Role of ACSL4 in modulating farnesoid X receptor expression and M2 macrophage polarization in HBV-induced hepatocellular carcinoma.

The intricate relationship between bile acid (BA) metabolism, M2 macrophage polarization, and hepatitis B virus-hepatocellular carcinoma (HBV-HCC) necessitates a thorough investigation of ACSL4's (acyl-CoA synthetase long-chain family member 4) role. This study combines advanced bioinformatics and experimental methods to elucidate ACSL4's significance in HBV-HCC development. Using bioinformatics, we identified differentially expressed genes in HBV-HCC. STRING and gene set enrichment analysis analyses were employed to pinpoint critical genes and pathways. Immunoinfiltration analysis, along with in vitro and in vivo experiments, assessed M2 macrophage polarization and related factors. ACSL4 emerged as a pivotal gene influencing HBV-HCC. In HBV-HCC liver tissues, ACSL4 exhibited upregulation, along with increased levels of M2 macrophage markers and BA. Silencing ACSL4 led to heightened farnesoid X receptor (FXR) expression, reduced BA levels, and hindered M2 macrophage polarization, thereby improving HBV-HCC conditions. This study underscores ACSL4's significant role in HBV-HCC progression. ACSL4 modulates BA-mediated M2 macrophage polarization and FXR expression, shedding light on potential therapeutic targets and novel insights into HBV-HCC pathogenesis.

ErbB3 is required for hyperaminoacidemia-induced pancreatic α cell hyperplasia.

Blood amino acid levels are maintained in a narrow physiological range. The pancreatic α cells have emerged as the primary aminoacidemia regulator through glucagon secretion to promote hepatic amino acid catabolism. Interruption of glucagon signaling disrupts the liver-α cells axis leading to hyperaminoacidemia, which triggers a compensatory rise in glucagon secretion and α cell hyperplasia. The mechanisms of hyperaminoacidemia-induced α cell hyperplasia remain incompletely understood. Using a mouse α cell line and in vivo studies in zebrafish and mice, we found that hyperaminoacidemia-induced α cell hyperplasia requires ErbB3 signaling. In addition to mechanistic target of rapamycin complex 1, another ErbB3 downstream effector signal transducer and activator of transcription 3 also plays a role in α cell hyperplasia. Mechanistically, ErbB3 may partner with ErbB2 to stimulate cyclin D2 and suppress p27 via mechanistic target of rapamycin complex 1 and signal transducer and activator of transcription 3. Our study identifies ErbB3 as a new regulator for hyperaminoacidemia-induced α cell proliferation and a critical component of the liver-α cells axis that regulates aminoacidemia.

NAC1 transcriptional activation of LDHA induces hepatitis B virus immune evasion leading to cirrhosis and hepatocellular carcinoma development.

Our study aimed to elucidate the molecular mechanisms underlying NAC1 (nucleus accumbens associated 1) transcriptional regulation of LDHA and its role in HBV immune evasion, thus contributing to the development of cirrhosis and hepatocellular carcinoma (HCC). Utilizing public datasets, we performed differential gene expression and weighted gene co-expression network analysis (WGCNA) on HBV-induced cirrhosis/HCC data. We identified candidate genes by intersecting differentially expressed genes with co-expression modules. We validated these genes using the TCGA database, conducting survival analysis to pinpoint key genes affecting HBV-HCC prognosis. We also employed the TIMER database for immune cell infiltration data and analyzed correlations with identified key genes to uncover potential immune escape pathways. In vitro, we investigated the impact of NAC1 and LDHA on immune cell apoptosis and HBV immune evasion. In vivo, we confirmed these findings using an HBV-induced cirrhosis model. Bioinformatics analysis revealed 676 genes influenced by HBV infection, with 475 genes showing differential expression in HBV-HCC. NAC1 emerged as a key gene, potentially mediating HBV immune escape through LDHA transcriptional regulation. Experimental data demonstrated that NAC1 transcriptionally activates LDHA, promoting immune cell apoptosis and HBV immune evasion. Animal studies confirmed these findings, linking NAC1-mediated LDHA activation to cirrhosis and HCC development. NAC1, highly expressed in HBV-infected liver cells, likely drives HBV immune escape by activating LDHA expression, inhibiting CD8 + T cells, and promoting cirrhosis and HCC development.

