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The impact of EpCAM expression on response to chemotherapy and clinical outcomes in patients with epithelial ovarian cancer.

ABSTRACT: Epithelial ovarian cancer is a highly lethal malignancy; moreover, overcoming chemoresistance is the major challenging in treating ovarian cancer patients. The cancer stem cell (CSC) hypothesis considers CSCs to be the main culprits in driving tumor initiation, metastasis, and resistance to conventional therapy. Although growing evidence suggest that CSCs are responsible for chemoresistance, the contribution of CSC marker EpCAM to resistance to chemotherapy remains unresolved.Here we have demonstrated that ovarian cancers containing high levels of EpCAM have a significantly much lower probability of achieving overall responsive rates after first-line chemotherapy. In addition, multivariate analysis revealed that EpCAM expression is an independent risk factor for chemoresistance, indicating that EpCAM expression is a predictive biomarker of chemotherapeutic response. Consistent with these clinical observations, in vitro assays, we found that the subpopulation of EpCAM-positive ovarian cancer cells shows a significantly higher viability compared with EpCAM-negative cells in response to cisplatin treatment by preventing chemotherapy-induced apoptosis, which is regulated by EpCAM-Bcl-2 axis. Furthermore, in an in vivo mouse model, platinum agents preferentially eliminated EpCAM-negative cells in comparison with EpCAM-positive cells, suggesting that the remaining subpopulation of EpCAM-positive cells contributes to tumor recurrence after chemotherapy. Finally, we also found that an increased expression of EpCAM is associated with poor prognosis in ovarian cancer patients.Our findings highlight the clinical significance of EpCAM in the resistance to chemotherapy and provide a rationale for EpCAM-targeted therapy to improve chemoresistance. Targeting EpCAM should be a promising approach to effectively extirpate the CSCs as the putative root of ovarian cancer.

SUBMITTER: Tayama S

PROVIDER: S-EPMC5546482 | biostudies-other | 2017 Jul

REPOSITORIES: biostudies-other

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Project description:BACKGROUND:Over the last twenty years, the efforts of the scientific community devoted to the comprehension and treatment of ovarian cancer have remained poorly remunerative, with the case-fatality ratio of this disease remaining disappointedly high. Limited knowledge of the basic principles regulating ovarian carcinogenesis and factors impacting the course of disease may significantly impair our ability to intervene in early stages and lessen our expectations in terms of treatment outcomes. In the present study, we sought to assess whether metabolic factors and anthropometric indicators, i.e., pre-treatment fasting glucose and body mass index, are associated with renown cancer related prognostic factors such as tumour stage and grade at diagnosis. MATERIALS AND METHODS:Study participants were 147 women diagnosed with epithelial ovarian cancer and treated with platinum based regimens and/or surgery at the Regina Elena National Cancer Institute of Rome, Italy. Glucose levels were assessed at the institutional laboratories on venous blood collected in overnight fasting conditions and prior to any therapeutic procedure. Stage was coded according to the FIGO staging system based on the results of the diagnostic workup, while tumour grade was locally assessed by an expert pathologist. Participants' characteristics were descriptively analyzed for the overall study population and in a subgroup of 70 patients for whom data on body mass index (BMI) were available. FIGO stage and grade were compared by categories of pre-treatment fasting glucose defined upon the median value, i.e., 89 mg/dl. The association of interest was tested in regression models including BMI. RESULTS:For the overall study population, patients in the lowest category of fasting glucose were significantly more likely to exhibit a FIGO stage III-IV at diagnosis compared with their counterpart in the highest glucose category (81.3 vs 66.7%, p: 0.021). Subgroup analysis in 70 patients with BMI data confirmed this association (81.5 vs 55.8, p: 0.049), which remained significant when tested in regression models including BMI (OR: 0.28 95% CI 0.086-0.89, p: 0.031). No relevant evidence emerged when testing the association between fasting glucose and tumour grade. CONCLUSIONS:In patients diagnosed with epithelial ovarian cancer, pre-treatment glucose levels appear to be inversely associated with FIGO stage. Further studies are warranted to eventually confirm and correctly interpret the implications of this novel finding.

