Low expression of GOT2 promotes tumor progress and predicts poor prognosis in hepatocellular carcinoma.

Background: To explore the biological function and the underlying mechanisms of GOT2 in hepatocellular carcinoma (HCC). Materials & methods: The expression level and prognostic value of GOT2 were examined using International Cancer Genome Consortium and International Cancer Proteogenome Consortium databases. The cell counting kit-8 method, clone formation, Transwell® assays and western blotting were used to evaluate the effects of GOT2 on the biological function and autophagy of HCC cells. Results: The expression of GOT2 was downregulated in HCC tissues and correlated with poor prognosis of HCC patients. Knockdown of GOT2 promoted proliferation, migration and invasion of HCC cells and promoted cells' proliferation by inducing autophagy. Conclusion: GOT2 plays a tumor-inhibitory role in HCC and may be a potential therapeutic target for HCC.

Integrated profiling identifies ITGB3BP as prognostic biomarker for hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a highly malignant tumor. In this study, we sought to identify a novel biomarker for HCC by analyzing transcriptome and clinical data. The R software was used to analyze the differentially expressed genes (DEGs) in the datasets GSE74656 and GSE84598 downloaded from the Gene Expression Omnibus database, followed by a functional annotation. A total of 138 shared DEGs were screened from two datasets. They were mainly enriched in the "Metabolic pathways" pathway (Padj = 8.21E-08) and involved in the carboxylic acid metabolic process (Padj = 0.0004). The top 10 hub genes were found by protein-protein interaction analysis and were upregulated in HCC tissues compared to normal tissues in The Cancer Genome Atlas database. Survival analysis distinguished 8 hub genes CENPE, SPDL1, Hyaluronan-mediated motility receptor, Rac GTPase activating protein 1, Thyroid hormone receptor interactor 13, cytoskeleton-associated protein (CKAP) 2, CKAP5, and Integrin subunit beta 3 binding protein (ITGB3BP) were considered as prognostic hub genes. Multivariate cox regression analysis indicated that all the prognostic hub genes were independent prognostic factors for HCC. Furthermore, the receiver operating characteristic curve revealed that the 8-hub genes model had better prediction performance for overall survival compared to the T stage (p = 0.008) and significantly improved the prediction value of the T stage (p = 0.002). The Human Protein Atlas showed that the protein expression of ITGB3BP was upregulated in HCC, so the expression of ITGB3BP was further verified in our cohort. The results showed that ITGB3BP was upregulated in HCC tissues and was significantly associated with lymph node metastasis.

Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer.

Simultaneous identification of multiple single genes and multi-gene prognostic signatures with higher efficacy in liver cancer has rarely been reported. Here, 1,173 genes potentially related to the liver cancer prognosis were mined with Coremine, and the gene expression and survival data in 370 samples for overall survival (OS) and 319 samples for disease-free survival (DFS) were retrieved from The Cancer Genome Atlas. Numerous survival analyses results revealed that 39 genes and 28 genes significantly associated with DFS and OS in liver cancer, including 18 and 12 novel genes that have not been systematically reported in relation to the liver cancer prognosis, respectively. Next, totally 9,139 three-gene combinations (including 816 constructed by 18 novel genes) for predicting DFS and 3,276 three-gene combinations (including 220 constructed by 12 novel genes) for predicting OS were constructed based on the above genes, and the top 15 of these four parts three-gene combinations were selected and shown. Moreover, a huge difference between high and low expression group of these three-gene combination was detected, with median survival difference of DFS up to 65.01 months, and of OS up to 83.57 months. The high or low expression group of these three-gene combinations can predict the longest prognosis of DFS and OS is 71.91 months and 102.66 months, and the shortest is 6.24 months and 13.96 months. Quantitative real-time polymerase chain reaction and immunohistochemistry reconfirmed that three genes F2, GOT2, and TRPV1 contained in one of the above combinations, are significantly dysregulated in liver cancer tissues, low expression of F2, GOT2, and TRPV1 is associated with poor prognosis in liver cancer. Overall, we discovered a few novel single genes and multi-gene combinations biomarkers that are closely related to the long-term prognosis of liver cancer, and they can be potential therapeutic targets for liver cancer.

Clinical significance and biological mechanisms of glutathione S-transferase mu gene family in colon adenocarcinoma.

BACKGROUND: Colon adenocarcinoma (COAD) is the most common form of colon cancer. The glutathione S-transferase Mu (GSTM) gene belongs to the GST gene family, which functions in cell metabolism and detoxification. The relationship between GSTM and COAD and the underlying mechanism remain unknown. METHODS: Data extracted from The Cancer Genome Atlas included mRNA expression and clinical information such as gender, age, and tumor stage. Prognostic values of GSTM genes were identified by survival analysis. Function and mechanism of prognostic GSTM genes were identified by gene set enrichment analysis. A nomogram was used to predict the contribution of risk factors to the outcome of COAD patients. RESULTS: Low expression of GSTM1 and GSTM2 was related to favorable OS (adjusted P = 0.006, adjusted HR = 0.559, 95% CI = 0.367-0.849 and adjusted P = 0.002, adjusted HR = 0.519, 95% CI = 0.342-0.790, respectively) after adjusting for tumor stage. Enrichment analysis also showed that genes involved were related to cell cycle, metabolism, and detoxification processes, as well as the Wnt signaling and NF-κB pathways. CONCLUSIONS: In conclusion, low expression of GSTM1 and GSTM2 were significantly associated with favorable prognosis in COAD. These two genes may serve as potential biomarkers of COAD prognosis.