非肝硬化乙型肝炎病毒相关肝细胞癌的转录组测序及其对患者生存的影响

doi:10.3969/j.issn.1006-7795.2023.05.016

首都医科大学学报 ›› 2023, Vol. 44 ›› Issue (5): 811-820.doi: 10.3969/j.issn.1006-7795.2023.05.016

非肝硬化乙型肝炎病毒相关肝细胞癌的转录组测序及其对患者生存的影响

万妍¹,刘芳²,郭闪²,吴剑^1*

1.首都体育学院运动科学与健康学院，北京 100191；2.首都医科大学附属北京佑安医院北京肝病研究所，北京 100069

收稿日期:2022-12-21 出版日期:2023-10-20 发布日期:2023-10-25
通讯作者: 吴剑 E-mail:wujiancupes@126.com
基金资助:
北京市百千万人才工程资助项目 (2019A15)，北京市属医学科研院所公益发展改革试点项目 (京医研2021-10)

Transcriptome sequencing and survival analysis of noncirrhotic hepatitis B viral（HBV）-related hepatocellular carcinoma

Wan Yan¹, Liu Fang², Guo Shan², Wu Jian^1*

1.School of Kinesiology and Health, Capital University of Physical Education and Sports, Beijing 100191, China; 2. Beijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing 100069, China

Received:2022-12-21 Online:2023-10-20 Published:2023-10-25
Supported by:
This study was supported by Beijing Hundred Thousand Talents Project (2019A15), the Beijing Municipal Institute of Public Medical Research Development and Reform Pilot Project (2021-10).

摘要/Abstract

摘要： 目的通过转录组测序以及生物信息学分析探讨非肝硬化乙型肝炎病毒（hepatitis B viral，HBV）相关肝细胞癌的转录特征及与患者生存的关系。方法通过转录组测序获得非肝硬化HBV相关肝细胞癌（hepatocellular carcinoma，HCC）的差异表达基因；利用基因本体（gene ontology， GO）和京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes， KEGG）数据库富集分析获得差异表达基因涉及的生物功能过程及信号通路；通过基因-基因功能相互作用网络分析获得关键基因；利用癌症基因图谱（the cancer genome atlas,TCGA）数据库肝癌队列对关键基因进行生存预后分析。结果共发现上调差异基因3 672个，下调差异基因2 715个。GO功能富集分析主要涉及细胞分化、DNA复制、DNA修复、炎症反应免疫应答、细胞黏附等。KEGG通路富集主要包括细胞周期、氧化磷酸化、p53信号通路、肿瘤坏死因子（tumor necrosis factor，TNF）信号通路和核因子κB（nuclear factor kappa-B，NF-κB）信号通路等。其中丝裂原活化蛋白激酶3（mitogen-activated protein kinase 3，MAPK3）、Ras相关C3肉毒毒素底物1（ras-related C3 cotulinum toxin substrate 1，RAC1）、磷脂酶Cβ1(phospholipase C beta 1，PLCβ1)、连环蛋白β1（catenin beta 1，CTNNβ1）、非转移性细胞1（non-metastatic cells 1，NME1）基因和非转移性细胞6（non-metastatic cells 6，NME6）基因高表达与肝癌患者预后不良相关（P<0.05）；FYN、细胞色素P450（cytochrome P450，CYP）2C8和CYP2C9低表达与肝癌患者预后不良有关（P<0.05）。结论非肝硬化HBV相关肝细胞癌发生涉及多个生物学过程和信号通路的改变，与肝癌患者的生存预后相关的关键基因为理解非肝硬化HBV相关HCC发生机制提供新线索。

关键词: 非肝硬化肝细胞癌, 差异表达基因, 信号通路

Abstract: Objective Transcriptome sequencing and bioinformatics analysis were used to explore the transcriptional characteristics and survival analysis of non-cirrhotic hepatitis B viral（HBV）-related hepatocellular carcinoma (HCC). Methods The differentially expressed genes in non-cirrhotic HBV-related HCC were obtained by transcriptome sequencing. The biological functional processes and signaling pathways involved in the differentially expressed genes were obtained by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The key genes were obtained by gene-gene function interaction network analysis, and the key genes were analyzed for survival prognosis using the cancer genome atlas (TCGA) database’s HCC cohort. Results A total of 3 672 up-regulated differential genes and 2 715 down-regulated differential genes were identified. The GO functional enrichment analysis mainly involved cell differentiation, DNA replication, DNA repair, inflammation response, immune response, cell adhesion, etc, while the KEGG pathway enrichment mainly included cell cycle, oxidative phosphorylation, p53 signaling pathway,tumor necrosis factor（TNF） signaling pathway, and nuclear factor kappa-B（NF-κB） signaling pathway. Among them, high expression of mitogen-activated protein kinase 3（MAPK3）, ras-related C3 cotulinum toxin substrate 1（RAC1）,phospholipase C beta 1（PLCβ1）, catenin beta 1（CTNNβ1）, non-metastatic cells 1（NME1）, and non-metastatic cells 6（NME6） was associated with poor prognosis in HCC patients (P<0.05), while low expression of FYN, cytochrome P450 2C8（CYP2C8）, and cytochrome P450 2C9（CYP2C9） was associated with poor prognosis in HCC patients (P<0.05). Conclusions Non-cirrhotic HBV-related HCC involves multiple biological processes and alterations in signaling pathways, and the key genes related to the survival and prognosis of HCC patients provide new clues for understanding the mechanism of HBV-related HCC in non-cirrhosis patients.

