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Cited by 359Computational Drug Discovery MethodsCancer Cells and MetastasisCancer therapeutics and mechanisms

The National Cancer Institute ALMANAC: a comprehensive screening resource for the detection of anticancer drug pairs with enhanced therapeutic activity

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Holbeck, Susan L., Camalier, Richard, Crowell, James A., Govindharajulu, Jeevan Prasaad, Hollingshead, Melinda, Anderson, Lawrence W., Polley, Eric, Rubinstein, Larry +4 more·2017·Cancer Research
DOI 10.1158/0008-5472.can-17-0489PMC PMC5499996

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Abstract

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.

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  • Most in vivo synergy studies simply compare tumor volume at a single day using t test, or use survival analysis to compare time-to-event between groups.

    “Most studies simply compare TV at a single day using t test, or use survival analysis to compare the time-to-event (i.e., time for TV to reach a threshold) between groups (4–6, 23).”

    From Statistical Assessment of Drug Synergy from <i>In Vivo</i> Combination Studies Using Mouse Tumor Models (2023) · cites this paper as [5]

    The Materials and Methods section (Human Tumor Xenografts; page unavailable) describes comparing groups with Kaplan–Meier and log-rank analyses of time to tumor-volume doubling. The Results section (Examination of Promising Anticancer Drug Combinations; page unavailable) says various methods have been used in xenograft studies, but it does not establish that most studies use these methods or report single-day tumor-volume comparisons using a t test. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Holbeck, S. L., Camalier, R., Crowell, J. A., Govindharajulu, J. P., Hollingshead, M., Anderson, L. W., Polley, E., Rubinstein, L., Srivastava, A., Wilsker, D., Collins, J. M., & Doroshow, J. H.
Affiliations
  • National Institutes of Health (US)
  • Frederick National Laboratory for Cancer Research (US)
Corresponding author
Doroshow, James H.
ORCID
Venue
Cancer Research
Publisher
American Association for Cancer Research (AACR)
Published
2017-07-01
Volume
77
Issue
13
Pages
3564-3576
ISSN
  • 0008-5472 (ISSN-L)
  • 1538-7445
DOI
10.1158/0008-5472.can-17-0489
PMC
PMC5499996
OpenAlex
W2608863179
Cited by
359
References
0
Citations by year
2026: 42 · 2025: 59 · 2024: 48 · 2023: 58 · 2022: 31 · 2021: 41 · 2020: 37 · 2019: 30 · 2018: 12 · 2017: 1
FWCI
16.42
Type
journal article
Language
en
Open access
Locations
  • Cancer Research (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Cancer Institute NIH (HHSN261200800001E)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Cancer therapeutics and mechanisms
Keywords
anticancer drug combination, drug synergy, NCI-60 cell lines, drug resistance, combination therapy, clofarabine, bortezomib, nilotinib, paclitaxel, mechanistic biomarkers, xenograft mouse model
MeSH terms
Animals, Antineoplastic Combined Chemotherapy Protocols, Drug Screening Assays, Antitumor, Humans, United States, Xenograft Model Antitumor Assays, Cell Line, Tumor, Mice, National Cancer Institute (U.S.), Small Molecule Libraries

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