Evidence map›Paper›PMID 32735556›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2020

Identification of Prognostic Biomarkers Associated with Cancer Stem Cell Features in Prostate Adenocarcinoma.

Dehua Zhang, Muchun Zhang, Qifu Zhang, Zhiyi Zhao, Yong Nie

Abstract read
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Dehua ZhangDepartment of Urology, Yiling Hospital of Yichang, Yichang, Hubei, China (mainland).
Muchun ZhangDepartment of Urology, Bethune First Hospital of Jilin University, Changchun, Jilin, China (mainland).
Qifu ZhangDepartment of Urology, Jilin Provincial Cancer Hospital, Changchun, Jilin, China (mainland).
Zhiyi ZhaoDepartment of Urology, Jilin Provincial Cancer Hospital, Changchun, Jilin, China (mainland).
Yong NieDepartment of Urology, Yiling Hospital of Yichang, Yichang, Hubei, China (mainland).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND Prostate adenocarcinoma (PRAD) is the second most common malignancy in males and the fifth leading cause of cancer mortality. Cancer stem cells (CSCs) play an important role in the occurrence and development of PRAD, however, the prognostic biomarkers associated with CSC features have not been identified in PRAD. MATERIAL AND METHODS In order to identify the prognostic stemness-related genes (SRGs) of PRAD, the RNA sequencing data of patients with PRAD were retrieved from The Cancer Genome Atlas (TCGA) databases. The mRNA expression-based stemness index (mRNAsi) and the differential expressed genes (DEGs) were evaluated and identified. The associations between the mRNAsi and tumorigenesis, overall survival (OS), prostate-specific antigen (PSA) value, and Gleason score were also established by nonparametric test and Kaplan-Meier survival analysis. The SRGs were identified as the overlapped DEGs of PRAD-associated DEGs and the mRNAsi-associated DEGs. Based on the prognostic SRGs, the predict model was constructed. Its accuracy was tested by the area under the curve (AUC) of the receiver operator characteristic (ROC) curve and the risk score. RESULTS A total of 6005 PRAD-associated DEGs and 2462 mRNAsi-associated DEGs were identified. The mRNAsi was significantly upregulated in PRAD and associated with the PSA value and Gleason score. A total of 1631 SRGs were identified, with 36 prognostic SRGs screened by the univariate Cox analysis. Based on the prognostic SRGs, the predict model was constructed with the AUC of 0.986. Moreover, the risk score of the model was proved to be an independent prognostic factor, indicating its significant applicability. CONCLUSIONS Our data demonstrate the mRNAsi as a reliable index for the tumorigenesis, PSA value, and Gleason score of PRAD. Additionally, this study provides a well-applied model for predicting the OS for patients with PRAD based on prognostic SRGs.

Indexed as

Gene Expression Regulation, NeoplasticAdenocarcinomaAdultAgedArea Under CurveAtlases as TopicBiomarkers, TumorCarcinogenesisDatabases, GeneticDNA MethylationGene Expression ProfilingGene Regulatory NetworksHumansMaleMiddle AgedNeoplasm GradingBiomarkers, TumorProstate-Specific Antigen

Identifiers

PMID32735556
PMCPMC7418486

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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.