Probing biological network in concurrent carcinomas and Type-2 diabetes for potential biomarker screening: An advanced computational paradigm

Abstract

Type-2 diabetes mellitus (T2DM), the predominant form of diabetes in adults, is a co-morbid condition that exacerbates the severity of many other diseases, including cardiovascular disease, obesity, dyslipidemia, hypertension, and cancer. Among these, cancer is particularly concerning due to elevated mortality rates and a distinct lack of cost-effective therapeutic interventions. Identifying novel biomarkers for improved early cancer detection is imperative. Therefore, an integrated bioinformatics analysis was conducted to elucidate the co-morbid relationship between T2DM and five different types of cancer, namely bladder (BLCA), breast (BRCA), colon (CRC), liver (HCC), and prostate cancer (PRAD) and identification of novel biomarkers for early cancer detection in individuals with T2DM. A significant comorbid relationship was observed among T2DM, BLCA, and BRCA through gene expression and pathway enrichment analysis, while a moderate association was observed for between T2DM, and PRAD. Notably, we identified 18 significant hub proteins in the context of cancer and T2DM, along with 16 transcription factors and 5 miRNAs. Among these, the hub proteins ESR1, PIK3CA, GNAI1, ERBB2, NR3C1, SNCA, TGFBR2, as well as the micro RNAs hsa-mir-335–5p, hsa-mir-16–5p, and hsa-mir-93–5p hold promise for understanding the comorbidities of T2DM and cancers; and could serve as valuable disease biomarkers for clinical diagnosis and prognosis. This study, centred on bioinformatics analysis for biomarker identification in comorbidities, paves the way for future research encompassing wet lab experimentation and translational studies. These endeavours are poised to validate and facilitate the integration of these findings into the realm of personalized medicine.