Bioinformatics analysis based on DNA methylation data identified in lung adenocarcinoma subgroups with different immune characteristics and clinical outcomes.

Background: DNA methylation can be used to predict clinical outcomes and improve the classification of tumors. The present study aimed to develop a new lung adenocarcinoma (LUAD) classification system according to the immune cell gene-related methylation sites and to reveal the survival outcomes, clinical characteristics, immune cell infiltration, stem cell characteristics, and genomic variations of each molecular subgroup. Methods: The DNA methylation sites of LUAD samples collected from The Cancer Genome Atlas (TCGA) database were analyzed, and the prognosis-related differential methylation sites (DMS) were screened. Consistent clustering of the samples was conducted using ConsensusClusterPlus, and the classification results were verified by principal component analysis (PCA). The survival and clinical results, immune cell infiltration, stemness, DNA mutation, and copy number variation (CNV) of each molecular subgroup were analyzed. Results: A total of 40 DMS were obtained by difference and univariate COX analyses, and the TCGA LUAD samples were divided into three subgroups: cluster 1 (C1), cluster 2 (C2), and cluster 3 (C3). Among these subgroups, the overall survival (OS) of C3 was significantly higher than that of C1 and C2. Compared with C1 and C3, C2 had the lowest innate immune cell and adaptive immune cell infiltration scores; the lowest stromal score, immune score, and iconic immune checkpoint expression; and the highest expression of messenger RNA (mRNA) expression-based stemness indices (mRNAsi), DNA methylation-based stemness index (mDNAsi), and tumor mutational burden (TMB). Conclusions: In this study, we proposed a LUAD typing system based on DMS, which was closely related to the survival, clinical features, immune characteristics, and genomic variations of LUAD, and may contribute to the development of personalized therapy for new specific subtypes.

Single-cell RNA sequencing reveals the mediatory role of cancer-associated fibroblast PTN in hepatitis B virus cirrhosis-HCC progression.

BACKGROUND: Cancer-associated fibroblasts (CAFs) are essential stromal components in the tumor microenvironment of hepatocellular carcinoma (HCC). Hepatitis B virus (HBV) infection induces pathological changes such as liver fibrosis/cirrhosis and HCC. The aim of this research was to explore the novel mediators of CAFs to modulate HBV cirrhosis-HCC progression. METHODS: The single-cell transcriptome data of HCC were divided into subsets, and the significant subset related to fibrotic cells, along with biological function, and clinical information of HCC was revealed by integrated data analyses. The cell communication, cells communicated weight analysis of signaling pathways, and key genes in signaling pathways analysis of significant CAFs subclasses were conducted to discover the novel gene of CAFs. Bioinformatics, vitro and HBV transfection assays were used to verify the novel gene is an important target for promoting the progression HBV cirrhosis-HCC progression. RESULTS: Fibroblasts derived from HCC single-cell data could be separated into three cell subclasses (CAF0-2), of which CAF2 was associated with the HCC clinical information. Fibroblasts have opposite developmental trajectories to immune B cells and CD8 + T cells. CAF0-2 had strong interaction with B cells and CD8 + T cells, especially CAF2 had the highest interaction frequency and weight with B cells and CD8 + T cells. Moreover, PTN participated in CAF2-related pathways involved in the regulation of cell communication, and the interactions among CAF2 and PTN contributed the most to B cells and CD8 + T cells. Furthermore, the genes of PTN, SDC1, and NCL from PTN signaling were highest expression in CAF2, B cells, and CD8 + T cells, respectively, and the interaction of PTN- SDC1 and PTN- NCL contributed most to the interaction of CAF2- B cells and CAF2-CD8 + T cells. Bioinformatics and vitro experiments confirm PTN was upregulated in HCC and promoted the proliferation of tumor cells, and HBV infection could initiate PTN to perform cirrhosis-HCC progression. CONCLUSION: Our findings revealed CAF was associated with hepatocarcinogenesis, and the functional importance of B cells and CD8 + T cells in modulating CAF in HCC. Importantly, PTN maybe a novel mediator of CAF to mediate HBV cirrhosis-HCC progression.

