Department of Radiation Oncology, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, China.
Department of Radiation Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Biosci Rep. 2021 Apr 30;41(4). doi: 10.1042/BSR20203676.
Detecting and diagnosing gastric cancer (GC) during its early period remains greatly difficult. Our analysis was performed to detect core genes correlated with GC and explore their prognostic values.
Microarray datasets from the Gene Expression Omnibus (GEO) (GSE54129) and The Cancer Genome Atlas (TCGA)-stomach adenocarcinoma (STAD) datasets were applied for common differentially co-expressed genes using differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Functional enrichment analysis and protein-protein interaction (PPI) network analysis of differentially co-expressed genes were performed. We identified hub genes via the CytoHubba plugin. Prognostic values of hub genes were explored. Afterward, Gene Set Enrichment Analysis (GSEA) was used to analyze survival-related hub genes. Finally, the tumor-infiltrating immune cell (TIC) abundance profiles were estimated.
Sixty common differentially co-expressed genes were found. Functional enrichment analysis implied that cell-cell junction organization and cell adhesion molecules were primarily enriched. Hub genes were identified using the degree, edge percolated component (EPC), maximal clique centrality (MCC), and maximum neighborhood component (MNC) algorithms, and serpin family E member 1 (SERPINE1) was highly associated with the prognosis of GC patients. Moreover, GSEA demonstrated that extracellular matrix (ECM) receptor interactions and pathways in cancers were correlated with SERPINE1 expression. CIBERSORT analysis of the proportion of TICs suggested that CD8+ T cell and T-cell regulation were negatively associated with SERPINE1 expression, showing that SERPINE1 may inhibit the immune-dominant status of the tumor microenvironment (TME) in GC.
Our analysis shows that SERPINE1 is closely correlated with the tumorigenesis and progression of GC. Furthermore, SERPINE1 acts as a candidate therapeutic target and prognostic biomarker of GC.
在胃癌（GC）早期阶段进行检测和诊断仍然非常困难。我们进行了分析，以检测与 GC 相关的核心基因，并探讨其预后价值。
使用差异基因表达分析和加权基因共表达网络分析（WGCNA）从基因表达综合数据库（GEO）（GSE54129）和癌症基因组图谱（TCGA）-胃腺癌（STAD）数据集应用微阵列数据集来检测共同差异共表达基因。对差异共表达基因进行功能富集分析和蛋白质-蛋白质相互作用（PPI）网络分析。我们通过 CytoHubba 插件确定了枢纽基因。探讨了枢纽基因的预后价值。之后，进行基因集富集分析（GSEA）以分析与生存相关的枢纽基因。最后，估计肿瘤浸润免疫细胞（TIC）丰度谱。
发现了 60 个共同差异共表达基因。功能富集分析表明，细胞-细胞连接组织和细胞黏附分子主要富集。使用度、边渗透成分（EPC）、最大聚类中心（MCC）和最大邻域成分（MNC）算法确定了枢纽基因，丝氨酸蛋白酶抑制剂家族 E 成员 1（SERPINE1）与 GC 患者的预后高度相关。此外，GSEA 表明细胞外基质（ECM）受体相互作用和癌症途径与 SERPINE1 表达相关。CIBERSORT 分析 TIC 的比例表明，CD8+T 细胞和 T 细胞调节与 SERPINE1 表达呈负相关，表明 SERPINE1 可能抑制 GC 肿瘤微环境（TME）的免疫主导状态。
我们的分析表明，SERPINE1 与 GC 的发生和发展密切相关。此外，SERPINE1 可作为 GC 的候选治疗靶点和预后生物标志物。
