A Comprehensive Bioinformatics Approach to Identify Key Genes and Comorbidities of Breast Cancer

Invasive Ductal Carcinoma (IDC) is among the most prevalent type of breast cancer (BC) which starts within milk ducts and attacks nearby tissues. It is the most common female cancer in world. It is rising all over the world, at different rates. To pinpoint and development of therapeutic target for cancer is vital to identify the influential genes. We analyzed TCGA dataset from BC for uncovering key regulated genes for BC. Then we refined the dataset and implemented Bonferroni correction and Kruskal-Wallis test method to recognize influential gene of breast cancer. We formed influential gene-disease association networks, heat-map and also identified dysregulated pathways, ontological pathways, protein-protein interaction (PPI) network, and protein-drug interaction (PDI) network. This analysis could contribute to developing strategy for disease cure and increasing consciousness of the impact of breast cancer. Differentially expressed genes (DEGs) linked to breast cancer were interrogated using the gold-standard dbGaP and OMIM repositories from the Enrichr platform. After careful statistical analysis and a review of the literature, we found six relevant comorbidities.