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Development of prognosis model for colon cancer based on autophagy-related genes
BACKGROUND: Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602324/ https://www.ncbi.nlm.nih.gov/pubmed/33126898 http://dx.doi.org/10.1186/s12957-020-02061-w |
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author | Wang, Xu Xu, Yuanmin Li, Ting Chen, Bo Yang, Wenqi |
author_facet | Wang, Xu Xu, Yuanmin Li, Ting Chen, Bo Yang, Wenqi |
author_sort | Wang, Xu |
collection | PubMed |
description | BACKGROUND: Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied. METHODS: Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazard models were used to investigate the association between ARG expression profiles and patient prognosis. RESULTS: Twenty ARGs were significantly associated with the overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3-, and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians. CONCLUSION: The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-020-02061-w. |
format | Online Article Text |
id | pubmed-7602324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-76023242020-11-02 Development of prognosis model for colon cancer based on autophagy-related genes Wang, Xu Xu, Yuanmin Li, Ting Chen, Bo Yang, Wenqi World J Surg Oncol Research BACKGROUND: Autophagy is an orderly catabolic process for degrading and removing unnecessary or dysfunctional cellular components such as proteins and organelles. Although autophagy is known to play an important role in various types of cancer, the effects of autophagy-related genes (ARGs) on colon cancer have not been well studied. METHODS: Expression profiles from ARGs in 457 colon cancer patients were retrieved from the TCGA database (https://portal.gdc.cancer.gov). Differentially expressed ARGs and ARGs related to overall patient survival were identified. Cox proportional-hazard models were used to investigate the association between ARG expression profiles and patient prognosis. RESULTS: Twenty ARGs were significantly associated with the overall survival of colon cancer patients. Five of these ARGs had a mutation rate ≥ 3%. Patients were divided into high-risk and low-risk groups based on Cox regression analysis of 8 ARGs. Low-risk patients had a significantly longer survival time than high-risk patients (p < 0.001). Univariate and multivariate Cox regression analysis showed that the resulting risk score, which was associated with infiltration depth and metastasis, could be an independent predictor of patient survival. A nomogram was established to predict 1-, 3-, and 5-year survival of colon cancer patients based on 5 independent prognosis factors, including the risk score. The prognostic nomogram with online webserver was more effective and convenient to provide information for researchers and clinicians. CONCLUSION: The 8 ARGs can be used to predict the prognosis of patients and provide information for their individualized treatment. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12957-020-02061-w. BioMed Central 2020-10-30 /pmc/articles/PMC7602324/ /pubmed/33126898 http://dx.doi.org/10.1186/s12957-020-02061-w Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wang, Xu Xu, Yuanmin Li, Ting Chen, Bo Yang, Wenqi Development of prognosis model for colon cancer based on autophagy-related genes |
title | Development of prognosis model for colon cancer based on autophagy-related genes |
title_full | Development of prognosis model for colon cancer based on autophagy-related genes |
title_fullStr | Development of prognosis model for colon cancer based on autophagy-related genes |
title_full_unstemmed | Development of prognosis model for colon cancer based on autophagy-related genes |
title_short | Development of prognosis model for colon cancer based on autophagy-related genes |
title_sort | development of prognosis model for colon cancer based on autophagy-related genes |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7602324/ https://www.ncbi.nlm.nih.gov/pubmed/33126898 http://dx.doi.org/10.1186/s12957-020-02061-w |
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