Evidence map›Paper›PMID 25597938›Full record

ArticleScientific reports2015

Systems pharmacology of mifepristone (RU486) reveals its 47 hub targets and network: comprehensive analysis and pharmacological focus on FAK-Src-Paxillin complex.

Suhong Yu, Xingtian Yang, Yewei Zhu, Fangwei Xie, Yusheng Lu, Ting Yu, Cuicui Yan, Jingwei Shao, Yu Gao, Fan Mo and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
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 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.2field-weighted citation impact, top 6% 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

14 citing papers in PubMed, 29 citations in OpenAlex.

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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

13 authors at 1 institution in 1 country.

Suhong YuCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Xingtian YangCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Yewei ZhuCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Fangwei XieDepartment of Oncology, Fuzhou General Hospital, Fuzhou 350025, China.
Yusheng LuCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Ting YuCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Cuicui YanCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Jingwei ShaoCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Yu GaoCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Fan MoCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Guoneng CaiCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Patrick J SinkoRutgers, The State University of New Jersey, New Jersey 08854, USA.
Lee JiaCancer Metastasis Alert and Prevention Center, College of Chemistry, Fuzhou University, Fuzhou 350002, China.
Fuzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mifepristone (RU486), a synthetic steroid compound used as an abortifacient drug, has received considerable attention to its anticancer activity recently. To explore the possibility of using mifepristone as a cancer metastasis chemopreventive, we performed a systems pharmacology analysis of mifepristone-related molecules in the present study. Data were collected by using Natural Language Processing (NLP) and 513 mifepristone-related genes were dug out and classified functionally using a gene ontology (GO) hierarchy, followed by KEGG pathway enrichment analysis. Potential signal pathways and targets involved in cancer were obtained by integrative network analysis. Total thirty-three proteins were involved in focal adhesion-the key signaling pathway associated with cancer metastasis. Molecular and cellular assays further demonstrated that mifepristone had the ability to prevent breast cancer cells from migration and interfere with their adhesion to endothelial cells. Moreover, mifepristone inhibited the expression of focal adhesion kinase (FAK), paxillin, and the formation of FAK/Src/Paxillin complex, which are correlated with cell adhesion and migration. This study set a good example to identify chemotherapeutic potential seamlessly from systems pharmacology to cellular pharmacology, and the revealed hub genes may be the promising targets for cancer metastasis chemoprevention.

Indexed as

Cell AdhesionCell Line, TumorCell MovementCell SurvivalFocal Adhesion Protein-Tyrosine KinasesGene Regulatory NetworksHumansMetabolic Networks and PathwaysMifepristonePaxillinProto-Oncogene Proteins pp60(c-src)Focal Adhesion Protein-Tyrosine KinasesMifepristonePaxillinProto-Oncogene Proteins pp60(c-src)

Identifiers

PMID25597938
PMCPMC4297966
OpenAlexW2034824061

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.