Genetic insights: High germline variant rate in an indigenous African cohort with early-onset colorectal cancer

Introduction

The increase in incidence of colorectal cancer in young patients of African ancestry coupled with increased aggressiveness has warranted investigation of the heritable nature of these cancers. Only a limited number of published reports of hereditary colorectal cancer in indigenous African populations have been reported and no systematic screening of these groups has been performed previously. We aimed to investigate causative germline variants and to establish the incidence of pathogenic/likely pathogenic germline variants in the known colorectal cancer genes in indigenous African colorectal cancer patients using a next-generation sequencing (NGS) multigene panel.

Materials and methods

Patients were selected from two hospitals in Cape Town and Johannesburg, South Africa. Patients with unresolved molecular diagnosis with an age of onset below or at 60 years were selected. Germline DNA samples were analyzed using a 14-gene NGS panel on the Ion Torrent platform. Variant calling and annotation were performed, and variants were classified according to the American College of Medical Genetics and Genomics guidelines. Observed variants were verified by Sanger sequencing and/or long-range PCR.

Results

Out of 107 patients, 25 (23.4%) presented with a pathogenic/likely pathogenic germline variant (PGV). Fourteen PGVs in at least one mismatch repair (MMR) gene were identified and verified in 12 patients (11.2%). Of these MMR gene variants, five were novel. The remaining 10 PGVs were in the APC, BMPR1A, MUTYH, POLD1, and TP53 genes.

Conclusion

The high incidence of PGVs associated with early-onset colorectal cancer in indigenous African patients has important implications for hereditary colorectal cancer risk management. These findings pave the way for personalized genetic screening programs and cascade testing in South Africa. The next step would involve further screening of the unresolved cases using tools to detect copy number variation, methylation, and whole exome sequencing.