Prognostic Prediction Using a Stemness Index-Related Signature in a Cohort of Gastric Cancer

作者：Xiaowei Chen, Dawei Zhang, Fei Jiang, Yan Shen, Xin Li, Xueju Hu, Pingmin Wei, Xiaobing Shen · 发表于：Frontiers in Molecular Biosciences · 年份：2020 · DOI：10.3389/fmolb.2020.570702 · 被引用次数：87 · 研究领域：Ferroptosis and cancer prognosis、Cancer Cells and Metastasis、Gastric Cancer Management and Outcomes

Background. With characteristic self-renewal and multipotent differentiation, cancer stem cells (CSCs) have a crucial influence on the metastasis, relapse and drug resistance of gastric cancer (GC). However, the genes that participates in the stemness of GC stem cells have not been identified. Methods. The mRNA expression-based stemness index (mRNAsi) was analyzed with differential expressions in GC. The weighted gene co-expression network analysis (WGCNA) was utilized to build a co-expression network targeting differentially expressed genes (DEG) and discover mRNAsi-related modules and genes. We assessed the association between the key genes at both the transcription and protein level. Gene Expression Omnibus (GEO) database was used to validate the expression levels of the key genes. The risk model was established according to the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Furthermore, we determined the prognostic value of the model by employing Kaplan-Meier (KM) plus multivariate Cox analysis. Results. GC tissues exhibited a substantially higher mRNAsi relative to the healthy non-tumor tissues. Based on WGCNA, 17 key genes (ARHGAP11A, BUB1, BUB1B, C1orf112, CENPF, KIF14, KIF15, KIF18B, KIF4A, NCAPH, PLK4, RACGAP1, RAD54L, SGO2, TPX2, TTK, and XRCC2) were identified. These key genes were clearly overexpressed in GC and validated in the GEO database. The PPI (protein-protein interaction) network as assessed by STRING indicated that the ke...