Identification of Novel Mutations in Colorectal Cancer Patients Using AmpliSeq Comprehensive Cancer Panel

• Published in: Journal of personalized medicine 2021-06, Vol.11 (6), p.535
• Main Authors: Almuzzaini, Bader, Alghamdi, Jahad, Alomani, Alhanouf, AlGhamdi, Saleh, Alsharm, Abdullah A., Alshieban, Saeed, Sayed, Ahood, Alhejaily, Abdulmohsen G., Aljaser, Feda S., Abudawood, Manal, Almajed, Faisal, Samman, Abdulhadi, Balwi, Mohammed A. Al, Aziz, Mohammad Azhar
• Format: Article
• Language: English
• Subjects: Adenomatous polyposis coli; Biomarkers; Cancer; Colorectal cancer; Colorectal carcinoma; Epidermal growth factor receptors; ErbB-2 protein; Genes; Large intestine; Metastasis; Mutation; Next-generation sequencing; Pathogenicity; Patients; Population; Precision medicine; Software
• ISSN: 2075-4426; 2075-4426
• DOI: 10.3390/jpm11060535

Biomarker discovery would be an important tool in advancing and utilizing the concept of precision and personalized medicine in the clinic. Discovery of novel variants in local population provides confident targets for developing biomarkers for personalized medicine. We identified the need to generate high-quality sequencing data from local colorectal cancer patients and understand the pattern of occurrence of variants. In this report, we used archived samples from Saudi Arabia and used the AmpliSeq comprehensive cancer panel to identify novel somatic variants. We report a comprehensive analysis of next-generation sequencing results with a coverage of >300X. We identified 466 novel variants which were previously unreported in COSMIC and ICGC databases. We analyzed the genes associated with these variants in terms of their frequency of occurrence, probable pathogenicity, and clinicopathological features. Among pathogenic somatic variants, 174 were identified for the first time in the large intestine. APC, RET, and EGFR genes were most frequently mutated. A higher number of variants were identified in the left colon. Occurrence of variants in ERBB2 was significantly correlated with those of EGFR and ATR genes. Network analyses of the identified genes provide functional perspective of the identified genes and suggest affected pathways and probable biomarker candidates. This report lays the ground work for biomarker discovery and identification of driver gene mutations in local population.