Deciphering the scalene association among type‐2 diabetes mellitus, prostate cancer, and chronic myeloid leukemia via enrichment analysis of disease‐gene network

Abstract

Abstract The potential biological relationship between type‐2 diabetes mellitus (T2DM) has been focused in numerous studies. To investigate the molecular associations among T2DM, prostate cancer (PCa), and chronic myeloid leukemia (CML), using a biomolecular network enrichment analysis. We obtained a list of disease‐related genes and constructed disease networks. Then, GO enrichment analysis was performed to identify the significant functions and pathways of overlapping modules in the Database for Annotation, Visualization and Integrated Discovery (DAVID) database. More than 75% of these overlapping genes were found to be consistent with the findings of previous studies. In the three diseases, we found that Sarcoglycan delta (SGCD) and Rho family GTPase 3 (RND3) were the overlapping genes and identified negative regulation of apoptotic process and negative regulation of transcription from RNA polymerase II promoter RNA as the two overlapping biological functions. CML and PCa were the most closely related, with 34 overlapping genes, five overlapping modules, 27 overlapping biological functions, and nine overlapping pathways. There were 13 overlapping genes, one overlapping modules, four overlapping biological functions and one overlapping pathway (FoxO signaling pathway) were found in T2DM and CML.And T2DM and PCa were the least related pair in our study, with only six overlapping genes, five overlapping modules, and one overlapping biological function. SGCD and RND3 were the main gene‐to‐gene relationship among T2DM, CML, and PCa; apoptosis, development, and transcription from RNA polymerase II promote processes were the main functional connections among T2DM, CML, and PCa by network enrichment analysis. There is a “scalene” relationship among T2DM, CML, and PCa at gene, pathway, biological process, and module levels: CML and PCa were the most closely related, the second were T2DM and PCa, and T2DM and PCa were the least related pair in our study. Our study provides a new avenue for further studies on T2DM and cancers, which may promote the discovery and development of novel therapeutic and can be used to treat multiple diseases.

Keywords

• chronic myeloid leukemia
• overlapping gene and module
• prostate cancer
• therapeutic prediction
• type 2 diabetes mellitus