Literature DB >> 28446463

The National Cancer Institute ALMANAC: A Comprehensive Screening Resource for the Detection of Anticancer Drug Pairs with Enhanced Therapeutic Activity.

Susan L Holbeck1, Richard Camalier1, James A Crowell1, Jeevan Prasaad Govindharajulu2, Melinda Hollingshead1, Lawrence W Anderson1, Eric Polley1, Larry Rubinstein1, Apurva Srivastava2, Deborah Wilsker2, Jerry M Collins1, James H Doroshow3,4.   

Abstract

To date, over 100 small-molecule oncology drugs have been approved by the FDA. Because of the inherent heterogeneity of tumors, these small molecules are often administered in combination to prevent emergence of resistant cell subpopulations. Therefore, new combination strategies to overcome drug resistance in patients with advanced cancer are needed. In this study, we performed a systematic evaluation of the therapeutic activity of over 5,000 pairs of FDA-approved cancer drugs against a panel of 60 well-characterized human tumor cell lines (NCI-60) to uncover combinations with greater than additive growth-inhibitory activity. Screening results were compiled into a database, termed the NCI-ALMANAC (A Large Matrix of Anti-Neoplastic Agent Combinations), publicly available at https://dtp.cancer.gov/ncialmanac Subsequent in vivo experiments in mouse xenograft models of human cancer confirmed combinations with greater than single-agent efficacy. Concomitant detection of mechanistic biomarkers for these combinations in vivo supported the initiation of two phase I clinical trials at the NCI to evaluate clofarabine with bortezomib and nilotinib with paclitaxel in patients with advanced cancer. Consequently, the hypothesis-generating NCI-ALMANAC web-based resource has demonstrated value in identifying promising combinations of approved drugs with potent anticancer activity for further mechanistic study and translation to clinical trials. Cancer Res; 77(13); 3564-76. ©2017 AACR. ©2017 American Association for Cancer Research.

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Year:  2017        PMID: 28446463      PMCID: PMC5499996          DOI: 10.1158/0008-5472.CAN-17-0489

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


  47 in total

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2.  Phase I Study of Single-Agent AZD1775 (MK-1775), a Wee1 Kinase Inhibitor, in Patients With Refractory Solid Tumors.

Authors:  Khanh Do; Deborah Wilsker; Jiuping Ji; Jennifer Zlott; Tomoko Freshwater; Robert J Kinders; Jerry Collins; Alice P Chen; James H Doroshow; Shivaani Kummar
Journal:  J Clin Oncol       Date:  2015-05-11       Impact factor: 44.544

3.  Cell cycle specific induction of apoptosis and necrosis by paclitaxel in the leukemic U937 cells.

Authors:  Pei-Chin Liao; Chien-Hui Lieu
Journal:  Life Sci       Date:  2005-01-20       Impact factor: 5.037

Review 4.  Combining imaging and pathway profiling: an alternative approach to cancer drug discovery.

Authors:  Neil O Carragher; Valerie G Brunton; Margaret C Frame
Journal:  Drug Discov Today       Date:  2012-03       Impact factor: 7.851

5.  The ubiquitin-proteasome system as a molecular target in solid tumors: an update on bortezomib.

Authors:  A Milano; F Perri; F Caponigro
Journal:  Onco Targets Ther       Date:  2009-02-18       Impact factor: 4.147

6.  Drug synergy screen and network modeling in dedifferentiated liposarcoma identifies CDK4 and IGF1R as synergistic drug targets.

Authors:  Martin L Miller; Evan J Molinelli; Jayasree S Nair; Tahir Sheikh; Rita Samy; Xiaohong Jing; Qin He; Anil Korkut; Aimee M Crago; Samuel Singer; Gary K Schwartz; Chris Sander
Journal:  Sci Signal       Date:  2013-09-24       Impact factor: 8.192

7.  Phase I clinical and pharmacology study of clofarabine in patients with solid and hematologic cancers.

Authors:  Hagop M Kantarjian; Varsha Gandhi; Peter Kozuch; Stefan Faderl; Francis Giles; Jorge Cortes; Susan O'Brien; Nuhad Ibrahim; Fadlo Khuri; Min Du; Mary Beth Rios; Sima Jeha; Peter McLaughlin; William Plunkett; Michael Keating
Journal:  J Clin Oncol       Date:  2003-03-15       Impact factor: 44.544

Review 8.  Efficacy of therapy with bortezomib in solid tumors: a review based on 32 clinical trials.

