Journal
ANNALS OF TRANSLATIONAL MEDICINE
Volume 8, Issue 11, Pages -Publisher
AME PUBLISHING COMPANY
DOI: 10.21037/atm-20-3296
Keywords
Acute myeloid leukemia (AML); bioinformatics analysis; functional network; glutathione peroxidases (GPXs); prognosis
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Funding
- National Natural Science Foundation of China [81560028, 81160072]
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Background: Glutathione peroxidases (GPXs) are an enzyme family with peroxidase activity. Abnormal GPX expression is associated with carcinogenesis. However, the potential role of the GPX gene family in acute myeloid leukemia (AML) remains to be comprehensively examined. Methods: We analyzed GPX mRNA expression levels and determined the correlation between gene expression and the prognostic value via multiple universally acknowledged databases including the Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), PROGgeneV2, UALCAN, Cancer Cell Line Encyclopedia (CCLE), and The European Bioinformatics Institute (EMBL-EBI) databases. The functional network of differentially expressed GPXs was investigated via the NetworkAnalyst platform. Correlated genes as well as kinase, microRNA (miRNA), and transcription factor (TF) targets were identified using LinkedOmics. Results: We observed that the transcriptional expression levels of GPX-1, -2, -4, -7, and -8 had significant difference between AML patients samples and normal samples, and that AML patients with high expression of GPX-1, -3, -4, and -7 were associated with poorer prognosis of overall survival (OS). Functional enrichment analysis showed that the differentially expressed GPXs were mainly enriched in response to oxidative stress, regulation of immune response, and inflammatory response, along with glutathione metabolism and ferroptosis. Overexpression of correlated genes, PSMB10, VPS13D, NDUFS8, ATP5D, POLR2E, and HADH were linked to adverse OS in AML. Regulatory network analysis indicated that differentially expressed GPXs regulated cell proliferation, cancer progression, apoptosis, and cell cycle signaling via pathways involving cancer-related kinases (such as DAPK1 and SRC), miRNAs (such as miR-202 and miR-181), and TFs (such as SRF and E2F1). Conclusions: Our findings offer novel insights into the differential expression and prognostic potential of the GPX family in AML, and lay a foundation for subsequent research of GPX's role in the carcinogenesis and regulatory network of AML.
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