Evidence map›Paper›PMID 32694939›Full record

ArticleCancer cell international2020

Identification of a three-miRNA signature as a novel prognostic model for papillary renal cell carcinoma.

Ge Li, Haifan Yang, Yong Cheng, Xin Zhao, Xu Li, Rui Jiang

Abstract read
In one paragraph

Article in Cancer cell international, 2020. 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

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. A multi-omics prognostic model and functional validation ofTranslational andrology and urology · 2026
    Article
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4 · The record

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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.

Ge LiDepartment of Urology, The Affiliated Hospital of Southwest Medical University, No. 25 Taiping Road, Jiangyang District, Luzhou, 646000 China.
Haifan YangDepartment of Urology, The Affiliated Hospital of Southwest Medical University, No. 25 Taiping Road, Jiangyang District, Luzhou, 646000 China.
Yong ChengDepartment of Urology, The Affiliated Hospital of Southwest Medical University, No. 25 Taiping Road, Jiangyang District, Luzhou, 646000 China.
Xin ZhaoDepartment of Urology, The Affiliated Hospital of Southwest Medical University, No. 25 Taiping Road, Jiangyang District, Luzhou, 646000 China.
Xu LiDepartment of Urology, The Affiliated Hospital of Southwest Medical University, No. 25 Taiping Road, Jiangyang District, Luzhou, 646000 China.
Rui JiangDepartment of Urology, The Affiliated Hospital of Southwest Medical University, No. 25 Taiping Road, Jiangyang District, Luzhou, 646000 China.ORCID 0000-0002-1970-2809

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPapillary renal cell carcinoma (pRCC) accounting for near 20% of renal cell carcinoma is the second most common histological subtype. MiRNAs have been demonstrated to played significant roles on predicting prognosis of patients with tumors. An appropriate and comprehensive miRNAs analysis based on a great deal of pRCC samples from The Cancer Genome Atlas (TCGA) will provide perspective in this field.

methodsWe integrated the expression of mRNAs, miRNAs and the relevant clinical data of 321 pRCC patients recorded in the TCGA database. The survival-related differential expressed miRNAs (sDEmiRs) were estimated by COX regression analysis. The high-risk group and the low-risk group were separated by the median risk score of the risk score model (RSM) based on three screened sDEmiRs. The target genes, underlying molecular mechanisms of these sDEmiRs were explored by computational biology. The expression levels of the three sDEmiRs and their correlations with clinicopathological parameters were further validated by qPCR.

resultsBased on univariate COX analysis (

conclusionThe study developed a RSM based on the identified sDEmiRs with significant prognosis prediction values for pRCC patients. The results pave the avenue for establishing and optimizing a reliable and referable risk assessing model and provide novel insight into the researches of biomarkers and clinical treatment strategies.

Indexed as

miRNAsPapillary renal cell carcinomaPrognosisRisk score

Identifiers

PMID32694939
PMCPMC7367267

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