Background & Aims Stearoyl-CoA desaturase (SCD) synthesizes monounsaturated fatty acids (MUFAs) and has been associated with development of metabolic syndrome, tumorigenesis, and stem cell characteristics. We investigated whether and how SCD promotes liver fibrosis and tumor development in mice. Methods Rodent primary hepatic stellate cells (HSCs), mouse liver tumor-initiating stem cell-like cells (TICs), and human hepatocellular carcinoma (HCC) cell lines were exposed to Wnt signaling inhibitors and changes in gene expression patterns were analyzed. We assessed the functions of SCD by pharmacologic and conditional genetic manipulation in mice with hepatotoxic or cholestatic induction of liver fibrosis, orthotopic transplants of TICs, or liver tumors induced by administration of diethyl nitrosamine. We performed bioinformatic analyses of SCD expression in HCC vs non-tumor liver samples collected from patients, and correlate levels with HCC stage and patient mortality. We performed nano-bead pull-down assays, liquid chromatography-mass spectrometry, computational modeling, and ribonucleoprotein immunoprecipitation analyses to identify MUFA-interacting proteins. We examined the effects of SCD inhibition on Wnt signaling, including expression and stability of low-density lipoprotein receptor-related proteins 5 and 6 (LRP5 and LRP6), by immunoblot and quantitative PCR analyses. Results SCD was overexpressed in activated HSC and HCC cells from patients; levels of SCD mRNA correlated with HCC stage and patient survival time. In rodent HSCs and TICs, the Wnt effector beta-catenin increased sterol regulatory element binding protein 1-dependent transcription of Scd, and beta-catenin was in return stabilized by MUFAs generated by SCD. This loop required MUFA inhibition of binding of RAS-related nuclear protein 1 to transportin 1 and reduced nuclear import of elav-like protein 1 (ELAVL1), increasing cytosolic levels of ELAVL1 and ELAVL1-mediated stabilization of mRNAs encoding LRP5 and LRP6. Genetic disruption of Scd and pharmacologic inhibitors of SCD reduced HSC activation and TIC self-renewal and attenuated liver fibrosis and tumorigenesis in mice. Conditional disruption of Scd2 in activated HSCs prevented growth of tumors from TICs and reduced formation of diethyl nitrosamine-induced liver tumors in mice. Conclusions In rodent HSCs and TICs, we found Scd expression to be regulated by Wnt–beta-catenin signaling and MUFAs produced by SCD to provide a positive-feedback loop that amplifies Wnt signaling via stabilization of Lrp5 and Lrp6 mRNAs, leading to liver fibrosis and tumor growth. SCD expressed by HSCs promoted liver tumor development. SCD expression was increased in HCCs from patients compared with non-tumor tissue, and correlated positively with tumor state and inversely with patient survival time.

Background & Aims-Mechanisms underlying synergistic liver injury caused by alcohol and obesity are not clear. We have produced a mouse model of synergistic steatohepatitis by recapitulating the natural history of the synergism seen in patients for mechanistic studies.

We are reporting qualitative and quantitative changes of the extracellular matrix (ECM) and associated receptor proteomes, occurring during the transition from liver fibrosis and steatohepatitis to hepatocellular carcinoma (HCC). We compared two mouse models relevant to human HCC: PDGFC transgenic (Tg) and Pten null mice, models of disease progression from fibrosis and steatohepatitis to HCC. Using mass spectrometry, we identified in the liver of both models proteins for 26 collagen-encoding genes, providing the first evidence of expression at the protein level for 16 collagens. We also identified post-transcriptional protein variants for six collagens and lysine hydroxylation modifications for 14 collagens. Tumor-associated collagen proteomes were similar in both models with increased expression of collagens type IV, VI, VII, X, XIV, XV, XVI, and XVIII. Splice variants for Col4a2, Col6a2, Col6a3 were co-upregulated while only the short form of Col18a1 increased in the tumors. We also identified tumor specific increases of nidogen 1, decorin, perlecan, and of six laminin subunits. The changes in these non-collagenous ECM proteins were similar in both models with the exception of laminin β3, detected specifically in the Pten null tumors. Pdgfa and Pdgfc mRNA expression was increased in the Pten null liver, a possible mechanism for the similarity in ECM composition observed in the tumors of both models. In contrast and besides the strong up-regulation of integrin α5 protein observed in the liver tumors of both models, the expression of the six other integrins identified was specific to each model, with integrins α2b, α3, α6, and β1 up-regulated in Pten null tumors and integrins α8 and β5 up-regulated in the PDGFC Tg tumors. In conclusion, HCC–associated ECM proteins and ECM–integrin networks, common or specific to HCC subtypes, were identified, providing a unique foundation to using ECM composition for HCC classification, diagnosis, prevention, or treatment.

We report a comprehensive and quantitative analysis of the mouse liver and plasma proteomes. The method used is based on extensive fractionation of intact proteins, further separation of proteins based on their abundance and size, and high-accuracy mass spectrometry. This analysis reached a depth in proteomic profiling not reported to date for a mammalian tissue or a biological fluid, with 7099 and 4727 proteins identified with high confidence in the liver and in the corresponding plasma, respectively. This method allowed for the identification in both compartments of low-abundance proteins such as cytokines, chemokines, and receptors and for the detection in plasma of proteins in the pg/mL concentration range. This method also allowed for semiquantitation of all identified proteins. The calculated abundance scores correlated with the abundance of the corresponding transcripts for the large majority of the proteins identified in the liver. Finally, comparison of the liver and plasma datasets demonstrated that a significant number of proteins identified in the liver can be detected in plasma. These included proteins involved in complement and coagulation, in fatty acid, purine and pyruvate metabolism, in gluconeogenesis and glycolysis, in protein ubiquitination, and in insulin, interleukin-4, epidermal growth factor, and platelet-derived growth factor signaling. Conclusion: This in-depth analysis of the mouse liver and corresponding plasma proteomes provides a strong basis for investigations of liver pathobiology and biology that employ mouse models of hepatic diseases in an effort to better understand, diagnose, treat, and prevent human hepatic diseases. (HEPATOLOGY 2008;47: 1043-1051.)