Systematically analyzed molecular characteristics of lung adenocarcinoma using metabolism-related genes classification.

High heterogeneity of lung adenocarcinoma (LUAD) is a major clinical challenge. This study aims to characterize the molecular features of LUAD through classification based on metabolism-related genes. A total of 500 LUAD samples from The Cancer Genome Atlas (TCGA) and 612 from Gene Expression Omnibus (GEO) were integrated with 2,753 metabolism-related genes to determine the molecular classification. Systematic bioinformatics analysis was used to conduct correlation analysis between metabolism-related classification and molecular characteristics of LUAD. LUAD patients were divided into three molecular clusters (C1-C3). Survival analysis revealed that C1 and C2 showed good and poor prognoses, respectively. Associational analysis of classification and molecular characteristics revealed that C1 was associated with low pathological stage, metabolic pathways, high metabolic process, active immune process and checkpoint, sensitive drug response, as well as a low genetic mutation. Nevertheless, C2 was associated with high pathological stage, carcinogenic pathways, low metabolic process, inactive immune signatures, resistant drug response, and frequent genetic mutation. Eventually, a classifier with 60 metabolic genes was constructed, confirming the robustness of molecular classification on LUAD. Our findings promote the understanding of LUAD molecular characteristics, and the research data may be used for providing information be helpful for clinical diagnosis and treatment.

Classification and Prognostic Characteristics of Hepatocellular Carcinoma Based on Glycolysis Cholesterol Synthesis Axis.

Background: Liver hepatocellular carcinoma (LIHC) is among the most frequent causes of cancer-related death across the world with a considerably poor prognosis. The current study targeted providing a new type of LIHC from the perspective of the glycolysis/cholesterol synthesis axis, predicting its prognostic characteristics, and exploring the potential role and mechanism of the glycolysis/cholesterol synthesis axis in the occurrence and development of LIHC. Methods: Based on the two expression profile data and clinical information of LIHC in The Cancer Genome Atlas (TCGA) database and hepatocellular carcinoma database (HCCDB), as well as glycolysis/cholesterol-related genes from the Molecular Signatures Database (MSigDB), unsupervised consistent clustering method was used to identify molecular subtypes. In addition, the differential genes were identified by limma package, and then the gene set was enriched, analyzed, and annotated by WebGestaltR package. At the same time, the immune infiltration analysis of tumor samples was carried out using the ESTIMATE to evaluate the tumor immune score of the samples. Finally, the differences in clinical characteristics among molecular subtypes were measured using univariate and multivariate Cox analyses. Results: According to the median standardized expression levels of glycolysis/cholesterol production genes, samples were divided into four groups (molecular subtypes): Quiescent group, Glycolysis group, Cholesterol group, and Mixed group. Significant prognostic differences were observed among the four groups. In both TCGA and HCCDB18 datasets, the prognosis of subtype Mixed was the worst, while Quiescent had a good prognosis. Cell cycle and oncogenic pathways were significantly enriched in the Mixed group. In addition, glycolysis and cholesterol production gene expressions were related to the prognostic LIHC subtype classification genes' expression levels. Conclusion: Metabolic classification regarding glycolysis and cholesterol production pathways provided new insights into the biological aspects of LIHC molecular subtypes and might help to develop personalized therapies for unique tumor metabolic profiles.

Integrative analysis of the characteristic of lipid metabolism-related genes for the prognostic prediction of hepatocellular carcinoma.

