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

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. HCC occurs mainly in chronically diseased livers, e.g. following hepatitis B and C infection. These high-risk patients are closely followed up, and increasing numbers of small equivocal lesions are detected by imaging diagnosis. They are now widely recognized as precursor or early-stage HCCs and are classified as dysplastic nodule or early HCC. These lesions lack typical imaging and histology of ordinary HCC and do not show elevated serum markers of alpha-fetoprotein and PIVKA-II, for example. Molecular analysis of these lesions would help to develop molecular markers for objective histological diagnosis of early HCC and possibly new serum markers for early detection of HCC. It has been reported that HSP70, CAP2, glypican 3 and glutamine synthetase could serve as molecular markers for early HCC. Further analysis is expected to evaluate their usefulness in routine pathological diagnosis including biopsy diagnosis and also as serum markers for early detection of HCC.
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PMID:Candidate molecular markers for histological diagnosis of early hepatocellular carcinoma. 1854 47

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. HCC occurs mainly in patients with chronic liver disease such as in hepatitis B and C infection. These high-risk patients are closely followed up, and increasing numbers of small equivocal lesions are detected by imaging diagnosis. They are now widely recognized as a precursor or early stage of HCC and are classified as dysplastic nodules or early HCC. It is considered that early HCC is a key step in the process of HCC development and progression. However, the molecular mechanisms of early hepatocarcinogenesis are far from clear. Specific mutations of classical oncogenes or tumor suppressor genes have not been identified in early HCC so far. Recent progress in comprehensive analysis of gene expression is shedding some light on this issue. It has been reported that HSP70, CAP2, glypican 3, and glutamine synthetase could serve as molecular markers for early HCC. Further analysis is expected to evaluate their usefulness in routine pathological diagnosis including biopsy diagnosis and also as serum markers for early detection of HCC.
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PMID:Early HCC: diagnosis and molecular markers. 1914 3

Hepatocellular carcinoma (HCC) is the sixth most common malignancy and the third leading cause of cancer deaths worldwide. Proper classification and early identification of HCC and precursor lesions is essential to the successful treatment and survival of HCC patients. Recent molecular genetic, pathologic, and clinical data have led to the stratification of hepatic adenomas into three subgroups: those with mutant TCF1/HNF1 alpha gene, those with mutant beta-catenin, and those without mutations in either of these loci. Hepatic adenomas with alpha-catenin mutations have a significantly greater risk for malignant transformation in comparison with the other two subgroups. Telangiectatic focal nodular hyperplasia has now been reclassified as telangiectatic adenoma due to the presence of non-random methylation patterns, consistent with the monoclonal origin which is similar to hepatic adenoma and HCC. HCC precursor lesions demonstrate unique molecular alterations of HSP70, CAP2, glypican 3, and glutamine synthetase that have proven useful in the histologic diagnosis of early HCC. Though specific genetic alterations depend on HCC etiology, the main proteins affected include cell membrane receptors (in particular tyrosine kinase receptors) as well as proteins involved in cell signaling (specifically Wnt/beta-catenin, Ras/Raf/MEK/ERK and PI3K/Akt/mTOR pathways), cell cycle regulation (i.e. p53, p16/INK4, cyclin/cdk complex), invasiveness (EMT, TGF-beta) and DNA metabolism. Advances in gene expression profiling have provided new insights into the molecular genetics of HCC. HCCs can now be stratified into two clinically relevant groups: Class A, the low survival subclass (overall survival time 30.3+/- 8.02 months), shows strong expression signatures of cell proliferation and antiapoptosis genes (such as PNCA and cell cycle regulators CDK4, CCNB1, CCNA2, and CKS2) as well as genes involving ubiquitination and sumoylation; Class B, the high survival subclass (overall survival time 83.7 +/-10.3 months), does not have the above expression signature. In fact, insights into HCC-specific alterations of signal transduction pathways and protein expression patterns have led to the development of new therapeutic agents with molecular targets such as EGFR, VEGF, or other multi-kinase inhibitors. In the future, these specific molecular alterations in HCC can potentially serve as diagnostic tools, prognostic markers, and/or therapeutic targets with the potential to alter clinical outcomes.
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PMID:Molecular genetics of hepatocellular neoplasia. 2018 87

