Evidence map›Paper›PMID 41562084›Full record

ArticleFrontiers in immunology2025

Identification of immune-related prognostic biomarkers in lung squamous cell carcinoma microenvironment.

Zhihao Wang, Zhengsheng Wu

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Zhihao WangDepartment of Pathology, School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, China.
Zhengsheng WuDepartment of Pathology, School of Basic Medical Sciences, Anhui Medical University, Hefei, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lung squamous cell carcinoma (LUSC) is a leading cause of cancer-related mortality. Although immunotherapy has recently demonstrated clinical benefits, the biological roles of immune-related genes (IRGs) in LUSC remain insufficiently understood. Methods: In this study, transcriptomic and clinical data from 493 LUSC patients were obtained from The Cancer Genome Atlas (TCGA). IRGs were identified through weighted gene co-expression network analysis, followed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression to screen for prognostic genes and establish a risk prediction model. The model's predictive performance was validated, and the immune landscape associated with distinct risk subgroups was systematically characterized. Expression patterns and clinical significance of the signature genes were further investigated using bioinformatics analysis, quantitative real-time PCR, Western blotting, and immunohistochemistry. Results: A total of 55 differentially expressed IRGs were identified, among which 8 genes ( Conclusion: This study establishes a novel IRGs-based prognostic signature with potential utility for risk stratification and individualized immunotherapeutic strategies in LUSC. Furthermore, it also provides valuable insights into the role of

Indexed as

Biomarkers, TumorCarcinoma, Squamous CellLung NeoplasmsTumor MicroenvironmentComputational BiologyFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMiddle AgedPrognosisTranscriptomeBiomarkers, Tumorimmune-related geneslung squamous cell carcinomaNR1D2prognosistumor microenvironment

Identifiers

PMID41562084
PMCPMC12813068

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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.