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Objective Prostate cancer (PCa) is a complex heterogeneous disease and a major health risk to men throughout the world. The potential tumorigenic genetic hallmarks associated with PCa include sustaining proliferative signaling, resisting cell death, aberrant androgen receptor signaling, androgen independence, and castration resistance. Despite numerous comprehensive genome-wide association studies (GWAS), certain genetic elements associated with PCa are still unknown. This situation demands more systematic GWAS studies in different populations. This study presents a computational strategy for identification of novel and uncharacterized genetic factors associated with incidence of PCa in South Asian populations. Materials and methods Genome-wide association studies (GWAS) catalog and Gene Expression Omnibus (GEO) furnished PCa-related genetic studies. Database for Annotation, Visualization and Integrated Discovery (DAVID) functionally annotated these genes and wANNOVAR separated South Asian (SAS) populations – specific genetic factors at MAF threshold <0.05. Results The study reports 195 genes as potential contributors to prostate cancer in SAS populations. Some of identified genes are PYGO2, RALBP1, RFX5, SLC22A3, VPS53, HMCN1 and KIF1C. Conclusion The identified genetic elements may assist in development of population-specific screening and management strategies for PCa. Moreover, this approach may also be used to retrieve potential genetic elements associated with other types of cancers.

Currently, the whole world is facing the coronavirus disease-19 pandemic. As of now, approximately 0.15 million people around the globe are infected with the novel coronavirus. In the last decade, two strains of the coronavirus family, severe acute respiratory syndrome-related coronavirus and Middle East respiratory syndrome coronavirus, also resulted in epidemics in south Asian and the Middle Eastern countries with high mortality rate. This scenario demands the development of a putative vaccine which may provide immunity against all current and new evolving coronavirus strains. In this study, we designed an epitope-based vaccine using an immunoinformatic approach. This vaccine may protect against all coronavirus strains. The vaccine is developed by considering