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Clinical significance of EPHX2 deregulation in prostate cancer.


ABSTRACT: The arachidonic acid (AA) metabolic pathway participates in various physiological processes as well as in the development of malignancies. We analyzed genomic alterations in AA metabolic enzymes in the Cancer Genome Atlas (TCGA) prostate cancer (PCa) dataset and found that the gene encoding soluble epoxide hydrolase (EPHX2) is frequently deleted in PCa. EPHX2 mRNA and protein expression in PCa was examined in multiple datasets by differential gene expression analysis and in a tissue microarray by immunohistochemistry. The expression data were analyzed in conjunction with clinicopathological variables. Both the mRNA and protein expression levels of EPHX2 were significantly decreased in tumors compared with normal prostate tissues and were inversely correlated with the Gleason grade and disease-free survival time. Furthermore, EPHX2 mRNA expression was significantly decreased in metastatic and recurrent PCa compared with localized and primary PCa, respectively. In addition, EPHX2 protein expression correlated negatively with Ki67 expression. In conclusion, EPHX2 deregulation is significantly correlated with the clinical characteristics of PCa progression and may serve as a prognostic marker for PCa.

SUBMITTER: Liu MS 

PROVIDER: S-EPMC7831821 | biostudies-literature | 2021 Jan-Feb

REPOSITORIES: biostudies-literature

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Clinical significance of EPHX2 deregulation in prostate cancer.

Liu Ming-Sheng MS   Zhao Hui H   Xu Chen-Xiang CX   Xie Ping-Bo PB   Wang Wei W   Yang Ying-Yu YY   Lee Wen-Hui WH   Jin Yang Y   Zhou Hong-Qing HQ  

Asian journal of andrology 20210101 1


The arachidonic acid (AA) metabolic pathway participates in various physiological processes as well as in the development of malignancies. We analyzed genomic alterations in AA metabolic enzymes in the Cancer Genome Atlas (TCGA) prostate cancer (PCa) dataset and found that the gene encoding soluble epoxide hydrolase (EPHX2) is frequently deleted in PCa. EPHX2 mRNA and protein expression in PCa was examined in multiple datasets by differential gene expression analysis and in a tissue microarray b  ...[more]

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