Evidence map›Paper›PMID 39985635›Full record

ArticleDiscover oncology2025

Prognostic implications of ERLncRNAs in ccRCC: a novel risk score model and its association with tumor mutation burden and immune microenvironment.

Kunlun Feng, Jingxiang Li, Jianye Li, Zhichao Li, Yahui Li

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 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

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

1 citing paper in PubMed.

  1. 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

5 authors.

Kunlun Feng *Shandong University of Traditional Chinese Medicine, Jinan, 250013, Shandong, China.
Jingxiang Li *The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Jianye Li *The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China.
Zhichao LiThe Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China. lizhichaosd@126.com.
Yahui LiThe Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, Shandong, China. littlemole2000@163.com.

Funding

Natural Science Foundation of Shandong Province ZR2022QH105Shandong Provincial Medical and Health Science and Technology Project 202304071619
6 · The paper itself

Abstract

INTRODUCTION/

backgroundThe specific role of efferocytosis-related long noncoding RNAs (ERLncRNAs) in Clear Cell Renal Cell Carcinoma (ccRCC) has not been thoroughly examined. This study aims to identify and validate a signature of ERLncRNAs for prognostic prediction and characterization of the immune landscape in individuals with ccRCC. MATERIALS AND

methodsAnalysis of ccRCC samples was conducted by utilizing clinical and RNA sequencing information obtained from The Cancer Genome Atlas (TCGA). Pearson correlation analysis was utilized to identify lncRNAs associated with efferocytosis, which was then used to create a new prognostic model through univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and stepwise multivariate Cox analysis. In order to investigate the biological significance, we performed a functional enrichment analysis to assess how well the model predicts outcomes. Differences in the immune landscape were observed through a comparison of immune cell infiltration, tumor mutational burden (TMB), and tumor microenvironment (TME) characteristics. Following this, drug sensitivity analysis was conducted.

resultsThis led to the identification of a unique signature consisting of seven ERLncRNAs (LINC01615, RUNX3-AS1, FOXD2-AS1, AC002070.1, LINC02747, LINC00944, and AC092296.1). Model performance was measured by Kaplan-Meier curves and receiver operating characteristic (ROC) curves. The nomogram and C-index provided additional validation of the strong correlation between the risk signature and clinical decision-making.

conclusionOn the whole, our innovative signature exhibits potential for prognostic prediction and assessment of immunotherapeutic response in patients with ccRCC.

Indexed as

ccRCCEfferocytosisImmunityLncRNAPrognosticTumor mutation burden

Identifiers

PMID39985635
PMCPMC11846825

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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.