Cargando…

Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma

BACKGROUND: The tumor immune microenvironment is pivotal in predicting clinical outcomes and therapeutic efficacy in cancer patients. This study aims to develop an immune prediction model (IPM) to effectively predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Yu, Xie, Yanting, Ma, Junyong, Wang, Yizhou, Gong, Renyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576066/
https://www.ncbi.nlm.nih.gov/pubmed/33241026
http://dx.doi.org/10.21037/atm-20-6112
_version_ 1783597939391725568
author Wang, Yu
Xie, Yanting
Ma, Junyong
Wang, Yizhou
Gong, Renyan
author_facet Wang, Yu
Xie, Yanting
Ma, Junyong
Wang, Yizhou
Gong, Renyan
author_sort Wang, Yu
collection PubMed
description BACKGROUND: The tumor immune microenvironment is pivotal in predicting clinical outcomes and therapeutic efficacy in cancer patients. This study aims to develop an immune prediction model (IPM) to effectively predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma (HCC). METHODS: An IPM was constructed and validated based on immune-related genes. The influence of IPM on the HCC immune microenvironment, as well as the possible mechanism, was comprehensively analyzed. The value of the model in predicting the response of HCC patients to immunotherapy was also evaluated. RESULTS: A novel IPM based on eight genes was developed and validated to predict the prognosis of HCC patients. These genes are matrix metalloproteinase 12 (MMP12), heme oxygenase 1 (HMOX1), C-X-C motif chemokine receptor 6 (CXCR6), hepatoma-derived growth factor (HDGF), placental growth factor (PGF), tyrosine kinase 2 (TYK2), retinoid X receptor beta (RXRB), and cyclin-dependent kinase 4 (CDK4). High-risk patients showed significantly poorer survival than low-risk patients. A nomogram was also established based on the IPM and tumor, node, metastasis (TNM) classification, which showed some net clinical benefit. Gene set enrichment analysis (GSEA) revealed several significantly enriched oncological signatures and immunologic signatures. Furthermore, high-risk patients were characterized by severe clinicopathological characteristics and immune cell infiltration. Finally, we found the that the IPM showed a significant positive correlation with programmed cell death 1 (PDCD1), cluster of differentiation 274 (CD274), and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) expression, suggesting a potentially enhanced effects of immunotherapy antibodies in HCC patients with a high risk score. CONCLUSIONS: A novel IPM that could predict clinical prognosis and immunotherapeutic response in HCC patients was developed. Our findings not only provide new insights into the identification of HCC patients with poor survival, but also deepen our understanding of the immune microenvironment, as well as the mechanism of immunotherapy, in HCC.
format Online
Article
Text
id pubmed-7576066
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher AME Publishing Company
record_format MEDLINE/PubMed
spelling pubmed-75760662020-11-24 Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma Wang, Yu Xie, Yanting Ma, Junyong Wang, Yizhou Gong, Renyan Ann Transl Med Original Article BACKGROUND: The tumor immune microenvironment is pivotal in predicting clinical outcomes and therapeutic efficacy in cancer patients. This study aims to develop an immune prediction model (IPM) to effectively predict prognosis and immunotherapeutic response in patients with hepatocellular carcinoma (HCC). METHODS: An IPM was constructed and validated based on immune-related genes. The influence of IPM on the HCC immune microenvironment, as well as the possible mechanism, was comprehensively analyzed. The value of the model in predicting the response of HCC patients to immunotherapy was also evaluated. RESULTS: A novel IPM based on eight genes was developed and validated to predict the prognosis of HCC patients. These genes are matrix metalloproteinase 12 (MMP12), heme oxygenase 1 (HMOX1), C-X-C motif chemokine receptor 6 (CXCR6), hepatoma-derived growth factor (HDGF), placental growth factor (PGF), tyrosine kinase 2 (TYK2), retinoid X receptor beta (RXRB), and cyclin-dependent kinase 4 (CDK4). High-risk patients showed significantly poorer survival than low-risk patients. A nomogram was also established based on the IPM and tumor, node, metastasis (TNM) classification, which showed some net clinical benefit. Gene set enrichment analysis (GSEA) revealed several significantly enriched oncological signatures and immunologic signatures. Furthermore, high-risk patients were characterized by severe clinicopathological characteristics and immune cell infiltration. Finally, we found the that the IPM showed a significant positive correlation with programmed cell death 1 (PDCD1), cluster of differentiation 274 (CD274), and cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) expression, suggesting a potentially enhanced effects of immunotherapy antibodies in HCC patients with a high risk score. CONCLUSIONS: A novel IPM that could predict clinical prognosis and immunotherapeutic response in HCC patients was developed. Our findings not only provide new insights into the identification of HCC patients with poor survival, but also deepen our understanding of the immune microenvironment, as well as the mechanism of immunotherapy, in HCC. AME Publishing Company 2020-09 /pmc/articles/PMC7576066/ /pubmed/33241026 http://dx.doi.org/10.21037/atm-20-6112 Text en 2020 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Wang, Yu
Xie, Yanting
Ma, Junyong
Wang, Yizhou
Gong, Renyan
Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma
title Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma
title_full Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma
title_fullStr Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma
title_full_unstemmed Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma
title_short Development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma
title_sort development and validation of a prognostic and immunotherapeutically relevant model in hepatocellular carcinoma
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576066/
https://www.ncbi.nlm.nih.gov/pubmed/33241026
http://dx.doi.org/10.21037/atm-20-6112
work_keys_str_mv AT wangyu developmentandvalidationofaprognosticandimmunotherapeuticallyrelevantmodelinhepatocellularcarcinoma
AT xieyanting developmentandvalidationofaprognosticandimmunotherapeuticallyrelevantmodelinhepatocellularcarcinoma
AT majunyong developmentandvalidationofaprognosticandimmunotherapeuticallyrelevantmodelinhepatocellularcarcinoma
AT wangyizhou developmentandvalidationofaprognosticandimmunotherapeuticallyrelevantmodelinhepatocellularcarcinoma
AT gongrenyan developmentandvalidationofaprognosticandimmunotherapeuticallyrelevantmodelinhepatocellularcarcinoma