Computational investigations into structure and function impact of novel mutations identified in targeted exons from ovarian cancer cell lines.

The lack of sensitive and specific biomarkers for ovarian cancer leads to late stage diagnosis of the disease in a majority of the cases. Mutation accumulation is the basis for cancer progression, thus identifying mutations is an important step in the disease diagnosis. In the present study, a comprehensive analysis of fifteen Next Generation Sequencing samples from thirteen ovarian cancer cell lines was carried out for the identification of new mutations. The study revealed eight clinically significant novel mutations in six ovarian cancer oncogenes, viz. SMARCA4, ARID1A, PPP2R1A, CTNNB1, DICER1 and PIK3CA. In-depth computational analysis revealed that the mutations affected the structure of the proteins in terms of stability, solvent accessible surface area and molecular dynamics. Moreover, the mutations were present in functionally significant domains of the proteins, thereby adversely affecting the protein functionality. PPI network for SMARCA4, CTNNB1, DICER1, PIK3CA, PPP2R1A and ARID1A showed that these genes were involved in certain significant pathways affecting various hallmarks of cancer. For further validation, studies were performed that revealed hypermutability of the CTNNB1 gene. Through this study we have identified some key mutations and have analysed their structural and functional impact. The study establishes some key mutations, which can be potentially explored as biomarker and drug target.Communicated by Ramaswamy H. Sarma.