Identification of prognostic markers by weighted gene co‐expression network analysis in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is one of the fatal tumors and is associated with a poor prognosis. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify the proportions of 22 types of immune cells. Weighted gene co-expression network analysis (WGCNA) was established from the GSE37745 data, and key modules correlating most with CD8⁺ T cell infiltration were determined. Genes that manifested a high module connectivity in the key module were identified as hub genes. Three bioinformatics online databases were used to evaluate hub gene expression levels in tumor and normal tissues. Finally, survival analysis was conducted for these hub genes. In this study, we chose four hub genes (<i>AURKB, CDC20, TPX2</i> and <i>KIF2C</i>) based on the comprehensive bioinformatics analyses. All hub genes were overexpressed in tumor tissue, and high expression of <i>AURKB, CDC20, TPX2</i>, and <i>KIF2C</i> correlated with the poor prognosis of these patients. In vitro experiments confirmed that <i>CDC20</i> knockdown inhibited cell proliferation and growth. The above results indicated that AURKB, CDC20, TPX2, and KIF2C are potential CD8⁺ T cell infiltration-related biomarkers and therapeutic targets.

非小细胞肺癌（Non-small cell lung cancer, NSCLC）是一类致命性肿瘤，且预后不良。本研究采用通过估算RNA转录本相对子集进行细胞类型鉴定（Cell-type identification by estimating relative subsets of RNA transcripts, CIBERSORT）算法，定量分析22种免疫细胞的占比。基于GSE37745数据集构建加权基因共表达网络分析（Weighted gene co-expression network analysis, WGCNA），筛选出与CD8⁺ T细胞浸润相关性最强的关键模块，并将关键模块中具有高模块连通性的基因鉴定为核心基因（hub genes）。通过3个生物信息学在线数据库评估核心基因在肿瘤组织与正常组织中的表达水平，随后针对这些核心基因开展生存分析。本研究经综合生物信息学分析，最终筛选出4个核心基因：AURKB、CDC20、TPX2及KIF2C。所有核心基因在肿瘤组织中均呈高表达状态，且AURKB、CDC20、TPX2与KIF2C的高表达与患者不良预后显著相关。体外实验证实，敲低CDC20可抑制细胞增殖与生长。上述结果表明，AURKB、CDC20、TPX2及KIF2C是潜在的与CD8⁺ T细胞浸润相关的生物标志物及治疗靶点。