Using bioinformatics approaches to investigate driver genes and identify BCL7A as a prognostic gene in colorectal cancer

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

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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.

Original languageEnglish
Pages (from-to)3922-3929
Number of pages8
JournalComputational and Structural Biotechnology Journal
StatePublished - Jan 2021


  • Cancer panel
  • Colorectal cancer
  • Driver genes
  • Next generation sequencing
  • Prognostic genes


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