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, 9 (1), 19601

Upregulation of Cancer-Associated Gene Expression in Activated Fibroblasts in a Mouse Model of Non-Alcoholic Steatohepatitis

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Upregulation of Cancer-Associated Gene Expression in Activated Fibroblasts in a Mouse Model of Non-Alcoholic Steatohepatitis

Masahiro Asakawa et al. Sci Rep.

Abstract

Non-alcoholic steatohepatitis (NASH), characterized by chronic inflammation and fibrosis, is predicted to be the leading cause of cirrhosis and hepatocellular carcinoma (HCC) in the next decade. Although recent evidence suggests the importance of fibrosis as the strongest determinant of HCC development, the molecular mechanisms underlying NASH-induced carcinogenesis still remain unclear. Here we performed RNA sequencing analysis to compare gene expression profiles of activated fibroblasts prepared from two distinct liver fibrosis models: carbon tetrachloride-induced fibrosis as a model without obesity and HCC and genetically obese melanocortin 4 receptor-deficient (MC4R-KO) mice fed Western diet, which develop steatosis, NASH, and eventually HCC. Our data showed that activated fibroblasts exhibited distinct gene expression patterns in each etiology, and that the 'pathways in cancer' were selectively upregulated in the activated fibroblasts from MC4R-KO mice. The most upregulated gene in these pathways was fibroblast growth factor 9 (FGF9), which was induced by metabolic stress such as palmitate. FGF9 exerted anti-apoptotic and pro-migratory effects in fibroblasts and hepatoma cells in vitro and accelerated tumor growth in a subcutaneous xenograft model. This study reveals upregulation of cancer-associated gene expression in activated fibroblasts in NASH, which would contribute to the progression from NASH to HCC.

Conflict of interest statement

Michiko Itoh and Ibuki Shirakawa are assigned to the Joint Research Department of Tokyo Medical and Dental University and Shionogi & Co. Ltd.

