Background:We aimed to identify key molecular drivers of gastric cancer progression and poor prognosis by integrating multi-omics analyses with experimental validation.Methods:Single-cell RNA-seq data were clustered to delineate major cell types. InferCNV identified tumor epithelial cells, and reclustering revealed a malignant subset with poor prognosis. The overlap between subset markers and The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD) upregulated differentially expressed genes (DEGs) was modeled with univariate, LASSO-, and multivariate Cox to derive a prognostic signature. Patients were stratified according to signature scores, and group differences in survival and immunologic features were compared. Spatial transcriptomics defined the localization patterns of key signature genes. In vitro functional assays (CCK-8, colony formation, EdU incorporation, flow cytometry, Transwell migration and invasion, and wound healing) confirmed the pivotal role of SRI.Results:Reclustering of tumor epithelial cells yielded seven subsets (C0–C6), with C5 displaying marked malignant features and correlating with poor prognosis in multiple cohorts. Intersecting 208 genes yielded a five-gene signature (ASCL2, REPIN1, CXCL3, TMEM176A, SRI). The signature stratified patients into high- and low-risk groups. The high-risk cohort exhibited significantly poorer survival, distinct immune-infiltration patterns, elevated immune-evasion scores, and a reduced predicted response to immunotherapy. Single-cell and spatial transcriptomics localized TMEM176A to fibroblasts and SRI to the tumor epithelium. Finally, in vitro knockdown of SRI inhibited tumor cell proliferation, migration and invasion.Conclusions:Our multi-omics approach identified a malignant epithelial subset, C5, and a five-gene signature that stratifies gastric cancer prognosis and immune response. Functional assays showed that SRI knockdown impairs tumor cell growth, migration and invasion.
背景：本研究旨在通过整合多组学分析与实验验证，识别胃癌进展及不良预后的关键分子驱动因素。 方法：对单细胞RNA测序数据进行聚类以界定主要细胞类型。通过InferCNV鉴定肿瘤上皮细胞，经二次聚类识别出与不良预后相关的恶性亚群。将该亚群标志物与癌症基因组图谱胃腺癌（TCGA-STAD）中上调的差异表达基因（DEGs）取交集，通过单变量、LASSO回归及多变量Cox回归分析构建预后特征模型。根据特征评分对患者进行分层，比较组间生存率及免疫学特征的差异。空间转录组学明确了关键特征基因的定位模式。通过体外功能实验（CCK-8、克隆形成、EdU掺入、流式细胞术、Transwell迁移侵袭及划痕愈合实验）验证SRI的核心作用。 结果：肿瘤上皮细胞二次聚类产生七个亚群（C0–C6），其中C5亚群呈现显著恶性特征，在多个队列中与不良预后相关。208个交集基因最终形成包含五个基因（ASCL2、REPIN1、CXCL3、TMEM176A、SRI）的特征模型。该模型将患者分为高风险组和低风险组：高风险组生存率显著降低，呈现独特的免疫浸润模式、更高的免疫逃逸评分及较差的免疫治疗预测反应。单细胞与空间转录组学分析显示TMEM176A定位于成纤维细胞，SRI定位于肿瘤上皮细胞。体外实验证实敲低SRI可抑制肿瘤细胞增殖、迁移和侵袭能力。 结论：本研究通过多组学方法识别出恶性上皮亚群C5及包含五个基因的预后特征模型，该模型可有效分层胃癌预后及免疫反应。功能实验表明敲低SRI能够抑制肿瘤细胞的生长、迁移和侵袭。
肿瘤(癌症)患者之家