Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: UNIPROT:P80404 (GABA transaminase)
 786 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Hepatocellular carcinoma is the second leading cause of cancer death worldwide. DNA microarray analysis identified the ornithine aminotransferase (OAT) gene as a prominent gene overexpressed in hepatocellular carcinoma (HCC) from Psammomys obesus. In vitro studies demonstrated inactivation of OAT by gabaculine (1), a neurotoxic natural product, which suppressed in vitro proliferation of two HCC cell lines. Alpha-fetoprotein (AFP) secretion, a biomarker for HCC, was suppressed by gabaculine in both cell lines, but not significantly. Because of the active site similarity between GABA aminotransferase (GABA-AT) and OAT, a library of 24 GABA-AT inhibitors was screened to identify a more selective inhibitor of OAT. (1S,3S)-3-Amino-4-(hexafluoropropan-2-ylidene)cyclopentane-1-carboxylic acid (2) was found to be an inactivator of OAT that only weakly inhibits GABA-AT, l-aspartate aminotransferase, and l-alanine aminotransferase. In vitro administration of 2 significantly suppressed AFP secretion in both Hep3B and HepG2 HCC cells; in vivo, 2 significantly suppressed AFP serum levels and tumor growth in HCC-harboring mice, even at 0.1 mg/kg. Overexpression of the OAT gene in HCC and the ability to block the growth of HCC by OAT inhibitors support the role of OAT as a potential therapeutic target to inhibit HCC growth. This is the first demonstration of suppression of HCC by an OAT inactivator.
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PMID:Suppression of Hepatocellular Carcinoma by Inhibition of Overexpressed Ornithine Aminotransferase. 2628 81

Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, and its carcinogenesis and progression are influenced by a complex network of gene interactions. A weighted gene co-expression network was constructed to identify gene modules associated with the clinical traits in HCC (n = 214). Among the 13 modules, high correlation was only found between the red module and metastasis risk (classified by the HCC metastasis gene signature) (R2 = -0.74). Moreover, in the red module, 34 network hub genes for metastasis risk were identified, six of which (ABAT, AGXT, ALDH6A1, CYP4A11, DAO and EHHADH) were also hub nodes in the protein-protein interaction network of the module genes. Thus, a total of six hub genes were identified. In validation, all hub genes showed a negative correlation with the four-stage HCC progression (P for trend < 0.05) in the test set. Furthermore, in the training set, HCC samples with any hub gene lowly expressed demonstrated a higher recurrence rate and poorer survival rate (hazard ratios with 95% confidence intervals > 1). RNA-sequencing data of 142 HCC samples showed consistent results in the prognosis. Gene set enrichment analysis (GSEA) demonstrated that in the samples with any hub gene highly expressed, a total of 24 functional gene sets were enriched, most of which focused on amino acid metabolism and oxidation. In conclusion, co-expression network analysis identified six hub genes in association with HCC metastasis risk and prognosis, which might improve the prognosis by influencing amino acid metabolism and oxidation.
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PMID:Co-expression network analysis identified six hub genes in association with metastasis risk and prognosis in hepatocellular carcinoma. 2843 Jun 63