A Novel Signature Composed of Hypoxia, Glycolysis, Lactylation Related Genes to Predict Prognosis and Immunotherapy in Hepatocellular Carcinoma.

IF 3.3 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Feng Yi, Shichao Long, Yuanbing Yao, Kai Fu
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引用次数: 0

Abstract

Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide. The hypoxic microenvironment in HCC enhances glycolysis and co-directed lactate accumulation, which leads to increased lactylation. However, the exact biological pattern remains to be elucidated. Therefore, we sought to identify hypoxia-glycolysis-lactylation (HGL) prognosis-related signatures and validate this in vitro.

Methods: Transcriptomic data of patients with HCC were collected from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Differentially expressed HGL genes between HCC and normal tissues were obtained by DEseq2. The consensus clustering algorithm was employed to stratify patients into two distinct clusters. Subsequently, the single sample Gene Set Enrichment Analysis (ssGSEA), Tumor Immune Estimation Resource (TIMER) and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were utilized to assess immune infiltration and immune evasion. Least Absolute Shrinkage and Selection Operator (LASSO) and COX regression analysis were used to identify an HGL prognosis-related signature. Based on spatial transcriptome and histological data, we analyzed the expression of these genes in HCC and explored the function of Homer Scaffold Protein 1 (HOMER1) in HCC cells.

Results: We identified 72 differentially expressed HGL genes and two HGL clusters. Cluster2, with better survival (p < 0.001), was significantly enriched in metabolic-related pathways. The HGL prognosis-related signature exhibited great predictive efficacy for patients in TCGA, ICGC, and GSE148355 databases (3-year area under the curve (AUC) = 0.822, 0.738, and 0.707, respectively). The elevated expression of HOMER1 in HCC was revealed by the combination of spatial transcriptome and histological data. Knocking down HOMER1 significantly inhibited the malignant progression of HCC cells.

Conclusions: We identified a signature with great predictive efficacy and discovered a gene, HOMER1, that influences the malignant progression of HCC with the potential to become a novel therapeutic target.

由缺氧、糖酵解、乳酸化相关基因组成的新特征预测肝癌预后和免疫治疗。
背景:肝细胞癌(HCC)是世界范围内癌症死亡的主要原因之一。HCC中的缺氧微环境促进糖酵解和共定向乳酸积累,从而导致乳酸化增加。然而,确切的生物学模式仍有待阐明。因此,我们试图确定缺氧-糖酵解-乳酸化(HGL)预后相关特征,并在体外验证。方法:从癌症基因组图谱(TCGA)、国际癌症基因组联盟(ICGC)和基因表达综合数据库(GEO)中收集HCC患者的转录组学数据。通过DEseq2获得HCC与正常组织间差异表达的HGL基因。采用共识聚类算法将患者分为两个不同的聚类。随后,利用单样本基因集富集分析(ssGSEA)、肿瘤免疫估计资源(TIMER)和肿瘤免疫功能障碍和排斥(TIDE)算法评估免疫浸润和免疫逃避。最小绝对收缩和选择算子(LASSO)和COX回归分析用于确定与HGL预后相关的特征。基于空间转录组和组织学数据,我们分析了这些基因在HCC中的表达,并探讨了Homer Scaffold Protein 1 (HOMER1)在HCC细胞中的功能。结果:我们鉴定出72个差异表达的HGL基因和2个HGL集群。Cluster2在代谢相关通路中显著富集,生存率更高(p < 0.001)。在TCGA、ICGC和GSE148355数据库中,HGL预后相关特征对患者具有良好的预测效果(3年曲线下面积(AUC)分别为0.822、0.738和0.707)。结合空间转录组和组织学数据,揭示了HOMER1在HCC中的表达升高。敲低HOMER1可显著抑制HCC细胞的恶性进展。结论:我们发现了一个具有很大预测功效的特征,并发现了一个影响HCC恶性进展的基因HOMER1,它有可能成为一个新的治疗靶点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
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