Evidence map›Paper›PMID 26416286›Full record

ArticleScientific reports2015

A streamlined search technology for identification of synergistic drug combinations.

Andrea Weiss, Robert H Berndsen, Xianting Ding, Chih-Ming Ho, Paul J Dyson, Hubert van den Bergh, Arjan W Griffioen, Patrycja Nowak-Sliwinska

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
9.1field-weighted citation impact, top 2% of its field
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

33 citing papers in PubMed, 82 citations in OpenAlex.

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  7. Forcing dividing cancer cells to die; low-dose drug combinations to prevent spindle pole clustering.Apoptosis : an international journal on programmed cell death · 2021
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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 at 4 institutions in 4 countries.

Andrea WeissInstitute of Chemical Sciences and Engineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Robert H BerndsenInstitute of Chemical Sciences and Engineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Xianting DingMed-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Chih-Ming HoDepartment of Mechanical and Aerospace Engineering, University of California, Los Angeles, USA.
Paul J DysonInstitute of Chemical Sciences and Engineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Hubert van den BerghInstitute of Chemical Sciences and Engineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Arjan W GriffioenAngiogenesis Laboratory, Department of Medical Oncology, VU University Medical Center, Amsterdam, The Netherlands.
Patrycja Nowak-SliwinskaInstitute of Chemical Sciences and Engineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.
Amsterdam UMC Location VUmc · NLÉcole Polytechnique Fédérale de Lausanne · CHShanghai Jiao Tong University · CNUniversity of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A major key to improvement of cancer therapy is the combination of drugs. Mixing drugs that already exist on the market may offer an attractive alternative. Here we report on a new model-based streamlined feedback system control (s-FSC) method, based on a design of experiment approach, for rapidly finding optimal drug mixtures with minimal experimental effort. We tested combinations in an in vitro assay for the viability of a renal cell adenocarcinoma (RCC) cell line, 786-O. An iterative cycle of in vitro testing and s-FSC analysis was repeated a few times until an optimal low dose combination was reached. Starting with ten drugs that target parallel pathways known to play a role in the development and progression of RCC, we identified the best overall drug combination, being a mixture of four drugs (axitinib, erlotinib, dasatinib and AZD4547) at low doses, inhibiting 90% of cell viability. The removal of AZD4547 from the optimized drug combination resulted in 80% of cell viability inhibition, while still maintaining the synergistic interaction. These optimized drug combinations were significantly more potent than monotherapies of all individual drugs (p < 0.001, CI < 0.3).

Indexed as

Antineoplastic AgentsAxitinibBenzamidesCell Line, TumorCell SurvivalDasatinibDose-Response Relationship, DrugDrug CombinationsDrug Screening Assays, AntitumorDrug SynergismEpithelial CellsErlotinib HydrochlorideHumansImidazolesIndazolesKidneyAntineoplastic AgentsAxitinibAZD4547BenzamidesDasatinibDrug CombinationsErlotinib HydrochlorideImidazolesIndazolesPiperazinesPyrazoles

Identifiers

PMID26416286
PMCPMC4586442
OpenAlexW2194348484

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.