Circular RNA cVIM promotes hepatic stellate cell activation in liver fibrosis via miR-122-5p/miR-9-5p-mediated TGF-ß signaling cascade.

Hepatic stellate cell (HSC) activation is considered as a central driver of liver fibrosis and effective suppression of HSC activation contributes to the treatment of liver fibrosis. Circular RNAs (circRNAs) have been reported to be important in tumor progression. However, the contributions of circRNAs in liver fibrosis remain largely unclear. The liver fibrosis-specific circRNA was explored by a circRNA microarray and cVIM (a circRNA derived from exons 4 to 8 of the vimentin gene mmu_circ_32994) was selected as the research object. Further studies revealed that cVIM, mainly expressed in the cytoplasm, may act as a sponge for miR-122-5p and miR-9-5p to enhance expression of type I TGF-ß receptor (TGFBR1) and TGFBR2 and promotes activation of the TGF-ß/Smad pathway, thereby accelerating the progression of liver fibrosis. Our results demonstrate a vital role for cVIM in promoting liver fibrosis progression and provide a fresh perspective on circRNAs in liver fibrosis.

Schisandrin B Promotes Hepatic Stellate Cell Ferroptosis via Wnt Pathway-Mediated Ly6Clo Macrophages.

A key event in liver fibrosis is the activation of the hepatic stellate cell (HSC). Schisandrin B (Sch B), a major component extracted from Schisandra chinensis, has been shown to inhibit HSC activation. Recently, ferroptosis (FPT) has been reported to be involved in HSC activation. However, whether Sch B has an effect on the HSC FPT remains unclear. Herein, we explored the effects of Sch B on liver fibrosis in vivo and in vitro and the roles of Wnt agonist 1 and ferrostatin-1 in the antifibrotic effects of Sch B. Sch B effectively alleviated CCl4-induced liver fibrosis, with decreased collagen deposition and α-SMA level. Additionally, Sch B resulted in an increase in lymphocyte antigen 6 complex locus C low (Ly6Clo) macrophages, contributing to a reduced level of TIMP1 and increased MMP2. Notably, the Wnt pathway was involved in Sch B-mediated Ly6C macrophage phenotypic transformation. Further studies demonstrated that Sch B-treated macrophages had an inhibitory effect on HSC activation, which was associated with HSC FPT. GPX4, a negative regulator of FPT, was induced by Sch B and found to be involved in the crosstalk between macrophage and HSC FPT. Furthermore, HSC inactivation as well as FPT induced by Sch B-treated macrophages was blocked down by Wnt pathway agonist 1. Collectively, we demonstrate that Sch B inhibits liver fibrosis, at least partially, through mediating Ly6Clo macrophages and HSC FPT. Sch B enhances Wnt pathway inactivation, leading to the increase in Ly6Clo macrophages, which contributes to HSC FPT. Sch B may be a promising drug for liver fibrosis treatment.

Exploration and validation of a novel signature of seven necroptosis-related genes to improve the clinical outcome of hepatocellular carcinoma.

Necroptosis has been reported to be involved in cancer progression and associated with cancer prognosis. However, the prognostic values of necroptosis-related genes (NRGs) in hepatocellular carcinoma (HCC) remain largely unknown. This study aimed to build a signature on the basis of NRGs to evaluate the prognosis of HCC patients. In this study, using bioinformatic analyses of transcriptome sequencing data of HCC (n = 370) from The Cancer Genome Atlas (TCGA) database, 63 differentially expressed NRGs between HCC and adjacent normal tissues were determined. 24 differentially expressed NRGs were found to be related with overall survival (OS). Seven optimum NRGs, determined using Lasso regression and multivariate Cox regression analysis, were used to construct a new prognostic risk signature for predicting the prognosis of HCC patients. Then survival status scatter plots and survival curves demonstrated that the prognosis of patients with high-Riskscore was worse. The prognostic value of this 7-NRG signature was validated by the International Cancer Genome Consortium (ICGC) cohort and a local cohort (Wenzhou, China). Notably, Riskscore was defined as an independent risk factor for HCC prognosis using multivariate cox regression analysis. Immune infiltration analysis suggested that higher macrophage infiltration was found in patients in the high-risk group. Finally, enhanced 7 NRGs were found in HCC tissues by immunohistochemistry. In conclusion, a novel 7-NRG prognostic risk signature is generated, which contributes to the prediction in the prognosis of HCC patients for the clinicians.

