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Literature DB >> 24141220

Drug discovery: Rethinking cellular drug response.

Jeremy L Jenkins¹.

Abstract

Mesh：

Substances：
Antineoplastic Agents

Year: 2013 PMID： 24141220 DOI： 10.1038/nchembio.1365

Source DB: PubMed Journal: Nat Chem Biol ISSN： 1552-4450 Impact factor: 15.040

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9 in total

1. An interactive resource to identify cancer genetic and lineage dependencies targeted by small molecules.

Authors: Amrita Basu; Nicole E Bodycombe; Jaime H Cheah; Edmund V Price; Ke Liu; Giannina I Schaefer; Richard Y Ebright; Michelle L Stewart; Daisuke Ito; Stephanie Wang; Abigail L Bracha; Ted Liefeld; Mathias Wawer; Joshua C Gilbert; Andrew J Wilson; Nicolas Stransky; Gregory V Kryukov; Vlado Dancik; Jordi Barretina; Levi A Garraway; C Suk-Yee Hon; Benito Munoz; Joshua A Bittker; Brent R Stockwell; Dineo Khabele; Andrew M Stern; Paul A Clemons; Alykhan F Shamji; Stuart L Schreiber
Journal: Cell Date: 2013-08-29 Impact factor: 41.582

2. A gene expression database for the molecular pharmacology of cancer.

Authors: U Scherf; D T Ross; M Waltham; L H Smith; J K Lee; L Tanabe; K W Kohn; W C Reinhold; T G Myers; D T Andrews; D A Scudiero; M B Eisen; E A Sausville; Y Pommier; D Botstein; P O Brown; J N Weinstein
Journal: Nat Genet Date: 2000-03 Impact factor: 38.330

3. Dose-response curve slope is a missing dimension in the analysis of HIV-1 drug resistance.

Authors: Maame Efua S Sampah; Lin Shen; Benjamin L Jilek; Robert F Siliciano
Journal: Proc Natl Acad Sci U S A Date: 2011-04-18 Impact factor: 11.205

4. Metrics other than potency reveal systematic variation in responses to cancer drugs.

Authors: Mohammad Fallahi-Sichani; Saman Honarnejad; Laura M Heiser; Joe W Gray; Peter K Sorger
Journal: Nat Chem Biol Date: 2013-09-08 Impact factor: 15.040

5. Feasibility of a high-flux anticancer drug screen using a diverse panel of cultured human tumor cell lines.

Authors: A Monks; D Scudiero; P Skehan; R Shoemaker; K Paull; D Vistica; C Hose; J Langley; P Cronise; A Vaigro-Wolff
Journal: J Natl Cancer Inst Date: 1991-06-05 Impact factor: 13.506

6. Mining the National Cancer Institute's tumor-screening database: identification of compounds with similar cellular activities.

Authors: Alfred A Rabow; Robert H Shoemaker; Edward A Sausville; David G Covell
Journal: J Med Chem Date: 2002-02-14 Impact factor: 7.446

7. Cell type variation in responses to antimitotic drugs that target microtubules and kinesin-5.

Authors: Jue Shi; James D Orth; Tim Mitchison
Journal: Cancer Res Date: 2008-05-01 Impact factor: 12.701

8. Integrating constitutive gene expression and chemoactivity: mining the NCI60 anticancer screen.

Authors: David G Covell
Journal: PLoS One Date: 2012-10-02 Impact factor: 3.240

9. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

Authors: Jordi Barretina; Giordano Caponigro; Nicolas Stransky; Kavitha Venkatesan; Adam A Margolin; Sungjoon Kim; Christopher J Wilson; Joseph Lehár; Gregory V Kryukov; Dmitriy Sonkin; Anupama Reddy; Manway Liu; Lauren Murray; Michael F Berger; John E Monahan; Paula Morais; Jodi Meltzer; Adam Korejwa; Judit Jané-Valbuena; Felipa A Mapa; Joseph Thibault; Eva Bric-Furlong; Pichai Raman; Aaron Shipway; Ingo H Engels; Jill Cheng; Guoying K Yu; Jianjun Yu; Peter Aspesi; Melanie de Silva; Kalpana Jagtap; Michael D Jones; Li Wang; Charles Hatton; Emanuele Palescandolo; Supriya Gupta; Scott Mahan; Carrie Sougnez; Robert C Onofrio; Ted Liefeld; Laura MacConaill; Wendy Winckler; Michael Reich; Nanxin Li; Jill P Mesirov; Stacey B Gabriel; Gad Getz; Kristin Ardlie; Vivien Chan; Vic E Myer; Barbara L Weber; Jeff Porter; Markus Warmuth; Peter Finan; Jennifer L Harris; Matthew Meyerson; Todd R Golub; Michael P Morrissey; William R Sellers; Robert Schlegel; Levi A Garraway
Journal: Nature Date: 2012-03-28 Impact factor: 49.962

9 in total

5 in total

Drug discovery: Rethinking cellular drug response.

1. An interactive resource to identify cancer genetic and lineage dependencies targeted by small molecules.

2. A gene expression database for the molecular pharmacology of cancer.

3. Dose-response curve slope is a missing dimension in the analysis of HIV-1 drug resistance.

4. Metrics other than potency reveal systematic variation in responses to cancer drugs.

5. Feasibility of a high-flux anticancer drug screen using a diverse panel of cultured human tumor cell lines.

6. Mining the National Cancer Institute's tumor-screening database: identification of compounds with similar cellular activities.

7. Cell type variation in responses to antimitotic drugs that target microtubules and kinesin-5.

8. Integrating constitutive gene expression and chemoactivity: mining the NCI60 anticancer screen.

9. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

1. A power law function describes the time- and dose-dependency of Vγ9Vδ2 T cell activation by phosphoantigens.

2. In vitro studies of deferasirox derivatives as potential organelle-targeting traceable anti-cancer therapeutics.

3. WX-132-18B, a novel microtubule inhibitor, exhibits promising anti-tumor effects.

4. ZINC40099027 activates human focal adhesion kinase by accelerating the enzymatic activity of the FAK kinase domain.

5. Phenotype-based probabilistic analysis of heterogeneous responses to cancer drugs and their combination efficacy.