Department of Clinical Laboratory, Guangyuan Central Hospital, Guangyuan 628000, China.
Department of Medical Imaging, Guangyuan Central Hospital, Guangyuan 628000, China.
J Diabetes Res. 2022 May 13;2022:4629419. doi: 10.1155/2022/4629419. eCollection 2022.
So far, type 2 diabetes (T2D) is considered as an independent risk factor for various cancers, but the underlying mechanism remains unclear. was first identified as a key gene strongly associated with fasting plasma glucose (FPG). Then, overlapped differentially expressed genes (DEGs) between T2D verse control and -high verse -low were extracted and imported into weighted correlation network analysis. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and gene set enrichment analysis were used for functional enrichment analysis of DEGs. Least absolute shrinkage and selection operator was utilized to build a T2D prediction model. Timer and - plotters were employed to find the expression and prognosis of in pan cancer.
Interestingly, both DEGs between T2D verse control and -high verse -low enriched in cancer-related pathways. Moreover, a total of 3719 overlapped DEGs were divided into 8 functional modules. Grey module negatively correlated with T2D and FPG and was markedly involved in ribosome biogenesis. Ten -related genes (, , , , , , , , , and ) were identified as hub genes, based on which the LASSO model accurately predicts the occurrence of T2D (AUC = 0.841). In addition, was only expressed in islet cells and showed abnormal expression in 17 kinds of cancers and significantly correlated with the prognosis of 10 kinds of cancers.
Taken together, may link T2D and cancer by influencing the ribosome function of islet cells and play different prognostic roles in different cancers.
到目前为止，2 型糖尿病（T2D）被认为是多种癌症的独立危险因素，但潜在机制尚不清楚。 最初被确定为与空腹血糖（FPG）强烈相关的关键基因。然后，提取 T2D 与对照相比和 -高与 -低之间的重叠差异表达基因（DEGs），并将其导入加权相关网络分析。基因本体论、京都基因与基因组百科全书和基因集富集分析用于 DEGs 的功能富集分析。最小绝对收缩和选择算子用于构建 T2D 预测模型。Timer 和 -plotters 用于在泛癌中寻找 的表达和预后。
有趣的是，T2D 与对照相比和 -高与 -低之间的 DEGs 都富集在癌症相关途径中。此外，共有 3719 个重叠的 DEGs 分为 8 个功能模块。灰色模块与 T2D 和 FPG 呈负相关，并且明显参与核糖体生物发生。基于此，确定了 10 个 -相关基因（、、、、、、、、和）作为枢纽基因，基于此，LASSO 模型可以准确预测 T2D 的发生（AUC = 0.841）。此外， 仅在胰岛 细胞中表达，在 17 种癌症中表达异常，与 10 种癌症的预后显著相关。
总之， 通过影响胰岛 细胞的核糖体功能， 可能将 T2D 和癌症联系起来，并在不同的癌症中发挥不同的预后作用。