Serum ribonucleotide reductase M2 is a potential biomarker for diagnosing and monitoring liver fibrosis in chronic hepatitis B patients.

It is known that ribonucleotide reductase M2 (RRM2) could be induced by hepatitis B virus (HBV) via DNA damage response. However, whether RRM2 is a potential biomarker for diagnosing and monitoring liver fibrosis in chronic hepatitis B (CHB) patients is still unclear. In this study, CHB patients from GSE84044 (a transcriptome data from GEO data set) were downloaded and RRM2 was selected as a hub gene. Interestingly, a positive correlation was found between serum RRM2 and liver fibrosis stage. The similar results were found in CHB patients with normal alanine aminotransferase (ALT). Notably, RRM2 could effectively differentiate preliminary fibrosis from advanced fibrosis in CHB patients with/without normal ALT. In addition, RRM2 had a better performance in diagnosing liver fibrosis than two commonly used noninvasive methods (aspartate aminotransferase-to-platelet ratio index and fibrosis index based on the four factors), two classic fibrotic biomarkers (hyaluronic acid and type IV collagen) as well as Mac-2 binding protein glycosylation isomer, a known serum fibrosis marker. Moreover, CHB patients with high RRM2, who were associated with advanced fibrosis, had higher expressions of immune checkpoints. Overall, serum RRM2 may be a promising biomarker for diagnosing and monitoring liver fibrosis in CHB patients.

Hepatocyte-derived exosomal miR-146a-5p inhibits hepatic stellate cell EMT process: a crosstalk between hepatocytes and hepatic stellate cells.

Recently, Salidroside (Sal) has been demonstrated to suppress hepatic stellate cell (HSC) activation, a crucial event for liver fibrosis. Moreover, Sal has been reported to decrease hepatocyte injury. A growing number of reports have indicated that the crosstalk between hepatocytes and HSCs is very crucial for liver fibrosis development. Whether Sal-treated hepatocytes could inhibit HSC activation is unclear. Exosomes, as vital vehicles of intercellular communication, have been shown to transfer cargos between hepatocytes and HSCs. Herein, we aimed to investigate the roles of exosomal miRNAs from Sal-treated hepatocytes in HSC activation as well as liver fibrosis. Our results showed that Sal suppressed carbon tetrachloride (CCl4)-induced liver fibrosis in vivo. HSC activation as well as cell proliferation was repressed in HSCs co-cultured with Sal-treated hepatocytes. Interestingly, miR-146a-5p was up-regulated by Sal in CCl4-treated mice. Also, enhanced miR-146a-5p was found in hepatocytes isolated from Sal-treated CCl4 mice and hepatocyte-derived exosomes. Notably, hepatocyte exosomal miR-146a-5p contributed to HSC inactivation. Inhibiting miR-146a-5p in hepatocyte exosomes resulted in reduced E-cadherin (E-cad) and increased desmin in HSCs, indicating that miR-146a-5p caused HSC inactivation via epithelial-mesenchymal transition (EMT). miR-146a-5p inhibition-mediated HSC activation and EMT process were blocked down by loss of EIF5A2. Further studies revealed that EIF5A2 was a target of miR-146a-5p. Furthermore, exosomes with miR-146a-5p overexpression inhibited liver fibrosis in CCl4 mice. Collectively, exosomal miR-146a-5p from Sal-treated hepatocytes inhibits HSC activation and liver fibrosis, at least in part, by suppressing EIF5A2 and EMT process.

