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ORIGINAL ARTICLE
Year : 2021  |  Volume : 8  |  Issue : 1  |  Page : 44-51

In silico BRCA1 pathway analysis in breast invasive carcinoma


1 Department of Bioinformatics, Hazara University, Mansehra, Pakistan
2 School of Biological Sciences, Quaid-e-Azam Campus, University of the Punjab, Lahore, Pakistan

Correspondence Address:
Dr. Asima Tayyeb
School of Biological Sciences, Quaid-e-Azam Campus, University of the Punjab, Lahore
Pakistan
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/mgmj.mgmj_88_20

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Recent developments in clinical patient-based personalized genomics explored a variety of biomarkers for diagnosis, prognosis, and therapy in breast invasive carcinoma (BRIC). BRCA1 mutations mediated a catastrophic situation for a damage-repairing apparatus that induced malignant transformation of breast tissue. To identify an association between BRCA1 regulatory behavior and the pathway-level proteome for determining drug discovery channels, here we developed a computational scheme for BRCA1 pathway dataset retrieval from PathCards: PATHWAY UNIFICATION DATABASE (1,073 superpaths of 3,215 human pathways from 12 sources), BRCA1 pathway regulation analysis from cBioPortal for Cancer Genomics (more than 40 datasets of above 13,000 cancer samples), and BRC1 network construction from STRING v11.0 database (24,584,628 proteins of 5,090 organisms). Our study reveals about 700 alterations of 64 pathway components in 482 BRIC samples, in which there were 422 loss-of-function (LOF) mutations and 278 amplifications. We found 19 members (BRCA1, BRCA2, FANCA, ATM, NBN, SMARCD2, HDAC9, PLK1, SMARCA4, POU2F1, TP53, HDAC2, HLTF, BLM, E2F4, UBC, E2F5, MRE11, and RB1) based on a minimum 2% participation that showed 541 alterations in which there were 193 amplifications and 348 LOF mutations. From 19 components, BRCA1, BRCA2, FANCA, ATM, and TP53 have high-level LOF mutations whereas E2F5, NBN, SMARCD2, and POU2F1 have prominent amplifications. We developed three modules in which the BRCA1 module has 12 members that are involved in damage sensing and repairing processes as hot spots showing overexpression and LOF mutations. This in silico approach uniquely addressed BRCA1 mutations’ influence on BRIC at the pathway proteome level, with module identification as a hub for drug designing. We proposed these proteins as biomarkers for first-class diagnosis and clinical investigations. In the future, BRCA1 pathway-related therapeutic markers are used for further experimental investigations regarding drug development in breast cancer biology.


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