Genetic Ancestry Analysis Reveals Misclassification of Commonly Used Cancer Cell Lines

Cancer Epidemiol Biomarkers Prev. 2019 Jun;28(6):1003-1009. doi: 10.1158/1055-9965.EPI-18-1132. Epub 2019 Feb 20.

Abstract

Background: Given the scarcity of cell lines from underrepresented populations, it is imperative that genetic ancestry for these cell lines is characterized. Consequences of cell line mischaracterization include squandered resources and publication retractions.

Methods: We calculated genetic ancestry proportions for 15 cell lines to assess the accuracy of previous race/ethnicity classification and determine previously unknown estimates. DNA was extracted from cell lines and genotyped for ancestry informative markers representing West African (WA), Native American (NA), and European (EUR) ancestry.

Results: Of the cell lines tested, all previously classified as White/Caucasian were accurately described with mean EUR ancestry proportions of 97%. Cell lines previously classified as Black/African American were not always accurately described. For instance, the 22Rv1 prostate cancer cell line was recently found to carry mixed genetic ancestry using a much smaller panel of markers. However, our more comprehensive analysis determined the 22Rv1 cell line carries 99% EUR ancestry. Most notably, the E006AA-hT prostate cancer cell line, classified as African American, was found to carry 92% EUR ancestry. We also determined the MDA-MB-468 breast cancer cell line carries 23% NA ancestry, suggesting possible Afro-Hispanic/Latina ancestry.

Conclusions: Our results suggest predominantly EUR ancestry for the White/Caucasian-designated cell lines, yet high variance in ancestry for the Black/African American-designated cell lines. In addition, we revealed an extreme misclassification of the E006AA-hT cell line.

Impact: Genetic ancestry estimates offer more sophisticated characterization leading to better contextualization of findings. Ancestry estimates should be provided for all cell lines to avoid erroneous conclusions in disparities literature.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Biomarkers, Tumor / genetics
  • Black People / genetics*
  • Breast Neoplasms / classification*
  • Breast Neoplasms / diagnosis
  • Breast Neoplasms / genetics*
  • Cell Line, Tumor / classification*
  • Cell Line, Tumor / pathology
  • Female
  • Genetic Testing / methods
  • HeLa Cells
  • Humans
  • Male
  • Middle Aged
  • Polymorphism, Single Nucleotide
  • Prostatic Neoplasms / classification*
  • Prostatic Neoplasms / diagnosis
  • Prostatic Neoplasms / genetics*
  • White People / genetics*

Substances

  • Biomarkers, Tumor