Key words: non-cirrhotic hepatocellular carcinoma, differentially expressed genes, signalling pathways

中图分类号:

万妍, 刘芳, 郭闪, 吴剑. 非肝硬化乙型肝炎病毒相关肝细胞癌的转录组测序及其对患者生存的影响[J]. 首都医科大学学报, 2023, 44(5): 811-820.

Wan Yan, Liu Fang, Guo Shan, Wu Jian. Transcriptome sequencing and survival analysis of noncirrhotic hepatitis B viral（HBV）-related hepatocellular carcinoma[J]. Journal of Capital Medical University, 2023, 44(5): 811-820.

参考文献

［1］Kelley R K, Greten T F. Hepatocellular carcinoma-origins and outcomes［J］. N Engl J Med, 2021, 385(3): 280-282.
［2］Desai A, Sandhu S, Lai J P, et al. Hepatocellular carcinoma in non-cirrhotic liver: a comprehensive review［J］. World J Hepatol, 2019, 11(1): 1-18.
［3］Cucchetti A, Zhong J H, Berhane S, et al. The chances of hepatic resection curing hepatocellular carcinoma［J］. J Hepatol, 2020, 72(4): 711-717.
［4］Skidmore Z L, Kunisaki J, Lin Y, et al. Genomic and transcriptomic somatic alterations of hepatocellular carcinoma in non-cirrhotic livers［J］. Cancer Genet, 2022, 264/265: 90-99.
［5］Hyuna S, Jacques F, Rebecca L S, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries［J］. CA Cancer J Clin, 2021, 71(3): 209-249.
［6］Yang Y Q, Wen Z Y, Liu X Y, et al. Current status and prospect of treatments for recurrent hepatocellular carcinoma［J］. World J Hepatol, 2023, 15(2): 129-150.
［7］Levrero M, Zucman-Rossi J. Mechanisms of HBV-induced hepatocellular carcinoma［J］. J Hepatol, 2016, 64(1 Suppl): S84-S101.
［8］Farazi P A, DePinho R A. Hepatocellular carcinoma pathogenesis: from genes to environment［J］. Nat Rev Cancer, 2006, 6(9): 674-687.
［9］Moon H, Ro S W. MAPK/ERK signaling pathway in hepatocellular carcinoma［J］. Cancers (Basel), 2021, 13(12): 3026.
［10］Sauzeau V, Beignet J, Vergoten G, et al. Overexpressed or hyperactivated Rac1 as a target to treat hepatocellular carcinoma［J］. Pharmacol Res, 2022, 179: 106220.
［11］Liang S H, Guo H R, Ma K, et al. A PLCβ1-PI3K-AKT signaling axis activates EMT to promote cholangiocarcinoma progression［J］. Cancer Res, 2021, 81(23): 5889-5903.
［12］Javanmard D, Najafi M, Babaei M R, et al. Investigation of CTNNβ1 gene mutations and expression in hepatocellular carcinoma and cirrhosis in association with hepatitis B virus infection［J］. Infect Agent Cancer, 2020, 15: 37.
［13］Yang J, Lv Z H, Huang J T, et al. High expression of NME1 correlates with progression and poor prognosis in patients of hepatocellular carcinoma［J］. Int J Clin Exp Pathol, 2017, 10(8): 8561-8568.
［14］Proust B, Radi M, Vidac∨ek N , et al. NME6 is a phosphotransfer-inactive, monomeric NME/NDPK family member and functions in complexes at the interface of mitochondrial inner membrane and matrix［J］. Cell Biosci, 2021, 11(1): 195.
［15］Huang C K, Zhou J J, Nie Y, et al. A new finding in the key prognosis-related proto-oncogene FYN in hepatocellular carcinoma based on the WGCNA hub-gene screening trategy［J］. BMC Cancer, 2022, 22(1): 380.
［16］Wang X K, Yu T D, Liao X W, et al. The prognostic value of CYP2C subfamily genes in hepatocellular carcinoma［J］. Cancer Med, 2018, 7(4): 966-980.

非肝硬化乙型肝炎病毒相关肝细胞癌的转录组测序及其对患者生存的影响

Transcriptome sequencing and survival analysis of noncirrhotic hepatitis B viral（HBV）-related hepatocellular carcinoma

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 1

编辑推荐

Metrics

本文评价