Immune classifier-based signatures provide good prognostic stratification and predict the clinical benefits of immune-based therapies for hepatocellular carcinoma

Author:

Xue Chen,Gu Xinyu,Li LanjuanORCID

Abstract

Abstract Background Hepatocellular carcinoma (HCC) is an aggressive cancer with a high rate of death globally. The use of bioinformatics may help to identify immune cell-related genes both as targets for potential immunotherapies and for their value associated with predicting therapy responses. Methods In this study, mRNA expression profiles of HCC samples from The Cancer Genome Atlas (TCGA) database were subjected to gene enrichment, cell type abundance, immune cell infiltration, and pathway enrichment analyses to determine immune cell gene features, cell type abundance, and functional annotation characteristics. We also evaluated their prognostic values using Cox regression and Kaplan–Meier analyses and assessed potential responses to chemotherapy. Four subgroups (Groups 1–4) were identified. Group 4 was associated with advanced clinical characteristics, high immune cell enrichment scores, and the poorest outcomes. Results Differentially expressed genes (DEGs) in the HCC samples were enriched in the following pathways: antigen binding, cell surface receptor signal transduction of the immune response, and cell surface activated receptor signal transduction of the immune response. Highly expressed genes in Group 4 were enriched in elements of the WNT signalling pathway. We identified five immune-related genes (SEMA3A, TNFRSF11B, GUCA2A, SAA1, and CALCR) that were significantly related to HCC prognosis. A prognostic model based on these five genes exhibited good predictive value, with 1-year and 5-year area under the curve (AUC) values of  >  0.66. Group 4 was also potentially more sensitive to EHT 1864, FH535, and lapatinib chemotherapies than the other groups. Conclusions We identified and validated four HCC subgroups based on immune system-related genes and identified five genes that may be used for an immune-based prognostic model for HCC treatment.

Funder

national natural science foundation of china

zhejiang university academic award for outstanding doctoral candidates

Publisher

Springer Science and Business Media LLC

Subject

Cancer Research,Genetics,Oncology

Reference54 articles.

1. Erratum: global cancer statistics 2018. GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2020;70:313.

2. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70:7–30.

3. Zou RC, Liang Y, Li LL, Tang JZ, Yang YP, Geng YC, et al. Bioinformatics analysis identifies protein tyrosine kinase 7 (PTK7) as a potential prognostic and therapeutic biomarker in stages I to IV hepatocellular carcinoma. Med Sci Monit. 2019;25:8618–27.

4. Liao X, Bu Y, Jia Q. Traditional Chinese medicine as supportive care for the management of liver cancer: past, present, and future. Genes Dis. 2020;7:370–9.

5. Liu C, Zha Z, Zhou C, Chen Y, Xia W, Wang YN, et al. Ribonuclease 7-driven activation of ROS1 is a potential therapeutic target in hepatocellular carcinoma. J Hepatol. 2020;S0168–8278:33674–6.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3