Evidence map›Paper›PMID 32256826›Full record

ArticleOncology letters2020

Comprehensive gene and pathway analysis of cervical cancer progression.

Yuexiong Yi, Yan Fang, Kejia Wu, Yanyan Liu, Wei Zhang

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 2 pooled it
12.5field-weighted citation impact, top 1% 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

51 citing papers in PubMed, 2 syntheses or guidelines pooled it, 115 citations in OpenAlex.

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  10. New Diagnostic and Therapeutic Targets for Spinal Cord Injury: GRN Gene.Journal of cellular and molecular medicine · 2025
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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

5 authors at 2 institutions in 1 country.

Yuexiong YiDepartment of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China.
Yan FangDepartment of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China.
Kejia WuDepartment of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China.
Yanyan LiuDepartment of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China.
Wei ZhangDepartment of Obstetrics and Gynecology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China.
Wuhan University · CNZhongnan Hospital of Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cervical Cancer is one of the leading causes of cancer-associated mortality in women. The present study aimed to identify key genes and pathways involved in cervical cancer (CC) progression, via a comprehensive bioinformatics analysis. The GSE63514 dataset from the Gene Expression Omnibus database was analyzed for hub genes and cancer progression was divided into four phases (phases I-IV). Pathway enrichment, protein-protein interaction (PPI) and pathway crosstalk analyses were performed, to identify key genes and pathways using a criterion nodal degree ≥5. Gene pathway analysis was determined by mapping the key genes into the key pathways. Co-expression between key genes and their effect on overall survival (OS) time was assessed using The Cancer Genome Atlas database. A total of 3,446 differentially expressed genes with 107 hub genes were identified within the four phases. A total of 14 key genes with 11 key pathways were obtained, following extraction of ≥5 degree nodes from the PPI and pathway crosstalk networks. Gene pathway analysis revealed that

Indexed as

bioinformatics analysiscervical cancerdiagnosisprogression

Identifiers

PMID32256826
PMCPMC7074609
OpenAlexW3009973186

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.