BACKGROUND: Dysregulation of lipid metabolism is implicated in the progression of hepatocellular carcinoma (HCC). We therefore investigated the molecular characteristics of lipid-metabolism-related genes in HCC. METHODS: Multi-dimensional bioinformatics analysis was conducted to comprehensively identify the lipid metabolism-related genes (LMRGs) from public databases, as well as the clinical information, immune features, and biological characteristics of HCC. The IMGR were then used to classify HCC into molecular phenotypes. Six lipid metabolism-related genes sets with the potential to predict the prognosis of HCC patients were identified. RESULTS: A total of 770 HCC patients with complete clinical information and corresponding 776 LMRGs were downloaded from 3 databases. Univariate cox and non-negative matrix factorization analyses were used to classify HCC patients into 2 clusters. This molecular classification was associated with overall survival, clinical characteristics, and immune cells. The biological function of the differentially expressed LMRGs in the 2 clusters showed the genes associated with tumor-related metabolism pathways. A combination of multivariate/univariate cox regression and least absolute shrinkage and selection operator analyses were conducted to build a 6 LMRGs signature (6-IS) to predict the prognosis of HCC. The 6-IS signature was found to be an independent prognostic factor. Performance of the 6-IS prognostic signature was verified in a validation set and compared with an external data set. Results revealed the 6-IS signature could effectively predict the prognosis of patients with HCC. CONCLUSIONS: This study provides new insights into the role of LMRG in the pathogenesis of HCC and presents a novel prognostic signature 6-IS monitoring the clinical course of HCC.

The Association between Immune Subgroups and Gene Modules for the Clinical, Cellular, and Molecular Characteristic of Hepatocellular Carcinoma.

The heterogeneity of hepatocellular carcinoma (HCC) is related to immune cell infiltration and genetic aberrations in the tumor microenvironment. This study aimed to identify the novel molecular typing of HCC according to the genetic and immune characteristics, to obtain accurate clinical management of this disease. We performed consensus clustering to divide 424 patients into different immune subgroups and assessed the reproducibility and efficiency in two independent cohorts with 921 patients. The associations between molecular typing and molecular, cellular, and clinical characteristics were investigated by a multidimensional bioinformatics approach. Furthermore, we conducted graph structure learning-based dimensionality reduction to depict the immune landscape to reveal the interrelation between the immune and gene systems in molecular typing. We revealed and validated that HCC patients could be segregated into 5 immune subgroups (IS1-5) and 7 gene modules with significantly different molecular, cellular, and clinical characteristics. IS5 had the worst prognosis and lowest enrichment of immune characteristics and was considered the immune cold type. IS4 had the longest overall survival, high immune activity, and antitumorigenesis, which were defined as the immune hot and antitumorigenesis types. In addition, immune landscape analysis further revealed significant intraclass heterogeneity within each IS, and each IS represented distinct clinical, cellular, and molecular characteristics. Our study provided 5 immune subgroups with distinct clinical, cellular, and molecular characteristics of HCC and may have clinical implications for precise therapeutic strategies and facilitate the investigation of immune mechanisms in HCC.

Identification and Characterization of Genes Related to the Prognosis of Hepatocellular Carcinoma Based on Single-Cell Sequencing.

