Genetic and transcriptional evolution alters cancer cell line drug response
Open accessAbstract
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.
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Immortalized cell lines frequently acquire genetic, epigenetic, and phenotypic alterations over successive passages, compromising tissue-specific functions and biological fidelity.
“Immortalized lines offer convenience and unlimited proliferative capacity but frequently acquire genetic, epigenetic, and phenotypic alterations that compromise tissue-specific functions and overall biological fidelity.”
From Primary cell cultures versus immortalized cell lines: critical comparative insights into biological fidelity and translational applications (2026) · cites this paper as Ben-David et al. 2018
The Extended Data table reports that prolonged passaging increases variation, and the Abstract and Discussion describe genetic, gene-expression, and phenotypic differences among cancer cell-line strains. The paper links those differences to changes in drug response, but the cited passages do not establish epigenetic alterations or compromised tissue-specific functions. Its evidence also concerns cancer cell lines, rather than immortalized lines generally. (LLM, conf=0.87)
Experimental — accuracy not yet measuredThese effects may bias assay interpretation, increase inter-line variability, and reduce translational predictivity of drug-screening results.
“Together, these effects may bias assay interpretation, increase inter-line variability, and reduce the translational predictivity of drug-screening results (Ben-David et al. 2018).”
From Primary cell cultures versus immortalized cell lines: critical comparative insights into biological fidelity and translational applications (2026) · cites this paper as Ben-David et al. 2018
The Discussion (page unavailable) says genetic heterogeneity produces differential drug sensitivity across strains of the same cancer cell line and that this variation must be considered in data interpretation. Extended Data Table 1 likewise links genetic and transcriptomic variability to inconsistencies in drug-response studies. The paper does not establish increased variability between distinct cell lines or reduced translational predictivity of screening results. (LLM, conf=0.84)
Experimental — accuracy not yet measuredExperiments testing cell-line strains against anti-cancer compounds uncovered disparate drug responses, although the exact sources of instabilities in culture environments that promoted cell-line heterogeneity were not resolved.
“Further experiments testing the cell-line strains against anti-cancer compounds uncovered disparate drug responses, although the exact sources of instabilities in culture environments that promoted cell-line heterogeneity were not resolved (Ben-David et al., 2018).”
From Toward Best Practices for Controlling Mammalian Cell Culture Environments (2022) · cites this paper as Ben-David et al., 2018
The Functional consequences of genomic variation section reports markedly different responses to anti-cancer compounds across 27 MCF7 strains. The Discussion and Sources of variation sections identify clonal selection under different culture conditions and ongoing genomic instability as contributors to heterogeneity. They do not establish the citing sentence’s additional claim that the exact sources of culture-related instability remained unresolved. No page numbers are available in our copy. (LLM, conf=0.82)
Experimental — accuracy not yet measuredBarcoding experiments showed that cancer cell-line evolution occurred from positive clonal selection that was highly sensitive to culture conditions.
“Indeed, barcoding experiments showed that cancer cell-line evolution occurred from positive clonal selection that was highly sensitive to culture conditions (Ben-David et al., 2018).”
From Toward Best Practices for Controlling Mammalian Cell Culture Environments (2022) · cites this paper as Ben-David et al., 2018
Previously described hallmark genomic events characteristic of PDAC lesions were observed in pseudo-bulk summary, in some cases only in a subset of genomic subclones for each line.
“In this “pseudo-bulk” summary, previously described hallmark genomic events characteristic of PDAC lesions1–6 were readily observed, albeit in some cases only in a subset of genomic subclones for each line.”
From Occult polyclonality of preclinical pancreatic cancer models drives in vitro evolution (2022) · cites this paper as [6]
The length of time in culture, culture conditions and exogenous selective pressures on a cell line can lead to genetic drift.
“The length of time in culture, culture conditions and exogenous selective pressures on a cell line (e.g. PDX engraftment) can lead to genetic drift (16, 17).”
From Cell Model Passports-a hub for clinical, genetic and functional datasets of preclinical cancer models (2019) · cites this paper as [17]
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- Authors
- Ben-David, U., Siranosian, B., Ha, G., Tang, H., Oren, Y., Hinohara, K., Strathdee, C. A., Dempster, J., Lyons, N. J., Burns, R., Nag, A., Kugener, G., Cimini, B., Tsvetkov, P., Maruvka, Y. E., O’Rourke, R., Garrity, A., Tubelli, A. A., Bandopadhayay, P., Tsherniak, A., Vazquez, F., Wong, B., Birger, C., Ghandi, M., Thorner, A. R., Bittker, J. A., Meyerson, M., Getz, G., Beroukhim, R., & Golub, T. R.
- Affiliations
- Broad Institute (US)
- Dana-Farber Cancer Institute (US)
- Corresponding author
- Beroukhim, Rameen
- Golub, Todd R.
- ORCID
- Siranosian, Benjamin
- Ha, Gavin
- Oren, Yaara
- Hinohara, Kunihiko
- Dempster, Joshua
- Burns, Robert
- Nag, Anwesha
- Kugener, Guillaume
- Cimini, Beth
- Tsvetkov, Peter
- Maruvka, Yosef E.
- O’Rourke, Ryan
- Garrity, Anthony
- Tubelli, Andrew A.
- Bandopadhayay, Pratiti
- Tsherniak, Aviad
- Ghandi, Mahmoud
- Thorner, Aaron R.
- Bittker, Joshua A.
- Meyerson, Matthew
- Getz, Gad
- Beroukhim, Rameen
- Golub, Todd R.
- Venue
- Nature
- Published
- 2018-08
- Volume
- 560
- Issue
- 7718
- Pages
- 325-330
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6522222
- OpenAlex
- W2886855629
- Cited by
- 931
- References
- 62
- Citations by year
- 2026: 110 · 2025: 104 · 2024: 76 · 2023: 116 · 2022: 136 · 2021: 136 · 2020: 130 · 2019: 104 · 2018: 18 · 2017: 1
- FWCI
- 29.54
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Heart, Lung, and Blood Institute (U54HL127366)
- National Human Genome Research Institute (U54HG008097)
- National Cancer Institute (R01CA219943, R01CA188228)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Keywords
- cancer cell lines, clonal evolution, clonal selection, genetic heterogeneity, transcriptional heterogeneity, drug response, anticancer agents, single-cell clones, culture conditions, transcriptional programs
- MeSH terms
- Breast Neoplasms, Clone Cells, Humans, Transcription, Genetic, Genetic Variation, Reproducibility of Results, Evolution, Molecular, Genomic Instability, Cell Shape, Cell Proliferation, MCF-7 Cells
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