Suppr超能文献

[EHHADH是肝细胞癌脂肪酸代谢途径中的关键基因:一项转录组分析]

[EHHADH is a key gene in fatty acid metabolism pathways in hepatocellular carcinoma: a transcriptomic analysis].

作者信息

Xie S, Li M, Jiang F, Yi Q, Yang W

机构信息

Department of Pathology, School of Basic Medical Sciences, Southern Medical University, Guangzhou 510515, China.

出版信息

Nan Fang Yi Ke Da Xue Xue Bao. 2023 May 20;43(5):680-693. doi: 10.12122/j.issn.1673-4254.2023.05.02.

Abstract

OBJECTIVE

To explore the driving gene of hepatocellular carcinoma (HCC) occurrence and progression and its potential as new therapeutic target of HCC.

METHODS

The transcriptome and genomic data of 858 HCC tissues and 493 adjacent tissues were obtained from TCGA, GEO, and ICGC databases. Gene Set Enrichment Analysis (GSEA) identified EHHADH (encoding enoyl-CoA hydratase/L-3-hydroxyacyl-CoA dehydrogenase) as the hub gene in the significantly enriched differential pathways in HCC. The downregulation of EHHADH expression at the transcriptome level was found to correlate with TP53 mutation based on analysis of the TCGA- HCC dataset, and the mechanism by which TP53 mutation caused EHHADH downregulation was explored through correlation analysis. Analysis of the data from the Metascape database suggested that EHHADH was strongly correlated with the ferroptosis signaling pathway in HCC progression, and to verify this result, immunohistochemical staining was used to examine EHHADH expression in 30 HCC tissues and paired adjacent tissues.

RESULTS

All the 3 HCC datasets showed signficnatly lowered EHHADH expression in HCC tissues as compared with the adjacent tissues ( < 0.05) with a close correlation with the degree of hepatocyte de-differentiation ( < 0.01). The somatic landscape of HCC cohort in TCGA dataset showed that HCC patients had the highest genomic TP53 mutation rate. The transcriptomic level of PPARGC1A, the upstream gene of EHHADH, was significantly downregulated in HCC patients with TP53 mutation as compared with those without the mutation ( < 0.05), and was significantly correlated with EHHADH expression level. GO and KEGG enrichment analyses showed that EHHADH expression was significantly correlated with abnormal fatty acid metabolism in HCC. The immunohistochemical results showd that the expression level of EHHADH in HCC tissues was down-regulated, and its expression level was related to the degree of hepatocytes de-differentiation and the process of ferroptosis.

CONCLUSION

TP53 mutations may induce abnormal expression of PPARGC1A to cause downregulation of EHHADH expression in HCC. The low expression of EHHADH is closely associated with aggravation of de-differentiation and ferroptosis escape in HCC tissues, suggesting the potential of EHHADH as a therapeutic target for HCC.

摘要

目的

探索肝细胞癌(HCC)发生发展的驱动基因及其作为HCC新治疗靶点的潜力。

方法

从TCGA、GEO和ICGC数据库获取858例HCC组织和493例癌旁组织的转录组和基因组数据。基因集富集分析(GSEA)确定EHHADH(编码烯酰辅酶A水合酶/L-3-羟酰基辅酶A脱氢酶)为HCC中显著富集的差异通路中的枢纽基因。基于对TCGA-HCC数据集的分析,发现转录组水平上EHHADH表达下调与TP53突变相关,并通过相关性分析探索TP53突变导致EHHADH下调的机制。对Metascape数据库数据的分析表明,EHHADH在HCC进展中与铁死亡信号通路密切相关,为验证这一结果,采用免疫组织化学染色检测30例HCC组织及配对癌旁组织中EHHADH的表达。

结果

所有3个HCC数据集均显示,与癌旁组织相比,HCC组织中EHHADH表达显著降低(<0.05),且与肝细胞去分化程度密切相关(<0.01)。TCGA数据集中HCC队列的体细胞图谱显示,HCC患者的基因组TP53突变率最高。与未发生TP53突变的HCC患者相比,发生TP53突变的HCC患者中EHHADH上游基因PPARGC1A的转录组水平显著下调(<0.05),且与EHHADH表达水平显著相关。GO和KEGG富集分析表明,EHHADH表达与HCC中异常脂肪酸代谢显著相关。免疫组织化学结果显示,HCC组织中EHHADH表达水平下调,其表达水平与肝细胞去分化程度及铁死亡过程有关。

结论

TP53突变可能诱导PPARGC1A异常表达,导致HCC中EHHADH表达下调。EHHADH低表达与HCC组织去分化加重和铁死亡逃逸密切相关,提示EHHADH作为HCC治疗靶点的潜力。

相似文献

引用本文的文献

本文引用的文献

2
Ordered and deterministic cancer genome evolution after p53 loss.p53 失活后有序且确定的癌症基因组进化。
Nature. 2022 Aug;608(7924):795-802. doi: 10.1038/s41586-022-05082-5. Epub 2022 Aug 17.
5
Fatty Acids Metabolism: The Bridge Between Ferroptosis and Ionizing Radiation.脂肪酸代谢:铁死亡与电离辐射之间的桥梁
Front Cell Dev Biol. 2021 Jun 24;9:675617. doi: 10.3389/fcell.2021.675617. eCollection 2021.
7
Liver Cancer: Therapeutic Challenges and the Importance of Experimental Models.肝癌:治疗挑战与实验模型的重要性
Can J Gastroenterol Hepatol. 2021 Feb 28;2021:8837811. doi: 10.1155/2021/8837811. eCollection 2021.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验