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Prostate cancer (PCa) represents the second most frequently diagnosed malignancy among males in the United States and ranks fourth in terms of general cancer prevalence on a global scale. A critical assessment of existing literature indicates a notable deficiency in the identification of biomarkers that are uniquely associated with aggressive forms of PCa. The principal objective of this paper is to discover biomarkers at the genetic variant level by deploying statistical methodologies to determine associations between such variants and the aggressive and lethal form of the disease. Employing the multiple comparisons technique, we identified four variants that were statistically significant at the 5 % significance level. Furthermore, we utilized Over-representation analysis (ORA) to identify the biological pathways linked with these genetic variants. To validate our findings, we employed a decision tree algorithm on an independent dataset comparing the proposed biomarkers with random subsets of variants. Results have shown that the predictive accuracy of aggressive samples was 97 % for the proposed biomarkers, while this figure dropped to 67 % when randomly selected variants were considered. 

Similar molecular and genetic aberrations among diseases can lead to the discovery of jointly important treatment options across biologically similar diseases. Oncologists closely looked at several hormone-dependent cancers and identified remarkable pathological and molecular similarities in their DNA repair pathway abnormalities. Although deficiencies in Homologous Recombination (HR) pathway plays a significant role towards cancer progression, there could be other DNA-repair pathway deficiencies that requires careful investigation. In this paper, through a biomarker-driven drug repurposing model, we identified several potential drug candidates for breast and prostate cancer patients with DNA-repair deficiencies based on common specific biomarkers and irrespective of the organ the tumors originated from. Normalized discounted cumulative gain (NDCG) and sensitivity analysis were used to assess the performance of the drug repurposing model. Our results showed that Mitoxantrone and Genistein were among drugs with high therapeutic effects that significantly reverted the gene expression changes caused by the disease (FDR adjusted p-values for prostate cancer =1.225e-4 and 8.195e-8, respectively) for patients with deficiencies in their homologous recombination (HR) pathways. The proposed multi-cancer treatment framework, suitable for patients whose cancers had common specific biomarkers, has the potential to identify promising drug candidates by enriching the study population through the integration of multiple cancers and targeting patients who respond poorly to organ-specific treatments.