Evidence map›Paper›PMID 31205412›Full record

ArticleCancer informatics2019

Pathway Interactions Based on Drug-Induced Datasets.

Shinuk Kim

Open access · goldAbstract read
In one paragraph

Article in Cancer informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

1 author at 1 institution in 1 country.

Shinuk KimDepartment of Civil Engineering, Sangmyung University, Cheonan, Republic of Korea.
Sangmyung University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we identified enrichment pathway connections from MCF7 breast cancer epithelial cells that were treated with 87 drugs. We extracted drug-treated samples, where the sample size was greater than or equal to 5. The drugs included 17-allylamino-geldanamycin, LY294002, trichostatin A, valproic acid, sirolimus, and wortmannin, which had sample sizes of 11, 8, 7, 7, 7, and 5, respectively. We found meaningful pathways using gene set enrichment analysis and identified intradrug and interdrug pathway interactions, which implied the influence of drug combination. Among the top 20 enrichment pathways that were wortmannin induced, there were a total of 37 intradrug pathway interactions via common genes. Thirty-seven pathway interactions were induced by valproic acid, 11 induced by trichostatin A, 20 induced by LY294002, and 59 induced by sirolimus, all via common genes. The number of interdrug-induced pathway interactions ranged from one pair of pathways to 23. The pair of ERBB_SIGNALING and INSULIN_SIGNALING pathways showed the highest score from a pair of 2 individual drugs. The highest number of pathway interactions was observed between the drugs 17-allylamino-geldanamycin and LY294002.

Indexed as

cancerdrug-induced pathwaygene set analysisinterdrug and intradrug pathway interactions

Identifiers

PMID31205412
PMCPMC6535899
OpenAlexW2946334595

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.