Evidence map›Paper›PMID 39385288›Full record

ArticleJournal of ovarian research2024

Comprehensive in silico analysis of prognostic and immune infiltrates for FGFs in human ovarian cancer.

Yu Wang, Haiyue Zhang, Yuanyuan Zhan, Zhuoran Li, Sujing Li, Shubin Guo

Abstract read
In one paragraph

Article in Journal of ovarian research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. 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.

Yu Wang *Emergency Medicine Clinical Research Center, Beijing Chao-yang Hospital, Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Capital Medical University, Beijing, 100020, P.R. China.
Haiyue Zhang *Thrombosis research center, Beijing Jishuitan hospital, Capital Medical University, Beijing, China, Xicheng District, Beijing 100035, China.
Yuanyuan Zhan *Department of Endocrinology, Beijing Chao-yang Hospital, Capital Medical University, Beijing, 100020, P.R. China.
Zhuoran LiEmergency Medicine Clinical Research Center, Beijing Chao-yang Hospital, Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Capital Medical University, Beijing, 100020, P.R. China.
Sujing LiDepartment of Plastic Surgery, Zhengzhou First People's Hospital, Zhengzhou, China.
Shubin GuoEmergency Medicine Clinical Research Center, Beijing Chao-yang Hospital, Beijing Key Laboratory of Cardiopulmonary Cerebral Resuscitation, Capital Medical University, Beijing, 100020, P.R. China. Shubinguo@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFibroblast growth factors (FGFs) are cell signaling proteins that perform multiple biological processes in many biological processes (cell development, repair, and metabolism). The dynamics of tumor cells, such as angiogenesis, transformation, and proliferation, have a significant impact on neoplasia and are modulated by FGFs. FGFs' expression and prognostic significance in ovarian cancer (OC), however, remain unclear.

methodsThrough a series of in silico analysis, we investigated the transcriptional, survival data, genetic variation, gene-gene interaction network, ferroptosis-related genes, and DNA methylation of FGFs in OC patients.

resultsWe discovered that while FGF18 expression levels were higher in OC tissues than in normal OC tissues, FGF2/7/10/17/22 expression levels were lower in the former, and that FGF1/19 expression was related to the tumor stage in OC patients. According to the survival analysis, the clinical prognosis of individuals with OC was associated with the aberrant expression of FGFs. The function of FGFs and their neighboring genes was mainly connected to the cellular response to FGF stimulus. There was a negative correlation between FGF expression and various immune cell infiltration.

conclusionsThis study clarifies the relationship between FGFs and OC, which might provide new insights into the choice of prognostic biomarkers of OC patients.

Indexed as

Fibroblast Growth FactorsOvarian NeoplasmsComputer SimulationDNA MethylationFemaleGene Expression Regulation, NeoplasticHumansPrognosisFibroblast Growth FactorsBioinformatics analysisFibroblast growth factorsOvarian cancerPrognostic valueTumor microenvironment

Identifiers

PMID39385288
PMCPMC11465590

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