Next‐generation sequencing (NGS) has emerged as an affordable and reproducible means to query tumors for somatic genetic anomalies. To help interpret somatic NGS data, many institutions have created a molecular tumor board to analyze the results of NGS and make recommendations. This article evaluates the utility of cognitive computing systems to analyze data for clinical decision‐making.

Esophageal squamous cell carcinoma (ESCC) is endemic in regions of sub-Saharan Africa (SSA), where it is the third most common cancer. Here, we describe whole-exome tumor/normal sequencing and RNA transcriptomic analysis of 59 patients with ESCC in Malawi. We observed similar genetic aberrations as reported in Asian and North American cohorts, including mutations of ,, ,, ,, and . Analyses for nonhuman sequences did not reveal evidence for infection with HPV or other occult pathogens. Mutational signature analysis revealed common signatures associated with aging, cytidine deaminase activity (APOBEC), and a third signature of unknown origin, but signatures of inhaled tobacco use, aflatoxin and mismatch repair were notably absent. Based on RNA expression analysis, ESCC could be divided into 3 distinct subtypes, which were distinguished by their expression of cell cycle and neural transcripts. This study demonstrates discrete subtypes of ESCC in SSA, and suggests that the endemic nature of this disease reflects exposure to a carcinogen other than tobacco and oncogenic viruses.

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Background: Esophageal squamous cell carcinoma (ESCC) comprises 90% of all esophageal cancer cases globally and is the most common histology in low-resource settings. Eastern Africa has a disproportionately high incidence of ESCC. Methods: We describe the genomic profiles of 61 ESCC cases from Tanzania and compare them to profiles from an existing cohort of ESCC cases from Malawi. We also provide a comparison to ESCC tumors in The Cancer Genome Atlas. Results: We observed substantial transcriptional overlap with other squamous histologies via comparison with The Cancer Genome Atlas (TCGA) PanCan dataset. DNA analysis revealed known mutational patterns, both genome-wide as well as in genes known to be commonly mutated in ESCC. TP53 mutations were the most common somatic mutation in tumors from both Tanzania and Malawi but were detected at lower frequencies than previously reported in ESCC cases from other settings. In a combined analysis, two unique transcriptional clusters were identified: a proliferative/epithelial cluster and an invasive/migrative/mesenchymal cluster. Mutational signature analysis of the Tanzanian cohort revealed common signatures associated with aging and cytidine deaminase activity (APOBEC) and an absence of signature 29, which was previously reported in the Malawi cohort. Conclusion: This study defines the molecular characteristics of ESCC in Tanzania, and enriches the Eastern African dataset, with findings of overall similarities but also some heterogeneity across two unique sites. Impact: Despite a high burden of ESCC in Eastern Africa, genomic investigations in this region are nascent. This represents the largest comprehensive genomic analysis ESCC from sub-Saharan Africa to date.

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