Evidence map›Paper›PMID 33109151›Full record

ArticleBMC cancer2020

High expression of fibroblast activation protein (FAP) predicts poor outcome in high-grade serous ovarian cancer.

Min Li, Xue Cheng, Rong Rong, Yan Gao, Xiuwu Tang, Youguo Chen

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 8% 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

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.

  1. Pooled it
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  17. Translational assessment of a DATA-functionalized FAP inhibitor with facileEuropean journal of nuclear medicine and molecular imaging · 2023
    Article
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  19. Efficiency of Promoters of Human GenesInternational journal of molecular sciences · 2023
    Article
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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

6 authors at 2 institutions in 1 country.

Min LiDepartment of Gynecology & Obstetrics, the First Affiliated Hospital of Soochow University, No.188, Shizi Street, Suzhou, Jiangsu Province, 215006, China.
Xue ChengDepartment of Pathology, Obstetrics and Gynecology Hospital Affiliated to Nanjing Medical University, Nanjing, 210004, China.
Rong RongDepartment of Pathology, the First Affiliated Hospital with Nanjing Medical University, Nanjing, 210029, China.
Yan GaoInstitute of Suzhou Biobank, Suzhou Center for Disease Prevention and Control, Suzhou, 215004, China.
Xiuwu TangDepartment of Gynecology & Obstetrics, the First Affiliated Hospital of Soochow University, No.188, Shizi Street, Suzhou, Jiangsu Province, 215006, China. tangxiuwu1982@yeah.net.ORCID http://orcid.org/0000-0002-3202-7377
Youguo ChenDepartment of Gynecology & Obstetrics, the First Affiliated Hospital of Soochow University, No.188, Shizi Street, Suzhou, Jiangsu Province, 215006, China. chenyouguo@suda.edu.cn.
Soochow University · CNNanjing Medical University · CN

Funding

Suzhou industrial technology innovation projection 201900180051Suzhou industrial technology innovation projection SYS2019041
6 · The paper itself

Abstract

backgroundHigh-grade serous ovarian cancer (HGSOC) is a fatal form of ovarian cancer. Previous studies indicated some potential biomarkers for clinical evaluation of HGSOC prognosis. However, there is a lack of systematic analysis of different expression genes (DEGs) to screen and detect significant biomarkers of HGSOC.

methodsTCGA database was conducted to analyze relevant genes expression in HGSOC. Outcomes of candidate genes expression, including overall survival (OS) and progression-free survival (PFS), were calculated by Cox regression analysis for hazard rates (HR). Histopathological investigation of the identified genes was carried out in 151 Chinese HGSOC patients to validate gene expression in different stages of HGSOC.

resultsOf all 57,331 genes that were analyzed, FAP was identified as the only novel gene that significantly contributed to both OS and PFS of HGSOC. In addition, FAP had a consistent expression profile between carcinoma-paracarcinoma and early-advanced stages of HGSOC. Immunological tests in paraffin section also confirmed that up-regulation of FAP was present in advanced stage HGSOC patients. Prediction of FAP network association suggested that FN1 could be a potential downstream gene which further influenced HGSOC survival.

conclusionsHigh-level expression of FAP was associated with poor prognosis of HGSOC via FN1 pathway.

Indexed as

Up-RegulationCystadenocarcinoma, SerousDatabases, GeneticEndopeptidasesFemaleFibroblast Activation Protein AlphaFibronectinsGelatinasesGene Expression Regulation, NeoplasticHumansMembrane ProteinsNeoplasm StagingOvarian NeoplasmsPrognosisSerine EndopeptidasesSignal TransductionEndopeptidasesFibroblast Activation Protein AlphaFibronectinsFN1 protein, humanGelatinasesMembrane ProteinsSerine EndopeptidasesFibroblast activation protein (FAP)High-grade serous ovarian cancer (HGSOC)SurvivalThe Cancer genome atlas program (TCGA)

Identifiers

PMID33109151
PMCPMC7590670
OpenAlexW3096784863

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.