CALB2介导的肿瘤微环境免疫细胞浸润在肝癌复发中的作用机制分析

摘要] 目的 利用生物信息学技术分析筛选出与肝癌复发相关的核心基因及信号通路，为探索肝癌复发的分子机制提供理论依据。方法 从TCGA和GEO数据库下载肝癌相关数据集，利用edgeR算法筛选差异表达基因。选择关键基因后，应用LASSO-Logistic回归分析构建复发预测模型。 ssGSEA、CIBERSORT和MCP算法用于评估免疫浸润细胞。结果 共筛选出343个复发相关差异表达基因。富集分析表明，大多数基因富集于细胞分化、跨膜转运蛋白、转运乙酰胆碱复合物。蛋白质-蛋白质相互作用网络分析确定了 12 个关键基因。然后，通过 Lasso-logistic 回归分析确定了一个独立的风险评分模型，其中包括3个基因 SST、CALB2 和 DRD2。该风险评分显示出较好的预测能力，并且还构建了基于风险评分的临床列线图。此外，证明了CALB2在肿瘤组织中低表达，与肿瘤微环境中的免疫浸润细胞呈正相关。结论 复发相关基因模型可以提供较好的预测患者复发的能力，其中的核心基因CALB2 可以在肝癌复发中发挥关键作用。

Effect of CALB2 mediated immune cell infiltration in tumor microenvironment for the recurrence of liver cancer:a mechanism study based on bioinformatics

Abstract] Objective To study the molecular mechanism of hepatocellular carcinoma (HCC) recurrence by screening the key genes and signal pathways based on bioinformatics technology. Methods The HCC related datasets were downloaded from TCGA and GEO database, and the edgeR algorithm was used to screen differentially expressed genes. After key genes were selected, LASSO-Logistic regression model was applied to construct recurrence prediction model. The ssGSEA, CIBERSORT, and MCP algorithm were used to evaluate immune infiltration cell. Results A total of 343 recurrence related differentially expressed genes were screened. Enrichment analysis indicated that most of the genes were enriched in cell differentiation, transmembrane transporters, transport acetylcholine complex. Protein-protein interaction network analysis identified 12 key genes. Then, we identified an independent risk-score model by Lasso-logistic regression analysis, which included SST, CALB2, and DRD2. This risk-score showed a better prediction ability and risk-score based clinical nomogram was also constructed. Moreover, CALB2 was proved to be positively correlated with immune infiltration cell in tumor microenvironment. Conclusion The three-genes based signature could provide a better efficacy to predict patient recurrence and CALB2 could play a crucial role in HCC recurrence.