Evidence map›Paper›PMID 33628782›Full record

ArticleBioMed research international2021

Identification of a Two-m6A RNA Methylation Regulator Risk Signature as an Independent Prognostic Biomarker in Papillary Renal Cell Carcinoma by Bioinformatic Analysis.

Feilong Yang, Guojiang Zhao, Liyuan Ge, Yimeng Song, Kai Hong, Hongxian Zhang, Cheng Liu, Peng Hong, Lulin Ma

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Observational
  2. Review
  3. Review
  4. Essential mJournal of oncology · 2022
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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

9 authors at 1 institution in 1 country.

Feilong YangDepartment of Urology, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0001-5939-4110
Guojiang ZhaoDepartment of Urology, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0002-7297-7377
Liyuan GeDepartment of Urology, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0002-5158-0311
Yimeng SongDepartment of Urology, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0003-1119-3154
Kai HongDepartment of Urology, Peking University Third Hospital, Beijing, China.
Hongxian ZhangDepartment of Urology, Peking University Third Hospital, Beijing, China.
Cheng LiuDepartment of Urology, Peking University Third Hospital, Beijing, China.
Peng HongDepartment of Urology, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0002-3028-8872
Lulin MaDepartment of Urology, Peking University Third Hospital, Beijing, China.ORCID https://orcid.org/0000-0003-2141-9348
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

N6-Methyladenosine (m6A), the most common form of mRNA modification, is dynamically regulated by the m6A RNA methylation regulators, which play an important role in regulating the gene expression and phenotype in both health and disease. However, the role of m6A in papillary renal cell carcinoma (pRCC) is unknown. The purpose of this work is to investigate the prognostic value of m6A RNA methylation regulators in pRCC; thus, we can build a risk score model based on m6A RNA methylation regulators as a risk signature for predicting the prognosis of pRCC. Here, we investigated the expression and corresponding clinical data by bioinformatic analysis based on 289 pRCC tissues and 32 normal kidney tissues obtained from TCGA database. As a result, we identified the landscape of m6A RNA methylation regulators in pRCC. We grouped all pRCC patients into two clusters by consensus clustering to m6A RNA methylation regulators, but we found that the clusters were not correlated to the prognosis and clinicopathological features of pRCC. Therefore, we additionally built a two-m6A RNA methylation regulator risk score model as a risk signature by the univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression. The risk signature was constructed as follows: 0.031HNRNPC + 0.199KIAA1429. It revealed that the risk score was associated with the clinicopathological features such as pT status and pN status of pRCC. More importantly, the risk score was an independent prognostic marker for pRCC patients. Thus, m6A RNA methylation regulators contributed to the malignant progression of pRCC influencing its prognosis.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsAdenosineBiomarkers, TumorCluster AnalysisComputational BiologyFemaleHeterogeneous-Nuclear Ribonucleoprotein Group CHumansKidneyMaleMethylationMethyltransferasesPrognosisRNA-Binding ProteinsTranscriptomeAdenosineBiomarkers, TumorHeterogeneous-Nuclear Ribonucleoprotein Group CHNRNPC protein, humanMethyltransferasesN-methyladenosineRNA-Binding ProteinsVIRMA protein, human

Identifiers

PMID33628782
PMCPMC7884118
OpenAlexW3128042743

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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.