Genetic and transcriptional evolution alters cancer cell line drug response
By U. Ben-David, B. Siranosian, G. Ha, Helen Tang, Yaara Oren, Kunihiko Hinohara, C. Strathdee, Joshua M. Dempster, Nicholas J. Lyons, Robert T. Burns and 20 more. Nature, 2018
787 citations recorded by the source corpus.
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. The extent, origins and consequences of genetic variation within human cell lines are studied, providing a framework for researchers to measure such variation in efforts to support maximally reproducible cancer research.
Subfields: Cancer Research, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/e6ab591012fcb54e327f9c80467fc5cc9559dbe6
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Citations in the corpus
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