Ginsenoside Rg1 Epigenetically Modulates Smad7 Expression in Liver Fibrosis via MicroRNA-152.

Background: Ginsenoside Rg1, a bioactive component of Ginseng, has demonstrated anti-inflammatory, anti-cancer, and hepatoprotective effects. It is known that the epithelial-mesenchymal transition (EMT) plays a key role in the activation of hepatic stellate cells (HSCs). Recently, Rg1 has been shown to reverse liver fibrosis by suppressing EMT, although the mechanism of Rg1-mediated anti-fibrosis effects is still largely unclear. Interestingly, Smad7, a negative regulator of the transforming growth factor ß (TGF-ß) pathway, is often methylated during liver fibrosis. Whether Smad7 methylation plays a vital role in the effects of Rg1 on liver fibrosis remains unclear. Methods: Anti-fibrosis effects were examined after Rg1 processing in vivo and in vitro. Smad7 expression, Smad7 methylation, and microRNA-152 (miR-152) levels were also analyzed. Results: Rg1 significantly reduced the liver fibrosis caused by carbon tetrachloride, and reduced collagen deposition was also observed. Rg1 also contributed to the suppression of collagenation and HSC reproduction in vitro. Rg1 caused EMT inactivation, reducing Desmin and increasing E-cadherin levels. Notably, the effect of Rg1 on HSC activation was mediated by the TGF-ß pathway. Rg1 induced Smad7 expression and demethylation. The over-expression of DNA methyltransferase 1 (DNMT1) blocked the Rg1-mediated inhibition of Smad7 methylation, and miR-152 targeted DNMT1. Further experiments suggested that Rg1 repressed Smad7 methylation via miR-152-mediated DNMT1 inhibition. MiR-152 inhibition reversed the Rg1-induced promotion of Smad7 expression and demethylation. In addition, miR-152 silencing led to the inhibition of the Rg1-induced EMT inactivation. Conclusion: Rg1 inhibits HSC activation by epigenetically modulating Smad7 expression and at least by partly inhibiting EMT.

20(S)- Protopanaxadiol suppresses hepatic stellate cell activation via WIF1 demethylation-mediated inactivation of the Wnt/ß-catenin pathway.

Background: 20(S)-protopanaxadiol (PPD), one of the main components of ginseng, has anti-inflammatory, anti-estrogenic, and anti-tumor activities. It is known that activated hepatic stellate cells (HSCs) are the primary producers of extracellular matrix (ECM) in the liver, and the Wnt/ß-catenin pathway participates in the activation of HSCs. We aimed to explore whether PPD inhibits liver fibrosis is associated with the Wnt/ß-catenin pathway inactivation. Methods: The anti-fibrotic roles of PPD were examined both in vitro and in vivo. We also examined the levels of Wnt inhibitory factor 1 (WIF1), DNA methyltransferase 1 (DNMT1) and WIF1 methylation. Results: PPD obviously ameliorated liver fibrosis in carbon tetrachloride (CCl4)-treated mice and reduced collagen deposition. PPD also suppressed the activation and proliferation of primary HSCs. Notably, PPD inhibited the Wnt/ß-catenin pathway, reduced TCF activity, and increased P-ß-catenin and GSK-3ß levels. Interestingly, WIF1 was found to mediate the inactivation of the Wnt/ß-catenin pathway in PPD-treated HSCs. WIF1 silencing suppressed the inhibitory effects of PPD on HSC activation and also restored α-SMA and type I collagen levels. The downregulation of WIF1 expression was associated with the methylation of its promoter. PPD induced WIF1 demethylation and restored WIF1 expression. Further experiments confirmed that DNMT1 overexpression blocked the effects of PPD on WIF1 expression and demethylation and enhanced HSC activation. Conclusion: PPD up-regulates WIF1 levels and impairs Wnt/ß-catenin pathway activation via the down-regulation of DNMT1-mediated WIF1 methylation, leading to HSC inactivation. Therefore, PPD may be a promising therapeutic drug for patients with liver fibrosis.

