Evidence map›Paper›PMID 30306731›Full record

ArticleCancer medicine2018

Identification of a six-gene signature with prognostic value for patients with endometrial carcinoma.

Yizi Wang, Fang Ren, Peng Chen, Shuang Liu, Zixuan Song, Xiaoxin Ma

Open access · goldAbstract read
In one paragraph

Article in Cancer medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
11.1field-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

30 citing papers in PubMed, 64 citations in OpenAlex.

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  14. Alterations in the CaExploration of targeted anti-tumor therapy · 2021
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  20. Novel miRNA markers for the diagnosis and prognosis of endometrial cancer.Journal of cellular and molecular medicine · 2020
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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 1 institution in 1 country.

Yizi WangDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Fang RenDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Peng ChenDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Shuang LiuDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Zixuan SongDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Xiaoxin MaDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.ORCID 0000-0003-0271-8035
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Uterine corpus endometrial carcinoma (UCEC) is frequently diagnosed among women worldwide. However, there are different prognostic outcomes because of heterogeneity. Thus, the aim of the current study was to identify a gene signature that can predict the prognosis of patients with UCEC. UCEC gene expression profiles were first downloaded from the The Cancer Genome Atlas (TCGA) database. After data processing and forward screening, 11 390 key genes were selected. The UCEC samples were randomly divided into training and testing sets. In total, 996 genes with prognostic value were then examined by univariate Cox survival analysis with a P-value <0.01 in the training set. Next, using robust likelihood-based survival modeling, we developed a six-gene signature (CTSW, PCSK4, LRRC8D, TNFRSF18, IHH, and CDKN2A) with a prognostic function in UCEC. A prognostic risk score system was developed by multivariate Cox proportional hazard regression based on this six-gene signature. According to the Kaplan-Meier curve, patients in the high-risk group had significantly poorer overall survival (OS) outcomes than those in the low-risk group (log-rank test P-value <0.0001). This signature was further validated in the testing dataset and the entire TCGA dataset. In conclusion, we conducted an integrated study to develop a six-gene signature for the prognostic prediction of patients with UCEC. Our findings may provide novel biomarkers for prognosis and have significant implications in the understanding of therapeutic targets for UCEC.

Indexed as

Biomarkers, TumorCathepsin WCyclin-Dependent Kinase Inhibitor p16Databases, GeneticEndometrial NeoplasmsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGlucocorticoid-Induced TNFR-Related ProteinHedgehog ProteinsHumansMembrane ProteinsPrognosisProprotein ConvertasesRandom AllocationSubtilisinsBiomarkers, TumorCathepsin WCDKN2A protein, humanCTSW protein, humanCyclin-Dependent Kinase Inhibitor p16Glucocorticoid-Induced TNFR-Related ProteinHedgehog ProteinsIHH protein, humanMembrane ProteinsPCSK4 protein, humanProprotein ConvertasesSubtilisinsTNFRSF18 protein, humangene signatureprognosisrbsurvThe Cancer Genome Atlasuterine corpus endometrial carcinoma

Identifiers

PMID30306731
PMCPMC6247034
OpenAlexW2897901396

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.