Authors:  Zebo Huang; Yinxia Wu; Xin Zhou; Jun Xu; Wei Zhu; Yongqian Shu; Ping Liu
Journal:  Future Oncol       Date:  2014-08       Impact factor: 3.404

9.  Nilotinib potentiates anticancer drug sensitivity in murine ABCB1-, ABCG2-, and ABCC10-multidrug resistance xenograft models.

Authors:  Amit K Tiwari; Kamlesh Sodani; Chun-Ling Dai; Alaa H Abuznait; Satyakam Singh; Zhi-Jie Xiao; Atish Patel; Tanaji T Talele; Liwu Fu; Amal Kaddoumi; James M Gallo; Zhe-Sheng Chen
Journal:  Cancer Lett       Date:  2012-10-09       Impact factor: 8.679

Review 10.  Necroptosis in tumorigenesis, activation of anti-tumor immunity, and cancer therapy.

Authors:  Mao-Bin Meng; Huan-Huan Wang; Yao-Li Cui; Zhi-Qiang Wu; Yang-Yang Shi; Nicholas G Zaorsky; Lei Deng; Zhi-Yong Yuan; You Lu; Ping Wang
Journal:  Oncotarget       Date:  2016-08-30
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  71 in total

1.  Exposure time versus cytotoxicity for anticancer agents.

Authors:  David M Evans; Jianwen Fang; Thomas Silvers; Rene Delosh; Julie Laudeman; Chad Ogle; Russell Reinhart; Michael Selby; Lori Bowles; John Connelly; Erik Harris; Julia Krushkal; Larry Rubinstein; James H Doroshow; Beverly A Teicher
Journal:  Cancer Chemother Pharmacol       Date:  2019-05-17       Impact factor: 3.333

2.  Predicting Tumor Cell Response to Synergistic Drug Combinations Using a Novel Simplified Deep Learning Model.

Authors:  Heming Zhang; Jiarui Feng; Amanda Zeng; Philip Payne; Fuhai Li
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

Review 3.  Machine learning approaches to drug response prediction: challenges and recent progress.

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Journal:  NPJ Precis Oncol       Date:  2020-06-15

4.  Prediction of drug combination effects with a minimal set of experiments.

Authors:  Aleksandr Ianevski; Anil K Giri; Prson Gautam; Alexander Kononov; Swapnil Potdar; Jani Saarela; Krister Wennerberg; Tero Aittokallio
Journal:  Nat Mach Intell       Date:  2019-12-09

5.  RNA Sequencing of the NCI-60: Integration into CellMiner and CellMiner CDB.

Authors:  William C Reinhold; Sudhir Varma; Margot Sunshine; Fathi Elloumi; Kwabena Ofori-Atta; Sunmin Lee; Jane B Trepel; Paul S Meltzer; James H Doroshow; Yves Pommier
Journal:  Cancer Res       Date:  2019-05-21       Impact factor: 12.701

6.  The transcriptomic response of cells to a drug combination is more than the sum of the responses to the monotherapies.

Authors:  Jennifer El Diaz; Mehmet Eren Ahsen; Thomas Schaffter; Xintong Chen; Ronald B Realubit; Charles Karan; Andrea Califano; Bojan Losic; Gustavo Stolovitzky
Journal:  Elife       Date:  2020-09-18       Impact factor: 8.140

7.  Anticancer drug synergy prediction in understudied tissues using transfer learning.

Authors:  Yejin Kim; Shuyu Zheng; Jing Tang; Wenjin Jim Zheng; Zhao Li; Xiaoqian Jiang
Journal:  J Am Med Inform Assoc       Date:  2021-01-15       Impact factor: 4.497

Review 8.  New insights into RAS biology reinvigorate interest in mathematical modeling of RAS signaling.

Authors:  Keesha E Erickson; Oleksii S Rukhlenko; Richard G Posner; William S Hlavacek; Boris N Kholodenko
Journal:  Semin Cancer Biol       Date:  2018-03-05       Impact factor: 15.707

Review 9.  Small-Molecule Screens: A Gateway to Cancer Therapeutic Agents with Case Studies of Food and Drug Administration-Approved Drugs.

Authors:  Nathan P Coussens; John C Braisted; Tyler Peryea; G Sitta Sittampalam; Anton Simeonov; Matthew D Hall
Journal:  Pharmacol Rev       Date:  2017-10       Impact factor: 25.468

10.  A Plug-and-Play, Drug-on-Pillar Platform for Combination Drug Screening Implemented by Microfluidic Adaptive Printing.

Authors:  Jiannan Li; Wen Tan; Wenwu Xiao; Randy P Carney; Yongfan Men; Yuanpei Li; Gerald Quon; Yousif Ajena; Kit S Lam; Tingrui Pan
Journal:  Anal Chem       Date:  2018-11-13       Impact factor: 6.986

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