Evidence map›Paper›PMID 33217795›Full record

ArticleMedicine2020

Comprehensive analysis of the expression and prognosis for S100 in human ovarian cancer: A STROBE study.

Hong-Yu Xu, Hua-Mei Song, Quan Zhou

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Influence of S100A2 in Human Diseases.Diagnostics (Basel, Switzerland) · 2022
    Review
  9. 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

3 authors at 1 institution in 1 country.

Hong-Yu XuDepartment of Gynecology and Obstetrics, the Second People's Hospital of Yichang, China Three Gorges University.
Hua-Mei SongDepartment of Gynecology and Obstetrics, the People's Hospital of China Three Gorges University/the First People's Hospital of Yichang, Yichang, Hubei, China.
Quan ZhouDepartment of Gynecology and Obstetrics, the People's Hospital of China Three Gorges University/the First People's Hospital of Yichang, Yichang, Hubei, China.
Second Hospital of Yichang · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

S100 family members are frequently deregulated in human malignancies, including ovarian cancer. However, the prognostic roles of each individual S100 family member in ovarian cancer (OC) patients remain elusive. In the present study, we assessed the prognostic roles and molecular function of 20 individual members of the S100 family in OC patients using GEPIA, Kaplan-Meier plotter, SurvExpress, GeneMANIA and Funrich database. Our results indicated that the mRNA expression levels of S100A1, S100A2, S100A4, S100A5, S100A11, S100A14, and S100A16 were significantly upregulated in patients with OC, and high mRNA expression of S100A1, S100A3, S100A5, S100A6, and S100A13 were significantly correlated with better overall survival, while increased S100A2, S100A7A, S100A10, and S100A11 mRNA expressions were associated with worse prognosis in OC patients. In stratified analysis, the trends of high expression of individual S100 members were nearly the same in different pathological grade, clinical stage, TP53 mutation status, and treatment. More importantly, S100 family signatures may be useful potential prognostic markers for OC. These findings suggest that S100 family plays a vital role in prognostic value and could potentially be an S100-targeted inhibitors for OC patients.

Indexed as

Carcinoma, Ovarian EpithelialDatabases, GeneticFemaleGenetic Predisposition to DiseaseHumansMutationNeoplasm GradingNeoplasm StagingPrognosisRNA, MessengerS100 ProteinsSurvival AnalysisRNA, MessengerS100 Proteins

Identifiers

PMID33217795
PMCPMC7676574
OpenAlexW3103800390

What OpenQuestion holds

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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.