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Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer
Colorectal cancer (CRC) results from the uncontrolled growth of cells in the colon, rectum, or appendix. The 5-year relative survival rate for patients with CRC is 65% and is correlated with the stage at diagnosis (being 91% for stage I at diagnosis versus 12% for stage IV). This study aimed to iden...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280477/ https://www.ncbi.nlm.nih.gov/pubmed/34306573 http://dx.doi.org/10.1016/j.csbj.2021.06.044 |
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author | Chao, Jeffrey Yung-chuan Chang, Hsin-Chuan Jiang, Jeng-Kai Yang, Chih-Yung Chen, Fang-Hsin Lai, Yo-Liang Lin, Wen-Jen Li, Chia-Yang Wang, Shu-Chi Yang, Muh-Hwa Lin, Yu-Feng Cheng, Wei-Chung |
author_facet | Chao, Jeffrey Yung-chuan Chang, Hsin-Chuan Jiang, Jeng-Kai Yang, Chih-Yung Chen, Fang-Hsin Lai, Yo-Liang Lin, Wen-Jen Li, Chia-Yang Wang, Shu-Chi Yang, Muh-Hwa Lin, Yu-Feng Cheng, Wei-Chung |
author_sort | Chao, Jeffrey Yung-chuan |
collection | PubMed |
description | Colorectal cancer (CRC) results from the uncontrolled growth of cells in the colon, rectum, or appendix. The 5-year relative survival rate for patients with CRC is 65% and is correlated with the stage at diagnosis (being 91% for stage I at diagnosis versus 12% for stage IV). This study aimed to identify CRC driver genes to assist in the design of a cancer panel to detect gene mutations during clinical early-stage screening and identify genes for use in prognostic assessments and the evaluation of appropriate treatment options. First, we utilized bioinformatics approaches to analyze 354 paired sequencing profiles from The Cancer Genome Atlas (TCGA) to identify CRC driver genes and analyzed the sequencing profiles of 38 patients with >5 years of follow-up data to search for prognostic genes. The results revealed eight driver genes and ten prognostic genes. Next, the presence of the identified gene mutations was verified using tissue and blood samples from Taiwanese CRC patients. The results showed that the set identified gene mutations provide high coverage for driver gene screening, and APC, TP53, PIK3CA, and FAT4 could be detected in blood as ctDNA test targets. We further found that BCL7A gene mutation was correlated with prognosis in CRC (log-rank p-value = 0.02), and that mutations of BCL7A could be identified in ctDNA samples. These findings may be of value in clinical early cancer detection, disease monitoring, drug development, and treatment efforts in the future. |
format | Online Article Text |
id | pubmed-8280477 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-82804772021-07-23 Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer Chao, Jeffrey Yung-chuan Chang, Hsin-Chuan Jiang, Jeng-Kai Yang, Chih-Yung Chen, Fang-Hsin Lai, Yo-Liang Lin, Wen-Jen Li, Chia-Yang Wang, Shu-Chi Yang, Muh-Hwa Lin, Yu-Feng Cheng, Wei-Chung Comput Struct Biotechnol J Research Article Colorectal cancer (CRC) results from the uncontrolled growth of cells in the colon, rectum, or appendix. The 5-year relative survival rate for patients with CRC is 65% and is correlated with the stage at diagnosis (being 91% for stage I at diagnosis versus 12% for stage IV). This study aimed to identify CRC driver genes to assist in the design of a cancer panel to detect gene mutations during clinical early-stage screening and identify genes for use in prognostic assessments and the evaluation of appropriate treatment options. First, we utilized bioinformatics approaches to analyze 354 paired sequencing profiles from The Cancer Genome Atlas (TCGA) to identify CRC driver genes and analyzed the sequencing profiles of 38 patients with >5 years of follow-up data to search for prognostic genes. The results revealed eight driver genes and ten prognostic genes. Next, the presence of the identified gene mutations was verified using tissue and blood samples from Taiwanese CRC patients. The results showed that the set identified gene mutations provide high coverage for driver gene screening, and APC, TP53, PIK3CA, and FAT4 could be detected in blood as ctDNA test targets. We further found that BCL7A gene mutation was correlated with prognosis in CRC (log-rank p-value = 0.02), and that mutations of BCL7A could be identified in ctDNA samples. These findings may be of value in clinical early cancer detection, disease monitoring, drug development, and treatment efforts in the future. Research Network of Computational and Structural Biotechnology 2021-07-01 /pmc/articles/PMC8280477/ /pubmed/34306573 http://dx.doi.org/10.1016/j.csbj.2021.06.044 Text en © 2021 The Author(s) 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 | Research Article Chao, Jeffrey Yung-chuan Chang, Hsin-Chuan Jiang, Jeng-Kai Yang, Chih-Yung Chen, Fang-Hsin Lai, Yo-Liang Lin, Wen-Jen Li, Chia-Yang Wang, Shu-Chi Yang, Muh-Hwa Lin, Yu-Feng Cheng, Wei-Chung Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer |
title | Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer |
title_full | Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer |
title_fullStr | Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer |
title_full_unstemmed | Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer |
title_short | Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer |
title_sort | using bioinformatics approaches to investigate driver genes and identify bcl7a as a prognostic gene in colorectal cancer |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280477/ https://www.ncbi.nlm.nih.gov/pubmed/34306573 http://dx.doi.org/10.1016/j.csbj.2021.06.044 |
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