancer: applications to the design and evaluation of new treatment approaches.

Experimental model systems of ovarian cancer: applications to the design and evaluation of new treatment approaches.