Evidence map›Paper›PMID 40568194›Full record

ArticleFrontiers in medicine2025

Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysis.

Weiyuan Li, Duo Han, Chunxiao Cao, Yuning Xie, Jingxia Shen

Abstract read
In one paragraph

Article in Frontiers in medicine, 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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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

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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

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.

Weiyuan LiNorth China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, China.
Duo HanNorth China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, China.
Chunxiao CaoZunhua People's Hospital, Tangshan, Hebei, China.
Yuning XieSchool of Public Health, North China University of Science and Technology, Tangshan, Hebei, China.
Jingxia ShenNorth China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to mine the TCGA database for differentially expressed genes in recurrent lung cancer tissues, determine the relationship between these recurrent genes and lung cancer at the single-cell level, and identify potential targets for lung cancer treatment. Methods: Data for lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) were obtained from the TCGA database and grouped based on clinical recurrence information. Single-cell data from GSE131907 were downloaded from the GEO database. R was utilized to screen for differentially expressed genes (DEGs), followed by weighted gene co-expression network analysis (WGCNA) of these DEGs. Additionally, the GSEA database was employed to visualize differential pathways and identify key genes. The relationship between the expression of these key genes and lung cancer recurrence was validated using the GSE131907 single-cell dataset. Results: A total of 2,239 differentially expressed genes were identified in the LUAD dataset, while 3,404 differentially expressed genes were found in the LUSC dataset. WGCNA revealed that the lapis lazuli module gene set was associated with recurrence. Validation at the single-cell level indicated that the FOXI1, FOXB1, and KCNA7 genes were linked to lung cancer progression. Conclusion: The differentially expressed genes primarily influence NSCLC recurrence through involvement in biological processes related to metabolism and hormone secretion pathways. Notably, the KCNA7 and FOX gene families were identified as critical for NSCLC recurrence. This study highlights specific genes within proliferation and cell cycle pathways as key therapeutic targets for managing NSCLC recurrence.

Indexed as

foxFOX NSCLCKCNA7NSCLCSingle-Cell AnalysisTCGAWGCNA analysis

Identifiers

PMID40568194
PMCPMC12187672

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