Literature DB >> 26248648

Tumor-Derived Cell Lines as Molecular Models of Cancer Pharmacogenomics.

Andrew Goodspeed1, Laura M Heiser2, Joe W Gray2, James C Costello3.   

Abstract

Compared with normal cells, tumor cells have undergone an array of genetic and epigenetic alterations. Often, these changes underlie cancer development, progression, and drug resistance, so the utility of model systems rests on their ability to recapitulate the genomic aberrations observed in primary tumors. Tumor-derived cell lines have long been used to study the underlying biologic processes in cancer, as well as screening platforms for discovering and evaluating the efficacy of anticancer therapeutics. Multiple -omic measurements across more than a thousand cancer cell lines have been produced following advances in high-throughput technologies and multigroup collaborative projects. These data complement the large, international cancer genomic sequencing efforts to characterize patient tumors, such as The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Given the scope and scale of data that have been generated, researchers are now in a position to evaluate the similarities and differences that exist in genomic features between cell lines and patient samples. As pharmacogenomics models, cell lines offer the advantages of being easily grown, relatively inexpensive, and amenable to high-throughput testing of therapeutic agents. Data generated from cell lines can then be used to link cellular drug response to genomic features, where the ultimate goal is to build predictive signatures of patient outcome. This review highlights the recent work that has compared -omic profiles of cell lines with primary tumors, and discusses the advantages and disadvantages of cancer cell lines as pharmacogenomic models of anticancer therapies. ©2015 American Association for Cancer Research.

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Year:  2015        PMID: 26248648      PMCID: PMC4828339          DOI: 10.1158/1541-7786.MCR-15-0189

Source DB:  PubMed          Journal:  Mol Cancer Res        ISSN: 1541-7786            Impact factor:   5.852


  97 in total

1.  Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR.

Authors:  Anirudh Prahallad; Chong Sun; Sidong Huang; Federica Di Nicolantonio; Ramon Salazar; Davide Zecchin; Roderick L Beijersbergen; Alberto Bardelli; René Bernards
Journal:  Nature       Date:  2012-01-26       Impact factor: 49.962

2.  Subtype and pathway specific responses to anticancer compounds in breast cancer.

Authors:  Laura M Heiser; Anguraj Sadanandam; Wen-Lin Kuo; Stephen C Benz; Theodore C Goldstein; Sam Ng; William J Gibb; Nicholas J Wang; Safiyyah Ziyad; Frances Tong; Nora Bayani; Zhi Hu; Jessica I Billig; Andrea Dueregger; Sophia Lewis; Lakshmi Jakkula; James E Korkola; Steffen Durinck; François Pepin; Yinghui Guan; Elizabeth Purdom; Pierre Neuvial; Henrik Bengtsson; Kenneth W Wood; Peter G Smith; Lyubomir T Vassilev; Bryan T Hennessy; Joel Greshock; Kurtis E Bachman; Mary Ann Hardwicke; John W Park; Laurence J Marton; Denise M Wolf; Eric A Collisson; Richard M Neve; Gordon B Mills; Terence P Speed; Heidi S Feiler; Richard F Wooster; David Haussler; Joshua M Stuart; Joe W Gray; Paul T Spellman
Journal:  Proc Natl Acad Sci U S A       Date:  2011-10-14       Impact factor: 11.205

3.  Inhibition of PI3K/mTOR leads to adaptive resistance in matrix-attached cancer cells.

Authors:  Taru Muranen; Laura M Selfors; Devin T Worster; Marcin P Iwanicki; Loling Song; Fabiana C Morales; Sizhen Gao; Gordon B Mills; Joan S Brugge
Journal:  Cancer Cell       Date:  2012-02-14       Impact factor: 31.743

4.  Engineering tumors with 3D scaffolds.

Authors:  Claudia Fischbach; Ruth Chen; Takuya Matsumoto; Tobias Schmelzle; Joan S Brugge; Peter J Polverini; David J Mooney
Journal:  Nat Methods       Date:  2007-09-02       Impact factor: 28.547

Review 5.  Drug resistance and the solid tumor microenvironment.

Authors:  Olivier Trédan; Carlos M Galmarini; Krupa Patel; Ian F Tannock
Journal:  J Natl Cancer Inst       Date:  2007-09-25       Impact factor: 13.506

6.  Identification of genotype-correlated sensitivity to selective kinase inhibitors by using high-throughput tumor cell line profiling.

Authors:  Ultan McDermott; Sreenath V Sharma; Lori Dowell; Patricia Greninger; Clara Montagut; Jennifer Lamb; Heidi Archibald; Raul Raudales; Angela Tam; Diana Lee; S Michael Rothenberg; Jeffrey G Supko; Raffaella Sordella; Lindsey E Ulkus; A John Iafrate; Shyamala Maheswaran; Ching Ni Njauw; Hensin Tsao; Lisa Drew; Jeff H Hanke; Xiao-Jun Ma; Mark G Erlander; Nathanael S Gray; Daniel A Haber; Jeffrey Settleman
Journal:  Proc Natl Acad Sci U S A       Date:  2007-12-06       Impact factor: 11.205

7.  MET amplification occurs with or without T790M mutations in EGFR mutant lung tumors with acquired resistance to gefitinib or erlotinib.

