Literature DB >> 30089904

Genetic and transcriptional evolution alters cancer cell line drug response.

Uri Ben-David1, Benjamin Siranosian1, Gavin Ha1,2, Helen Tang1, Yaara Oren1,3, Kunihiko Hinohara1,2, Craig A Strathdee1, Joshua Dempster1, Nicholas J Lyons1, Robert Burns2, Anwesha Nag2, Guillaume Kugener1, Beth Cimini1, Peter Tsvetkov1, Yosef E Maruvka1, Ryan O'Rourke1,2, Anthony Garrity1, Andrew A Tubelli1, Pratiti Bandopadhayay1,2,3, Aviad Tsherniak1, Francisca Vazquez1, Bang Wong1, Chet Birger1, Mahmoud Ghandi1, Aaron R Thorner2, Joshua A Bittker1, Matthew Meyerson1,2,3, Gad Getz1,4, Rameen Beroukhim5,6,7,8, Todd R Golub9,10,11,12.   

Abstract

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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Mesh:

Year:  2018        PMID: 30089904      PMCID: PMC6522222          DOI: 10.1038/s41586-018-0409-3

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  59 in total

1.  Circular binary segmentation for the analysis of array-based DNA copy number data.

Authors:  Adam B Olshen; E S Venkatraman; Robert Lucito; Michael Wigler
Journal:  Biostatistics       Date:  2004-10       Impact factor: 5.899

2.  Adjusting batch effects in microarray expression data using empirical Bayes methods.

Authors:  W Evan Johnson; Cheng Li; Ariel Rabinovic
Journal:  Biostatistics       Date:  2006-04-21       Impact factor: 5.899

3.  Isolation and characterization of a spontaneously immortalized human breast epithelial cell line, MCF-10.

Authors:  H D Soule; T M Maloney; S R Wolman; W D Peterson; R Brenz; C M McGrath; J Russo; R J Pauley; R F Jones; S C Brooks
Journal:  Cancer Res       Date:  1990-09-15       Impact factor: 12.701

4.  A continuous tumor-cell line from a human lung carcinoma with properties of type II alveolar epithelial cells.

Authors:  M Lieber; B Smith; A Szakal; W Nelson-Rees; G Todaro
Journal:  Int J Cancer       Date:  1976-01-15       Impact factor: 7.396

5.  Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

Authors:  Aravind Subramanian; Pablo Tamayo; Vamsi K Mootha; Sayan Mukherjee; Benjamin L Ebert; Michael A Gillette; Amanda Paulovich; Scott L Pomeroy; Todd R Golub; Eric S Lander; Jill P Mesirov
Journal:  Proc Natl Acad Sci U S A       Date:  2005-09-30       Impact factor: 11.205

6.  A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers.

Authors:  Scott L Carter; Aron C Eklund; Isaac S Kohane; Lyndsay N Harris; Zoltan Szallasi
Journal:  Nat Genet       Date:  2006-08-20       Impact factor: 38.330

7.  Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.

Authors:  T R Golub; D K Slonim; P Tamayo; C Huard; M Gaasenbeek; J P Mesirov; H Coller; M L Loh; J R Downing; M A Caligiuri; C D Bloomfield; E S Lander
Journal:  Science       Date:  1999-10-15       Impact factor: 47.728

8.  A method for high-throughput gene expression signature analysis.

Authors:  David Peck; Emily D Crawford; Kenneth N Ross; Kimberly Stegmaier; Todd R Golub; Justin Lamb
Journal:  Genome Biol       Date:  2006       Impact factor: 13.583

9.  Fast and accurate short read alignment with Burrows-Wheeler transform.

Authors:  Heng Li; Richard Durbin
Journal:  Bioinformatics       Date:  2009-05-18       Impact factor: 6.937

10.  The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website.

Authors:  S Bamford; E Dawson; S Forbes; J Clements; R Pettett; A Dogan; A Flanagan; J Teague; P A Futreal; M R Stratton; R Wooster
Journal:  Br J Cancer       Date:  2004-07-19       Impact factor: 7.640

