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...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-01-01
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| Series: | Computational and Structural Biotechnology Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2001037021002828 |
| _version_ | 1831641573111103488 |
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| author | Jeffrey Yung-chuan Chao Hsin-Chuan Chang Jeng-Kai Jiang Chih-Yung Yang Fang-Hsin Chen Yo-Liang Lai Wen-Jen Lin Chia-Yang Li Shu-Chi Wang Muh-Hwa Yang Yu-Feng Lin Wei-Chung Cheng |
| author_facet | Jeffrey Yung-chuan Chao Hsin-Chuan Chang Jeng-Kai Jiang Chih-Yung Yang Fang-Hsin Chen Yo-Liang Lai Wen-Jen Lin Chia-Yang Li Shu-Chi Wang Muh-Hwa Yang Yu-Feng Lin Wei-Chung Cheng |
| author_sort | Jeffrey Yung-chuan Chao |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-12-19T12:26:25Z |
| format | Article |
| id | doaj.art-418360957aca483988173b82ae0d0b88 |
| institution | Directory Open Access Journal |
| issn | 2001-0370 |
| language | English |
| last_indexed | 2024-12-19T12:26:25Z |
| publishDate | 2021-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computational and Structural Biotechnology Journal |
| spelling | doaj.art-418360957aca483988173b82ae0d0b882022-12-21T20:21:33ZengElsevierComputational and Structural Biotechnology Journal2001-03702021-01-011939223929Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancerJeffrey Yung-chuan Chao0Hsin-Chuan Chang1Jeng-Kai Jiang2Chih-Yung Yang3Fang-Hsin Chen4Yo-Liang Lai5Wen-Jen Lin6Chia-Yang Li7Shu-Chi Wang8Muh-Hwa Yang9Yu-Feng Lin10Wei-Chung Cheng11Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Radiation Oncology, Taichung Veterans General Hospital, Taichung, TaiwanInstitute of Microbiology and Immunology, National Yang Ming Chiao Tung University, Taipei, TaiwanDivision of Colon & Rectal Surgery, Department of Surgery, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, National Yang-Ming University, Taipei, TaiwanDepartment of Teaching and Research, Taipei City Hospital, Taipei, Taiwan; Commission for General Education, National United University, Miaoli, Taiwan; General Education Center, University of Taipei, Taipei, TaiwanDepartment of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan; Department of Radiation Oncology, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University and Chang Gung Memorial Hospital, Taoyuan, TaiwanDepartment of Radiation Oncology, China Medical University Hospital, Taichung, Taiwan; Graduate Institute of Biomedical Science, China Medical University, Taichung, TaiwanGraduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, TaiwanDepartment of Medical Laboratory Science and Biotechnology, College of Health Sciences, Kaohsiung Medical University, Kaohsiung 80708, TaiwanDivision of Medical Oncology, Taipei Veterans General Hospital, Taipei 112, TaiwanInstitute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Division of Medical Oncology, Taipei Veterans General Hospital, Taipei 112, TaiwanDepartment of Medical Laboratory Science and Biotechnology, College of Medical and Health Science, Asia University, Taichung, Taiwan; Corresponding authors at: Graduate Institute of Biomedical Science, China Medical University, No. 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung 406040, Taiwan (Wei-Chung Cheng); Department of Medical Laboratory Science and Biotechnology, College of Medical and Health Science, Asia University, No. 500, Lioufeng Rd., Wufeng, Taichung 41354, Taiwan (Yu-Feng Lin).Graduate Institute of Biomedical Science, China Medical University, Taichung, Taiwan; The Ph.D. Program for Cancer Biology and Drug Discovery, China Medical University and Academia Sinica, Taichung 404, Taiwan; Research Center for Cancer Biology, China Medical University, Taichung, Taiwan; Corresponding authors at: Graduate Institute of Biomedical Science, China Medical University, No. 100, Sec. 1, Jingmao Rd., Beitun Dist., Taichung 406040, Taiwan (Wei-Chung Cheng); Department of Medical Laboratory Science and Biotechnology, College of Medical and Health Science, Asia University, No. 500, Lioufeng Rd., Wufeng, Taichung 41354, Taiwan (Yu-Feng Lin).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.http://www.sciencedirect.com/science/article/pii/S2001037021002828Driver genesColorectal cancerPrognostic genesNext generation sequencingCancer panel |
| spellingShingle | Jeffrey Yung-chuan Chao Hsin-Chuan Chang Jeng-Kai Jiang Chih-Yung Yang Fang-Hsin Chen Yo-Liang Lai Wen-Jen Lin Chia-Yang Li Shu-Chi Wang Muh-Hwa Yang Yu-Feng Lin Wei-Chung Cheng Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer Computational and Structural Biotechnology Journal Driver genes Colorectal cancer Prognostic genes Next generation sequencing Cancer panel |
| 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 | Driver genes Colorectal cancer Prognostic genes Next generation sequencing Cancer panel |
| url | http://www.sciencedirect.com/science/article/pii/S2001037021002828 |
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