Ginsenoside Rh2 promotes hepatic stellate cell ferroptosis and inactivation via regulation of IRF1-inhibited SLC7A11.

BACKGROUND: Sustained liver fibrosis may lead to cirrhosis. Activated hepatic stellate cells (HSCs) are crucial for liver fibrosis development. Ferroptosis, a newly iron-dependent regulated cell death, has been demonstrated to be involved in HSC inactivation. PURPOSE: Ginsenoside Rh2 (GRh2), a natural bioactive product derived from ginseng, has been shown to promote HSC inactivation. However, the effect of GRh2 on HSC ferroptosis remains unclear. METHODS: We explored the effects of GRh2 on liver fibrosis in vivo and in vitro. RNA-sequence analysis was performed in HSCs after GRh2 treatment. The crosstalk between ferroptotic HSCs and macrophages was also explored. RESULTS: GRh2 alleviated liver fibrosis in vivo. In vitro, GRh2 reduced HSC proliferation and activation via ferroptosis, with increased intracellular iron, reactive oxygen species, malondialdehyde and glutathione depletion. The expression of SLC7A11, a negative regulator of ferroptosis, was obviously reduced by GRh2. Interestingly, interferon regulatory factor 1 (IRF1), a transcription factor, was predicted to bind the promoter region of SCL7A11. The interaction between IRF1 and SCL7A11 was further confirmed by the results of chromatin immunoprecipitation and luciferase reporter assays. Furthermore, loss of IRF1 led to an increase in SCL7A11, which contributed to the suppression of HSC ferroptosis and the enhancement of HSC activation in GRh2-treated HSCs. Further studies revealed that GRh2-induced HSC ferroptosis contributed to the inhibition of macrophage recruitment via regulation of inflammation-related genes. Moreover, GRh2 caused a reduction in liver inflammation in vivo. CONCLUSION: Collectively, GRh2 up-regulates IRF1 expression, resulting in the suppression of SLC7A11, which contributes to HSC ferroptosis and inactivation. GRh2 ameliorates liver fibrosis through enhancing HSC ferroptosis and inhibiting liver inflammation. GRh2 may be a promising drug for treating liver fibrosis.

LncRNA-MIAT activates hepatic stellate cells via regulating Hippo pathway and epithelial-to-mesenchymal transition.

Long non-coding RNA-myocardial infarction-associated transcript (lncRNA-MIAT) has been reported to play an important role in the development of multiple cancers. However, the biological roles of MIAT in liver fibrosis are still unknown. In this study, the expression of MIAT is up-regulated during liver fibrosis. Silencing MIAT leads to the suppression of hepatic stellate cell (HSC) proliferation and collagen expression. Double immunofluorescence analysis additionally demonstrates that MIAT inhibition leads to the suppression of type I collagen and α-SMA in vitro. In vivo, MIAT knockdown contributes to the inhibition of fibrosis progression and collagen accumulation. MIAT is confirmed as a target of miR-3085-5p, and the co-location of MIAT and miR-3085-5p is found in HSC cytoplasm. Interestingly, there is a negative correlation between MIAT expression and miR-3085-5p level in cirrhotic patients as well as activated HSCs. In addition, the effects of MIAT inhibition on HSC inactivation are blocked down by miR-3085-5p inhibitor. YAP is a target of miR-3085-5p. Reduced YAP caused by loss of MIAT is reversed by miR-3085-5p inhibitor. Notably, YAP knockdown results in the suppression of MIAT-mediated epithelial-to-mesenchymal transition (EMT) process. In conclusion, we demonstrate that MIAT enhances the activation of HSCs, at least in part, via miR-3085-5p/YAP/EMT signaling pathway.

Machine learning integrations develop an antigen-presenting-cells and T-Cells-Infiltration derived LncRNA signature for improving clinical outcomes in hepatocellular carcinoma.

