Evidence map›Paper›PMID 26997864›Full record

ArticleCancer informatics2015

Assessing Combinational Drug Efficacy in Cancer Cells by Using Image-based Dynamic Response Analysis.

Chao Sima, Jianping Hua, Milana Cypert, Tasha Miller, Heather M Wilson-Robles, Jeffrey M Trent, Edward R Dougherty, Michael L Bittner

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer informatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Chao SimaCenter for Bioinformatics and Genomic Systems Engineering, Texas A&M Engineering Experiment Station, Texas A&M University, College Station, TX, USA.
Jianping HuaCenter for Bioinformatics and Genomic Systems Engineering, Texas A&M Engineering Experiment Station, Texas A&M University, College Station, TX, USA.
Milana CypertCenter for Bioinformatics and Genomic Systems Engineering, Texas A&M Engineering Experiment Station, Texas A&M University, College Station, TX, USA.
Tasha MillerCollege of Veterinary Medicine, Texas A&M University, College Station, TX, USA.
Heather M Wilson-RoblesCollege of Veterinary Medicine, Texas A&M University, College Station, TX, USA.
Jeffrey M TrentTranslational Genomics Research Institute, Phoenix, AZ, USA.
Edward R DoughertyDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA.
Michael L BittnerCenter for Bioinformatics and Genomic Systems Engineering, Texas A&M Engineering Experiment Station, Texas A&M University, College Station, TX, USA.; Translational Genomics Research Institute, Phoenix, AZ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The landscape of translational research has been shifting toward drug combination therapies. Pairing of drugs allows for more types of drug interaction with cells. In order to accurately and comprehensively assess combinational drug efficacy, analytical methods capable of recognizing these alternative reactions will be required to prioritize those drug candidates having better chances of delivering appreciable therapeutic benefits. Traditional efficacy measures are primarily based on the "extent" of drug inhibition, which is the percentage of cells being killed after drug exposure. Here, we introduce a second dimension of evaluation criterion, speed of killing, based on a live cell imaging assay. This dynamic response trajectory approach takes advantage of both "extent" and "speed" information and uncovers synergisms that would otherwise be missed, while also generating hypotheses regarding important mechanistic modes of drug action.

Indexed as

cell imagingcombinational drugdrug responsedynamicssynergism

Identifiers

PMID26997864
PMCPMC4786100

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.