ArticleScientific reports2018
Transcriptomic and functional network features of lung squamous cell carcinoma through integrative analysis of GEO and TCGA data.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers.
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87 citing papers in PubMed.
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- Bioinformatics-Based Discovery of Therapeutic Targets in Cadmium-Induced Lung Adenocarcinoma: The Role of Oxyresveratrol.Biological trace element research · 2026Article
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- Lipidomics reveals effect of EHHADH in lung squamous cell.Cell biology and toxicology · 2025Article
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- [Isoliquiritigenin Modulates the Effect of LINC01503 on Lung Squamous Carcinoma Cells].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2024Article
- p27 specifically decreases in squamous carcinoma, and mediates NNK-induced transformation of human bronchial epithelial cells.Journal of cellular and molecular medicine · 2024Article
- STAT1 aggravates kidney injury by NOD-like receptor (NLRP3) signaling in MRL-lpr mice.Journal of molecular histology · 2024Article
- Development of a disulfidptosis-related lncRNA prognostic signature for enhanced prognostic assessment and therapeutic strategies in lung squamous cell carcinoma.Scientific reports · 2024Article
- Integrative analysis of aging-related genes reveals CEBPA as a novel therapeutic target in non-small cell lung cancer.Cancer cell international · 2024Article
- Integrated analysis identified the role of three family members of ARHGAP in pancreatic adenocarcinoma.Scientific reports · 2024Article
- Identification of GMFG as a novel biomarker in IgA nephropathy based on comprehensive bioinformatics analysis.Heliyon · 2024Article
27 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
Lung squamous cell carcinoma (LUSC) is associated with poor clinical prognosis and lacks available targeted therapy. Novel molecules are urgently required for the diagnosis and prognosis of LUSC. Here, we conducted our data mining analysis for LUSC by integrating the differentially expressed genes acquired from Gene Expression Omnibus (GEO) database by comparing tumor tissues versus normal tissues (GSE8569, GSE21933, GSE33479, GSE33532, GSE40275, GSE62113, GSE74706) into The Cancer Genome Atlas (TCGA) database which includes 502 tumors and 49 adjacent non-tumor lung tissues. We identified intersections of 129 genes (91 up-regulated and 38 down-regulated) between GEO data and TCGA data. Based on these genes, we conducted our downstream analysis including functional enrichment analysis, protein-protein interaction, competing endogenous RNA (ceRNA) network and survival analysis. This study may provide more insight into the transcriptomic and functional features of LUSC through integrative analysis of GEO and TCGA data and suggests therapeutic targets and biomarkers for LUSC.
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