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| LGN protein (GPSM2) is involved in transcription or cell division presented in several papers. However, how the molecular network and interpretation concerning GPSM2 signal transduction between no-tumor hepatitis/cirrhosis and hepatocellular carcinoma (HCC) transformation remains to be elucidated. Here we constructed and analyzed significant higher expression gene GPSM2 activated & inhibited upstream and downstream signal transduction network from HCC vs no-tumor hepatitis/cirrhosis pateints (viral infection HCV or HBV) in GEO Dataset by using gene regulatory network inference method based on linear programming and decomposition procedure, under covering GPSM2 pathway and matching signal transduction enrichment analysis by the CapitalBio MAS 3.0 integrated of public databases including Gene Ontology, KEGG, BioCarta, GenMapp, Intact, UniGene, OMIM, etc. By compared the different activated & inhibited GPSM2 network with GO analysis between no-tumor hepatitis/cirrhosis and HCC transformation, our result showed GPSM2 signal transduction network: (1) more nucleus and cytoplasm but less extracellular space protein binding in no-tumor hepatitis/cirrhosis; (2) more growth factor activity but less cytoplasm enzyme activator activity in HCC; (3) less activation & more inhibition molecular numbers in no-tumor hepatitis/cirrhosis but more activation & less inhibition in HCC. Therefore, we inferred (4) GPSM2 signal transduction network stronger transcription but weaker cell differentiation as a result increasing cytoplasm protein translation in no-tumor hepatitis/cirrhosis; (5) stronger cell proliferation but weaker regulation of muscle contraction as a result inceasing nuclear cell division in HCC. |
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| Keywords:LGN protein (GPSM2) computational network; signal transduction; human hepatocellular carcinoma; transformation; no-tumor hepatitis/cirrhosis |
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