Evidence map›Paper›PMID 34526089›Full record

ArticleJournal of ovarian research2021

Systematic analysis of the relationship between ovarian cancer prognosis and alternative splicing.

Di Zhang, Dan Zou, Yue Deng, Lihua Yang

Abstract read
In one paragraph

Article in Journal of ovarian research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Alternative splicing in ovarian cancer.Cell communication and signaling : CCS · 2024
    Review
  4. Article
  5. 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

4 authors.

Di ZhangDepartment of Gynaecology, the 2nd Afliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Dan ZouDepartment of Gynaecology, the 2nd Afliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Yue DengDepartment of Gynaecology, the 2nd Afliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Lihua YangDepartment of Gynaecology, the 2nd Afliated Hospital of Kunming Medical University, Kunming, Yunnan, China. 13759481789@163.com.ORCID http://orcid.org/0000-0002-6293-4816

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOvarian cancer(OC) is the gynecological tumor with the highest mortality rate, effective biomarkers are of great significance in improving its prognosis. In recent years, there have been many studies on alternative splicing (AS) events, and the role of AS events in tumor has become a focus of attention.

methodsData were downloaded from the TCGA database and Univariate Cox regression analysis was performed to determine AS events associated with OC prognosis.Eight prognostic models of OC were constructed in R package, and the accuracy of the models were evaluated by the time-dependent receiver operating characteristic (ROC) curves.Eight types of survival curves were drawn to evaluate the differences between the high and low risk groups.Independent prognostic factors of OC were analyzed by single factor independent analysis and multi-factor independent prognostic analysis.Again, Univariate Cox regression analysis was used to analyze the relationship between splicing factors(SF) and AS events, and Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis were performed on OS-related SFs to understand the pathways.

resultsUnivariate Cox regression analysis showed that among the 15,278 genes, there were 31,286 overall survival (OS) related AS events, among which 1524 AS events were significantly correlated with OS. The area under the time-dependent receiver operating characteristic curve (AUC) of AT and ME were the largest and the RI was the smallest,which were 0.757 and 0.68 respectively. The constructed models have good value for the prognosis assessment of OC patients. Among the eight survival curves, AP was the most significant difference between the high and low risk groups, with a P value of 1.61e - 1.The results of single factor independent analysis and multi-factor independent prognostic analysis showed that risk score calculated by the model and age could be used as independent risk factors.According to univariate COX regression analysis,109 SFs were correlated with AS events and adjusted in two ways: positive and negative.

conclusionsSFs and AS events can directly or indirectly affect the prognosis of OC patients. It is very important to find effective prognostic markers to improve the survival rate of OC.

Indexed as

Alternative SplicingDatabases, GeneticFemaleHumansOvarian NeoplasmsPrognosisProportional Hazards ModelsRNA Splicing FactorsSurvival AnalysisRNA Splicing FactorsAlternative splicingOvarian cancerPrognosisSplicing factorsSurvival model

Identifiers

PMID34526089
PMCPMC8442315

What Socratic 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 Socratic graph.