Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysis
ObjectiveThis 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.MethodsData for lung ade...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Medicine |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2025.1549969/full |
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| author | Weiyuan Li Duo Han Chunxiao Cao Yuning Xie Jingxia Shen |
| author_facet | Weiyuan Li Duo Han Chunxiao Cao Yuning Xie Jingxia Shen |
| author_sort | Weiyuan Li |
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| description | ObjectiveThis 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.MethodsData 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.ResultsA 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.ConclusionThe 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. |
| format | Article |
| id | doaj-art-520d5dc5243f40dcaf089b09b664f06c |
| institution | Kabale University |
| issn | 2296-858X |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Medicine |
| spelling | doaj-art-520d5dc5243f40dcaf089b09b664f06c2025-08-20T03:46:42ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2025-06-011210.3389/fmed.2025.15499691549969Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysisWeiyuan Li0Duo Han1Chunxiao Cao2Yuning Xie3Jingxia Shen4North China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, ChinaNorth China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, ChinaZunhua People’s Hospital, Tangshan, Hebei, ChinaSchool of Public Health, North China University of Science and Technology, Tangshan, Hebei, ChinaNorth China University of Science and Technology Affiliated Hospital, Tangshan, Hebei, ChinaObjectiveThis 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.MethodsData 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.ResultsA 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.ConclusionThe 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.https://www.frontiersin.org/articles/10.3389/fmed.2025.1549969/fullNSCLCTCGAWGCNA analysisSingle-Cell AnalysisKCNA7FOX NSCLC |
| spellingShingle | Weiyuan Li Duo Han Chunxiao Cao Yuning Xie Jingxia Shen Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysis Frontiers in Medicine NSCLC TCGA WGCNA analysis Single-Cell Analysis KCNA7 FOX NSCLC |
| title | Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysis |
| title_full | Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysis |
| title_fullStr | Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysis |
| title_full_unstemmed | Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysis |
| title_short | Identifying key genes associated with recurrence in non-small cell lung cancer through TCGA and single-cell analysis |
| title_sort | identifying key genes associated with recurrence in non small cell lung cancer through tcga and single cell analysis |
| topic | NSCLC TCGA WGCNA analysis Single-Cell Analysis KCNA7 FOX NSCLC |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2025.1549969/full |
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