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review · Neuro-Oncology Practice

Race and “omic” data in glioma: A systematic review of contemporary research to explore the digital divide

20251 citationOpen accessUniversity College Hospital, Ibadan

Abstract

Background: The expanding repertoire of studies generating genome-scale omic datasets from glioma samples provides a generational opportunity to uncover mechanisms driving aggressive biology and develop new treatments. However, ensuring such studies reflect the breadth of racial groups and ethnicities affected by gliomas is critical to support equity in future therapeutic advances. We therefore report a contemporary snapshot of the representation of race and ethnicity in omic glioma studies. Methods: We searched PubMed, Embase, Web of Science, and Scopus and systematically reviewed articles published between January and November 2023 reporting de novo genome-scale sequencing data generated using samples from patients diagnosed with glioma (according to World Health Organization 2021 criteria) to characterize the reporting and composition of race and ethnicity data. Results: Thirty-five studies involving 5601 patients were analyzed. Race or ethnicity data was reported in only 3 studies (8.6%), of which none provided omic data in a format that could be stratified by race or ethnicity. Reporting varied by continent with all 3 studies including race or ethnicity data based in North America. Where racial data was available, we found that samples used for genome-scale characterization came from patients reported as being White in 91.1% cases (41 patients), with 6.7% (3 patients) reported as Black and 2.2% (1 patient) as Hispanic. Conclusions: These studies underscore an urgent need for improved reporting and representation to enhance our understanding of glioma biology across different populations and guide targeted initiatives from policymakers and funders to support equitable improvements in healthcare.

Research topics

  • Glioma Diagnosis and Treatment
  • Cancer Genomics and Diagnostics
  • Single-cell and spatial transcriptomics

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DOI: 10.1093/nop/npaf016

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