31 December 2020 : Clinical Research
Characterization of the Relationship Between the Expression of Aspartate β-Hydroxylase and the Pathological Characteristics of Breast Cancer
Yanan Zhang12ABEF, Yimeng Gao3CF, Yingxue Li2DF, Xuedong Zhang2AD, Haitao Xie4G*DOI: 10.12659/MSM.926752
Med Sci Monit 2020; 26:e926752
Abstract
BACKGROUND: This study aimed to investigate the relationship between the expression of aspartate b-hydroxylase (ASPH) and the molecular mechanisms of ASPH-related genes in breast cancer (BC).
MATERIAL AND METHODS: ASPH expression was determined by immunohistochemistry and western blot analysis in samples of BC tissues and adjacent normal tissues. ASPH mRNA expression data and their clinical significance in BC were retrieved from the Oncomine and GEPIA datasets. Enrichment analysis of genes coexpressed with ASPH and annotation of potential pathways were performed with Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) analysis. Hub genes were shown in an ASPH coexpression gene-interaction network. The expression of the hub genes associated with patient survival were analyzed to determine the role of ASPH in the progression of BC.
RESULTS: ASPH levels were overexpressed in BC and correlated with cancer type, lymph node involvement, and TNM stage. Conversely, ASPH levels did not correlate with patient age, invasive carcinoma types, or molecular subtypes. Enrichment analysis showed the involvement of multiple pathways, including lipid metabolism and oxidation-reduction processes. Six hub genes, PPARG, LEP, PLIN1, AGPAT2, CAV1, and PNPLA2, were related to ASPH expression and had functional roles in the occurrence and progression of BC.
CONCLUSIONS: ASPH may be involved in the development of BC and may have utility as a prognostic biomarker in BC. The coexpression of ASPH-associated genes may also be beneficial in improving BC prognosis.
Keywords: Biological Markers, Breast Neoplasms, Dioxygenases, Acyltransferases, Atlases as Topic, Calcium-Binding Proteins, Carcinoma, Ductal, Breast, Caveolin 1, Datasets as Topic, Disease Progression, gene ontology, Gene Regulatory Networks, Leptin, Lipase, Membrane Proteins, Metabolic Networks and Pathways, Mixed Function Oxygenases, Molecular Sequence Annotation, Muscle Proteins, PPAR gamma, Perilipin-1, RNA, Messenger
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