Genebased evidence for burden of rare pathogenic variants in pharmacogenes and oncogens of Czech breast cancer patients Panel of 509 pharmacogenes and oncogenes was selected for targeted next generation sequencing. Data mining in databases and functional impact software tools were used as an evidence for potential pathogenicity. Survey of several in silico methods revealed significant differences in resultant set of genes mostly due to number of tools used. Following the most stringent approach with fully concordant prediction in comparison to specific combination of tools and majority vote prediction, ten prioritized genes were statistically correlated with the clinical patient data. The highest burden of pathogenic variants correlating with clinical data was statistically significant in CFTR gene. Patients carrying these variants had significantly reduced diseasefreesurvival in comparison with patients without these variants.

Computational analyses prioritize and reveal the deleterious nsSNPs in human angiotensinogen gene Abstract   Angiotensinogen (AGT) is a key component of reninangiotensinaldosterone system (RAAS), which plays central role in blood pressure homeostasis. Association of AGT polymorphisms have been investigated in different ethnic populations in variety of cardiovascular and noncardiovascular conditions. In this study, 354 nonsynonymous SNPs (nsSNPs) of AGT were evaluated to predict damaging and structurally important variants. Majority of the deleterious nsSNPs occurred in the evolutionary conserved regions. Several of these nsSNPs were found to affect posttranslational modifications like methylation, glycosylation, phosphorylation, ubiquitination etc. Structural evaluations predicted 19 variants as destabilizing and some of them were also predicted to destabilize the reninAGT interaction. Therefore, the present computational investigation predicted pathogenic and functionally important variants of human AGT gene. The study has also shown that AGT deregulation is associated with survival outcome in patients with gastric and breast cancer, using microarray gene expression profile. Furthermore, the computationally screened nsSNPs can be analyzed in population based genotyping studies and may help futuristic drug development in the area of AGT pharmacogenomics.