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pmid:38617515
Gastric cancer prognosis: unveiling autophagy-related signatures and immune infiltrates.
Yichen Yin · Baozhen Wang · Mingzhe Yang · Jing Chen · Tao Li
Translational cancer research · 2024 doi:10.21037/tcr-23-1755
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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Therefore, we aimed to comprehensively analyze autophagy-related genes (ARGs) in gastric cancer, focusing on their expression, prognostic value, and potential functions.\nMethods: The gastric cancer gene chip datasets (GSE79973 and GSE54129) were collected from the Gene Expression Omnibus (GEO) database. Subsequently, the Limma package was employed to identify differentially expressed genes (DEGs) between the normal and disease groups. The selected ARGs were further authenticated using the Human Protein Atlas (HPA) database, The Cancer Genome Atlas (TCGA) database, and GSE19826 database.\nResults: A total of 15 autophagy-related DEGs, eight of which were upregulated [FKBP1A, IL24, PEA15, HSP90AB1, cathepsin B (CTSB), ITGB1, SPHK1, HIF1A], while seven were downregulated (DAPK2, EIF2AK3, FKBP1B, PTK6, NKX2-3, NFE2L2, PRKCD). Analysis revealed that CTSB was specifically associated with the prognosis of gastric cancer patients. Gene set enrichment analysis (GSEA) showcased a significant enrichment of CTSB-related genes within immune-related pathways. Moreover, correlation analysis demonstrated a clear association between the expression of CTSB and immune infiltration. The upregulation of CTSB in gastric cancer was linked to poor survival and increased immune infiltration.\nConclusions: We conjectured that CTSB likely played a critical role in regulating immunity and autophagy in gastric cancer.", "claims": [{"id": "claim-method", "statement": "In analyzing the GEO dataset using R software (version 4.3.0), we utilized the limma, tidyverse, and ggpubr packages.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38617515", "locator": "sections[5] \"Identification of differentially expressed genes (DEGs)\" paragraph 2", "quote": "In analyzing the GEO dataset using R software (version 4.3.0), we utilized the limma, tidyverse, and ggpubr packages."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GSE79973 dataset included 10 gastric cancer and 10 normal tissue samples. 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