The increase of long noncoding RNA Fendrr in hepatocytes contributes to liver fibrosis by promoting IL-6 production.

Liver fibrosis/cirrhosis is a pathological state caused by excessive extracellular matrix deposition. Sustained activation of hepatic stellate cells (HSC) is the predominant cause of liver fibrosis, but the detailed mechanism is far from clear. In this study, we found that long noncoding RNA Fendrr is exclusively increased in hepatocytes in the murine model of CCl4- and bile duct ligation-induced liver fibrosis, as well as in the biopsies of liver cirrhosis patients. In vivo, ectopic expression of Fendrr aggravated the severity of CCl4-induced liver fibrosis in mice. In contrast, inhibiting Fendrr blockaded the activation of HSC and ameliorated CCl4-induced liver fibrosis. Our mechanistic study showed that Fendrr binds to STAT2 and enhances its enrichment in the nucleus, which then promote the expression of interleukin 6 (IL-6), and, ultimately, activates HSC in a paracrine manner. Accordingly, disrupting the interaction between Fendrr and STAT2 by ectopic expression of a STAT2 mutant attenuated the profibrotic response inspired by Fendrr in the CCl4-induced liver fibrosis. Notably, the increase of Fendrr in patient fibrotic liver is positively correlated with the severity of fibrosis and the expression of IL-6. Meanwhile, hepatic IL-6 positively correlates with the extent of liver fibrosis and HSC activation as well, thus suggesting a causative role of Fendrr in HSC activation and liver fibrosis. In conclusion, these observations identify an important regulatory cross talk between hepatocyte Fendrr and HSC activation in the progression of liver fibrosis, which might represent a potential strategy for therapeutic intervention.

Loss of EGFR contributes to high-fat diet-induced nonalcoholic fatty liver disease.

Using a murine model of high-fat diet (HFD)-induced nonalcoholic fatty liver disease (NAFLD), we found that the expression of the epidermal growth factor receptor (EGFR) significantly decreased in hepatocytes. In vitro, free fatty acid influx decreased EGFR in hepatocytes. In HFD-fed mice, ectopic expression of EGFR alleviated intrahepatic lipid accumulation and reduced serum triglyceride and cholesterol, whereas knockdown of EGFR aggravated hepatic steatosis. Notably, EGFR inhibited the induction of lipogenic genes, including Srebf1, Srebf2, Fasn, Acc1 and Ppara, both in vitro and in vivo. Mechanistically, EGFR potentiates TGF-ß/Smad signalling and augments the inhibitory effects of TGF-ß1 on lipogenic genes in hepatocytes. Our findings suggest a hitherto unknown paradigm in the pathogenesis of NAFLD, thereby providing a rational basis for future therapeutic considerations.

Sox9/INHBB axis-mediated crosstalk between the hepatoma and hepatic stellate cells promotes the metastasis of hepatocellular carcinoma.

The activation of hepatic stellate cells (HSCs) and liver fibrosis in the peri-tumoral tissue contributes to the progression of hepatocellular carcinoma (HCC). However, the mechanisms underlying the crosstalk between hepatoma and peri-tumoral HSCs remain elusive. We found that the Sox9/INHBB axis is upregulated in HCC and is associated with tumor metastasis. Using gain- and loss-of-function approaches, we revealed that the Sox9/INHBB axis promotes the growth and metastasis of an orthotopic HCC tumor by activating the peri-tumoral HSCs. Mechanistically, Sox9 induces INHBB expression by directly binding to its enhancer, thus aiding in the secretion of activin B from hepatoma cells, and in turn, promoting the activation of the surrounding HSCs through activin B/Smad signaling. Furthermore, inhibition of activin B/Smad singaling attenuates the fibrotic response in the peri-tumoral tissue and decreases the incidence of metastasis. Finally, clinical analyses indicated a positive correlation between Sox9 and INHBB expression in HCC specimens and identified the Sox9/INHBB axis as a positive regulator of liver fibrosis. In conclusion, Sox9/INHBB axis-mediated crosstalk between hepatoma cells and HSCs induces a fertile environment favoring HCC metastasis, thereby exhibiting as a potential therapeutic target.

A Novel Sox9/lncRNA H19 Axis Contributes to Hepatocyte Death and Liver Fibrosis.

Sox9 has been previously characterized as a transcription factor responsible for the extracellular matrix production during liver fibrosis. However, the deregulation and functional role of hepatocyte Sox9 in the progression of liver fibrosis remains elusive. Here, we found a significant increase of Sox9 in the hepatocytes isolated from CCl4-induced fibrotic liver and showed that antisense oligoribonucleotides depletion of Sox9 was sufficient to attenuate CCl4-induced liver fibrosis. Notably, the increase of Sox9 in hepatocyte was associated with the upregulation of long noncoding RNA H19 in both in vitro and in vivo systems. Mechanistic studies revealed that Sox9 induced H19 by binding to a conserved promoter region of H19. In vitro, hepatocyte injury triggered the increase of Sox9/H19 axis, whereas silence of H19 greatly alleviated the H2O2-induced hepatocyte apoptosis, suggesting that H19 functions as a downstream effector of Sox9 signaling and is involved in hepatocyte apoptosis. In animal experiments, inhibition of H19 alleviated the activation of hepatic stellate cells and reduced the extent of liver fibrosis, whereas ectopic expression of H19 abolished the inhibitory effects of Sox9 depletion on liver fibrosis, suggesting that the profibrotic effect of hepatocyte Sox9 depends on H19. Finally, we investigated the clinical relevance of Sox9/H19 axis to liver fibrosis and identified the increase of Sox9/H19 axis in liver cirrhosis patients. In conclusion, our findings link Sox9/H19 axis to the intrinsic mechanisms of hepatocyte apoptosis and may represent a hitherto unknown paradigm in hepatocyte injury associated with the progression of liver fibrosis.

