Literature DB >> 25015668

Enhancing reproducibility in cancer drug screening: how do we move forward?

Christos Hatzis1, Philippe L Bedard2, Nicolai J Birkbak3, Andrew H Beck4, Hugo J W L Aerts5, David F Stem, David F Stern6, Leming Shi7, Robert Clarke8, John Quackenbush9, Benjamin Haibe-Kains10.   

Abstract

Large-scale pharmacogenomic high-throughput screening (HTS) studies hold great potential for generating robust genomic predictors of drug response. Two recent large-scale HTS studies have reported results of such screens, revealing several known and novel drug sensitivities and biomarkers. Subsequent evaluation, however, found only moderate interlaboratory concordance in the drug response phenotypes, possibly due to differences in the experimental protocols used in the two studies. This highlights the need for community-wide implementation of standardized assays for measuring drug response phenotypes so that the full potential of HTS is realized. We suggest that the path forward is to establish best practices and standardization of the critical steps in these assays through a collective effort to ensure that the data produced from large-scale screens would not only be of high intrastudy consistency, so that they could be replicated and compared successfully across multiple laboratories. ©2014 American Association for Cancer Research.

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Year:  2014        PMID: 25015668      PMCID: PMC4119520          DOI: 10.1158/0008-5472.CAN-14-0725

Source DB:  PubMed          Journal:  Cancer Res        ISSN: 0008-5472            Impact factor:   12.701


  36 in total

1.  Minimum information about a microarray experiment (MIAME)-toward standards for microarray data.

Authors:  A Brazma; P Hingamp; J Quackenbush; G Sherlock; P Spellman; C Stoeckert; J Aach; W Ansorge; C A Ball; H C Causton; T Gaasterland; P Glenisson; F C Holstege; I F Kim; V Markowitz; J C Matese; H Parkinson; A Robinson; U Sarkans; S Schulze-Kremer; J Stewart; R Taylor; J Vilo; M Vingron
Journal:  Nat Genet       Date:  2001-12       Impact factor: 38.330

Review 2.  Designing screens: how to make your hits a hit.

Authors:  W Patrick Walters; Mark Namchuk
Journal:  Nat Rev Drug Discov       Date:  2003-04       Impact factor: 84.694

Review 3.  Envisioning the future of early anticancer drug development.

Authors:  Timothy A Yap; Shahneen K Sandhu; Paul Workman; Johann S de Bono
Journal:  Nat Rev Cancer       Date:  2010-06-10       Impact factor: 60.716

4.  The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Authors:  Leming Shi; Laura H Reid; Wendell D Jones; Richard Shippy; Janet A Warrington; Shawn C Baker; Patrick J Collins; Francoise de Longueville; Ernest S Kawasaki; Kathleen Y Lee; Yuling Luo; Yongming Andrew Sun; James C Willey; Robert A Setterquist; Gavin M Fischer; Weida Tong; Yvonne P Dragan; David J Dix; Felix W Frueh; Frederico M Goodsaid; Damir Herman; Roderick V Jensen; Charles D Johnson; Edward K Lobenhofer; Raj K Puri; Uwe Schrf; Jean Thierry-Mieg; Charles Wang; Mike Wilson; Paul K Wolber; Lu Zhang; Shashi Amur; Wenjun Bao; Catalin C Barbacioru; Anne Bergstrom Lucas; Vincent Bertholet; Cecilie Boysen; Bud Bromley; Donna Brown; Alan Brunner; Roger Canales; Xiaoxi Megan Cao; Thomas A Cebula; James J Chen; Jing Cheng; Tzu-Ming Chu; Eugene Chudin; John Corson; J Christopher Corton; Lisa J Croner; Christopher Davies; Timothy S Davison; Glenda Delenstarr; Xutao Deng; David Dorris; Aron C Eklund; Xiao-hui Fan; Hong Fang; Stephanie Fulmer-Smentek; James C Fuscoe; Kathryn Gallagher; Weigong Ge; Lei Guo; Xu Guo; Janet Hager; Paul K Haje; Jing Han; Tao Han; Heather C Harbottle; Stephen C Harris; Eli Hatchwell; Craig A Hauser; Susan Hester; Huixiao Hong; Patrick Hurban; Scott A Jackson; Hanlee Ji; Charles R Knight; Winston P Kuo; J Eugene LeClerc; Shawn Levy; Quan-Zhen Li; Chunmei Liu; Ying Liu; Michael J Lombardi; Yunqing Ma; Scott R Magnuson; Botoul Maqsodi; Tim McDaniel; Nan Mei; Ola Myklebost; Baitang Ning; Natalia Novoradovskaya; Michael S Orr; Terry W Osborn; Adam Papallo; Tucker A Patterson; Roger G Perkins; Elizabeth H Peters; Ron Peterson; Kenneth L Philips; P Scott Pine; Lajos Pusztai; Feng Qian; Hongzu Ren; Mitch Rosen; Barry A Rosenzweig; Raymond R Samaha; Mark Schena; Gary P Schroth; Svetlana Shchegrova; Dave D Smith; Frank Staedtler; Zhenqiang Su; Hongmei Sun; Zoltan Szallasi; Zivana Tezak; Danielle Thierry-Mieg; Karol L Thompson; Irina Tikhonova; Yaron Turpaz; Beena Vallanat; Christophe Van; Stephen J Walker; Sue Jane Wang; Yonghong Wang; Russ Wolfinger; Alex Wong; Jie Wu; Chunlin Xiao; Qian Xie; Jun Xu; Wen Yang; Liang Zhang; Sheng Zhong; Yaping Zong; William Slikker
Journal:  Nat Biotechnol       Date:  2006-09       Impact factor: 54.908

