高血糖和胰岛素不敏感会导致终生慢性代谢性疾病，称为 2 型糖尿病 (T2D)，这种疾病更有可能患上不同的恶性肿瘤。患有癌症等合并症的 T2D 可能会使治疗这些疾病的常规药物变得更加困难。合并症之间可能存在显着相关性，并对彼此的健康产生影响。这些关联可能是由于许多直接和间接机制造成的。 T2D 和癌症的分子机制尚不清楚。然而，有关这些疾病的大量数据使我们能够使用分析工具来揭示其相互关联的途径。在这里，我们试图提出一个系统，通过观察所涉及的分子过程，使用生物信息学分析大量可免费访问的各种疾病的转录组数据集，来研究 T2D 和癌症疾病之间潜在的共病关系。利用语义相似性和基因集富集分析，我们创建了一个信息学管道，用于评估和集成基因本体 (GO)、基因表达和生物过程数据。我们发现了 T2D 和癌症中常见的基因以及分子途径和 GO。我们比较了每个选定的 T2D 和癌症数据集中的前 200 个差异表达基因 (DEG)，并找到了最重要的常见基因。在所有常见基因中，有 13 个基因出现频率最高。我们还在 T2d 和不同癌症之间的所有常见 GO 术语中发现了 4 个常见 GO 术语：GO:0000003、GO:0000122、GO:0000165 和 GO:0000278。利用这些基因和 GO 术语语义相似性，我们计算了这两种疾病之间的距离。我们研究的语义相似性结果显示肝癌 (LiC)、乳腺癌 (BreC)、结直肠癌 (CC) 和膀胱癌 (BlaC) 与 T2D 的关联性较高。此外，我们发现 KIF4A、NUSAP1、CENPF、CCNB1、TOP2A、CCNB2、RRM2、HMMR、NDC80、NCAPG 和 IGFBP5 是与 T2D 相关的不同癌症中的常见枢纽蛋白。糖尿病并发症中AGE-RAGE信号通路、破骨细胞分化、TNF信号通路、IL-17信号通路、p53信号通路、MAPK信号通路、人类T细胞白血病病毒1感染、非酒精性脂肪肝是前8位在 T2D 和选定癌症之间的 18 种常见途径中发现了重要途径。由于我们的技术，我们现在对 T2D 和癌症之间至关重要的疾病途径有了更多了解。版权所有 © 2023。由 Elsevier Inc. 出版。

High blood sugar and insulin insensitivity causes the lifelong chronic metabolic disease called Type 2 diabetes (T2D) which has a higher chance of developing different malignancies. T2D with comorbidities like Cancers can make normal medications for those disorders more difficult. There may be a significant correlation between comorbidities and have an impact on one another's health. These associations may be due to a number of direct and indirect mechanisms. Such molecular mechanisms that underpin T2D and cancer are yet unknown. However, the large volumes of data available on these diseases allowed us to use analytical tools for uncovering their interrelated pathways. Here, we tried to present a system for investigating potential comorbidity relationships between T2D and Cancer disease by looking at the molecular processes involved, analyzing a huge number of freely accessible transcriptomic datasets of various disorders using bioinformatics. Using semantic similarity and gene set enrichment analysis, we created an informatics pipeline that evaluates and integrates Gene Ontology (GO), expression of genes, and biological process data. We discovered genes that are common in T2D and Cancer along with molecular pathways and GOs. We compared the top 200 Differentially Expressed Genes (DEGs) from each selected T2D and cancer dataset and found the most significant common genes. Among all the common genes 13 genes were found most frequent. We also found 4 common GO terms: GO:0000003, GO:0000122, GO:0000165, and GO:0000278 among all the common GO terms between T2d and different cancers. Using these genes and GO term semantic similarity, we calculated the distance between these two diseases. The semantic similarity results of our study showed a higher association of Liver Cancer (LiC), Breast Cancer (BreC), Colorectal Cancer (CC), and Bladder Cancer (BlaC) with T2D. Furthermore we found KIF4A, NUSAP1, CENPF, CCNB1, TOP2A, CCNB2, RRM2, HMMR, NDC80, NCAPG, and IGFBP5 common hub proteins among different cancers correlated to T2D. AGE-RAGE signaling pathway in diabetic complications, Osteoclast differentiation, TNF signaling pathway, IL-17 signaling pathway, p53 signaling pathway, MAPK signaling pathway, Human T-cell leukemia virus 1 infection, and Non-alcoholic fatty liver disease are the 8 most significant pathways found among 18 common pathways between T2D and selected cancers. As a result of our technique, we now know more about disease pathways that are critical between T2D and cancer.Copyright © 2023. Published by Elsevier Inc.