Evidence map›Paper›PMID 29800349›Full record

ArticleNucleic acids research2018

GDA, a web-based tool for Genomics and Drugs integrated analysis.

Jimmy Caroli, Giovanni Sorrentino, Mattia Forcato, Giannino Del Sal, Silvio Bicciato

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

7 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
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  6. Review
  7. g-Nomic: a new pharmacogenetics interpretation software.Pharmacogenomics and personalized medicine · 2019
    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

5 authors at 3 institutions in 2 countries.

Jimmy CaroliDept. of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi, 287, 41125 Modena, Italy.
Giovanni SorrentinoLaboratory of Metabolic Signaling, Ecole Polytechnique Fédérale de Lausanne EPFL, Lausanne, Switzerland.
Mattia ForcatoDept. of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi, 287, 41125 Modena, Italy.
Giannino Del SalLaboratorio Nazionale CIB, Area Science Park Padriciano, Trieste, Italy.
Silvio BicciatoDept. of Life Sciences, University of Modena and Reggio Emilia, Via G. Campi, 287, 41125 Modena, Italy.
University of Modena and Reggio Emilia · ITÉcole Polytechnique Fédérale de Lausanne · CHUniversity of Trieste · IT

Funding

European Research Council 670126
6 · The paper itself

Abstract

Several major screenings of genetic profiling and drug testing in cancer cell lines proved that the integration of genomic portraits and compound activities is effective in discovering new genetic markers of drug sensitivity and clinically relevant anticancer compounds. Despite most genetic and drug response data are publicly available, the availability of user-friendly tools for their integrative analysis remains limited, thus hampering an effective exploitation of this information. Here, we present GDA, a web-based tool for Genomics and Drugs integrated Analysis that combines drug response data for >50 800 compounds with mutations and gene expression profiles across 73 cancer cell lines. Genomic and pharmacological data are integrated through a modular architecture that allows users to identify compounds active towards cancer cell lines bearing a specific genomic background and, conversely, the mutational or transcriptional status of cells responding or not-responding to a specific compound. Results are presented through intuitive graphical representations and supplemented with information obtained from public repositories. As both personalized targeted therapies and drug-repurposing are gaining increasing attention, GDA represents a resource to formulate hypotheses on the interplay between genomic traits and drug response in cancer. GDA is freely available at http://gda.unimore.it/.

Indexed as

SoftwareAntineoplastic AgentsCell Line, TumorGenomicsHumansInternetMutationNeoplasmsProtein Kinase InhibitorsProto-Oncogene Proteins B-rafSignal TransductionTranscriptional ActivationTranscriptomeAntineoplastic AgentsProtein Kinase InhibitorsProto-Oncogene Proteins B-raf

Identifiers

PMID29800349
PMCPMC6031047
OpenAlexW2804582507

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.