5.  Systematic assessment of analytical methods for drug sensitivity prediction from cancer cell line data.

Authors:  In Sock Jang; Elias Chaibub Neto; Juistin Guinney; Stephen H Friend; Adam A Margolin
Journal:  Pac Symp Biocomput       Date:  2014

6.  Relationships between inhibition constants and fractional inhibition in enzyme-catalyzed reactions with different numbers of reactants, different reaction mechanisms, and different types and mechanisms of inhibition.

Authors:  T Chou
Journal:  Mol Pharmacol       Date:  1974-03       Impact factor: 4.436

7.  Genotype-selective combination therapies for melanoma identified by high-throughput drug screening.

Authors:  Matthew A Held; Casey G Langdon; James T Platt; Tisheeka Graham-Steed; Zongzhi Liu; Ashok Chakraborty; Antonella Bacchiocchi; Andrew Koo; Jonathan W Haskins; Marcus W Bosenberg; David F Stern
Journal:  Cancer Discov       Date:  2012-12-13       Impact factor: 39.397

Review 8.  Tackling the widespread and critical impact of batch effects in high-throughput data.

Authors:  Jeffrey T Leek; Robert B Scharpf; Héctor Corrada Bravo; David Simcha; Benjamin Langmead; W Evan Johnson; Donald Geman; Keith Baggerly; Rafael A Irizarry
Journal:  Nat Rev Genet       Date:  2010-09-14       Impact factor: 53.242

9.  The use of ATP bioluminescence as a measure of cell proliferation and cytotoxicity.

Authors:  S P Crouch; R Kozlowski; K J Slater; J Fletcher
Journal:  J Immunol Methods       Date:  1993-03-15       Impact factor: 2.303

10.  Model-based analysis of oligonucleotide arrays: model validation, design issues and standard error application.

Authors:  C Li; W Hung Wong
Journal:  Genome Biol       Date:  2001-08-03       Impact factor: 13.583

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  34 in total

Review 1.  Systems biology: perspectives on multiscale modeling in research on endocrine-related cancers.

Authors:  Robert Clarke; John J Tyson; Ming Tan; William T Baumann; Lu Jin; Jianhua Xuan; Yue Wang
Journal:  Endocr Relat Cancer       Date:  2019-06       Impact factor: 5.678

Review 2.  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 3.  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

Review 4.  Screening out irrelevant cell-based models of disease.

Authors:  Peter Horvath; Nathalie Aulner; Marc Bickle; Anthony M Davies; Elaine Del Nery; Daniel Ebner; Maria C Montoya; Päivi Östling; Vilja Pietiäinen; Leo S Price; Spencer L Shorte; Gerardo Turcatti; Carina von Schantz; Neil O Carragher
Journal:  Nat Rev Drug Discov       Date:  2016-09-12       Impact factor: 84.694

5.  Evaluating the consistency of large-scale pharmacogenomic studies.

Authors:  Raziur Rahman; Saugato Rahman Dhruba; Kevin Matlock; Carlos De-Niz; Souparno Ghosh; Ranadip Pal
Journal:  Brief Bioinform       Date:  2019-09-27       Impact factor: 11.622

6.  Systematic Drug Screening Identifies Tractable Targeted Combination Therapies in Triple-Negative Breast Cancer.

Authors:  Vikram B Wali; Casey G Langdon; Matthew A Held; James T Platt; Gauri A Patwardhan; Anton Safonov; Bilge Aktas; Lajos Pusztai; David F Stern; Christos Hatzis
Journal:  Cancer Res       Date:  2016-11-21       Impact factor: 12.701

7.  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

8.  Combinatorial Screening of Pancreatic Adenocarcinoma Reveals Sensitivity to Drug Combinations Including Bromodomain Inhibitor Plus Neddylation Inhibitor.

Authors:  Casey G Langdon; James T Platt; Robert E Means; Pinar Iyidogan; Ramanaiah Mamillapalli; Michael Klein; Matthew A Held; Jong Woo Lee; Ja Seok Koo; Christos Hatzis; Howard S Hochster; David F Stern
Journal:  Mol Cancer Ther       Date:  2017-03-14       Impact factor: 6.261

Review 9.  Phenotypic screening with primary neurons to identify drug targets for regeneration and degeneration.

Authors:  Daniel J Cooper; Giulia Zunino; John L Bixby; Vance P Lemmon
Journal:  Mol Cell Neurosci       Date:  2016-07-18       Impact factor: 4.314

10.  Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells.

Authors:  Brent M Kuenzi; Jisoo Park; Samson H Fong; Kyle S Sanchez; John Lee; Jason F Kreisberg; Jianzhu Ma; Trey Ideker
Journal:  Cancer Cell       Date:  2020-10-22       Impact factor: 31.743

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