Type 2 diabetes (T2D) has become increasingly recognized not just as a chronic metabolic disorder but also as a significant risk factor for various cancers, particularly pancreatic cancer (PC) and kidney cancer (KC). Across the globe, the problem is rapidly worsening; by the year 2045, it is projected there will be around 629 million individuals with diabetes, according to the International Diabetes Federation. Alarmingly, 80% of pancreatic cancer patients and 40% of kidney cancer patients are estimated to also have T2D. Yet, currently, effective therapeutic strategies for treating patients suffering from both cancer and diabetes are scarce.
Research presented by authors analyzed existing genomic data using sophisticated bioinformatics tools to identify shared genomic biomarkers and potential common drug treatments for patients afflicted with T2D alongside either PC or KC. Utilizing transcriptomic profiles, weighted gene co-expression network analysis (WGCNA), and protein-protein interaction (PPI) network approaches, they identified 78 common differentially expressed genes (cDEGs) associated with these conditions.
Following this, six top-ranked common genomic biomarkers (cGBs) were identified as targets for therapeutic exploration: TOP2A, BIRC5, RRM2, ALB, MUC1, and E2F7. These genes are deeply tied to the disease processes of T2D, PC, and KC and reveal common cellular mechanisms at play.
"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," wrote the authors of the article. The cGBs were analyzed for their functional roles through gene ontology (GO) terms, KEGG pathways, and regulatory networks, enriching the connection between these diseases and the insights gleaned from genetic interactions. The regulatory investigations yielded key transcription factors and microRNAs, elucidated the molecular pathways, and examined the effects of DNA methylation.
Perhaps more significantly, the researchers also evaluated the binding affinities of 434 candidate drugs against these biomarkers through molecular docking, identifying six top-ranked drug molecules—NVP.BHG712, Irinotecan, Olaparib, Imatinib, RG-4733, and Linsitinib—with promise for common treatment across these diseases. Each drug was carefully selected based on pharmacokinetic properties and potential clinical effectiveness.
The urgency for developing effective treatments is heightened as both PC and KC are predicted to experience dramatic increases in incidence and mortality over the next decade, with pancreatic cancer potentially becoming the second leading cause of cancer-related deaths by 2030. The authors assert, "The findings of this study might be valid resources for diagnosis and therapies for PC and KC patients who are also suffering from T2D." The identification and validation of these biomarkers and drug candidates could pave the way for significant advancements in managing patients facing the dual challenges of T2D and cancer.
While this research presents promising avenues, it carries with it the caution typical of bioinformatics explorations: findings must be empirically validated through rigorous clinical trials. Nevertheless, the interconnections unearthed between these diseases represent an important step forward, not only highlighting shared genetic underpinnings but also equipping the medical community with potential targeted strategies to combat these devasting health conditions effectively.