Cargando…
Diagnosis and prognosis models for hepatocellular carcinoma patient’s management based on tumor mutation burden
INTRODUCTION: The development and prognosis of HCC involve complex molecular mechanisms, which affect the effectiveness of its treatment strategies. Tumor mutational burden (TMB) is related to the efficacy of immunotherapy, but the prognostic role of TMB-related genes in HCC has not yet been determi...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463909/ https://www.ncbi.nlm.nih.gov/pubmed/34603786 http://dx.doi.org/10.1016/j.jare.2021.01.018 |
_version_ | 1784572496619503616 |
---|---|
author | Tang, Bufu Zhu, Jinyu Zhao, Zhongwei Lu, Chenying Liu, Siyu Fang, Shiji Zheng, Liyun Zhang, Nannan Chen, Minjiang Xu, Min Yu, Risheng Ji, Jiansong |
author_facet | Tang, Bufu Zhu, Jinyu Zhao, Zhongwei Lu, Chenying Liu, Siyu Fang, Shiji Zheng, Liyun Zhang, Nannan Chen, Minjiang Xu, Min Yu, Risheng Ji, Jiansong |
author_sort | Tang, Bufu |
collection | PubMed |
description | INTRODUCTION: The development and prognosis of HCC involve complex molecular mechanisms, which affect the effectiveness of its treatment strategies. Tumor mutational burden (TMB) is related to the efficacy of immunotherapy, but the prognostic role of TMB-related genes in HCC has not yet been determined clearly. OBJECTIVES: In this study, we identified TMB-specific genes with good prognostic value to build diagnostic and prognostic models and provide guidance for the treatment of HCC patients. METHODS: Weighted gene co-expression network analysis (WGCNA) was applied to identify the TMB-specific genes. And LASSO method and Cox regression were used in establishing the prognostic model. RESULTS: The prognostic model based on SMG5 and MRPL9 showed patients with higher prognostic risk had a remarkedly poorer survival probability than their counterparts with lower prognostic risk in both a TCGA cohort (P < 0.001, HR = 1.93) and an ICGC cohort (P < 0.001, HR = 3.58). In addition, higher infiltrating fractions of memory B cells, M0 macrophages, neutrophils, activated memory CD4 + T cells, follicular helper T cells and regulatory T cells and higher expression of B7H3, CTLA4, PD1, and TIM3 were present in the high-risk group than in the low-risk group (P < 0.05). Patients with high prognostic risk had higher resistance to some chemotherapy and targeted drugs, such as methotrexate, vinblastine and erlotinib, than those with low prognostic risk (P < 0.05). And a diagnostic model considering two genes was able to accurately distinguish patients with HCC from normal samples and those with dysplastic nodules. In addition, knockdown of SMG5 and MRPL9 was determined to significantly inhibit cell proliferation and migration in HCC. CONCLUSION: Our study helps to select patients suitable for chemotherapy, targeted drugs and immunotherapy and provide new ideas for developing treatment strategies to improve disease outcomes in HCC patients. |
format | Online Article Text |
id | pubmed-8463909 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-84639092021-10-01 Diagnosis and prognosis models for hepatocellular carcinoma patient’s management based on tumor mutation burden Tang, Bufu Zhu, Jinyu Zhao, Zhongwei Lu, Chenying Liu, Siyu Fang, Shiji Zheng, Liyun Zhang, Nannan Chen, Minjiang Xu, Min Yu, Risheng Ji, Jiansong J Adv Res Medicine INTRODUCTION: The development and prognosis of HCC involve complex molecular mechanisms, which affect the effectiveness of its treatment strategies. Tumor mutational burden (TMB) is related to the efficacy of immunotherapy, but the prognostic role of TMB-related genes in HCC has not yet been determined clearly. OBJECTIVES: In this study, we identified TMB-specific genes with good prognostic value to build diagnostic and prognostic models and provide guidance for the treatment of HCC patients. METHODS: Weighted gene co-expression network analysis (WGCNA) was applied to identify the TMB-specific genes. And LASSO method and Cox regression were used in establishing the prognostic model. RESULTS: The prognostic model based on SMG5 and MRPL9 showed patients with higher prognostic risk had a remarkedly poorer survival probability than their counterparts with lower prognostic risk in both a TCGA cohort (P < 0.001, HR = 1.93) and an ICGC cohort (P < 0.001, HR = 3.58). In addition, higher infiltrating fractions of memory B cells, M0 macrophages, neutrophils, activated memory CD4 + T cells, follicular helper T cells and regulatory T cells and higher expression of B7H3, CTLA4, PD1, and TIM3 were present in the high-risk group than in the low-risk group (P < 0.05). Patients with high prognostic risk had higher resistance to some chemotherapy and targeted drugs, such as methotrexate, vinblastine and erlotinib, than those with low prognostic risk (P < 0.05). And a diagnostic model considering two genes was able to accurately distinguish patients with HCC from normal samples and those with dysplastic nodules. In addition, knockdown of SMG5 and MRPL9 was determined to significantly inhibit cell proliferation and migration in HCC. CONCLUSION: Our study helps to select patients suitable for chemotherapy, targeted drugs and immunotherapy and provide new ideas for developing treatment strategies to improve disease outcomes in HCC patients. Elsevier 2021-02-09 /pmc/articles/PMC8463909/ /pubmed/34603786 http://dx.doi.org/10.1016/j.jare.2021.01.018 Text en © 2021 The Authors. Published by Elsevier B.V. on behalf of Cairo University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Medicine Tang, Bufu Zhu, Jinyu Zhao, Zhongwei Lu, Chenying Liu, Siyu Fang, Shiji Zheng, Liyun Zhang, Nannan Chen, Minjiang Xu, Min Yu, Risheng Ji, Jiansong Diagnosis and prognosis models for hepatocellular carcinoma patient’s management based on tumor mutation burden |
title | Diagnosis and prognosis models for hepatocellular carcinoma patient’s management based on tumor mutation burden |
title_full | Diagnosis and prognosis models for hepatocellular carcinoma patient’s management based on tumor mutation burden |
title_fullStr | Diagnosis and prognosis models for hepatocellular carcinoma patient’s management based on tumor mutation burden |
title_full_unstemmed | Diagnosis and prognosis models for hepatocellular carcinoma patient’s management based on tumor mutation burden |
title_short | Diagnosis and prognosis models for hepatocellular carcinoma patient’s management based on tumor mutation burden |
title_sort | diagnosis and prognosis models for hepatocellular carcinoma patient’s management based on tumor mutation burden |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8463909/ https://www.ncbi.nlm.nih.gov/pubmed/34603786 http://dx.doi.org/10.1016/j.jare.2021.01.018 |
work_keys_str_mv | AT tangbufu diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT zhujinyu diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT zhaozhongwei diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT luchenying diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT liusiyu diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT fangshiji diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT zhengliyun diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT zhangnannan diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT chenminjiang diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT xumin diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT yurisheng diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden AT jijiansong diagnosisandprognosismodelsforhepatocellularcarcinomapatientsmanagementbasedontumormutationburden |