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  250 in total

1.  Inter-generational consequences for growing Caenorhabditis elegans in liquid.

Authors:  Itamar Lev; Roberta Bril; Yunan Liu; Lucila Inés Ceré; Oded Rechavi
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-04-15       Impact factor: 6.237

2.  Meta-analysis of Chromatin Programming by Steroid Receptors.

Authors:  Ville Paakinaho; Erin E Swinstead; Diego M Presman; Lars Grøntved; Gordon L Hager
Journal:  Cell Rep       Date:  2019-09-24       Impact factor: 9.423

3.  Synthetic Antigen Gels as Practical Controls for Standardized and Quantitative Immunohistochemistry.

Authors:  Kathy J Hötzel; Charles A Havnar; Hai V Ngu; Sandra Rost; Scot D Liu; Linda K Rangell; Franklin V Peale
Journal:  J Histochem Cytochem       Date:  2019-03-18       Impact factor: 2.479

Review 4.  An Interactive Resource to Probe Genetic Diversity and Estimated Ancestry in Cancer Cell Lines.

Authors:  Julie Dutil; Zhihua Chen; Alvaro N Monteiro; Jamie K Teer; Steven A Eschrich
Journal:  Cancer Res       Date:  2019-03-20       Impact factor: 12.701

Review 5.  Genome editing to define the function of risk loci and variants in rheumatic disease.

Authors:  Yuriy Baglaenko; Dana Macfarlane; Alexander Marson; Peter A Nigrovic; Soumya Raychaudhuri
Journal:  Nat Rev Rheumatol       Date:  2021-06-29       Impact factor: 20.543

6.  Memory Sequencing Reveals Heritable Single-Cell Gene Expression Programs Associated with Distinct Cellular Behaviors.

Authors:  Sydney M Shaffer; Benjamin L Emert; Raúl A Reyes Hueros; Christopher Cote; Guillaume Harmange; Dylan L Schaff; Ann E Sizemore; Rohit Gupte; Eduardo Torre; Abhyudai Singh; Danielle S Bassett; Arjun Raj
Journal:  Cell       Date:  2020-07-30       Impact factor: 41.582

7.  Aneuploidy increases resistance to chemotherapeutics by antagonizing cell division.

Authors:  John Michael Replogle; Wen Zhou; Adrianna E Amaro; James M McFarland; Mariana Villalobos-Ortiz; Jeremy Ryan; Anthony Letai; Omer Yilmaz; Jason Sheltzer; Stephen J Lippard; Uri Ben-David; Angelika Amon
Journal:  Proc Natl Acad Sci U S A       Date:  2020-11-17       Impact factor: 11.205

8.  Harnessing biomolecules for bioinspired dental biomaterials.

Authors:  Nicholas G Fischer; Eliseu A Münchow; Candan Tamerler; Marco C Bottino; Conrado Aparicio
Journal:  J Mater Chem B       Date:  2020-08-04       Impact factor: 6.331

9.  CellMiner Cross-Database (CellMinerCDB) version 1.2: Exploration of patient-derived cancer cell line pharmacogenomics.

Authors:  Augustin Luna; Fathi Elloumi; Sudhir Varma; Yanghsin Wang; Vinodh N Rajapakse; Mirit I Aladjem; Jacques Robert; Chris Sander; Yves Pommier; William C Reinhold
Journal:  Nucleic Acids Res       Date:  2021-01-08       Impact factor: 16.971

10.  An in vitro model of tumor heterogeneity resolves genetic, epigenetic, and stochastic sources of cell state variability.

Authors:  Corey E Hayford; Darren R Tyson; C Jack Robbins; Peter L Frick; Vito Quaranta; Leonard A Harris
Journal:  PLoS Biol       Date:  2021-06-01       Impact factor: 8.029

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