Evidence map›Paper›PMID 35251475›Full record

ArticleOxidative medicine and cellular longevity2022

Significance of a PTEN Mutational Status-Associated Gene Signature in the Progression and Prognosis of Endometrial Carcinoma.

Ying Wu, Jun Wang, Lina Ge, Qing Hu

Open access · hybridAbstract read
In one paragraph

Article in Oxidative medicine and cellular longevity, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 44% of its field
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 6 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Ying WuDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Jun WangDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Lina GeDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.
Qing HuDepartment of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.ORCID https://orcid.org/0000-0002-6681-3034
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPTEN mutations have been reported to be involved in the development and prognosis of endometrial carcinoma (EC). However, a prognostic gene signature associated with PTEN mutational status has not yet been developed. In this study, we generated a PTEN mutation-associated prognostic gene signature for EC.

methodsWe obtained the single-nucleotide variation and transcriptomic profiling data from The Cancer Genome Atlas database as training data and implemented the least absolute shrinkage and selection operator (LASSO) Cox regression algorithm to establish a PTEN mutation-associated prognostic gene signature. The overall survival rates of the high-risk and low-risk groups were determined with the Kaplan-Meier (K-M) method, and the accuracy of risk score prediction was tested by using the receiver operating characteristic (ROC) curve.

resultsThe K-M curves revealed that the EC patients with PTEN mutations augured favorable survival outcomes. Differential expression analysis between the EC patients with PTEN mutation and wild-type PTEN identified 224 differentially expressed genes (DEGs). Eighty-four DEGs that manifested prognostic value were fitted into the LASSO-Cox analysis, and a PTEN gene signature with seven mutation-associated prognostic genes that showed robust prognostic ability was constructed; this signature was then successfully validated in the other two datasets from the cBioPortal database as well as with 60 clinical specimens. Furthermore, the PTEN mutation-associated prognostic gene signature proved to be an independent prognostic predictor of EC. Remarkably, the EC patients in the high-risk group were characterized by higher tumor stages and grades as well as lower tumor mutation burden with respect to EC, with a poor survival outcome. Collectively, the PTEN mutation-associated prognostic gene signature that we developed could now be used as a favorable prognostic biomarker for EC.

conclusionIn summary, we developed and validated a prognostic predictor for EC associated with PTEN mutational status that may be used as a favorable prognostic biomarker and therapeutic target for EC.

Indexed as

Disease ProgressionGene Expression Regulation, NeoplasticMutationAdultBiomarkers, TumorEndometrial NeoplasmsFemaleGene Expression ProfilingHumansKaplan-Meier EstimateMiddle AgedNomogramsPolymorphism, Single NucleotidePrognosisPTEN PhosphohydrolaseROC CurveBiomarkers, TumorPTEN PhosphohydrolasePTEN protein, human

Identifiers

PMID35251475
PMCPMC8890874
OpenAlexW4213411949

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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.