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Autophagy-Related Signatures as Prognostic Indicators for Hepatocellular Carcinoma
BACKGROUND: Hepatocellular carcinoma (HCC) is the most common and deadly type of liver cancer. Autophagy is the process of transporting damaged or aging cellular components into lysosomes for digestion and degradation. Accumulating evidence implies that autophagy is a key factor in tumor progression...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987527/ https://www.ncbi.nlm.nih.gov/pubmed/35402224 http://dx.doi.org/10.3389/fonc.2022.654449 |
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author | Ye, Wen Shi, Zhehao Zhou, Yilin Zhang, Zhongjing Zhou, Yi Chen, Bicheng Zhang, Qiyu |
author_facet | Ye, Wen Shi, Zhehao Zhou, Yilin Zhang, Zhongjing Zhou, Yi Chen, Bicheng Zhang, Qiyu |
author_sort | Ye, Wen |
collection | PubMed |
description | BACKGROUND: Hepatocellular carcinoma (HCC) is the most common and deadly type of liver cancer. Autophagy is the process of transporting damaged or aging cellular components into lysosomes for digestion and degradation. Accumulating evidence implies that autophagy is a key factor in tumor progression. The aim of this study was to determine a panel of novel autophagy-related prognostic markers for liver cancer. METHODS: We conducted a comprehensive analysis of autophagy-related gene (ARG) expression profiles and corresponding clinical information based on The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The univariate Cox proportional regression model was used to screen candidate autophagy-related prognostic genes. In addition, a multivariate Cox proportional regression model was used to identify five key prognostic autophagy-related genes (ATIC, BAX, BIRC5, CAPNS1, and FKBP1A), which were used to construct a prognostic signature. Real-time qPCR analysis was used to evaluate the expression levels of ARGs in 20 surgically resected HCC samples and matched tumor-adjacent normal tissue samples. In addition, the effect of FKBP1A on autophagy and tumor progression was determined by performing in vitro and in vivo experiments. RESULTS: Based on the prognostic signature, patients with liver cancer were significantly divided into high-risk and low-risk groups in terms of overall survival (OS). A subsequent multivariate Cox regression analysis indicated that the prognostic signature remained an independent prognostic factor for OS. The prognostic signature possessing a better area under the curve (AUC) displayed better performance in predicting the survival of patients with HCC than other clinical parameters. Furthermore, FKBP1A was overexpressed in HCC tissues, and knockdown of FKBP1A impaired cell proliferation, migration, and invasion through the PI3K/AKT/mTOR signaling pathway. CONCLUSION: This study provides a prospective biomarker for monitoring outcomes of patients with HCC. |
format | Online Article Text |
id | pubmed-8987527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89875272022-04-08 Autophagy-Related Signatures as Prognostic Indicators for Hepatocellular Carcinoma Ye, Wen Shi, Zhehao Zhou, Yilin Zhang, Zhongjing Zhou, Yi Chen, Bicheng Zhang, Qiyu Front Oncol Oncology BACKGROUND: Hepatocellular carcinoma (HCC) is the most common and deadly type of liver cancer. Autophagy is the process of transporting damaged or aging cellular components into lysosomes for digestion and degradation. Accumulating evidence implies that autophagy is a key factor in tumor progression. The aim of this study was to determine a panel of novel autophagy-related prognostic markers for liver cancer. METHODS: We conducted a comprehensive analysis of autophagy-related gene (ARG) expression profiles and corresponding clinical information based on The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The univariate Cox proportional regression model was used to screen candidate autophagy-related prognostic genes. In addition, a multivariate Cox proportional regression model was used to identify five key prognostic autophagy-related genes (ATIC, BAX, BIRC5, CAPNS1, and FKBP1A), which were used to construct a prognostic signature. Real-time qPCR analysis was used to evaluate the expression levels of ARGs in 20 surgically resected HCC samples and matched tumor-adjacent normal tissue samples. In addition, the effect of FKBP1A on autophagy and tumor progression was determined by performing in vitro and in vivo experiments. RESULTS: Based on the prognostic signature, patients with liver cancer were significantly divided into high-risk and low-risk groups in terms of overall survival (OS). A subsequent multivariate Cox regression analysis indicated that the prognostic signature remained an independent prognostic factor for OS. The prognostic signature possessing a better area under the curve (AUC) displayed better performance in predicting the survival of patients with HCC than other clinical parameters. Furthermore, FKBP1A was overexpressed in HCC tissues, and knockdown of FKBP1A impaired cell proliferation, migration, and invasion through the PI3K/AKT/mTOR signaling pathway. CONCLUSION: This study provides a prospective biomarker for monitoring outcomes of patients with HCC. Frontiers Media S.A. 2022-03-24 /pmc/articles/PMC8987527/ /pubmed/35402224 http://dx.doi.org/10.3389/fonc.2022.654449 Text en Copyright © 2022 Ye, Shi, Zhou, Zhang, Zhou, Chen and Zhang 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 | Oncology Ye, Wen Shi, Zhehao Zhou, Yilin Zhang, Zhongjing Zhou, Yi Chen, Bicheng Zhang, Qiyu Autophagy-Related Signatures as Prognostic Indicators for Hepatocellular Carcinoma |
title | Autophagy-Related Signatures as Prognostic Indicators for Hepatocellular Carcinoma |
title_full | Autophagy-Related Signatures as Prognostic Indicators for Hepatocellular Carcinoma |
title_fullStr | Autophagy-Related Signatures as Prognostic Indicators for Hepatocellular Carcinoma |
title_full_unstemmed | Autophagy-Related Signatures as Prognostic Indicators for Hepatocellular Carcinoma |
title_short | Autophagy-Related Signatures as Prognostic Indicators for Hepatocellular Carcinoma |
title_sort | autophagy-related signatures as prognostic indicators for hepatocellular carcinoma |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8987527/ https://www.ncbi.nlm.nih.gov/pubmed/35402224 http://dx.doi.org/10.3389/fonc.2022.654449 |
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