Scaling for African Inclusion in High-Throughput Whole Cancer Genome Bioinformatic Workflows

Globally, Sub-Saharan Africa is experiencing the highest mortality rates for several cancer types. Exasperated by a one-size-fits-all, non-African-derived treatment strategies, Africa has largely been excluded from the genomic era and received little benefits from precision oncology. Through a thorough literature review, we identified five whole cancer genome databases that include patients from Sub-Saharan Africa. Irrespective of cancer type (breast, esophageal, prostate and Burkitt lymphoma), these studies report higher tumour genome instability, including African-specific cancer drivers and mutational signatures, suggesting unique contributory mechanisms at play. Reviewing bioinformatic tools applied to African databases, we provide a rationale for workflow selection that incorporates cohort-level data and integrates a scalable design achieving high-level parallelism through physical data or genomic interval chunking strategies. Furthermore, we provide rationale for improving variant calling accuracy for African data, including adopting more sequencing techniques and sourcing African-derived data to meet different priorities of applications. Together, these enhancements and genomic scaling, aim to facilitate early diagnosis and treatment strategies, and ultimately reduce the disparity gap in cancer mortality rates across Sub-Saharan Africa.