Evidence map›Paper›PMID 39987537›Full record

ArticleDiscover oncology2025

Identification and validation of an m5C-related lncRNA signature for predicting prognosis and immune response in clear cell renal cell carcinoma.

Shan Ao, Leqi Liang, Lei Peng, Riwei Yang, Zugen Chen, Tuo Deng

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. Article
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.

Shan Ao *Department of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Leqi Liang *Department of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Lei Peng *Department of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Riwei YangDepartment of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Zugen ChenDepartment of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
Tuo DengDepartment of Urology and Guangdong Key Laboratory of Urology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China. dengtuo@gzhmu.edu.cn.

Funding

Science and T echnology Planning Project of Guangzhou 2023A04J0577Science and T echnology Planning Project of Guangzhou No. 202102010194
6 · The paper itself

Abstract

This study investigated whether m5C-related Long non-coding RNAs (lncRNAs) can predict clear cell renal cell carcinoma (ccRCC) patient prognosis. Co-expression and Cox regression analyses identified 9 prognostic lncRNAs, which were closely associated with tumor immune characteristics and immune escape. The model also predicted the sensitivity of drugs, including Entinostat, SB216763, and Sapitinib. In vitro experiments showed that GNG12-AS1 inhibited ccRCC cell proliferation and migration by reducing the activity of the ERK/GSK-3β/β-catenin pathway. Overall, these findings suggest that the 9 m5C-related lncRNAs can accurately predict ccRCC patient prognosis, providing potential applications for clinical and immunotherapy approaches. GNG12-AS1 emerges as a promising prognostic biomarker for predicting survival outcomes in ccRCC, potentially influencing cell migration through the activation of the ERK/GSK-3β/β-catenin signaling pathway.

Indexed as

ccRCCGNG12-AS1lncRNAm5CPrognosis

Identifiers

PMID39987537
PMCPMC11847763

What OpenQuestion holds

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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.