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The prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma
Background: Mitophagy has been found to play a significant part in the cancer process in a growing number of studies in recent years. However, there is still a lack of study on mitophagy-related genes’ (MRGs) prognostic potential and clinical significance in hepatocellular carcinoma (HCC). Methods:...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9388833/ https://www.ncbi.nlm.nih.gov/pubmed/35991574 http://dx.doi.org/10.3389/fgene.2022.917584 |
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author | Xu, Wei Zhao, Dongxu Huang, Xiaowei Zhang, Man Yin, Minyue Liu, Lu Wu, Hongyu Weng, Zhen Xu, Chunfang |
author_facet | Xu, Wei Zhao, Dongxu Huang, Xiaowei Zhang, Man Yin, Minyue Liu, Lu Wu, Hongyu Weng, Zhen Xu, Chunfang |
author_sort | Xu, Wei |
collection | PubMed |
description | Background: Mitophagy has been found to play a significant part in the cancer process in a growing number of studies in recent years. However, there is still a lack of study on mitophagy-related genes’ (MRGs) prognostic potential and clinical significance in hepatocellular carcinoma (HCC). Methods: We employed bioinformatics and statistical knowledge to examine the transcriptome data of HCC patients in the TCGA and GEO databases, with the goal of constructing a multigene predictive model. Then, we separated the patients into high- and low-risk groups based on the score. The model’s dependability was determined using principal components analysis (PCA), survival analysis, independent prognostic analysis, and receiver operating characteristic (ROC) analysis. Following that, we examined the clinical correlations, pharmacological treatment sensitivity, immune checkpoint expression, and immunological correlations between patients in high and low risk groups. Finally, we evaluated the variations in gene expression between high- and low-risk groups and further analyzed the network core genes using protein-protein interaction network analysis. Results: Prognostic models were built using eight genes (OPTN, ATG12, CSNK2A2, MFN1, PGAM5, SQSTM1, TOMM22, TOMM5). During validation, the prognostic model demonstrated high reliability, indicating that it could accurately predict the prognosis of HCC patients. Additionally, we discovered that typical HCC treatment medicines had varying impacts on patients classified as high or low risk, and that individuals classified as high risk are more likely to fail immunotherapy. Additionally, the high-risk group expressed more immunological checkpoints. The immunological status of patients in different risk categories varies as well, and patients with a high-risk score have a diminished ability to fight cancer. Finally, PPI analysis identified ten related genes with potential for research. Conclusion: Our prognostic model had good and reliable predictive ability, as well as clinical diagnosis and treatment guiding significance. Eight prognostic MRGs and ten network core genes merited further investigation. |
format | Online Article Text |
id | pubmed-9388833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93888332022-08-20 The prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma Xu, Wei Zhao, Dongxu Huang, Xiaowei Zhang, Man Yin, Minyue Liu, Lu Wu, Hongyu Weng, Zhen Xu, Chunfang Front Genet Genetics Background: Mitophagy has been found to play a significant part in the cancer process in a growing number of studies in recent years. However, there is still a lack of study on mitophagy-related genes’ (MRGs) prognostic potential and clinical significance in hepatocellular carcinoma (HCC). Methods: We employed bioinformatics and statistical knowledge to examine the transcriptome data of HCC patients in the TCGA and GEO databases, with the goal of constructing a multigene predictive model. Then, we separated the patients into high- and low-risk groups based on the score. The model’s dependability was determined using principal components analysis (PCA), survival analysis, independent prognostic analysis, and receiver operating characteristic (ROC) analysis. Following that, we examined the clinical correlations, pharmacological treatment sensitivity, immune checkpoint expression, and immunological correlations between patients in high and low risk groups. Finally, we evaluated the variations in gene expression between high- and low-risk groups and further analyzed the network core genes using protein-protein interaction network analysis. Results: Prognostic models were built using eight genes (OPTN, ATG12, CSNK2A2, MFN1, PGAM5, SQSTM1, TOMM22, TOMM5). During validation, the prognostic model demonstrated high reliability, indicating that it could accurately predict the prognosis of HCC patients. Additionally, we discovered that typical HCC treatment medicines had varying impacts on patients classified as high or low risk, and that individuals classified as high risk are more likely to fail immunotherapy. Additionally, the high-risk group expressed more immunological checkpoints. The immunological status of patients in different risk categories varies as well, and patients with a high-risk score have a diminished ability to fight cancer. Finally, PPI analysis identified ten related genes with potential for research. Conclusion: Our prognostic model had good and reliable predictive ability, as well as clinical diagnosis and treatment guiding significance. Eight prognostic MRGs and ten network core genes merited further investigation. Frontiers Media S.A. 2022-08-05 /pmc/articles/PMC9388833/ /pubmed/35991574 http://dx.doi.org/10.3389/fgene.2022.917584 Text en Copyright © 2022 Xu, Zhao, Huang, Zhang, Yin, Liu, Wu, Weng and Xu. 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 | Genetics Xu, Wei Zhao, Dongxu Huang, Xiaowei Zhang, Man Yin, Minyue Liu, Lu Wu, Hongyu Weng, Zhen Xu, Chunfang The prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma |
title | The prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma |
title_full | The prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma |
title_fullStr | The prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma |
title_full_unstemmed | The prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma |
title_short | The prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma |
title_sort | prognostic value and clinical significance of mitophagy-related genes in hepatocellular carcinoma |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9388833/ https://www.ncbi.nlm.nih.gov/pubmed/35991574 http://dx.doi.org/10.3389/fgene.2022.917584 |
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