Evidence map›Paper›PMID 41822495›Full record

ArticleFrontiers in immunology2026

A 12-gene immune signature predicts prognosis and identifies KRT6B as a therapeutic target in lung adenocarcinoma.

Weiwei Gu, Yahua Wu, Rongqi Jiang, Mingliang Shi, Jiude Qi, Jinhuo Lai

Abstract read
In one paragraph

Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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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.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors.

Weiwei Gu *Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
Yahua Wu *Department of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
Rongqi JiangDepartment of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
Mingliang ShiDepartment of Oncology, People's Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
Jiude QiDepartment of Oncology, People's Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
Jinhuo LaiDepartment of Medical Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Lung adenocarcinoma (LUAD) exhibits high mortality and heterogeneity. While immune-related signatures show prognostic potential, robust models validated through both computational screening and experimental methods are lacking. Methods: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) database and three Gene Expression Omnibus (GEO) cohorts (GSE3141, GSE30219, and GSE50081) were analyzed. A 12-gene immune-related prognostic signature was constructed using LASSO Cox regression. The model was subsequently validated using three independent external cohorts. Its prognostic performance was comprehensively assessed using time-dependent receiver operating characteristic (ROC) curves. Functional enrichment analyses (GO, KEGG, and GSEA), tumor microenvironment (TME) profiling (via CIBERSORT and ESTIMATE algorithms), and drug sensitivity analyses were conducted. Protein-protein interaction (PPI) network analysis identified KRT6B as a central hub gene. KRT6B expression and its functional role were further validated through tissue microarray immunohistochemistry (IHC), as well as Results: We developed a prognostic model for LUAD based on 12 immune-related genes and derived a risk score via LASSO regression. High-risk patients exhibited significantly worse overall survival compared to low-risk patients in both the training set (TCGA) and the three independent validation cohorts (GSE3141, GSE30219, and GSE50081) (all P < 0.05). Time-dependent ROC analysis confirmed the model's predictive accuracy for 1-, 2-, and 3-year survival (AUC: 0.624-0.788). A nomogram incorporating the risk score and key clinical indicators further enhanced prognostic performance (AUC: 0.753 to 0.763). PPI network analysis pinpointed KRT6B as a core hub gene within the signature. Subsequent experimental validation confirmed the overexpression of KRT6B in LUAD tumor cells and demonstrated its tumor-promoting functions both Conclusion: We established and validated an immune-related gene signature for prognostic prediction and identified KRT6B as a promising prognostic biomarker and potential therapeutic target in LUAD.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorKeratin-6Lung NeoplasmsTranscriptomeAnimalsFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMicePrognosisProtein Interaction MapsROC CurveTumor MicroenvironmentBiomarkers, TumorKeratin-6biomarkerimmune-related gene signatureKRT6blung adenocarcinomaprognostic model

Identifiers

PMID41822495
PMCPMC12975743

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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.