As a highly heterogeneous cancer, the prognostic stratification and personalized management of hepatocellular carcinoma (HCC) are still challenging. Recently, Antigen-presenting-cells (APCs) and T-cells-infiltration (TCI) have been reported to be implicated in modifying immunology in HCC. Nevertheless, the clinical value of APCs and TCI-related long non-coding RNAs (LncRNAs) in the clinical outcomes and precision treatment of HCC is still obscure. In this study, a total of 805 HCC patients were enrolled from three public datasets and an external clinical cohort. 5 machine learning (ML) algorithms were transformed into 15 kinds of ML integrations, which was used to construct the preliminary APC-TCI related LncRNA signature (ATLS). According to the criterion with the largest average C-index in the validation sets, the optimal ML integration was selected to construct the optimal ATLS. By incorporating several vital clinical characteristics and molecular features for comparison, ATLS was demonstrated to have a relatively more significantly superior predictive capacity. Additionally, it was found that the patients with high ATLS score had dismal prognosis, relatively high frequency of tumor mutation, remarkable immune activation, high expression levels of T cell proliferation regulators and anti-PD-L1 response as well as extraordinary sensitivity to Oxaliplatin/Fluorouracil/Lenvatinib. In conclusion, ATLS may serve as a robust and powerful biomarker for improving the clinical outcomes and precision treatment of HCC.

Machine learning integrations for development of a T-cell-tolerance derived signature to improve the clinical outcomes and precision treatment of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is characterized by high rates of recurrence and metastasis and poor prognosis. A recently discovered concept of T cell tolerance (TCT) has become an entirely new target of cancer immunotherapy. Unfortunately, the effect of TCT on the outcomes of HCC has not been explored. In this study, 7 public datasets and one external clinical cohort, including 1716 HCC patients were explored. Through WGCNA analysis and differential analysis, we explored the key TCT-related modulates. A total of 95 machine learning integrations across all validation cohorts were compared and the optimal method with the highest average C-index value was selected to construct the TCT derived signature (TCTS). In all independent clinical cohorts, TCTS showed accurate prediction of the prognosis, and was significantly correlated with clinical indicators and molecular features. Compared with 77 published gene signatures, the TCTS exhibited superior predictive performance. In the external clinical cohort, a novel nomogram (comprising TNM stage, Hepatitis B, Vascular invasion, Perineural invasion, AFP and TCTS) was constructed to test the clinical performance of TCTS. The results showed that the high TCTS scoring group showed dismal prognosis, improved sensitivity to oxaliplatin and good response to anti-PD-1/PD-L1 immunotherapy. Moreover, the low TCTS score group had few genomic alterations, low immune activation and low PD-1/PD-L1 expression levels. In conclusion, TCTS is an ideal biomarker for predicting the clinical outcomes and improving precision treatment of HCC.

Development and validation of a potential biomarker to improve the assessment of liver fibrosis progression in patients with chronic hepatitis B.

We aimed to develop and validate a novel combined score to improve the assessment of liver fibrosis progression in patients with chronic hepatitis B (CHB). In this study, a total of 331 CHB patients from three cohorts who underwent liver biopsy were enrolled, and the Scheuer system was used for liver fibrosis classification. The combined score was derived by principal component analysis of key differentially expressed genes. For significant liver fibrosis (≥S2), the areas under the receiver operating characteristics curves (AUROCs) of the combined score were 0.838, 0.842, and 0.881 in the three cohorts, respectively. And for advanced liver fibrosis (≥S3), the AUROCs were 0.794, 0.801, and 0.901, respectively. Compared with the results of AUROCs for aspartate aminotransferase≥to≥platelet ratio (APRI) and fibrosis index based on four factors (FIB-4) in the validation cohorts, better clinical diagnostic value for assessing the progression of liver fibrosis was found in the combined score. Additionally, univariate ordered logistic regression analysis indicated that the combined score could serve as a more superior and stable risk factor than APRI and FIB-4 in the assessment of liver fibrosis. For CHB patients with normal alanine aminotransferase (ALT), our results further emphasized the diagnostic value of the combined score for significant fibrosis (≥S2) and advanced fibrosis (≥S3). Moreover, it was found that patients with the high combined score, who were associated with the advanced fibrosis stage, had higher levels of drug sensitivity and immune checkpoint expression. In conclusion, the novel combined score could serve as a potential biomarker and contribute to improving the assessment of fibrosis stage in CHB patients.

