Evidence map›Paper›PMID 32510146›Full record

ArticleBioscience reports2020

Identification of metastasis and prognosis-associated genes for serous ovarian cancer.

Yijun Yang, Suwan Qi, Can Shi, Xiao Han, Juanpeng Yu, Lei Zhang, Shanshan Qin, Yingchun Gao

Open access · goldAbstract read
In one paragraph

Article in Bioscience reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.8field-weighted citation impact, top 12% 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

17 citing papers in PubMed, 20 citations in OpenAlex.

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  17. A Comprehensive Analysis of the Downregulation ofFrontiers in molecular biosciences · 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 1 institution in 1 country.

Yijun Yang *Department of Obstetrics and Gynecology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
Suwan Qi *Department of Obstetrics and Gynecology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
Can ShiDepartment of Obstetrics and Gynecology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
Xiao HanDepartment of Central Laboratory, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
Juanpeng YuDepartment of Obstetrics and Gynecology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
Lei ZhangDepartment of Obstetrics and Gynecology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
Shanshan QinDepartment of Obstetrics and Gynecology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
Yingchun GaoDepartment of Obstetrics and Gynecology, The Affiliated Huai'an No. 1 People's Hospital of Nanjing Medical University, Huai'an, China.
Xuzhou Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Serous ovarian cancer is one of the most fatal gynecological tumors with an extremely low 5-year survival rate. Most patients are diagnosed at an advanced stage with wide metastasis. The dysregulation of genes serves an important role in the metastasis progression of ovarian cancer. Differentially expressed genes (DEGs) between primary tumors and metastases of serous ovarian cancer were screened out in the gene expression profile of GSE73168 from Gene Expression Omnibus (GEO). Cytoscape plugin cytoHubba and weighted gene co-expression network analysis (WGCNA) were utilized to select hub genes. Univariate and multivariate Cox regression analyses were used to screen out prognosis-associated genes. Furthermore, the Oncomine validation, prognostic analysis, methylation mechanism, gene set enrichment analysis (GSEA), TIMER database analysis and administration of candidate molecular drugs were conducted for hub genes. Nine hundred and fifty-seven DEGs were identified in the gene expression profile of GSE73168. After using Cytoscape plugin cytoHubba, 83 genes were verified. In co-expression network, the blue module was most closely related to tumor metastasis. Furthermore, the genes in Cytoscape were analyzed, showing that the blue module and screened 17 genes were closely associated with tumor metastasis. Univariate and multivariate Cox regression revealed that the age, stage and STMN2 were independent prognostic factors. The Cancer Genome Atlas (TCGA) suggested that the up-regulated expression of STMN2 was related to poor prognosis of ovarian cancer. Thus, STMN2 was considered as a new key gene after expression validation, survival analysis and TIMER database validation. GSEA confirmed that STMN2 was probably involved in ECM receptor interaction, focal adhesion, TGF beta signaling pathway and MAPK signaling pathway. Furthermore, three candidate small molecule drugs for tumor metastasis (diprophylline, valinomycin and anisomycin) were screened out. The quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and western blot showed that STMN2 was highly expressed in ovarian cancer tissue and ovarian cancer cell lines. Further studies are needed to investigate these prognosis-associated genes for new therapy target.

Indexed as

Age FactorsBiomarkers, TumorCell Line, TumorCell MovementDatabases, GeneticFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansNeoplasm InvasivenessNeoplasms, Cystic, Mucinous, and SerousNeoplasm StagingOvarian NeoplasmsProtein Interaction MapsSignal TransductionStathminBiomarkers, TumorStathminSTMN2 protein, humanbioinformatics analysisprognosisserous ovarian cancerTIMER database analysistumor metastasisweighted gene coexpression network analysis (WGCNA)

Identifiers

PMID32510146
PMCPMC7317593
OpenAlexW3033327266

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.