相当多的胃癌（GC）患者无法从当前的治疗中获益。我们的目的是鉴定 GC 患者中铜凋亡相关基因 (CRG) 的可能生物标志物，这可能有助于指导基于精准医学的决策。RNA 测序数据、拷贝数变异 (CNV) 数据和单核苷酸变异 (SNV) 数据来自癌症基因组图谱（TCGA）数据库和基因集癌症分析（GSCA）数据库。采用卡方检验筛选14种癌组织样本与癌旁组织样本之间差异表达的CRGs（DE-CRGs）。然后，根据DE-CRG将GC样本分为高表达组和低表达组，以进行进一步的生存分析和生物标志物的选择。获得与生物标志物相关的甲基化位点。验证了免疫细胞和生物标志物之间的相关性。最后，建立miRNA-mRNA、TFs-mRNA和共表达网络来检测对生物标志物具有调节作用的因子。LIAS、GLS和CDKN2A等三种CRG被确定为GC患者的生物标志物。获得了cg13601799、07562918和07253264这三个具有显着生存效应的甲基化位点。然后，我们发现B细胞天然与CDKN2A显着相关，T细胞调节等四种免疫细胞与GLS显着相关，CD4记忆激活的T细胞等两种免疫细胞与LIAS显着相关。此外，miRNA-mRNA 网络中的 10 个 miRNA 和 TFs-mRNA 网络中的 3 个转录因子 (TF) 与总生存期 (OS) 具有显着相关性。最终在共表达网络的基础上得到了20个富集函数，找到了3个具有GC预后预测价值的生物标志物，并构建了多因素调控网络，筛选出了13个对生物标志物有调节影响的因素。2024胃肠肿瘤学。版权所有。

A considerable number of gastric cancer (GC) patients cannot receive benefits from current treatments. We aimed to identify possible biomarkers of cuproptosis-related genes (CRGs) in GC patients, which may help guide precision medicine-based decision-making.RNA sequencing data, copy number variations (CNVs) data, and single nucleotide variant (SNV) data were obtained from The Cancer Genome Atlas (TCGA) database and Gene Set Cancer Analysis (GSCA) database. Chi-squared test was adopted to screen differentially expressed CRGs (DE-CRGs) between samples from 14 kinds of carcinoma and adjacent tissue samples. Then, GC samples were divided into high- and low-expressed groups based on DE-CRGs for further survival analyses and the selection of biomarkers. Methylation sites related with biomarkers were acquired. The correlation between immune cells and biomarkers was verified. Finally, miRNA-mRNA, TFs-mRNA, and co-expression networks were established to detect factors with regulating effects on biomarkers.Three CRGs including LIAS, GLS, and CDKN2A were identified as biomarkers in GC patients. Three methylation sites with a significant survival effect including cg13601799, 07562918, and 07253264 were acquired. Then, we found that B cells native was significantly correlated with CDKN2A, four immune cells such as T cells regulatory are significantly correlated with GLS, and two immune cells such as T cells CD4 memory activated were significantly correlated with LIAS. Moreover, 10 miRNAs in the miRNA-mRNA network and three transcription factors (TFs) in the TFs-mRNA network had a significant correlation with overall survival (OS). Finally, 20 enrichment functions were obtained on the basis of the co-expression network.Three biomarkers with a prognosis prediction value of GC were found, and multi-factor regulatory networks were constructed to screen out 13 factors with regulating influences of biomarkers.2024 Journal of Gastrointestinal Oncology. All rights reserved.