Authors:  James Bean; Cameron Brennan; Jin-Yuan Shih; Gregory Riely; Agnes Viale; Lu Wang; Dhananjay Chitale; Noriko Motoi; Janos Szoke; Stephen Broderick; Marissa Balak; Wen-Cheng Chang; Chong-Jen Yu; Adi Gazdar; Harvey Pass; Valerie Rusch; William Gerald; Shiu-Feng Huang; Pan-Chyr Yang; Vincent Miller; Marc Ladanyi; Chih-Hsin Yang; William Pao
Journal:  Proc Natl Acad Sci U S A       Date:  2007-12-18       Impact factor: 11.205

8.  Stem cell patterns in cell lines derived from head and neck squamous cell carcinoma.

Authors:  Lisa J Harper; Kim Piper; John Common; Farida Fortune; Ian C Mackenzie
Journal:  J Oral Pathol Med       Date:  2007-11       Impact factor: 4.253

9.  Changes in breast cancer biomarkers in the IGF1R/PI3K pathway in recurrent breast cancer after tamoxifen treatment.

Authors:  S C Drury; S Detre; A Leary; J Salter; J Reis-Filho; V Barbashina; C Marchio; E Lopez-Knowles; Z Ghazoui; K Habben; S Arbogast; S Johnston; M Dowsett
Journal:  Endocr Relat Cancer       Date:  2011-08-30       Impact factor: 5.678

10.  Global gene expression analysis of the interaction between cancer cells and osteoblasts to predict bone metastasis in breast cancer.

Authors:  Michal Rajski; Brigitte Vogel; Florent Baty; Christoph Rochlitz; Martin Buess
Journal:  PLoS One       Date:  2012-01-03       Impact factor: 3.240

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  88 in total

Review 1.  Opportunities and challenges in phenotypic drug discovery: an industry perspective.

Authors:  John G Moffat; Fabien Vincent; Jonathan A Lee; Jörg Eder; Marco Prunotto
Journal:  Nat Rev Drug Discov       Date:  2017-07-07       Impact factor: 84.694

2.  Safikhani et al. reply.

Authors:  Zhaleh Safikhani; Nehme El-Hachem; Petr Smirnov; Mark Freeman; Anna Goldenberg; Nicolai J Birkbak; Andrew H Beck; Hugo J W L Aerts; John Quackenbush; Benjamin Haibe-Kains
Journal:  Nature       Date:  2016-11-30       Impact factor: 49.962

3.  Feasibility of Ultra-High-Throughput Functional Screening of Melanoma Biopsies for Discovery of Novel Cancer Drug Combinations.

Authors:  Adam A Friedman; Yun Xia; Lorenzo Trippa; Long Phi Le; Vivien Igras; Dennie T Frederick; Jennifer A Wargo; Kenneth K Tanabe; Donald P Lawrence; Donna S Neuberg; Keith T Flaherty; David E Fisher
Journal:  Clin Cancer Res       Date:  2017-04-26       Impact factor: 12.531

4.  Intranuclear and higher-order chromatin organization of the major histone gene cluster in breast cancer.

Authors:  Andrew J Fritz; Prachi N Ghule; Joseph R Boyd; Coralee E Tye; Natalie A Page; Deli Hong; David J Shirley; Adam S Weinheimer; Ahmet R Barutcu; Diana L Gerrard; Seth Frietze; Andre J van Wijnen; Sayyed K Zaidi; Anthony N Imbalzano; Jane B Lian; Janet L Stein; Gary S Stein
Journal:  J Cell Physiol       Date:  2017-06-22       Impact factor: 6.384

Review 5.  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 6.  Biomaterials-Based Approaches to Tumor Spheroid and Organoid Modeling.

Authors:  Pradip Shahi Thakuri; Chun Liu; Gary D Luker; Hossein Tavana
Journal:  Adv Healthc Mater       Date:  2017-12-04       Impact factor: 9.933

7.  Improving the value of public RNA-seq expression data by phenotype prediction.

Authors:  Shannon E Ellis; Leonardo Collado-Torres; Andrew Jaffe; Jeffrey T Leek
Journal:  Nucleic Acids Res       Date:  2018-05-18       Impact factor: 16.971

8.  Revisiting inconsistency in large pharmacogenomic studies.

Authors:  Zhaleh Safikhani; Petr Smirnov; Mark Freeman; Nehme El-Hachem; Adrian She; Quevedo Rene; Anna Goldenberg; Nicolai J Birkbak; Christos Hatzis; Leming Shi; Andrew H Beck; Hugo J W L Aerts; John Quackenbush; Benjamin Haibe-Kains
Journal:  F1000Res       Date:  2016-09-16

9.  Integration of Tumor Genomic Data with Cell Lines Using Multi-dimensional Network Modules Improves Cancer Pharmacogenomics.

Authors:  James T Webber; Swati Kaushik; Sourav Bandyopadhyay
Journal:  Cell Syst       Date:  2018-11-07       Impact factor: 10.304

Review 10.  Genetic and epigenetic effects on centromere establishment.

Authors:  Yick Hin Ling; Zhongyang Lin; Karen Wing Yee Yuen
Journal:  Chromosoma       Date:  2019-11-28       Impact factor: 4.316

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