Literature DB >> 27193678

Reproducible pharmacogenomic profiling of cancer cell line panels.

Peter M Haverty1, Eva Lin2, Jenille Tan2, Yihong Yu2, Billy Lam2, Steve Lianoglou1, Richard M Neve2, Scott Martin2, Jeff Settleman2, Robert L Yauch2, Richard Bourgon1.   

Abstract

The use of large-scale genomic and drug response screening of cancer cell lines depends crucially on the reproducibility of results. Here we consider two previously published screens, plus a later critique of these studies. Using independent data, we show that consistency is achievable, and provide a systematic description of the best laboratory and analysis practices for future studies.

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Year:  2016        PMID： 27193678     DOI： 10.1038/nature17987

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


  24 in total

1.  Outcome signature genes in breast cancer: is there a unique set?

Authors:  Liat Ein-Dor; Itai Kela; Gad Getz; David Givol; Eytan Domany
Journal:  Bioinformatics       Date:  2004-08-12       Impact factor: 6.937

2.  A charged aerosol detector/chemiluminescent nitrogen detector/liquid chromatography/mass spectrometry system for regular and fragment compound analysis in drug discovery.

Authors:  Yutao Jiang; Daniel Hascall; Delia Li; Joseph H Pease
Journal:  J Chromatogr A       Date:  2015-08-01       Impact factor: 4.759

3.  Spatial smoothing and hot spot detection for CGH data using the fused lasso.

Authors:  Robert Tibshirani; Pei Wang
Journal:  Biostatistics       Date:  2007-05-18       Impact factor: 5.899

4.  A resource for cell line authentication, annotation and quality control.

Authors:  Mamie Yu; Suresh K Selvaraj; May M Y Liang-Chu; Sahar Aghajani; Matthew Busse; Jean Yuan; Genee Lee; Franklin Peale; Christiaan Klijn; Richard Bourgon; Joshua S Kaminker; Richard M Neve
Journal:  Nature       Date:  2015-04-16       Impact factor: 49.962

5.  Regularization Paths for Generalized Linear Models via Coordinate Descent.

Authors:  Jerome Friedman; Trevor Hastie; Rob Tibshirani
Journal:  J Stat Softw       Date:  2010       Impact factor: 6.440

6.  Inconsistency in large pharmacogenomic studies.

Authors:  Benjamin Haibe-Kains; Nehme El-Hachem; Nicolai Juul Birkbak; Andrew C Jin; Andrew H Beck; Hugo J W L Aerts; John Quackenbush
Journal:  Nature       Date:  2013-11-27       Impact factor: 49.962

7.  Fast and SNP-tolerant detection of complex variants and splicing in short reads.

Authors:  Thomas D Wu; Serban Nacu
Journal:  Bioinformatics       Date:  2010-02-10       Impact factor: 6.937

8.  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

9.  COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer.

Authors:  Simon A Forbes; Nidhi Bindal; Sally Bamford; Charlotte Cole; Chai Yin Kok; David Beare; Mingming Jia; Rebecca Shepherd; Kenric Leung; Andrew Menzies; Jon W Teague; Peter J Campbell; Michael R Stratton; P Andrew Futreal
Journal:  Nucleic Acids Res       Date:  2010-10-15       Impact factor: 16.971

10.  Differential expression analysis for sequence count data.

Authors:  Simon Anders; Wolfgang Huber
Journal:  Genome Biol       Date:  2010-10-27       Impact factor: 13.583
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  105 in total

Review 1.  Genomic evolution of cancer models: perils and opportunities.

Authors:  Uri Ben-David; Rameen Beroukhim; Todd R Golub
Journal:  Nat Rev Cancer       Date:  2019-02       Impact factor: 60.716

Review 2.  Microfluidics cell sample preparation for analysis: Advances in efficient cell enrichment and precise single cell capture.

Authors:  Liang Huang; Shengtai Bian; Yinuo Cheng; Guanya Shi; Peng Liu; Xiongying Ye; Wenhui Wang
Journal:  Biomicrofluidics       Date:  2017-02-06       Impact factor: 2.800

3.  Why imaging data alone is not enough: AI-based integration of imaging, omics, and clinical data.

Authors:  Andreas Holzinger; Benjamin Haibe-Kains; Igor Jurisica
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-06-15       Impact factor: 9.236

Review 4.  Artificial Intelligence Transforms the Future of Health Care.

Authors:  Nariman Noorbakhsh-Sabet; Ramin Zand; Yanfei Zhang; Vida Abedi
Journal:  Am J Med       Date:  2019-01-31       Impact factor: 4.965

Review 5.  Machine learning approaches to drug response prediction: challenges and recent progress.

Authors:  George Adam; Ladislav Rampášek; Zhaleh Safikhani; Petr Smirnov; Benjamin Haibe-Kains; Anna Goldenberg
Journal:  NPJ Precis Oncol       Date:  2020-06-15

Review 6.  Applications of chemogenomic library screening in drug discovery.

Authors:  Lyn H Jones; Mark E Bunnage
Journal:  Nat Rev Drug Discov       Date:  2017-01-20       Impact factor: 84.694

Review 7.  Predictive approaches for drug combination discovery in cancer.

Authors:  Seyed Ali Madani Tonekaboni; Laleh Soltan Ghoraie; Venkata Satya Kumar Manem; Benjamin Haibe-Kains
Journal:  Brief Bioinform       Date:  2018-03-01       Impact factor: 11.622

8.  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

9.  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

10.  Discovery of novel drug sensitivities in T-PLL by high-throughput ex vivo drug testing and mutation profiling.

Authors:  E I Andersson; S Pützer; B Yadav; O Dufva; S Khan; L He; L Sellner; A Schrader; G Crispatzu; M Oleś; H Zhang; S Adnan-Awad; S Lagström; D Bellanger; J P Mpindi; S Eldfors; T Pemovska; P Pietarinen; A Lauhio; K Tomska; C Cuesta-Mateos; E Faber; S Koschmieder; T H Brümmendorf; S Kytölä; E-R Savolainen; T Siitonen; P Ellonen; O Kallioniemi; K Wennerberg; W Ding; M-H Stern; W Huber; S Anders; J Tang; T Aittokallio; T Zenz; M Herling; S Mustjoki
Journal:  Leukemia       Date:  2017-08-14       Impact factor: 11.528
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