A novel 10-gene ferroptosis-related prognostic signature in acute myeloid leukemia.

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies and exhibits a high rate of relapse and unfavorable outcomes. Ferroptosis, a relatively recently described type of cell death, has been reported to be involved in cancer development. However, the prognostic value of ferroptosis-related genes (FRGs) in AML remains unclear. In this study, we found 54 differentially expressed ferroptosis-related genes (DEFRGs) between AML and normal marrow tissues. 18 of 54 DEFRGs were correlated with overall survival (OS) (P<0.05). Using the least absolute shrinkage and selection operator (LASSO) Cox regression analysis, we selected 10 DEFRGs that were associated with OS to build a prognostic signature. Data from AML patients from the International Cancer Genome Consortium (ICGC) cohort as well as the First Affiliated Hospital of Wenzhou Medical University (FAHWMU) cohort were used for validation. Notably, the prognostic survival analyses of this signature passed with a significant margin, and the riskscore was identified as an independent prognostic marker using Cox regression analyses. Then we used a machine learning method (SHAP) to judge the importance of each feature in this 10-gene signature. Riskscore was shown to have the highest correlation with this 10-gene signature compared with each gene in this signature. Further studies showed that AML was significantly associated with immune cell infiltration. In addition, drug-sensitive analysis showed that 8 drugs may be beneficial for treatment of AML. Finally, the expressions of 10 genes in this signature were verified by real-time quantitative polymerase chain reaction. In conclusion, our study establishes a novel 10-gene prognostic risk signature based on ferroptosis-related genes for AML patients and FRGs may be novel therapeutic targets for AML.

Machine learning identifies exosome features related to hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is one of the most malignant tumors with a poor prognosis. There is still a lack of effective biomarkers to predict its prognosis. Exosomes participate in intercellular communication and play an important role in the development and progression of cancers. Methods: In this study, two machine learning methods (univariate feature selection and random forest (RF) algorithm) were used to select 13 exosome-related genes (ERGs) and construct an ERG signature. Based on the ERG signature score and ERG signature-related pathway score, a novel RF signature was generated. The expression of BSG and SFN, members of 13 ERGs, was examined using real-time quantitative polymerase chain reaction and immunohistochemistry. Finally, the effects of the inhibition of BSG and SFN on cell proliferation were examined using the cell counting kit-8 (CCK-8) assays. Results: The ERG signature had a good predictive performance, and the ERG score was determined as an independent predictor of HCC overall survival. Our RF signature showed an excellent prognostic ability with the area under the curve (AUC) of 0.845 at 1 year, 0.811 at 2 years, and 0.801 at 3 years in TCGA, which was better than the ERG signature. Notably, the RF signature had a good performance in the prediction of HCC prognosis in patients with the high exosome score and high NK score. Enhanced BSG and SFN levels were found in HCC tissues compared with adjacent normal tissues. The inhibition of BSG and SFN suppressed cell proliferation in Huh7 cells. Conclusion: The RF signature can accurately predict prognosis of HCC patients and has potential clinical value.

Development and validation of a novel necroptosis-related score to improve the outcomes of clear cell renal cell carcinoma.

