Journal Article

Screening of common genomic biomarkers to explore common drugs for the treatment of pancreatic and kidney cancers with type-2 diabetes through bioinformatics analysis

Haque Mollah, Md. Nurul, Ajadee, Alvira, Mahmud, Sabkat, Noor, Tasfia, Sarkar, Arnob, Ahmmed, Reaz

2025

Overview

Type 2 diabetes (T2D) is a crucial risk factor for both pancreatic cancer (PC) and kidney cancer (KC). However, effective common drugs for treating PC and/or KC patients who are also suffering from T2D are currently lacking, despite the probability of their co-occurrence. Taking disease-specific multiple drugs during the co-existence of multiple diseases may lead to adverse side effects or toxicity to the patients due to drug-drug interactions. This study aimed to identify T2D-, PC and KC-causing common genomic biomarkers (cGBs) highlighting their pathogenetic mechanisms to explore effective drugs as their common treatment. We analyzed transcriptomic profile datasets, applying weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis approaches to identify T2D-, PC-, and KC-causing cGBs. We then disclosed common pathogenetic mechanisms through gene ontology (GO) terms, KEGG pathways, regulatory networks, and DNA methylation of these cGBs. Initially, we identified 78 common differentially expressed genes (cDEGs) that could distinguish T2D, PC, and KC samples from controls based on their transcriptomic profiles. From these, six top-ranked cDEGs (TOP2A, BIRC5, RRM2, ALB, MUC1, and E2F7) were selected as cGBs and considered targets for exploring common drug molecules for each of three diseases. Functional enrichment analyses, including GO terms, KEGG pathways, and regulatory network analyses involving transcription factors (TFs) and microRNAs, along with DNA methylation and immune infiltration studies, revealed critical common molecular mechanisms linked to PC, KC, and T2D. Finally, we identified six top-ranked drug molecules (NVP.BHG712, Irinotecan, Olaparib, Imatinib, RG-4733, and Linsitinib) as potential common treatments for PC, KC and T2D during their co-existence, supported by the literature reviews. Thus, this bioinformatics study provides valuable insights and resources for developing a genome-guided common treatment strategy for PC and/or KC patients who are also suffering from T2D.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 631/114 / 631/154 / 631/67 / 692/53 / 692/699 / 692/700 / Bioinformatics / Biomarkers / Biomarkers, Tumor - genetics / Cancer / Common drugs and toxicity / Computational Biology - methods / Deoxyribonucleic acid / Diabetes / Diabetes mellitus (non-insulin dependent) / Diabetes Mellitus, Type 2 - complications / Diabetes Mellitus, Type 2 - drug therapy / Diabetes Mellitus, Type 2 - genetics / DNA / DNA Methylation / Drug interaction / Drugs / Gene expression / Gene Expression Profiling / Gene Expression Regulation, Neoplastic / Gene Ontology / Gene Regulatory Networks / Genetic association / Genomics / Genomics - methods / Humanities and Social Sciences / Humans / Imatinib / Immunosuppressive agents / Inhibitor drugs / Irinotecan / Kidney and pancreatic cancers / Kidney cancer / Kidney Neoplasms - complications / Kidney Neoplasms - drug therapy / Kidney Neoplasms - genetics / Kidneys / Literature reviews / miRNA / Molecular modelling / multidisciplinary / Pancreatic cancer / Pancreatic Neoplasms - complications / Pancreatic Neoplasms - drug therapy / Pancreatic Neoplasms - genetics / Protein interaction / Protein Interaction Maps / Risk factors / Science / Science (multidisciplinary) / Side effects / Statistics and bioinformatics analysis / Toxicity / Transcription factors / Transcriptome / Transcriptomics / Transcriptomics profiles and shared key genes / Type-2 diabetes