Accelerated wound healing in diabetes by reprogramming the macrophages with particle-induced clustering of the mannose receptors.

The rate-limiting step in cutaneous wound healing, namely, the transition from inflammation to cell proliferation, depends on the high plasticity of macrophages to prevent inflammation in the wound tissues in a timely manner. Thus, strategies that reprogram inflammatory macrophages may improve the healing of poor wounds, particularly in the aged skin of individuals with diabetes or other chronic diseases. As shown in our previous study, KGM-modified SiO2 nanoparticles (KSiNPs) effectively activate macrophages to differentiate into the M2-type phenotype by inducing mannose receptor (MR) clustering on the cell surface. Here, we assess whether KSiNPs accelerate wound healing following acute or chronic skin injury. Using a full-thickness excision model in either diabetic mice or healthy mice, the wounds treated with KSiNPs displayed a dramatically increased closure rate and collagen production, along with decreased inflammation and increased angiogenesis in the regenerating tissues. Furthermore, KSiNPs induced the formation of M2-like macrophages by clustering MR on the cells. Accordingly, the cytokines produced by the KSiNP-treated macrophages were capable of inducing fibroblast proliferation and subsequent secretion of extracellular matrix (ECM). Based on these results, KSiNPs display great potential as an effective therapeutic approach for cutaneous wounds by effectively suppressing excessive or persistent inflammation and fibrosis.

TGF-ß-induced hepatocyte lincRNA-p21 contributes to liver fibrosis in mice.

Hepatocyte death, as well as the following inflammatory and fibrogenic signaling cascades, is the key trigger of liver fibrosis. Here, we isolated hepatocytes from CCl4-induced fibrotic liver and found that hepatocyte lincRNA-p21 significantly increased during liver fibrosis. The increase of hepatocyte lincRNA-p21 was associated with the loss of miR-30, which can inhibit TGF-ß signaling by targeting KLF11. We revealed that lincRNA-p21 modulated miR-30 availability by acting as a competing endogenous RNA (ceRNA). The physiological significance of this interaction is highlighted by the feedback loop, in which lincRNA-p21 works as a downstream effector of the TGF-ß signaling to strengthen TGF-ß signaling and mediate its role in promoting liver fibrosis by interacting with miR-30. In vivo results showed that knockdown of hepatocyte lincRNA-p21 greatly reduced CCl4-induced liver fibrosis and inflammation, whereas ectopic expression of miR-30 in hepatocyte exhibited the similar results. Mechanistic studies further revealed that inhibition of miR-30 impaired the effects of lincRNA-p21 on liver fibrosis. Additionally, lincRNA-p21 promoted hepatocyte apoptosis in vitro and in vivo, whereas the proliferation rate of hepatocyte was suppressed by lincRNA-p21. The pleiotropic roles of hepatocyte lincRNA-p21 suggest that it may represent an unknown paradigm in liver fibrosis and serve as a potential target for therapy.

Unraveling the hidden heterogeneities of breast cancer based on functional miRNA cluster.

It has become increasingly clear that the current taxonomy of clinical phenotypes is mixed with molecular heterogeneity, which potentially affects the treatment effect for involved patients. Defining the hidden molecular-distinct diseases using modern large-scale genomic approaches is therefore useful for refining clinical practice and improving intervention strategies. Given that microRNA expression profiling has provided a powerful way to dissect hidden genetic heterogeneity for complex diseases, the aim of the study was to develop a bioinformatics approach that identifies microRNA features leading to the hidden subtyping of complex clinical phenotypes. The basic strategy of the proposed method was to identify optimal miRNA clusters by iteratively partitioning the sample and feature space using the two-ways super-paramagnetic clustering technique. We evaluated the obtained optimal miRNA cluster by determining the consistency of co-expression and the chromosome location among the within-cluster microRNAs, and concluded that the optimal miRNA cluster could lead to a natural partition of disease samples. We applied the proposed method to a publicly available microarray dataset of breast cancer patients that have notoriously heterogeneous phenotypes. We obtained a feature subset of 13 microRNAs that could classify the 71 breast cancer patients into five subtypes with significantly different five-year overall survival rates (45%, 82.4%, 70.6%, 100% and 60% respectively; p = 0.008). By building a multivariate Cox proportional-hazards prediction model for the feature subset, we identified has-miR-146b as one of the most significant predictor (p = 0.045; hazard ratios = 0.39). The proposed algorithm is a promising computational strategy for dissecting hidden genetic heterogeneity for complex diseases, and will be of value for improving cancer diagnosis and treatment.