Necroptosis has been indicated as a key regulator of tumor progression. However, the prognostic regulatory role of necroptosis in clear cell renal cell carcinoma (ccRCC) needs to be further investigated. In this study, necroptosis-related subtypes were identified by mining the public cohort (n = 530) obtained from The Cancer Genome Atlas. By applying Principal Component Analysis (PCA), the necroptosis-related scores (N-Score) were developed to assess the prognosis procession of ccRCC. The results were further validated by an external clinical cohort (n = 116) obtained from the First Affiliated Hospital of Wenzhou Medical University. It has been found that N-Score could precisely distinguish the prognostic outcomes of patients as an independent risk factor (Hazard ratio = 4.990, 95% confidence interval (CI) = 2.007-12.403, p < 0.001). In addition, changes in N-Score were associated with differences in tumor mutational burden as well as immune infiltration characterization. Moreover, higher N-Scores were also correlated significantly molecular drug sensitivity and stronger immune checkpoint activity. Notably, the prognosis of ccRCC could be effectively guided by combining the N-Scores and external clinical indicators. In conclusion, N-Scores could be served as a robust and effective biomarker to improve the prognosis outcomes and targeted therapy of ccRCC.

Construction of a novel exosomes-related gene signature in hepatocellular carcinoma.

Background: Exosomes are extracellular vesicles between 40 and 150 nm in diameter and are cargoes for a wide range of small biological molecules. Recent studies have reported that lncRNAs, miRNAs, circRNAs in serum exosomes may serve as biomarkers to predict hepatocellular carcinoma (HCC) prognosis. However, the prognostic values of exosomes-related mRNAs in HCC are still unclear. Methods: Data of HCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The serum exosome sequencing data of HCC patients and healthy individuals were obtained from the exobase database. Univariate cox regression analysis was used to identify prognostic exosomes-related genes. LASSO and multivariate cox regression analyses were applied to construct prognostic signature. Results: 22 exosomes-related mRNAs differentially expressed between HCC tissues and normal tissues were identified. Then, 8 prognostic exosomes-related mRNAs were screened. Subsequently, G6PD and ADAMTS5, selected by LASSO and multivariate cox regression analyses, were used to construct a prognostic signature. The patients with high-risk scores had a poor prognosis in TCGA cohort as well as ICGC cohort. Notably, this prognostic signature was also validated in a local cohort collected from the First Affiliated Hospital of Wenzhou Medical University. Receiver Operating Characteristic (ROC) analyses indicated that the signature had a good performance in all the cohorts. The gene set enrichment analysis revealed that this signature was associated with cell cycle and metabolism pathways. Immune infiltration analysis indicated that the patients with high-risk scores had a higher M0 macrophages infiltration. The univariate and multivariate cox regression analyses identified that the risk score is an independent risk factor for HCC. In addition, a nomogram containing age, gender, stage and risk score was constructed to precisely predict HCC prognosis. Conclusion: In conclusion, we develop a novel exosomes-related gene signature that helps to predict HCC prognosis.

M6A-related lncRNAs predict clinical outcome and regulate the tumor immune microenvironment in hepatocellular carcinoma.

LncRNA N6-methylandenosine (m6A) modification has been shown to be associated with the constitution of the tumor microenvironment (TME) and tumorigenesis. It's essential to understand the mechanisms of lncRNA m6A modification in hepatocellular carcinoma (HCC) and identify relative prognostic predictors to guide therapy and explore potential therapeutic targets. Pearson correlation analysis was performed to identify m6A-related lncRNAs in 374 patients with HCC. Unsupervised cluster analysis of the potential m6A-related lncRNA-based HCC subtypes was conducted, followed by the concurrent analysis of their relationship with TME characteristics, immune checkpoints, immune features, and prognosis through single sample gene set enrichment analysis and ESTIMATE algorithm. Cox regression analyses were performed to screen prognostic m6A-related lncRNA, construct an m6A-related lncRNA signature (m6A-RLRS), and establish an integrated nomogram for the prognosis of patients with HCC. We identified 61 m6A-related lncRNAs and two HCC subtypes defined by consensus cluster of m6A-related lncRNAs with distinct clinical features. Progression-free survival (PFS), three TME-related scores, 15 immune-associated gene sets, and two immune checkpoints expression were found to be significantly different among the two subtypes. Twenty-five prognostic m6A-related lncRNAs were determined, four of which were included to establish an m6A-RLRS with favorable discrimination, and the signature was validated in the validation set and an independent FAHWMU cohort (n = 60). Furthermore, a novel nomogram combining signature and clinical predictors was generated with a C-index of 0.703, and an original ceRNA regulatory network consisting of 9 lncRNAs, 28 miRNAs, and 75 target mRNAs was constructed. Finally, the differential expression of four m6A-related lncRNA was verified by qRT-PCR. In conclusion, m6A-related lncRNA prognostic signature and molecular subtype contributes to accurately predict the prognosis of HCC and provide potential novel therapeutic targets.