The heterogeneity of hepatocellular carcinoma (HCC) highlights the importance of precision therapy. In recent years, single-cell RNA sequencing has been used to reveal the expression of genes at the single-cell level and comprehensively study cell heterogeneity. This study combined big data analytics and single-cell data mining to study the influence of genes on HCC prognosis. The cells and genes closely related to the HCC were screened through single-cell RNA sequencing (71,915 cells, including 34,414 tumor cells) and big data analysis. Comprehensive bioinformatics analysis of the key genes of HCC was conducted for molecular classification and multi-dimensional correlation analyses, and a prognostic model for HCC was established. Finally, the correlation between the prognostic model and clinicopathological features was analyzed. 16,880 specific cells, screened from the single-cell expression profile matrix, were divided into 20 sub-clusters. Cell typing revealed that 97% of these cells corresponded to HCC cell lines, demonstrating the high specificity of cells derived from single-cell sequencing. 2,038 genes with high variability were obtained. The 371 HCC samples were divided into two molecular clusters. Cluster 1 (C1) was associated with tumorigenesis, high immune score, immunotherapy targets (PD-L1 and CYLA-4), high pathological stage, and poor prognosis. Cluster 2 (C2) was related to metabolic and immune function, low immune score, low pathological stage, and good prognosis. Seven differentially expressed genes (CYP3A4, NR1I2, CYP2C9, TTR, APOC3, CYP1A2, and AFP) identified between the two molecular clusters were used to construct a prognostic model. We further validated the correlation between the seven key genes and clinical features, and the established prognostic model could effectively predict HCC prognosis. Our study identified seven key genes related to HCC that were used to construct a prognostic model through single-cell sequencing and big data analytics. This study provides new insights for further research on clinical targets of HCC and new biomarkers for clinical application.

Macrophages and neutrophils are necessary for ER stress-induced ß cell loss.

Persistent endoplasmic reticulum (ER) stress induces islet inflammation and ß cell loss. How islet inflammation contributes to ß cell loss remains uncertain. We have reported previously that chronic overnutrition-induced ER stress in ß cells causes Ripk3-mediated islet inflammation, macrophage recruitment, and a reduction of ß cell numbers in a zebrafish model. We show here that ß cell loss results from the intricate communications among ß cells, macrophages, and neutrophils. Macrophage-derived Tnfa induces cxcl8a in ß cells. Cxcl8a, in turn, attracts neutrophils to macrophage-contacted "hotspots" where ß cell loss occurs. We also show potentiation of chemokine expression in stressed mammalian ß cells by macrophage-derived TNFA. In Akita and db/db mice, there is an increase in CXCL15-positive ß cells and intra-islet neutrophils. Blocking neutrophil recruitment in Akita mice preserves ß cell mass and slows diabetes progression. These results reveal an important role of neutrophils in persistent ER stress-induced ß cell loss.

Ameliorating role of microRNA-378 carried by umbilical cord mesenchymal stem cells-released extracellular vesicles in mesangial proliferative glomerulonephritis.

BACKGROUND: Mesenchymal stem cells (MSCs) and their released extracellular vesicles (Evs) have shown protective effects against kidney diseases. This study aims to study the functions of umbilical cord MSCs-released Evs (ucMSC-Evs) and their implicated molecules in mesangial proliferative glomerulonephritis (MsPGN). METHODS: A rat model of MsPGN was induced by anti-Thy-1.1, and rat mesangial cells (rMCs) HBZY-1 were treated with PDGF-BB/DD to mimic MsPGN condition in vitro. Rats and cells were treated with different doses of ucMSC-Evs, and then the pathological changes in renal tissues and proliferation of rMCs were determined. Differentially expressed microRNAs (miRNAs) after Evs treatment were screened by microarray analysis. The interactions among miR-378, PSMD14, and TGFBR1 were analyzed. Gain- and loss-of function studies of miR-378 and PSMD14 were performed to explore their effects on tissue hyperplasia and rMC proliferation and their interactions with the TGF-ß1/Smad2/3 signaling pathway. RESULTS: The ucMSC-Evs treatment ameliorated mesangial hyperplasia and fibrosis in rat renal tissues and suppressed the aberrant proliferation of rMCs in a dose-dependent manner. miR-378 was the most upregulated miRNA in tissues and cells after ucMSC-Evs treatment. miR-378 directly targeted PSMD14, and PSMD14 maintained the stability of TGFBR1 through deubiquitination modification, which led to TGF-ß1/Smad2/3 activation. Either miR-378 knockdown or PSMD14 overexpression diminished the protective functions of ucMSC-Evs by activating the TGF-ß1/Smad2/3 signaling pathway. CONCLUSION: UcMSC-Evs ameliorate pathological process in MsPGN through the delivery of miR-378, which suppresses PSMD14-mediated TGFBR1 stability and inactivates the TGF-ß1/Smad2/3 signaling pathway to reduce tissue hyperplasia and rMC proliferation. Video abstract.