Human hepatocellular carcinoma is recognized as a good model for multistage carcinogenesis, as the malignant steps from chronic liver disease through to advanced human hepatocellular carcinoma are relatively clear. We address the activation of different molecular pathways during hepatocarcinogenesis that is especially useful in the diagnosis of pathological multistage human hepatocellular carcinoma. In chronic liver disease, the gene-expression signature as well as the degree of liver fibrosis could help us to predict the development of human hepatocellular carcinoma or survival outcome after treatment for human hepatocellular carcinoma. Several genes, such as HSP70, CAP2 and GPC3, have been identified as potential biomarkers for early human hepatocellular carcinoma. Classical oncogenes or tumor suppressor genes, such as beta-catenin and p53, are mutated during the progression from early to advanced human hepatocellular carcinoma. Also, the presence of hepatoblastic feature like CK19 in advanced human hepatocellular carcinoma can be used as a predictor of aggressive human hepatocellular carcinoma. Although many advances have been made in the diagnosis of multistage hepatocarcinogenesis, we still need further useful markers to more precisely evaluate each step of hepatocarcinogenesis for better treatment choices, and that will promote future molecular-targeted therapy.
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PMID:Molecular diagnosis of multistage hepatocarcinogenesis. 2060 46

Hepatocellular carcinoma (HCC) is the most common sort of primary liver malignancy with poor prognosis. This study aimed at examining the effects of silibinin (a putative antimetastatic agent) on some transcriptional markers mechanistically related to HCC recurrence and metastasis in HepG-2 [hepatitis B virus (HBV)-negative and P53 intact) and PLC/PRF/5 (HBV-positive and P53 mutated) cells. The expression of 27 genes in response to silibinin was evaluated by real-time RT-PCR. The MMP gelatinolytic assay and microculture tetrazolium test (MTT) were tested. Silibinin was capable of suppressing the transcriptional levels of ANGPT2, ATP6L, CAP2, CCR6, CCR7, CLDN-10, cortactin, CXCR4, GLI2, HK2, ID1, KIAA0101, mortalin, PAK1, RHOA, SPINK1, and STMN1 as well as the enzymatic activity of MMP-2 but promoted the transcripts of CREB3L3, DDX3X, and PROX1 in both cells. Some significant differences between the cells in response to silibinin were detected that might be related to the differences of the cells in terms of HBV infection and/or P53 mutation, suggesting the possible influence of silibinin on HCC through biological functions of these 2 prognostic factors. In conclusion, our findings suggest that silibinin could potentially function as a multitargeting antimetastatic agent and might provide new insights for HCC therapy particularly for HBV-related and/or P53-mutated HCCs.
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PMID:Multitargeting and antimetastatic potentials of silibinin in human HepG-2 and PLC/PRF/5 hepatoma cells. 2365 51

Liver cancer is one of the leading causes of cancer mortality worldwide. Hepatocellular carcinoma (HCC) is the main type of liver cancer. We applied a machine learning approach with maximum-relevance-minimum-redundancy (mRMR) algorithm followed by incremental feature selection (IFS) to a set of microarray data generated from 43 tumor and 52 nontumor samples. With the machine learning approach, we identified 117 gene probes that could optimally separate tumor and nontumor samples. These genes not only include known HCC-relevant genes such as MT1X, BMI1, and CAP2, but also include cancer genes that were not found previously to be closely related to HCC, such as TACSTD2. Then, we constructed a molecular interaction network based on the protein-protein interaction (PPI) data from the STRING database and identified 187 genes on the shortest paths among the genes identified with the machine learning approach. Network analysis reveals new potential roles of ubiquitin C in the pathogenesis of HCC. Based on gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, we showed that the identified subnetwork is significantly enriched in biological processes related to cell death. These results bring new insights of understanding the process of HCC.
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PMID:Identification of hepatocellular carcinoma-related genes with a machine learning and network analysis. 2524 52

CAP2 has been suggested as a potential diagnostic biomarker for early hepatocellular carcinoma (HCC). However, its prognostic significance in HCC remains unclear. Here, we show that CAP2 expression is much higher in HCC tissues than that in paracarcinoma tissues, at both mRNA and protein levels. Data of immunohistochemistry (IHC) revealed that CAP2 was markedly up-regulated in 77.3% of HCC cases. High CAP2 expression, defined by the median score of IHC, was present in 53.3% of the patients. Kaplan-Meier analysis indicated that high CAP2 expression was associated with poor overall survival (P < .0001), disease-free survival (P = .013) and recurrence probability (P = .004) in a training cohort of 312 HCC patients. The prognostic implication of CAP2 in HCC was further confirmed in a validation cohort of 208 HCC patients and by stratified survival analysis. Multiple Cox regression analysis indicated CAP2 as an independent predictor for overall survival (hazard ratio (HR) = 1.615, 95% confidence interval: 1.345-1.938, P < .001). Collectively, we conclude that CAP2 is increased in HCC and is a novel unfavorable biomarker for prognostic prediction for patients with this deadly disease.
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PMID:Increased Expression of CAP2 Indicates Poor Prognosis in Hepatocellular Carcinoma. 2650 30