胃癌（GC）的药物治疗效果有限，因此，深入研究GC发生的分子机制并鉴定能够大幅延长患者生存期的新分子具有重要的科学意义。本研究利用生物信息学技术鉴定了 11 个与 GC 患者无复发生存（RFS）相关的基因，并通过单细胞转录组分析研究了这些基因的潜在生物学功能。随后，选择单基因胱抑素A（CSTA）进行进一步分析，探讨其对信号通路和治疗的影响。在RFS分析中鉴定差异表达基因（DEG）并重叠，以识别GC患者的潜在预后基因，基于基于癌症基因组图谱-胃腺癌 (TCGA-STAD) 和 GSE54129 的数据。随后，建立了基于RFS的GC患者预后模型。利用单细胞测序数据来探索这些模型基因的潜在功能。使用免疫组织化学（IHC）、细胞计数试剂盒8（CCK-8）、transwell、划痕、集落形成实验、流式细胞术和Western blotting方法对RFS相关基因之一的CSTA进行了进一步研究。通过生物信息学分析，我们在 GC 中鉴定出 23 个 RFS 相关基因。使用最小绝对收缩和选择算子 (LASSO)-Cox 方法，开发了 RFS 预后模型，该模型确定 11 个 GC 预后相关 (GPR) 基因是影响 GC 患者 RFS 的重要因素。单细胞分析揭示了它们在影响前成纤维细胞的分化和成熟方面的潜在作用，从而影响GC患者的RFS。 CSTA在GC组织中表现出低表达水平。 CSTA 的过度表达通过 caspase 依赖性凋亡途径促进 GC 细胞凋亡，并通过同一途径增强其对顺铂的反应。 11 个 GPR 基因主要富集在特定类型的基质细胞中，表现出增强的通讯、代谢和分化水平。这些基质细胞的基因特征对患者的预后具有影响。此外，CSTA（一种与预后相关的基因）已被证明会影响 GC 细胞的凋亡水平。2024 年胃肠肿瘤学杂志。版权所有。

The effect of pharmacological treatment of gastric cancer (GC) is limited, thus, it holds significant scientific importance to thoroughly investigate the molecular mechanisms underlying GC development and identify novel molecules capable of substantially extending patients' survival. This study utilized bioinformatics techniques to identify 11 genes associated with recurrence-free survival (RFS) in GC patients and investigated the potential biological functions of these genes through single-cell transcriptomic analysis. Subsequently, a single gene Cystatin A (CSTA) was selected for further analysis to explore its impact on signaling pathways and treatment.Differentially expressed genes (DEGs) were identified and overlapped in the analysis of RFS to identify potential prognostic genes for GC patients, based on data from the Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) and GSE54129. Subsequently, a prognostic model based on RFS in GC patients was established. Single-cell sequencing data were employed to explore the potential functions of these model genes. CSTA, one of the RFS-related genes, was further investigated using immunohistochemistry (IHC), Cell Counting Kit 8 (CCK-8), transwell, scratch, colony formation assays, flow cytometry, and Western blotting methods.Through bioinformatics analysis, we identified 23 RFS-related genes in GC. Using the least absolute shrinkage and selection operator (LASSO)-Cox method, an RFS prognostic model was developed which pinpointed 11 GC prognosis-related (GPR) genes as significant factors influencing RFS in GC patients. The single-cell analysis revealed their potential role in affecting differentiation and maturation of pre-fibroblasts thereby impacting RFS in GC patients. CSTA exhibited low expression levels in GC tissues. Overexpression of CSTA promoted apoptosis in GC cells through the caspase-dependent apoptotic pathway and enhanced their response to cisplatin via this same pathway.The 11 GPR genes are primarily enriched within a specific type of stromal cell exhibiting heightened communication, metabolism, and differentiation levels. The gene signature of these stromal cells has implications for patient prognosis. Additionally, CSTA, a gene related to prognosis, has been shown to influence apoptosis levels in GC cells.2024 Journal of Gastrointestinal Oncology. All rights reserved.