Evidence map›Paper›PMID 28453553›Full record

ArticlePloS one2017

A tool for discovering drug sensitivity and gene expression associations in cancer cells.

Yong Qin, Anthony P Conley, Elizabeth A Grimm, Jason Roszik

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

4 authors.

Yong QinDepartment of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Anthony P ConleyDepartment of Sarcoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Elizabeth A GrimmDepartment of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Jason RoszikDepartment of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The sensitivity of cancer cells to anticancer drugs is a crucial factor for developing effective treatments. However, it is still challenging to precisely predict the effectiveness of therapeutics in humans within a complex genomic and molecular context. We developed an interface which allows the user to rapidly explore drug sensitivity and gene expression associations. Predictions for how expression of various genes affect anticancer drug activity are available for all genes for a set of therapeutics based on data from various cell lines of different origin in the Cancer Cell Line Encyclopedia and the Genomics of Drug Sensitivity in Cancer projects. Our application makes discovery or validation of drug sensitivity and gene expression associations efficient. Effectiveness of this tool is demonstrated by multiple known and novel examples.

Indexed as

Drug DiscoverySoftwareAntineoplastic AgentsCell Line, TumorDatabases, PharmaceuticalDrug Screening Assays, AntitumorGene Expression Regulation, NeoplasticHumansInternetNAD(P)H Dehydrogenase (Quinone)NeoplasmsVascular Endothelial Growth Factor AAntineoplastic AgentsNAD(P)H Dehydrogenase (Quinone)NQO1 protein, humanVascular Endothelial Growth Factor AVEGFA protein, human

Identifiers

PMID28453553
PMCPMC5409143

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.