Genetic and transcriptional evolution alters cancer cell line drug response

Uri Ben-David, Benjamin Siranosian, Gavin Ha, Helen Tang, Yaara Oren, Kunihiko Hinohara, Craig A. Strathdee, Joshua Dempster, Nicholas J. Lyons, Robert Burns, Anwesha Nag, Guillaume Kugener, Beth Cimini, Peter Tsvetkov, Yosef E. Maruvka, Ryan O’Rourke, Anthony Garrity, Andrew A. Tubelli, Pratiti Bandopadhayay, Aviad TsherniakFrancisca Vazquez, Bang Wong, Chet Birger, Mahmoud Ghandi, Aaron R. Thorner, Joshua A. Bittker, Matthew Meyerson, Gad Getz, Rameen Beroukhim*, Todd R. Golub

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Human cancer cell lines are the workhorse of cancer research. Although cell lines are known to evolve in culture, the extent of the resultant genetic and transcriptional heterogeneity and its functional consequences remain understudied. Here we use genomic analyses of 106 human cell lines grown in two laboratories to show extensive clonal diversity. Further comprehensive genomic characterization of 27 strains of the common breast cancer cell line MCF7 uncovered rapid genetic diversification. Similar results were obtained with multiple strains of 13 additional cell lines. Notably, genetic changes were associated with differential activation of gene expression programs and marked differences in cell morphology and proliferation. Barcoding experiments showed that cell line evolution occurs as a result of positive clonal selection that is highly sensitive to culture conditions. Analyses of single-cell-derived clones demonstrated that continuous instability quickly translates into heterogeneity of the cell line. When the 27 MCF7 strains were tested against 321 anti-cancer compounds, we uncovered considerably different drug responses: at least 75% of compounds that strongly inhibited some strains were completely inactive in others. This study documents the extent, origins and consequences of genetic variation within cell lines, and provides a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.

Original languageEnglish
Pages (from-to)325-330
Number of pages6
Issue number7718
StatePublished - 16 Aug 2018
Externally publishedYes


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