Figures

Figure 1
Figure 1
Evaluation of obesity- and carbon tetrachloride-induced liver fibrosis models. Col1a2-GFP Tg mice were crossed with MC4R-KO mice (MC/COL), and were fed Western diet (WD) for 20 weeks to develop NASH (NASH). Col1a2-GFP Tg mice were received carbon tetrachloride (CCl4) twice a week for 8 weeks (CCl4). (a) Sirius red staining and quantification of area positive for Sirius red. (b) Activated fibroblasts determined by αSMA immunostaining. (c) Type I collagen-producing cells visualized by GFP fluorescence. (d) Percentage of fibroblasts (CD45 GFP+) in hepatic non-parenchymal cells analyzed by FACS. Scale bars: 50 μm. n = 6. *P < 0.05, **P < 0.01 vs. normal. P < 0.05 vs. NASH. Data represent mean ± SEM. (e) Unsupervised hierarchical clustering of RNA sequencing datasets of steady-state hepatic stellate cells (HSCs) and activated fibroblasts separated from NASH and CCl4-induced fibrotic livers (NASH-fib and CCl4-fib, respectively). Lower left and middle panels indicate the gene clusters upregulated selectively in CCl4-fib and NASH-fib, respectively. (f) Principal component analysis of gene expression data from HSCs, CCl4-fib, and NASH-fib.
Figure 2
Figure 2
Expression profiling of activated fibroblasts from two distinct liver fibrosis models. (a) Volcano plot of RNA sequencing analysis with the comparison between NASH-fib and HSCs. Yellow rectangle denotes significantly upregulated genes in NASH-fib compared with HSCs for more than 2 folds (log2 fold change ≧ 1 and adjusted p value < 0.05). (b) GO and pathway analysis of the 396 genes upregulated in NASH-fib against HSCs. Each top 8 were indicated. (c) Volcano plot of RNA sequencing analysis with the comparison between NASH-fib and CCl4-fib. Blue rectangle denotes significantly upregulated genes in NASH-fib compared with CCl4-fib for more than 2 folds (log2 fold change ≧ 1 and adjusted p value < 0.05). (d) GO and pathway analysis of the 700 genes upregulated in NASH-fib against CCl4-fib. (e) The overlap between the genes more than 2-fold upregulated (log2 fold change ≧ 1) in NASH-fib against HSCs and CCl4-fib, respectively.
Figure 3
Figure 3
Metabolic stress induces FGF9 expression in NASH-fib. (a) Hepatic mRNA expression levels of Fgf9 in wild-type mice fed standard diet (normal liver), Col1a2-GFP Tg mice received intraperitoneal CCl4 injection (CCl4 liver), and MC4R-KO mice fed WD for 20 weeks (NASH liver) evaluated by quantitative real-time PCR. n = 6. (b) Protein expression levels of FGF9 in normal and NASH livers by Western blot analysis. Blots are shown as cropped images. Uncropped Western blot images are included in Supplementary Fig. S2a. n = 3. *P < 0.05, **P < 0.01 vs. normal liver; P < 0.05 vs. CCl4 liver. (c) Fgf9 mRNA expression levels in isolated HSCs and activated fibroblasts (CCl4-Fib, NASH-fib). n = 3. (d) Fgf9 mRNA expression levels in various cell types separated from normal and NASH livers. Resident macrophages, CD45+ Ly6G F4/80hi CD11blo; recruited macrophages, CD45+ Ly6G F4/80lo CD11bhi; CD4+ T cells, CD45+ CD4+; and liver sinusoidal endothelial cells (LSEC), CD45 CD146+. Hepatocytes were isolated from lean wild-type mice and MC4R-KO mice fed WD for 4 weeks. n = 3–8. *P < 0.05 vs. HSCs; P < 0.05 vs. CCl4-fib. (e) mRNA expression levels in cultured HSCs treated with TGFβ (10 ng/ml), lipopolysaccharide (LPS, 10 ng/ml), and palmitic acid (200 μM) for 24 hours. (f) Dose-dependent effect of palmitate (100, 200, and 500 μM) on FGF9 induction in HSCs. (g) Effect of various fatty acids (200 μM) on FGF9 induction. Lau, laurate; Ole, oleate. n = 5. *P < 0.05, **P < 0.01 vs. veh; ##P < 0.01. Data represent mean ± SEM.
Figure 4
Figure 4
FGF9 induces inflammatory changes in LX2 cells. Human HSC cell line LX2 cells were treated with human recombinant FGF9 at a dose of 1 or 10 ng/ml for 24 hours. (a) mRNA expression levels of proinflammatory cytokines (IL1A, IL1B), chemokines (CCL2, CXCL8) and fibrogenic factors (COL1A1, TGFB). n = 4. *P < 0.05 vs. veh. FGF9 or GFP (control)-overexpressing LX2 cells (FGF9-LX2 and control-LX2, respectively) were established using lentiviral vectors. Western blot analysis (b) and FGF9 secretion (c) into culture supernatants using FGF9-overexpressing and control-LX2 cells. Blots are shown as cropped images. Uncropped Western blot images are included in Supplementary Fig. S2b. n = 4. **P < 0.01 vs. control-LX2. (d) mRNA expression levels of genes related to proinflammatory cytokines, chemokines and fibrogenic factors in FGF9-LX2 cells. n = 8. **P < 0.01 vs. control-LX2. Data represent mean ± SEM.
Figure 5
Figure 5
FGF9 enhances cell migration and inhibits apoptosis in LX2 cells. (a) Effect of FGF9 on LX2 cell proliferation determined by WST assay after 96-hour incubation. n = 8. Effect of serum starvation (starve) for 48 hours (b) and coexistence with recombinant FGF9 (c) evaluated by caspase-3/7 activity assay in LX2 cells. n = 6. (d) Migration activity of FGF9-treated LX2 cells determined by transwell migration assay. LX2 cells were seeded onto the insert of transwell in serum free medium containing recombinant FGF9 (1 or 10 ng/ml), and incubated with medium containing 2% FBS in the lower chamber for 24 hours. n = 4. **P < 0.01 vs. starve (−) or veh. n.s., not significant. Data represent mean ± SEM.
Figure 6
Figure 6
FGF9 enhances cell migration and inhibits apoptosis in HepG2 cells. (a) Effect of FGF9 on HepG2 cell proliferation determined by WST assay after 96-hour incubation. n = 8. Effect of anti-Fas antibody (Fas) at a dose of 100 ng/ml for 24 hours (b) and coexistence with recombinant FGF9 (c) evaluated by caspase-3/7 activity assay in HepG2 cells. n = 6. (d) Migration activity of FGF9-treated HepG2 cells determined by transwell migration assay. HepG2 cells were seeded onto the insert of transwell in serum free medium containing recombinant FGF9 (1 or 10 ng/ml), and incubated with medium containing 2% FBS in the lower chamber for 24 hours. n = 4. **P < 0.01 vs. veh. n.s., not significant. Data represent mean ± SEM.
Figure 7
Figure 7
FGF9 promotes tumor growth in a human tumor xenograft model. HepG2 cells (2 × 105 cells) together with control-LX2 or FGF9-LX2 cells (1 × 106 cells) were transplanted subcutaneously in the flank of immunodeficient mice. (a) Time course of the tumor volume. Weight (b) and representative images (c) of subcutaneous tumors at 4 weeks after transplantation. αSMA staining (d) and TUNEL staining (e) of the tumors. Arrows indicate TUNEL-positive cells. (f) GFP and TUNEL double immunofluorescent staining of the tumors that includes HepG2 cells and control (GFP)-LX2 cells. (g) Ki67 immunostaining of the tumors. Scale bars: 100 μm. *P < 0.05, **P < 0.01 vs. control. n = 7. Data represent mean ± SEM.

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