Kaempferol Inhibits Hepatic Stellate Cell Activation by Regulating miR-26b-5p/Jag1 Axis and Notch Pathway.

Kaempferol, a natural flavonoid molecule, has demonstrated anti-inflammatory, antimicrobial and antioxidant activities. Recent studies have shown the beneficial effects of kaempferol on liver fibrosis. Notch pathway has been reported to be involved in the aberrant activation of hepatic stellate cells (HSCs). However, whether Notch pathway plays a key role in the anti-fibrotic effects of kaempferol is largely unknown. In this study, kaempferol significantly suppressed liver fibrosis in CCl4 mice, with reduced collagen deposition as well as restored liver function. In vitro, kaempferol enhanced the suppression of HSC activation, with a decrease in α-SMA as well as collagen level. It was found that Notch pathway played an important role in kaempferol-reduced the activation of HSCs. Jag1, a ligand of Notch pathway, was obviously inhibited by kaempferol. Overexpression of Jag1 effectively abolished kaempferol-induced HSC inactivation. Furthermore, Jag1 was demonstrated as a target of microRNA-26b-5p (miR-26b-5p). Interestingly, miR-26b-5p inhibitor prevented HSC activation inhibition caused by kaempferol. Further studies indicated that kaempferol inhibited Notch pathway via miR-26b-5p and Jag1, leading to HSC inactivation. Collectively, we demonstrate that kaempferol could inhibit HSC activation, at least in part, via miR-26b-5p-mediated Jag1 axis and Notch pathway. Kaempferol may serve as a promising drug in the application of treating liver fibrosis.

Signature Construction and Molecular Subtype Identification Based on Pyroptosis-Related Genes for Better Prediction of Prognosis in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. However, there is a lack of adequate means of treatment prognostication for HCC. Pyroptosis is a newly discovered way of programmed cell death. However, the prognostic role of pyroptosis in HCC has not been thoroughly investigated. Here, we generated a novel prognostic signature to evaluate the prognostic value of pyroptosis-related genes (PRGs) using the data from The Cancer Genome Atlas (TCGA) database. The accuracy of the signature was validated using survival analysis through the International Cancer Genome Consortium cohort (n = 231) and the First Affiliated Hospital of Wenzhou Medical University cohort (n = 180). Compared with other clinical factors, the risk score of the signature was found to be associated with better patient outcomes. The enrichment analysis identified multiple pathways related with pyroptosis in HCC. Furthermore, drug sensitivity testing identified six potential chemotherapeutic agents to provide possible treatment avenues. Interestingly, patients with low risk were confirmed to be associated with lower tumor mutation burden (TMB). However, patients at high risk were found to have a higher count of immune cells. Consensus clustering was performed to identify two main molecular subtypes (named clusters A and B) based on the signature. It was found that compared with cluster B, better survival outcomes and lower TMB were observed in cluster A. In conclusion, signature construction and molecular subtype identification of PRGs could be used to predict the prognosis of HCC, which may provide a specific reference for the development of novel biomarkers for HCC treatment.