Network-Based Bioinformatics Approaches to Identify Molecular Biomarkers for Diabetes on the Progression of Cancers

Diabetes is one of the most concerning diseases in the world today. According to the IDF Diabetes Atlas, almost 537 million 20-79 years old adults are living with diabetes and they predicted this number will be increased 643 million in 2030. In Type-1 diabetes the pancreas doesn’t produce enough insulin, frequently seen in both children and adults. And In Type-2 diabetes (T2D) the body doesn’t use insulin hormone that regulate the movement of glucose into cells to use as energy effectively. Higher blood sugar level provides an adequate supply of energy for rapidly dividing cancer cells that causes cancer progression. Patients with both diabetes and cancer have more risky than without diabetes and diabetes influence cancer progression. In our study we tried to determine the link between Diabetes and various cancers including Breast Cancer (BS), Ovarian Cancer (OC), Cervical Cancer (CC) and Stomach or Gastric Cancer (GC). Here we were using a network-based bioinformatics approach to uncover the connection in Diabetes with the development of selected cancers. We have found that Diabetes is linked with cancers progression sharing with 46, 46, 46, 79 Differentially Expressed Genes (DEGs) with BC, OC, CC and GC respectively. Then we constructed up and down diseasome network, Protein-Protein Interactions (PPIs), significant pathways and ontological analysis, Protein-Drug Interactions (PDIs), survival analysis and validate our study using Gold Benchmark datasets. In our entire study we used the Gene Expression Omnibus (GEO) dataset, STRING database, TCGA database, gold benchmark database, Enrichr tools, NetworkAnalyst, Cytoscape, Python and R programming language. This study depicts the significant correlation between and specific cancers that require more clinical focus and facilitating better disease prediction based on genetic biomarker and advanced research.