Racial/ethnic disparities in genomic sequencing
Open accessAbstract
IMPORTANCE: Although poorly understood, there is heterogeneity in the molecular biology of cancer across race and ethnicities. The representation of racial minorities in large genomic sequencing efforts is unclear, and could have an impact on health care disparities. OBJECTIVE: To determine the racial distribution among samples sequenced within The Cancer Genome Atlas (TCGA) and the deficit of samples needed to detect moderately common mutational frequencies in racial minorities. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective review of individual patient data from TCGA data portal accessed in July 2015. TCGA comprises samples from a wide array of institutions primarily across the United States. Samples from 10 of the 31 currently available tumor types were analyzed, comprising 5729 samples from the approximately 11 000 available. MAIN OUTCOMES AND MEASURES: Using the estimated median somatic mutational frequency, the samples needed beyond TCGA to detect a 10% and 5% mutational frequency over the background somatic mutation frequency were calculated for each tumor type by racial ethnicity. RESULTS: Of the 5729 samples, 77% (n = 4389) were white, 12% (n = 660) were black, 3% (n = 173) were Asian, 3% (n = 149) were Hispanic, and less than 0.5% combined were from patients of Native Hawaiian, Pacific Islander, Alaskan Native, or American Indian decent. This overrepresents white patients compared with the US population and underrepresents primarily Asian and Hispanic patients. With a somatic mutational frequency of 0.7 (prostate cancer) to 9.9 (lung squamous cell cancer), all tumor types from white patients contained enough samples to detect a 10% mutational frequency. This is in contrast to all other racial ethnicities, for which group-specific mutations with 10% frequency would be detectable only for black patients with breast cancer. Group-specific mutations with 5% frequency would be undetectable in any racial minority, but detectable in white patients for all cancer types except lung (adenocarcinoma and squamous cell carcinoma) and colon cancer. CONCLUSIONS AND RELEVANCE: It is probable, but poorly understood, that ethnic diversity is related to the pathogenesis of cancer, and may have an impact on the generalizability of findings from TCGA to racial minorities. Despite the important benefits that continue to be gained from genomic sequencing, dedicated efforts are needed to avoid widening the already pervasive gap in health care disparities.
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Diversity of public datasets is a challenge across other oncology applications, including popular genomics datasets such as TCGA and GENIE.
“The diversity of public data sets is a challenge across other oncology applications, including popular genomics data sets, such as TCGA (181) and GENIE (182).”
From Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions (2024) · cites this paper as [181]
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- Authors
- Spratt, D. E., Chan, T., Waldron, L., Speers, C., Feng, F. Y., Ogunwobi, O. O., & Osborne, J. R.
- Affiliations
- University of Michigan (US)
- City University of New York (US)
- Memorial Sloan Kettering Cancer Center (US)
- Corresponding author
- Osborne, Joseph R.
- ORCID
- Venue
- JAMA Oncology
- Publisher
- American Medical Association (AMA)
- Published
- 2016-08-01
- Volume
- 2
- Issue
- 8
- Pages
- 1070
- ISSN
- 2374-2437 (ISSN-L)
- PMC
- PMC5123755
- OpenAlex
- W2475362987
- Cited by
- 375
- References
- 11
- Citations by year
- 2026: 36 · 2025: 51 · 2024: 46 · 2023: 39 · 2022: 41 · 2021: 50 · 2020: 41 · 2019: 34 · 2018: 20 · 2017: 16 · 2016: 1
- FWCI
- 9.85
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA Oncology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (7r03ca191447-02, 5u41hg004059-15)
- National Human Genome Research Institute (U41-HG004059)
- National Cancer Institute (U24CA180996, R03 CA191447, R21CA153177, P30CA008748, P30CA046592, U54CA137788, U54CA132378)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Race, Genetics, and Society
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Keywords
- racial disparities, ethnic minorities, genome sequencing, TCGA, somatic mutation frequency, cancer genomics, health care disparities, cancer types, breast cancer, lung cancer, prostate cancer, colon cancer, lung adenocarcinoma, lung squamous cell carcinoma, Black patients
- MeSH terms
- Alaska Natives, Asian, Black or African American, Ethnicity, Hispanic or Latino, Humans, Minority Groups, Neoplasms, Retrospective Studies, United States, Genomics, Databases, Genetic, White People, Native Hawaiian or Pacific Islander, Racial Groups, Healthcare Disparities, Mutation Rate
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