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pmid:35421271
Identification of autophagy-related biomarker and analysis of immune infiltrates in oral carcinoma.
Honghai Fu · Dianguo Zhao · Legang Sun · Yumei Huang · Xiangrui Ma
Journal of clinical laboratory analysis · 2022 doi:10.1002/jcla.24417
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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We aimed to investigate the expression, prognostic value, and immune infiltration of autophagy-related genes in oral carcinoma via bioinformatics analysis.\nMETHODS: The microarray datasets (GSE146483 and GSE23558) of oral carcinoma were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between normal and diseased groups were identified by the Limma package. The screened autophagy-related gene was further validated by the human protein atlas (HPA) database, TCGA database, and GSE78060 dataset.\nRESULTS: A total of 18 upregulated (top 10: EGFR, TNF, FADD, AURKA, E2F1, CHEK1, BRCA1, BIRC5, EIF2AK2, and CSF2) and 31 downregulated (top 10: MAP1LC3A, PARK2, AGT, IGF1, TP53INP1, CXCL12, IKBKB, SESN1, ULK2, and RRAGD) autophagy-related (DEGs) were identified, and FADD was found to be related to the prognosis of oral cancer patients. Gene set enrichment analysis indicated that FADD-associated genes were significantly enriched in immune-related pathways. Moreover, correlation analysis revealed that FADD expression was associated with immune infiltrates. 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