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pmid:36247089
Exploring Potential Biomarkers, Ferroptosis Mechanisms, and Therapeutic Targets Associated with Cutaneous Squamous Cell Carcinoma via Integrated Transcriptomic Analysis.
Wenxing Su · Biao Huang · Qingyi Zhang · Wei Han · Lu An · Yi Guan · Jiang Ji · Daojiang Yu
Journal of healthcare engineering · 2022 doi:10.1155/2022/3524022
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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However, the unclear pathogenesis of cSCC limits the application of molecular targeted therapy.\nMethods: Three microarray datasets (GSE2503, GSE45164, and GSE66359) were downloaded from the Gene Expression Omnibus (GEO). After identifying the differentially expressed genes (DEGs) in tumor and nontumor tissues, five kinds of analyses, namely, functional annotation, protein-protein interaction (PPI) network, hub gene selection, TF-miRNA-mRNA regulatory network analysis, and ferroptosis mechanism, were performed.\nResults: A total of 146 DEGs were identified with significant differences, including 113 upregulated genes and 33 downregulated genes. The enriched functions and pathways of the DEGs included microtubule-based movement, ATP binding, cell cycle, P53 signaling pathway, oocyte meiosis, and PLK1 signaling events. Nine hub genes were identified (CDK1, AURKA, RRM2, CENPE, CCNB1, KIAA0101, ZWINT, TOP2A, and ASPM). Finally, RRM2, AURKA, and SAT1 were identified as significant ferroptosis-related genes in cSCC. The differential expression of these genes has been verified in two other independent datasets.\nConclusions: By integrated bioinformatic analysis, the hub genes identified in this study elucidated the molecular mechanism of the pathogenesis and progression of cSCC and are expected to become future biomarkers or therapeutic targets.", "claims": [{"id": "claim-method", "statement": "The DEGs between cSCC and noncancerous samples were screened using GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r), which is an online tool for differential analysis of the original dataset based on the LIMMA software package [16].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36247089", "locator": "sections[4] \"2.2. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE2503", "GSE45164", "GSE66359", "GSE53462", "GSE7553"], "resolved_accessions": ["GSE2503", "GSE45164", "GSE66359", "GSE53462", "GSE7553"], "statements": ["In this study, mRNA microarray datasets were downloaded from the Gene Expression Omnibus (https://www.ncbi.nlm.nih.gov/geo)."], "basis": "The paper names GSE2503, GSE45164, GSE66359, GSE53462, GSE7553 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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Methods: Three microarray datasets (GSE2503, GSE45164, and GSE66359) w"], "order_basis": "paper_text_order:369", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The DEGs between cSCC and noncancerous samples were screened using GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r), which is an online tool for differential analysis of the original dataset based on the LIMMA software package [16]."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}