Evidence map›Paper›PMID 41082518›Full record

ArticlePloS one2025

Developing and experimentally validating a glucocorticoid signaling-related gene signature to evaluate the prognosis and immunotherapeutic response in kidney renal clear cell carcinoma.

Yu Zhang, Chen Chen, Tianhang Zhu, Wei Luo, Ranran Zhou, Wanlong Tan

Abstract read
In one paragraph

Article in PloS one, 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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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.

Yu ZhangDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Chen ChenDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Tianhang ZhuDepartment of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China.
Wei LuoDepartment of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0009-0004-0640-7941
Ranran ZhouDepartment of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong, China.
Wanlong TanDepartment of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0003-4265-4494

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glucocorticoids play a pivotal role in tumorigenesis and cancer progression. However, the prognostic significance of glucocorticoid signaling-related genes remains poorly understood, particularly in kidney renal clear cell carcinoma (KIRC). Collected samples indicated KIRC patients exhibited elevated serum glucocorticoid levels compared to healthy donors (P < 0.05). Glucocorticoid signaling-related genes were curated from the MSigDB database. The TCGA-KIRC cohort was utilized for training, while 7 independent public KIRC cohorts and local samples were employed for validation. Through LASSO and random forest analyses, ACADM, ANGPTL4, and NFKB2 were identified and subsequently incorporated into a multivariate Cox regression model. This gene signature emerged as a robust prognostic indicator across multiple cohorts (pooled hazard ratio [HR] = 2.73, 95% confidence interval [CI] = 2.05-3.65). In local samples, KIRC tissues exhibited increased infiltration of NFKB2+ cells and decreased levels of ACADM+ and ANGPTL4+ cells (all P < 0.05). Meta-analyses and spatial transcriptomics revealed a positive association between the signature and CD8+ T cell infiltration. Furthermore, the signature was associated with T cell exhaustion levels and could predict immunotherapeutic responses in both computational simulations and real-world clinical settings (all P < 0.05). In vivo experiments showed that NFKB2 knockdown inhibited tumor growth and the expansion of CD8+PDCD1+ T cells, effects that were reversible with corticosterone treatment (all P < 0.05). Collectively, a glucocorticoid signaling-related gene signature was developed and rigorously validated as a predictive tool for prognosis and immunotherapeutic response in KIRC, offering valuable insights for guiding personalized treatment strategies.

Indexed as

Carcinoma, Renal CellGlucocorticoidsKidney NeoplasmsAngiopoietin-Like Protein 4AnimalsCell Line, TumorFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansImmunotherapyMaleMicePrognosisSignal TransductionTranscriptomeAngiopoietin-Like Protein 4Glucocorticoids

Identifiers

PMID41082518
PMCPMC12517536

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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.