Precision medicine based on genetic makeup of tumors is leading to anticancer treatments that target specific — and smaller — numbers of patients. However, racial and ethnic minorities are underrepresented in genomic samples, resulting in less benefit from advances in cancer care for these patients, a study published in JAMA Oncology has shown.1

Because representation of minorities in The Cancer Genome Atlas (TCGA), a large genomic sequencing project, is unknown, researchers conducted a retrospective review to determine the racial distribution of TCGA samples and whether sample numbers are sufficient for detecting moderately common mutational frequencies in racial minorities.

For this study, individual patient data from 5729 TCGA samples were assessed in July 2015. Researchers analyzed samples from 10 currently available tumor types. Primary outcomes measure was a determination of whether the number of samples could detect a 10% and 5% frequency of mutation for each tumor type by racial ethnicity.

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Of the 5729 samples, 4389 (77%) were from whites and 660 (12%) from blacks, a percentage that matched the overall US population. But, the 3% (173) of samples from Asians was a slightly lower percentage than in the overall US population (5%). The 3% (149 samples) from Hispanics, however, was a much lower percentage than the 16% seen in the overall US population.

The researchers determined that they did not have enough samples to identify that a gene mutation would occur in 5% of any racial group. But the samples were enough to determine if a mutation would occur in 5% of white patients for every type of cancer.

The impact of ethnic diversity on pathogenesis of cancer is poorly understood, and may have significance in terms of applying genetic findings from TCGA to racial minorities; therefore, the authors suggest dedicated efforts are needed to ensure sufficient data on minorities are collected to avoid further widening gaps in health care disparities.


1. Spratt DE, Chan T, Waldron L, et al. Racial/ethnic disparities in genomic sequencing. JAMA Oncol. 2016;2(8):1070-1074.