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Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis
BACKGROUND: Hepatocellular carcinoma (HCC) remains the third leader cancer-associated cause of death globally, but the etiological basis for this complex disease remains poorly clarified. The present study was thus conceptualized to define a prognostic immune-related gene (IRG) signature capable of...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8480351/ https://www.ncbi.nlm.nih.gov/pubmed/33269615 http://dx.doi.org/10.1177/1073274820977114 |
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author | Lei, Jiasheng Zhang, Dengyong Yao, Chao Ding, Sheng Lu, Zheng |
author_facet | Lei, Jiasheng Zhang, Dengyong Yao, Chao Ding, Sheng Lu, Zheng |
author_sort | Lei, Jiasheng |
collection | PubMed |
description | BACKGROUND: Hepatocellular carcinoma (HCC) remains the third leader cancer-associated cause of death globally, but the etiological basis for this complex disease remains poorly clarified. The present study was thus conceptualized to define a prognostic immune-related gene (IRG) signature capable of predicting immunotherapy responsiveness and overall survival (OS) in patients with HCC. METHODS: Five differentially expressed IRG associated with HCC were established the immune-related risk model through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Patients were separated at random into training and testing cohorts, after which the association between the identified IRG signature and OS was evaluated using the “survival” R package. In addition, maftools was leveraged to assess mutational data, with tumor mutation burden (TMB) scores being calculated as follows: (total mutations/total bases) × 10(6). Immune-related risk term abundance was quantified via “ssGSEA” algorithm using the “gsva” R package. RESULTS: HCC patients were successfully stratified into low-risk and high-risk groups based upon a signature composed of 5 differentially expressed IRGs, with overall survival being significantly different between these 2 groups in training cohort, testing cohort and overall patient cohort (P = 1.745e-06, P = 1.888e-02, P = 4.281e-07). No association was observed between TMB and this IRG risk score in the overall patient cohort (P = 0.461). Notably, 19 out of 29 immune-related risk terms differed substantially in the overall patient dataset. These risk terms mainly included checkpoints, human leukocyte antigens, natural killer cells, dendritic cells, and major histocompatibility complex class I. CONCLUSION: In summary, an immune-related prognostic gene signature was successfully developed and used to predict survival outcomes and immune system status in patients with HCC. This signature has the potential to help guide immunotherapeutic treatment planning for patients affected by this deadly cancer. |
format | Online Article Text |
id | pubmed-8480351 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-84803512021-09-30 Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis Lei, Jiasheng Zhang, Dengyong Yao, Chao Ding, Sheng Lu, Zheng Cancer Control Research Article BACKGROUND: Hepatocellular carcinoma (HCC) remains the third leader cancer-associated cause of death globally, but the etiological basis for this complex disease remains poorly clarified. The present study was thus conceptualized to define a prognostic immune-related gene (IRG) signature capable of predicting immunotherapy responsiveness and overall survival (OS) in patients with HCC. METHODS: Five differentially expressed IRG associated with HCC were established the immune-related risk model through univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. Patients were separated at random into training and testing cohorts, after which the association between the identified IRG signature and OS was evaluated using the “survival” R package. In addition, maftools was leveraged to assess mutational data, with tumor mutation burden (TMB) scores being calculated as follows: (total mutations/total bases) × 10(6). Immune-related risk term abundance was quantified via “ssGSEA” algorithm using the “gsva” R package. RESULTS: HCC patients were successfully stratified into low-risk and high-risk groups based upon a signature composed of 5 differentially expressed IRGs, with overall survival being significantly different between these 2 groups in training cohort, testing cohort and overall patient cohort (P = 1.745e-06, P = 1.888e-02, P = 4.281e-07). No association was observed between TMB and this IRG risk score in the overall patient cohort (P = 0.461). Notably, 19 out of 29 immune-related risk terms differed substantially in the overall patient dataset. These risk terms mainly included checkpoints, human leukocyte antigens, natural killer cells, dendritic cells, and major histocompatibility complex class I. CONCLUSION: In summary, an immune-related prognostic gene signature was successfully developed and used to predict survival outcomes and immune system status in patients with HCC. This signature has the potential to help guide immunotherapeutic treatment planning for patients affected by this deadly cancer. SAGE Publications 2020-12-03 /pmc/articles/PMC8480351/ /pubmed/33269615 http://dx.doi.org/10.1177/1073274820977114 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Research Article Lei, Jiasheng Zhang, Dengyong Yao, Chao Ding, Sheng Lu, Zheng Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis |
title | Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis |
title_full | Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis |
title_fullStr | Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis |
title_full_unstemmed | Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis |
title_short | Development of a Predictive Immune-Related Gene Signature Associated With Hepatocellular Carcinoma Patient Prognosis |
title_sort | development of a predictive immune-related gene signature associated with hepatocellular carcinoma patient prognosis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8480351/ https://www.ncbi.nlm.nih.gov/pubmed/33269615 http://dx.doi.org/10.1177/1073274820977114 |
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