Cargando…

Identification of Immune-Related Genes for Establishment of Prognostic Index in Hepatocellular Carcinoma

Background: Immune checkpoint inhibitor (ICI) therapy has been proved to be a promising therapy to many types of solid tumors. However, effective biomarker for estimating the response to ICI therapy and prognosis of hepatocellular carcinoma (HCC) patients remains underexplored. The aim of this study...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Yinfang, Zou, Ling, Liu, Xuejun, Luo, Judong, Liu, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8593215/
https://www.ncbi.nlm.nih.gov/pubmed/34796177
http://dx.doi.org/10.3389/fcell.2021.760079
_version_ 1784599677342056448
author Li, Yinfang
Zou, Ling
Liu, Xuejun
Luo, Judong
Liu, Hui
author_facet Li, Yinfang
Zou, Ling
Liu, Xuejun
Luo, Judong
Liu, Hui
author_sort Li, Yinfang
collection PubMed
description Background: Immune checkpoint inhibitor (ICI) therapy has been proved to be a promising therapy to many types of solid tumors. However, effective biomarker for estimating the response to ICI therapy and prognosis of hepatocellular carcinoma (HCC) patients remains underexplored. The aim of this study is to build a novel immune-related prognostic index based on transcriptomic profiles. Methods: Weighted gene co-expression network analysis (WGCNA) was conducted to identify immune-related hub genes that are differentially expressed in HCC cohorts. Next, univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to detect hub genes associated to overall survival (OS). To validate the immune-related prognostic index, univariate and multivariate Cox regression analysis were performed. CIBERSORT and ESTIMATE were used to explore the tumor microenvironment and immune infiltration level. Results: The differential expression analysis detected a total of 148 immune-related genes, among which 25 genes were identified to be markedly related to overall survival in HCC patients. LASSO analysis yielded 10 genes used to construct the immune-related gene prognostic index (IRGPI), by which a risk score is computed to estimate low vs. high risk indicating the response to ICI therapy and prognosis. Further analysis confirmed that this immune-related prognostic index is an effective indicator to immune infiltration level, response to ICI treatment and OS. The IRGPI low-risk patients had better overall survival (OS) than IRGPI high-risk patients on two independent cohorts. Moreover, we found that IRGPI high-risk group was correlated with high TP53 mutation rate, immune-suppressing tumor microenvironment, and these patients acquired less benefit from ICI therapy. In contrast, IRGPI-low risk group was associated with low TP53 and PIK3CA mutation rate, high infiltration of naive B cells and T cells, and these patients gained relatively more benefit from ICI therapy.
format Online
Article
Text
id pubmed-8593215
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-85932152021-11-17 Identification of Immune-Related Genes for Establishment of Prognostic Index in Hepatocellular Carcinoma Li, Yinfang Zou, Ling Liu, Xuejun Luo, Judong Liu, Hui Front Cell Dev Biol Cell and Developmental Biology Background: Immune checkpoint inhibitor (ICI) therapy has been proved to be a promising therapy to many types of solid tumors. However, effective biomarker for estimating the response to ICI therapy and prognosis of hepatocellular carcinoma (HCC) patients remains underexplored. The aim of this study is to build a novel immune-related prognostic index based on transcriptomic profiles. Methods: Weighted gene co-expression network analysis (WGCNA) was conducted to identify immune-related hub genes that are differentially expressed in HCC cohorts. Next, univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were used to detect hub genes associated to overall survival (OS). To validate the immune-related prognostic index, univariate and multivariate Cox regression analysis were performed. CIBERSORT and ESTIMATE were used to explore the tumor microenvironment and immune infiltration level. Results: The differential expression analysis detected a total of 148 immune-related genes, among which 25 genes were identified to be markedly related to overall survival in HCC patients. LASSO analysis yielded 10 genes used to construct the immune-related gene prognostic index (IRGPI), by which a risk score is computed to estimate low vs. high risk indicating the response to ICI therapy and prognosis. Further analysis confirmed that this immune-related prognostic index is an effective indicator to immune infiltration level, response to ICI treatment and OS. The IRGPI low-risk patients had better overall survival (OS) than IRGPI high-risk patients on two independent cohorts. Moreover, we found that IRGPI high-risk group was correlated with high TP53 mutation rate, immune-suppressing tumor microenvironment, and these patients acquired less benefit from ICI therapy. In contrast, IRGPI-low risk group was associated with low TP53 and PIK3CA mutation rate, high infiltration of naive B cells and T cells, and these patients gained relatively more benefit from ICI therapy. Frontiers Media S.A. 2021-11-02 /pmc/articles/PMC8593215/ /pubmed/34796177 http://dx.doi.org/10.3389/fcell.2021.760079 Text en Copyright © 2021 Li, Zou, Liu, Luo and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cell and Developmental Biology
Li, Yinfang
Zou, Ling
Liu, Xuejun
Luo, Judong
Liu, Hui
Identification of Immune-Related Genes for Establishment of Prognostic Index in Hepatocellular Carcinoma
title Identification of Immune-Related Genes for Establishment of Prognostic Index in Hepatocellular Carcinoma
title_full Identification of Immune-Related Genes for Establishment of Prognostic Index in Hepatocellular Carcinoma
title_fullStr Identification of Immune-Related Genes for Establishment of Prognostic Index in Hepatocellular Carcinoma
title_full_unstemmed Identification of Immune-Related Genes for Establishment of Prognostic Index in Hepatocellular Carcinoma
title_short Identification of Immune-Related Genes for Establishment of Prognostic Index in Hepatocellular Carcinoma
title_sort identification of immune-related genes for establishment of prognostic index in hepatocellular carcinoma
topic Cell and Developmental Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8593215/
https://www.ncbi.nlm.nih.gov/pubmed/34796177
http://dx.doi.org/10.3389/fcell.2021.760079
work_keys_str_mv AT liyinfang identificationofimmunerelatedgenesforestablishmentofprognosticindexinhepatocellularcarcinoma
AT zouling identificationofimmunerelatedgenesforestablishmentofprognosticindexinhepatocellularcarcinoma
AT liuxuejun identificationofimmunerelatedgenesforestablishmentofprognosticindexinhepatocellularcarcinoma
AT luojudong identificationofimmunerelatedgenesforestablishmentofprognosticindexinhepatocellularcarcinoma
AT liuhui identificationofimmunerelatedgenesforestablishmentofprognosticindexinhepatocellularcarcinoma