Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts:   Target Concepts:
Query: UMLS:C0019204 (hepatocellular carcinoma)
 71,386 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Human toxicity screening is an important stage in the development of safe drug candidates. Hepatotoxicity is one of the major reasons for the withdrawal of drugs from the market because the liver is the major organ involved in drug metabolism, and it can generate toxic metabolites. There is a need to screen molecules for drug-induced hepatotoxicity in humans at an earlier stage. Transcriptomics is a technique widely used to screen molecules for toxicity and to unravel toxicity mechanisms. To date, the majority of such studies were performed using animals or animal cells, with concomitant difficulty in interpretation due to species differences, or in human hepatoma cell lines or cultured hepatocytes, suffering from the lack of physiological expression of enzymes and transporters and lack of nonparenchymal cells. The aim of this study was to classify known hepatotoxicants on their phenotype of toxicity in humans using gene expression profiles ex vivo in human precision-cut liver slices (PCLS). Hepatotoxicants known to induce either necrosis (n = 5) or cholestasis (n = 5) were used at concentrations inducing low (<30%) and medium (30-50%) cytotoxicity, based on ATP content. Random forest and support vector machine algorithms were used to classify hepatotoxicants using a leave-one-compound-out cross-validation method. Optimized biomarker sets were compared to derive a consensus list of markers. Classification correctly predicted the toxicity phenotype with an accuracy of 70-80%. The classification is slightly better for the low than for the medium cytotoxicity. The consensus list of markers includes endoplasmic reticulum stress genes, such as C2ORF30, DNAJB9, DNAJC12, SRP72, TMED7, and UBA5, and a sodium/bile acid cotransporter (SLC10A7). This study shows that human PCLS are a useful model to predict the phenotype of drug-induced hepatotoxicity. Additional compounds should be included to confirm the consensus list of markers, which could then be used to develop a biomarker PCR-array for hepatotoxicity screening.
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PMID:Classification of Cholestatic and Necrotic Hepatotoxicants Using Transcriptomics on Human Precision-Cut Liver Slices. 2688 66

Objective: MicroRNAs (miRNAs) have been explored in malignancies. We investigated the functions of clustered miRNAs hsa-miR-221/222-3p in hepatocellular carcinoma (HCC). Methods: Human miRNA tissue atlas website was determined expression levels in liver tissue. Four databases, TarBase, miRTarBase, miRecords and miRPathDB, were found experimentally validated target genes of clustered miRNAs. TargetScanHuman was predicted target genes. The STRING website was depicted protein-protein interaction (PPI) networks. The OncoLnc website analyzed prognostic values for hsa-miR-221/222-3p and their target genes. The MCODE plugin calculated modules of PPI networks. Receiver operating characteristic (ROC) curves were predicted 1, 3, and 5 years prognostic values. Results: Expression of clustered miRNAs was high in liver tissues. A total of 1577 target genes were identified. Enrichment analysis showed that target genes were enriched mainly in cancer, Wnt signaling and ErbB signaling pathways. Two modules were calculated using PPI networks. Has-miR-221-3p was not associated with prognosis (P = 0.401). Has-miR-222-3p and target genes ESR1, TMED7, CBFB, ETS2, UBE2J1 and UBE2N of the clustered miRNAs were associated with HCC survival (all P < 0.05). Has-miR-222-3p, CBFB, and UBE2N showed good performance of ROC in prognosis prediction at 1, 3, and 5 years (all area under curves > 0.600). Conclusion: Has-miR-222-3p and target genes, especially CBFB, UBE2N, may serve as prognostic predictors for HCC.
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PMID:Clustered microRNAs hsa-miR-221-3p/hsa-miR-222-3p and their targeted genes might be prognostic predictors for hepatocellular carcinoma. 3125 58