Exosomal circSHKBP1 participates in non-small cell lung cancer progression through PKM2-mediated glycolysis.

Non-small cell lung cancer (NSCLC) has a high morbidity and mortality, and it is imperative to explore the latent pathogenesis mechanism of NSCLC progression to find potential prognostic biomarkers and therapeutic targets. The present study aimed to explore the biological function of circSHKBP1 in NSCLC. circSHKBP1 was found to be upregulated in NSCLC tissues and cell lines and was enriched in exosomes derived from NSCLC cells. Exosomal circSHKBP1 enhanced the proliferation, migration, invasion, and stemness of NSCLC cells. miRNA-1294 was identified as a target for circSHKBP1, and circSHKBP1 upregulated PKM2 expression by sponging miR-1294. Exosomal circSHKBP1 regulated glycolysis through PKM2 in a HIF-1α-dependent manner in NSCLC cells and promoted M2 polarization and macrophage recruitment. Moreover, exosomal circSHKBP1 promoted NSCLC cell growth, metastasis, and M2 infiltration in vivo. Thus, exosomal circSHKBP1 participated in the progression of NSCLC via the miR-1294/PKM2 axis. circSHKBP1 may be potential biomarker for the diagnosis and treatment of NSCLC.

Prospective Analysis of Proteins Carried in Extracellular Vesicles with Clinical Outcome in Hepatocellular Carcinoma.

Background: Extracellular vehicles (EVs) contain different proteins that relay information between tumor cells, thus promoting tumorigenesis. Therefore, EVs can serve as an ideal marker for tumor pathogenesis and clinical application. Objective: Here, we characterised EV-specific proteins in hepatocellular carcinoma (HCC) samples and established their potential protein-protein interaction (PPI) networks. Materials and Methods: We used multi-dimensional bioinformatics methods to mine a network module to use as a prognostic signature and validated the model's prediction using additional datasets. The relationship between the prognostic model and tumor immune cells or the tumor microenvironment status was also examined. Results: 1134 proteins from 316 HCC samples were mapped to the exoRBase database. HCC-specific EVs specifically expressed a total of 437 proteins. The PPI network revealed 321 proteins and 938 interaction pathways, which were mined to identify a three network module (3NM) with significant prognostic prediction ability. Validation of the 3NM in two more datasets demonstrated that the model outperformed the other signatures in prognostic prediction ability. Functional analysis revealed that the network proteins were involved in various tumor-related pathways. Additionally, these findings demonstrated a favorable association between the 3NM signature and macrophages, dendritic, and mast cells. Besides, the 3NM revealed the tumor microenvironment status, including hypoxia and inflammation. Conclusion: These findings demonstrate that the 3NM signature reliably predicts HCC pathogenesis. Therefore, the model may be used as an effective prognostic biomarker in managing patients with HCC.

Pancreatic cancer: A review of epidemiology, trend, and risk factors.

Despite rapid advances in modern medical technology and significant improvements in survival rates of many cancers, pancreatic cancer is still a highly lethal gastrointestinal cancer with a low 5-year survival rate and difficulty in early detection. At present, the incidence and mortality of pancreatic cancer are increasing year by year worldwide, no matter in the United States, Europe, Japan, or China. Globally, the incidence of pancreatic cancer is projected to increase to 18.6 per 100000 in 2050, with the average annual growth of 1.1%, meaning that pancreatic cancer will pose a significant public health burden. Due to the special anatomical location of the pancreas, the development of pancreatic cancer is usually diagnosed at a late stage with obvious clinical symptoms. Therefore, a comprehensive understanding of the risk factors for pancreatic cancer is of great clinical significance for effective prevention of pancreatic cancer. In this paper, the epidemiological characteristics, developmental trends, and risk factors of pancreatic cancer are reviewed and analyzed in detail.

