School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China.
Department of Pharmaceutics and Pharmacy Administration, School of Pharmacy, Air Force Medical University, Xi'an, Shanxi 710032, China.
Biomed Res Int. 2021 Jan 9;2021:6905985. doi: 10.1155/2021/6905985. eCollection 2021.
The majority of lung cancers are adenocarcinomas, with the proportion being 40%. The patients are mostly diagnosed in the middle and late stages with metastasis and easy recurrence, which poses great challenge to the treatment and prognosis. Platinum-based chemotherapy is a primary treatment for adenocarcinoma, which frequently causes drug resistance. As a result, it is important to uncover the mechanisms of the chemoresponse of adenocarcinoma to platinum-based chemotherapy.
The genes from the dataset GSE7880 were gathered into gene modules with the assistance of weighted gene coexpression network analysis (WGCNA), the gene trait significance absolute value (|GS|), and gene module memberships (MM). The genes from hub gene modules were calculated with a protein-protein interaction (PPI) network analysis in order to obtain a screening map of hub genes. The hub genes with both a high |GS| and MM and a high degree were selected. Furthermore, genes in the hub gene modules also went through a Gene Ontology (GO) functional enrichment analysis.
11 hub genes in four hub gene modules (LY86, ACTR2, CDK2, CKAP4, KPNB1, RBBP4, SMAD4, MYL6, RPS27, TSPAN2, and VAMP2) were chosen as the significant hub genes. Through the GO function enrichment analysis, it was indicated that four modules were abundant in immune system functions (floralwhite), amino acid biosynthetic process (lightpink4), cell chemotaxis (navajowhite2), and targeting protein (paleturquoise). Four hub genes with the highest |GS| were verified by prognostic analysis.
大多数肺癌是腺癌,占比为 40%。这些患者大多在中晚期被诊断出来,存在转移和易复发的情况,这给治疗和预后带来了巨大挑战。铂类化疗是治疗腺癌的主要方法,但常导致耐药。因此,揭示腺癌对铂类化疗的化学反应机制非常重要。
利用加权基因共表达网络分析(WGCNA)、基因特征显著性绝对值(|GS|)和基因模块成员(MM),将数据集 GSE7880 中的基因收集到基因模块中。利用蛋白质-蛋白质相互作用(PPI)网络分析,计算枢纽基因模块中的基因,以获得枢纽基因的筛选图。选择具有高|GS|和 MM 以及高度数的枢纽基因。此外,枢纽基因模块中的基因还进行了基因本体(GO)功能富集分析。
从四个枢纽基因模块(LY86、ACTR2、CDK2、CKAP4、KPNB1、RBBP4、SMAD4、MYL6、RPS27、TSPAN2 和 VAMP2)中选择了 11 个枢纽基因作为显著枢纽基因。通过 GO 功能富集分析,表明四个模块富含免疫系统功能(floralwhite)、氨基酸生物合成过程(lightpink4)、细胞趋化作用(navajowhite2)和靶向蛋白(paleturquoise)。通过预后分析验证了四个具有最高|GS|的枢纽基因。