Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0023890 (cirrhosis)
 42,195 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Hepatocellular carcinoma (HCC) is a leading cause of global cancer mortality. However, little is known about the precise molecular mechanisms involved in tumor formation and pathogenesis. The primary goal of this study was to elucidate genome-wide molecular networks involved in development of HCC with multiple etiologies by exploring high quality microarray data. We undertook a comparative network analysis across 264 human microarray profiles monitoring transcript changes in healthy liver, liver cirrhosis, and HCC with viral and alcoholic etiologies. Gene co-expression profiling was used to derive a consensus gene relevance network of HCC progression that consisted of 798 genes and 2,012 links. The HCC interactome was further confirmed to be phenotype-specific and non-random. Additionally, we confirmed that co-expressed genes are more likely to share biological function, but not sub-cellular localization. Analysis of individual HCC genes revealed that they are topologically central in a human protein-protein interaction network. We used quantitative RT-PCR in a cohort of normal liver tissue (n = 8), hepatitis C virus (HCV)-induced chronic liver disease (n = 9), and HCC (n = 7) to validate co-expressions of several well-connected genes, namely ASPM, CDKN3, NEK2, RACGAP1, and TOP2A. We show that HCC is a heterogeneous disorder, underpinned by complex cross talk between immune response, cell cycle, and mRNA translation pathways. Our work provides a systems-wide resource for deeper understanding of molecular mechanisms in HCC progression and may be used further to define novel targets for efficient treatment or diagnosis of this disease.
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PMID:Functional and topological properties in hepatocellular carcinoma transcriptome. 2253 75

The molecular mechanism of the pathological progression from cirrhosis to hepatocellular carcinoma (HCC) remains elusive. In the present study, tissue samples from normal liver, cirrhosis and HCC were subjected to differentially gene expression analysis, weighted gene correlation network analysis to identify the twenty hub genes (TOP2A, CDC20, PTTG1, CDCA5, CCNB2, PRC1, KIF20A, SF3B4, HSP90AB1, FOXD2, PLOD3, CCT3, SETDB1, VPS45, SPDL1, RACGAP1, MED24, KIAA0101, ZNF282, and USP21) in the pathological progression from cirrhosis to HCC. Each sample was calculated a hub gene set variation analysis (HGSVA) score using Gene Set Variation Analysis, The HGSVA score significantly increased with progression from cirrhosis to HCC, and this result was validated in two independent data sets. Moreover, this score may be used as a blood-based marker for HCC and is an independent prognostic factor of recurrence-free survival (RFS) and overall survival (OS). High expression of the hub genes may be driven by hypomethylation. The twenty gene-based gene set variation score may reflect the pathological progression from cirrhosis to HCC and is an independent prognostic factor for both OS and RFS.
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PMID:A twenty gene-based gene set variation score reflects the pathological progression from cirrhosis to hepatocellular carcinoma. 3181 Nov 11