Potential predictive markers of chemotherapy resistance in stage III ovarian serous carcinomas

<p>Abstract</p> <p>Background</p> <p>Chemotherapy resistance remains a major obstacle in the treatment of women with ovarian cancer. Establishing predictive markers of chemoresponse would help to individualize therapy and improve survival of ovarian cancer patients. Chemotherapy resistance in ovarian cancer has been studied thoroughly and several non-overlapping single genes, gene profiles and copy number alterations have been suggested as potential markers. The objective of this study was to explore genetic alterations behind chemotherapy resistance in ovarian cancer with the ultimate aim to find potential predictive markers.</p> <p>Methods</p> <p>To create the best opportunities for identifying genetic alterations of importance for resistance, we selected a homogenous tumor material concerning histology, stage and chemotherapy. Using high-resolution whole genome array comparative genomic hybridization (CGH), we analyzed the tumor genomes of 40 fresh-frozen stage III ovarian serous carcinomas, all uniformly treated with combination therapy paclitaxel/carboplatin. Fisher's exact test was used to identify significant differences. Subsequently, we examined four genes in the significant regions (<it>EVI1</it>, <it>MDS1</it>, <it>SH3GL2</it>, <it>SH3KBP1</it>) plus the <it>ABCB1 </it>gene with quantitative real-time polymerase chain reaction (QPCR) to evaluate the impact of DNA alterations on the transcriptional level.</p> <p>Results</p> <p>We identified gain in 3q26.2, and losses in 6q11.2-12, 9p22.3, 9p22.2-22.1, 9p22.1-21.3, Xp22.2-22.12, Xp22.11-11.3, and Xp11.23-11.1 to be significantly associated with chemotherapy resistance. In the gene expression analysis, <it>EVI1 </it>expression differed between samples with gain versus without gain, exhibiting higher expression in the gain group.</p> <p>Conclusion</p> <p>In conclusion, we detected specific genetic alterations associated with resistance, of which some might be potential predictive markers of chemotherapy resistance in advanced ovarian serous carcinomas. Thus, further studies are required to validate these findings in an independent ovarian tumor series.</p

Bank Liability Structure, FDIC Loss, and Time to Failure: A Quantile Regression Approach

Bank liability structure, loss given default, market discipline, time to failure, quantile regression,