RBM15-mediated N6-methyladenosine modification affects COVID-19 severity by regulating the expression of multitarget genes.

Severe coronavirus disease 2019 (COVID-19) is characterized by symptoms of lymphopenia and multiorgan damage, but the underlying mechanisms remain unclear. To explore the function of N6-methyladenosine (m6A) modifications in COVID-19, we performed microarray analyses to comprehensively characterize the m6A epitranscriptome. The results revealed distinct global m6A profiles in severe and mild COVID-19 patients. Programmed cell death and inflammatory response were the major biological processes modulated by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Further, RBM15, a major m6A methyltransferase, was significantly elevated and positively correlated with disease severity. Silencing RBM15 drastically reduced lymphocyte death in vitro. Knockdown of RBM15 remarkably suppressed the expression levels of multitarget genes related to programmed cell death and inflammatory response. This study shows that SARS-CoV-2 infection alters the m6A epitranscriptome of lymphocytes, particularly in the case of severe patients. RBM15 regulated host immune response to SARS-CoV-2 by elevating m6A modifications of multitarget genes. These findings indicate that RBM15 can serve as a target for the treatment of COVID-19.

Hepatitis B virus P protein initiates glycolytic bypass in HBV-related hepatocellular carcinoma via a FOXO3/miRNA-30b-5p/MINPP1 axis.

BACKGROUND: Hepatitis B virus (HBV) infection is a crucial risk factor for hepatocellular carcinoma (HCC). However, its underlying mechanism remains understudied. METHODS: Microarray analysis was conducted to compare the genes and miRNAs in liver tissue from HBV-positive and HBV-negative HCC patients. Biological functions of these biomarkers in HBV-related HCC were validated via in vitro and in vivo experiments. Furthermore, we investigated the effect of HBV on the proliferation and migration of tumor cells in HBV-positive HCC tissue. Bioinformatics analysis was then performed to validate the clinical value of the biomarkers in a large HCC cohort. RESULTS: We found that a gene, MINPP1 from the glycolytic bypass metabolic pathway, has an important biological function in the development of HBV-positive HCC. MINPP1 is down-regulated in HBV-positive HCC and could inhibit the proliferation and migration of the tumor cells. Meanwhile, miRNA-30b-5p was found to be a stimulator for the proliferation of tumor cell through glycolytic bypass in HBV-positive HCC. More importantly, miRNA-30b-5p could significantly downregulate MINPP1 expression. Metabolic experiments showed that the miRNA-30b-5p/MINPP1 axis is able to accelerate the conversion of glucose to lactate and 2,3-bisphosphoglycerate (2,3-BPG). In the HBV-negative HCC cells, miRNA-30b-5p/MINPP1 could not regulate the glycolytic bypass to promote the tumorigenesis. However, once HBV was introduced into these cells, miRNA-30b-5p/MINPP1 significantly enhanced the proliferation, migration of tumor cells, and promoted the glycolytic bypass. We further revealed that HBV infection promoted the expression of miRNA-30b-5p through the interaction of HBV protein P (HBp) with FOXO3. Bioinformatics analysis on a large cohort dataset showed that high expression of MINPP1 was associated with favorable survival of HBV-positive HCC patients, which could lead to a slower progress of this disease. CONCLUSION: Our study found that the HBp/FOXO3/miRNA-30b-5p/MINPP1 axis contributes to the development of HBV-positive HCC cells through the glycolytic bypass. We also presented miRNA-30b-5p/MINPP1 as a novel biomarker for HBV-positive HCC early diagnosis and a potential pharmaceutical target for antitumor therapy.

Taste buds are not derived from neural crest in mouse, chicken, and zebrafish.