Project description:BackgroundEpithelial ovarian cancer (EOC) is a spectrum of different diseases, which makes their treatment a challenge. Forkhead box M1 (FOXM1) is an oncogene aberrantly expressed in many solid cancers including serous EOC, but its role in non-serous EOCs remains undefined. We examined FOXM1 expression and its correlation to prognosis across the three major EOC subtypes, and its role in tumorigenesis and chemo-resistance in vitro.MethodsGene signatures were generated by microarray for 14 clear-cell and 26 endometrioid EOCs, and 15 normal endometrium snap-frozen biopsies. Validation of FOXM1 expression was performed by RT-qPCR and immunohistochemistry in the same samples and additionally in 50 high-grade serous EOCs and in their most adequate normal controls (10 luminal fallopian tube and 20 ovarian surface epithelial brushings). Correlations of FOXM1 expression to clinic-pathological parameters and patients' prognosis were evaluated by Kaplan-Meier and Cox proportional-hazards analyses. OVCAR-3 and two novel deeply characterized EOC cell lines (EOC-CC1 and OSPC2, with clear-cell and serous subtype, respectively) were employed for in vitro studies. Effects of FOXM1 inhibition by transient siRNA transfection were evaluated on cell-proliferation, cell-cycle, colony formation, invasion, and response to conventional first- and second-line anticancer agents, and to the PARP-inhibitor olaparib. Gene signatures of FOXM1-silenced cell lines were generated by microarray and confirmed by RT-qPCR.ResultsA significant FOXM1 mRNA up-regulation was found in EOCs compared to normal controls. FOXM1 protein overexpression significantly correlated to serous histology (p = 0.001) and advanced FIGO stage (p = 0.004). Multivariate analyses confirmed FOXM1 protein overexpression as an independent indicator of worse disease specific survival in non-serous EOCs, and of shorter time to progression in platinum-resistant cases. FOXM1 downregulation in EOC cell lines inhibited cell growth and clonogenicity, and promoted the cytotoxic effects of platinum compounds, doxorubicin hydrochloride and olaparib. Upon FOXM1 knock-down in EOC-CC1 and OSPC2 cells, microarray and RT-qPCR analyses revealed the deregulation of several common and other unique subtype-specific FOXM1 putative targets involved in cell cycle, metastasis, DNA repair and drug response.ConclusionsFOXM1 is up-regulated in all three major EOCs subtypes, and is a prognostic biomarker and a potential combinatorial therapeutic target in platinum resistant disease, irrespective of tumor histology.

Project description:To identify potential aberrantly differentially methylated genes (DMGs) correlated with chemotherapy response (CR) and establish a polygenic methylation prediction model of CR in epithelial ovarian cancer (EOC), we accessed 177 (47 chemo-sensitive and 130 chemo-resistant) samples corresponding to three DNA-methylation microarray datasets from the Gene Expression Omnibus and 306 (290 chemo-sensitive and 16 chemo-resistant) samples from The Cancer Genome Atlas (TCGA) database. DMGs associated with chemotherapy sensitivity and chemotherapy resistance were identified by several packages of R software. Pathway enrichment and protein-protein interaction (PPI) network analyses were constructed by Metascape software. The key genes containing mRNA expressions associated with methylation levels were validated from the expression dataset by the GEO2R platform. The determination of the prognostic significance of key genes was performed by the Kaplan-Meier plotter database. The key genes-based polygenic methylation prediction model was established by binary logistic regression. Among accessed 483 samples, 457 (182 hypermethylated and 275 hypomethylated) DMGs correlated with chemo resistance. Twenty-nine hub genes were identified and further validated. Three genes, anterior gradient 2 (AGR2), heat shock-related 70-kDa protein 2 (HSPA2), and acetyltransferase 2 (ACAT2), showed a significantly negative correlation between their methylation levels and mRNA expressions, which also corresponded to prognostic significance. A polygenic methylation prediction model (0.5253 cutoff value) was established and validated with 0.659 sensitivity and 0.911 specificity. Graphical Abstract With the use of comprehensive bioinformatics analysis, AGR2, HSPA2, and ACAT2 were identified a significantly negative correlation between their differentially methylated levels and mRNA expressions, which also corresponded to prognostic significance in epithelial ovarian cancer. A polygenic methylation prediction model of chemotherapy response based on these three genes was established and validated.

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The impact of EpCAM expression on response to chemotherapy and clinical outcomes in patients with epithelial ovarian cancer.

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