Role of apoptotic regulators in human epithelial ovarian cancer

• Published in: Cancer biology & therapy Vol. 6; no. 7; pp. 1101 - 1105
• Main Authors: Kar, Rajarshi, Sen, Sudip, Singh, Archna, Sharma, Himani, Kumar, Sunesh, Gupta, Siddhartha Dutta, Singh, Neeta
• Format: Journal Article
• Language: English
• Published: United States Taylor & Francis 01.07.2007
• Subjects: Apoptosis; bcl-X Protein - analysis; Binding; Biology; Bioscience; Calcium; Cancer; Cell; Cycle; Female; Genes, BRCA1; Humans; Inhibitor of Apoptosis Proteins; Landes; Microtubule-Associated Proteins - analysis; Neoplasms, Glandular and Epithelial - pathology; Organogenesis; Ovarian Neoplasms - pathology; Proteins; Proto-Oncogene Proteins - analysis; Proto-Oncogene Proteins c-bcl-2 - analysis; Proto-Oncogene Proteins p21(ras); ras Proteins - analysis; Survivin; Telomerase - metabolism; Tumor Suppressor Protein p53 - analysis
• ISSN: 1538-4047; 1555-8576
• DOI: 10.4161/cbt.6.7.4329

We assessed molecular markers such as BRCA1, K-ras, p53, Bcl-2, Bcl-XL, Survivin and telomerase activity in untreated ovarian cancer tissue samples, ascitic cells and normal ovarian tissues and gathered insights into their correlation with each other and also with apoptotic index. The expression of these proteins was analyzed by Western blotting and immunohistochemistry. Apoptotic index was determined by TUNEL assay and telomerase activity was measured by PCR-ELISA kit. p53, Bcl-2, Bcl-XL, K-ras and Survivin were found to be over expressed in tumors and ascitic cells as compared to normal controls whereas there was no significant difference in expression of BRCA1. A significantly higher telomerase activity and lower apoptotic index in tumors as compared to controls was observed. p53 positively correlated with Bcl-2, Bcl-XL, K-ras and Survivin expression and also clinical stage of the disease. A positive correlation between Survivin and Bcl-2, Bcl-XL was seen. Apoptotic Index, telomerase activity and BRCA1 expression showed no correlation with any of the parameters. Our study confirms the fact that multiple gene interactions govern the pathogenesis of ovarian cancer, and analyzing ascitic cells of ovarian cancer patients may help to delineate molecular profile of the primary tumor.