Our lineage tracing studies using multiple Cre mouse lines showed a concurrent labeling of abundant taste bud cells and the underlying connective tissue with a neural crest (NC) origin, warranting a further examination on the issue of whether there is an NC derivation of taste bud cells. In this study, we mapped NC cell lineages in three different models, Sox10-iCreERT2/tdT mouse, GFP+ neural fold transplantation to GFP- chickens, and Sox10-Cre/GFP-RFP zebrafish model. We found that in mice, Sox10-iCreERT2 specifically labels NC cell lineages with a single dose of tamoxifen at E7.5 and that the labeled cells were widely distributed in the connective tissue of the tongue. No labeled cells were found in taste buds or the surrounding epithelium in the postnatal mice. In the GFP+/GFP- chicken chimera model, GFP+ cells migrated extensively to the cranial region of chicken embryos ipsilateral to the surgery side but were absent in taste buds in the base of oral cavity and palate. In zebrafish, Sox10-Cre/GFP-RFP faithfully labeled known NC-derived tissues but did not label taste buds in lower jaw or the barbel. Our data, together with previous findings in axolotl, indicate that taste buds are not derived from NC cells in rodents, birds, amphibians or teleost fish.

Epigenetic silencing of ZIC4 contributes to cancer progression in hepatocellular carcinoma.

Inactivation of tumor suppressor gene played critical roles in the development and progression of human hepatocellular carcinoma (HCC). Zic family member 4 (ZIC4) is transcription factor and plays an important role in the developmental process. However, the expression and biological role of ZIC4 in HCC is poorly understood. Here, bioinformatics analysis based on The Cancer Genome Atlas (TCGA) database revealed an aberrant hypermethylation of ZIC4 in HCC. ZIC4 is frequently hypermethylated in promoter region and down expressed in HCC cells and tissues. Functionally, ZIC4 inhibition facilitated the proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in vitro and in vivo. Conversely, ZIC4 overexpression reduced proliferation and invasiveness of HCC cells. In addition, ZIC4 inhibition rescued the antitumor effect induced by enhancer of zeste homolog 2 (EZH2) knockdown or EZH2 inhibitor. Mechanistically, EZH2 knockdown or EZH2 inhibitor reduced the enrichment of EZH2 and H3K27me3 in ZIC4 promoter region and leading to the upregulation of ZIC4. Altogether, these data indicate that epigenetic silencing of ZIC4 by EZH2 mediated H3K27me3 is an important mechanism in HCC and provide a new therapeutic target for the treatment of hepatocellular carcinoma disease.

Comprehensive Study of Tumor Immune Microenvironment and Relevant Genes in Hepatocellular Carcinoma Identifies Potential Prognostic Significance.

Background: The tumor immune microenvironment (TIME) is an external immune system that regulates tumorigenesis. However, cellular interactions involving the TIME in hepatocellular carcinoma (HCC) are poorly characterized. Methods: In this study, we used multidimensional bioinformatic methods to comprehensively analyze cellular TIME characteristics in 735 HCC patients. Additionally, we explored associations involving TIME molecular subtypes and gene types and clinicopathological features to construct a prognostic signature. Results: Based on their characteristics, we classified TIME and gene signatures into three phenotypes (TIME T1-3) and two gene clusters (Gene G1-2), respectively. Further analysis revealed that Gene G1 was associated with immune activation and surveillance and included CD8+ T cells, natural killer cell activation, and activated CD4+ memory T cells. In contrast, Gene G2 was characterized by increased M0 macrophage and regulatory T cell levels. After calculation of principal component algorithms, a TIME score (TS) model, including 78 differentially expressed genes, was constructed based on TIME phenotypes and gene clusters. Furthermore, we observed that the Gene G2 cluster was characterized by high TS, and Gene G1 was characterized by low TS, which correlated with poor and favorable prognosis of HCC, respectively. Correlation analysis showed that TS had a positive association with several clinicopathologic signatures [such as grade, stage, tumor (T), and node (N)] and known somatic gene mutations (such as TP53 and CTNNB1). The prognostic value of the TS model was verified using external data sets. Conclusion: We constructed a TS model based on differentially expressed genes and involving immune phenotypes and demonstrated that the TS model is an effective prognostic biomarker and predictor for HCC patients.