Background: Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality rate that seriously threatens human health. We aimed to investigate the expression, prognostic value, and immune cell infiltration of lactic acid metabolism-related genes (LAMRGs) in HCC using bioinformatics.Methods: The HCC database (The Cancer Genome Atlas–Liver Hepatocellular Carcinoma) was downloaded from the Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) between normal and tumor groups were identified. The LAMRGs were obtained from literature and GeneCards and MSigDB databases. Lactic acid metabolism-related differentially expressed genes (LAMRDEGs) in HCC were screened from the DEGs and LAMRGs. Functional enrichment analyses of the screened LAMRDEGs were further conducted using Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Set Enrichment Analysis (GSEA). The genes were used in multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses to construct a prognostic model. Then, a protein-protein interaction network was constructed using STRING and CTD databases. Furthermore, the CIBERSORTx online database was used to assess the relationship between immune cell infiltration and hub genes.Results: Twenty-eight lactic acid metabolism-related differentially expressed genes (LAMRDEGs) were identified. The GO and KEGG analyses showed that the LAMRDEGs were related to the prognosis of HCC. The GSEA indicated that the LAMRDEGs were significantly enriched in tumor related pathways. In the multivariate Cox regression analysis, 14 key genes (E2F1, SERPINE1, GYS2, SPP1, PCK1, CCNB1, CYP2C9, IGFBP3, KDM8, RCAN1, ALPL, FBP1, NQO1, and LCAT) were found to be independent prognostic factors of HCC. Finally, the LASSO and Cox regression analyses showed that six key genes (SERPINE1, SPP1, CCNB1, CYP2C9, NQO1, and LCAT) were associated with HCC prognosis. Moreover, the correlation analyses revealed that the expression of the six key genes were associated with immune infiltrates of HCC.Conclusion: The LAMRDEGs can predict the prognosis and may be associated with immune cells infiltration in patients with HCC. These genes might be the promising biomarkers for the prognosis and treatment of HCC.

中文翻译：

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肝细胞癌乳酸代谢相关差异表达基因的鉴定及功能分析

【摘要】：背景:肝细胞癌(HCC)是一种发病率和死亡率较高的恶性肿瘤,严重威胁人类健康。我们的目的是利用生物信息学研究乳酸代谢相关基因（LAMRG）在 HCC 中的表达、预后价值和免疫细胞浸润。方法：从 Cancer Genome 下载 HCC 数据库（The Cancer Genome Atlas–Liver Hepatocellular Carcinoma）阿特拉斯（TCGA）。鉴定了正常组和肿瘤组之间的差异表达基因（DEG）。 LAMRG 是从文献以及 GeneCards 和 MSigDB 数据库中获得的。从DEGs和LAMRGs中筛选出HCC中乳酸代谢相关差异表达基因(LAMRDEGs)。使用基因本体（GO）分析、京都基因和基因组百科全书（KEGG）分析和基因集富集分析（GSEA）进一步对筛选的LAMRDEG进行功能富集分析。这些基因用于多变量 Cox 回归和最小绝对收缩和选择算子 (LASSO) 分析，以构建预后模型。然后，使用 STRING 和 CTD 数据库构建了蛋白质-蛋白质相互作用网络。此外，利用CIBERSORTx在线数据库评估免疫细胞浸润与中枢基因之间的关系。结果：鉴定出28个乳酸代谢相关差异表达基因（LAMRDEG）。 GO和KEGG分析表明LAMRDEGs与HCC的预后相关。 GSEA 表明 LAMRDEG 在肿瘤相关通路中显着富集。在多变量Cox回归分析中，发现14个关键基因（E2F1、SERPINE1、GYS2、SPP1、PCK1、CCNB1、CYP2C9、IGFBP3、KDM8、RCAN1、ALPL、FBP1、NQO1和LCAT）是HCC的独立预后因素。最后，LASSO和Cox回归分析显示，6个关键基因（SERPINE1、SPP1、CCNB1、CYP2C9、NQO1和LCAT）与HCC预后相关。此外，相关性分析显示，6个关键基因的表达与HCC的免疫浸润有关。结论：LAMRDEGs可以预测肝癌患者的预后，并可能与HCC患者的免疫细胞浸润有关。这些基因可能是 HCC 预后和治疗的有希望的生物标志物。