Addressing Cancer Treatment in an African Setting: A Bioinformatics Analysis of Pharmacogenomically Relevant Variants Jorge da Rocha2, Dr Zané Lombard1, Prof Michèle Ramsay2, 1Division of Human Genetics, University of the Witwatersrand; 2Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand
Cancer is a critical health burden in Africa, and mortality rates are rising rapidly. Treatments are severe and expensive, and often cause adverse-drug-reactions (ADRs). Pharmacogenomics (PGx) aims to increase drug safety and efficacy by aligning drugs to known responses based on genomic variants, but data is sparse for African populations. Thirteen genes linked with ADRs to medicines used for treating major cancer types were identified: ABCB1, DPYD, TYMS, CYP19A1, GSTP1, CYP1B1, CYP3A4, CYP3A5, ESR1, CYP2D6, SLC19A1 and XRCC1/5. Public domain whole-genome-sequencing data from the 1000-Genomes-Project and the African-Genome-Variation-Project were mined to assess variants in eight African populations. Functional annotation was performed with a series of bioinformatics-based scoring tools to assess potential likelihood of deleterious impact. Two key African specific variants were identified: the CYP3A5 frameshift variant, rs41303343, which is highly likely to knockout gene function, and the CYP2D6 missense variant rs59421388, which was scored highly likely deleterious by all tools. Both variants are common in Africans, but lack clinical investigation into their PGx impact. For missense variants with known PGx effects, such as CYP2D6 - rs1065852 and DPYD - rs2297595, intra-African frequencies are significantly distinct, with rs1065852 being more common in West Africans, while rs2297595 is more common in East Africans. Many known variants are less common in Africans than other populations. These data indicate that guidelines for cancer drug safety based on African data are essential for use in Africa, and novel region-specific guidelines should be developed to ensure that Africans could benefit from a precision medicine approach.
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