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Summary: Increased blood amino acid levels (hyperaminoacidemia) stimulate pancreas expansion by unclear mechanisms. Here, by genetic and pharmacological disruption of glucagon receptor (GCGR) in mice and zebrafish, we found that the ensuing hyperaminoacidemia promotes pancreatic acinar cell proliferation and cell hypertrophy, which can be mitigated by a low protein diet in mice. In addition to mammalian target of rapamycin complex 1 (mTORC1) signaling, acinar cell proliferation required slc38a5, the most highly expressed amino acid transporter gene in both species. Transcriptomics data revealed the activation signature of yes-associated protein (YAP) in acinar cells of mice with hyperaminoacidemia, consistent with the observed increase in YAP-expressing acinar cells. Yap1 activation also occurred in acinar cells in gcgr−/− zebrafish, which was reversed by rapamycin. Knocking down yap1 in gcgr−/− zebrafish decreased mTORC1 activity and acinar cell proliferation and hypertrophy. Thus, the study discovered a previously unrecognized role of the YAP/Taz pathway in hyperaminoacidemia-induced acinar cell hypertrophy and hyperplasia.

Abstract 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.

Abstract 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.

Abstract 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.

Insufficient glucagon signalling results in hyperaminoacidemia, which drives adaptive proliferation of glucagon-producing α cells. Here the authors report that the amino acid sensitive calcium sensing receptor (CaSR) is necessary for α cell proliferation via Gq signalling during hyperaminoacidemia.

Type 2 diabetes (T2D) has become a worldwide epidemic, primarily driven by obesity from overnutrition and sedentariness. Recent results reveal there is heterogeneity in both pathology and treatment responses in T2D patients. Therefore, a variety of T2D animal models are necessary to obtain a mechanistic understanding of distinct disease processes. T2D results from insufficient insulin, either due to beta cell loss or inborn deficiency. Although decreases in beta cell mass can occur through loss of identity or cell death, in this review, we will highlight the T2D animal models that display beta cell death, including the Zucker Diabetic Fatty Rat, sand rat, db/db mouse, and a novel diabetic zebrafish model, the Zebrafish Muscle Insulin-Resistant (zMIR) fish. Procuring a mechanistic understanding of different T2D progression trajectories under a variety of contexts is paramount for developing and testing more individualized treatments.

Abstract 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-β1/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-β1/Smad2/3 activation. Either miR-378 knockdown or PSMD14 overexpression diminished the protective functions of ucMSC-Evs by activating the TGF-β1/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-β1/Smad2/3 signaling pathway to reduce tissue hyperplasia and rMC proliferation. Graphical Abstract Video abstract

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.

Summary: Here, we provide an optimized protocol to observe the interactions between infiltrating immune cells and islet β cells using live imaging. This protocol is useful for the characterization of cell-cell interactions and for the direct visualization of immune cell migration to the principal pancreatic islet during islet inflammation. We describe the preparation of zebrafish transgenic lines and detail steps for setting up the fish for live confocal imaging.For more details on the use and execution of this protocol, please refer to Yang et al. (2022).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract 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.

Insulin secretion from pancreatic beta cells is crucial for maintaining glucose homeostasis. The murine insulinoma derived MIN6 cell line is commonly used as a model for insulin secretion studies. However, its glucose responsiveness wanes with passaging, and insulin secretion is traditionally measured by expensive and time-consuming RIA or ELISA. We have developed a MIN6 subclone (MIN6-6) that allows for high throughput assay of insulin secretion in both population and single cells. In addition, MIN6-6 also expresses Cas9, permitting genome wide CRISPR screen of insulin secretion using a pooled sgRNA library. Here we provide methods for assaying insulin secretion both in bulk and in single cells in MIN6-6 cells, as well as for CRISPR screen of insulin secretion. • A highly glucose responsive beta cell reporter line (MIN6-6) with multiple engineered functionalities. • Allows for CRISPR/Cas9 mutagenesis, quantification of bulk insulin secretion by a straightforward nanoLuc assay and visualization of intracellular insulin granules. • Allows for en masse quantification of insulin granule exocytosis in individual cells under multiple conditions.

Objectives: Pancreatic beta cells secrete insulin postprandially and during fasting to maintain glucose homeostasis. Although glucose-stimulated insulin secretion (GSIS) has been extensively studied, much less is known about basal insulin secretion. Here, we performed a genome-wide CRISPR/Cas9 knockout screen to identify novel regulators of insulin secretion. Methods: To identify genes that cell autonomously regulate insulin secretion, we engineered a Cas9-expressing MIN6 subclone that permits irreversible fluorescence labeling of exocytic insulin granules. Using a fluorescence-activated cell sorting assay of exocytosis in low glucose and high glucose conditions in individual cells, we performed a genome-wide CRISPR/Cas9 knockout screen. Results: We identified several members of the COMMD family, a conserved family of proteins with central roles in intracellular membrane trafficking, as positive regulators of basal insulin secretion, but not GSIS. Mechanistically, we show that the Commander complex promotes insulin granules docking in basal state. This is mediated, at least in part, by its function in ITGB1 recycling. Defective ITGB1 recycling reduces its membrane distribution, the number of focal adhesions and cortical ELKS-containing complexes. Conclusions: We demonstrated a previously unknown function of the Commander complex in basal insulin secretion. We showed that by ITGB1 recycling, Commander complex increases cortical adhesions, which enhances the assembly of the ELKS-containing complexes. The resulting increase in the number of insulin granules near the plasma membrane strengthens basal insulin secretion.

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.

Abstract 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.

Abstract 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.

Abstract The pathological feature of diabetes, hyperglycemia, is a result of an inadequate number and/or function of insulin producing β cells. Replenishing functional β cells is a strategy to cure the disease. Although β-cell regeneration occurs in animal models under certain conditions, human β cells are refractory to proliferation. A better understanding of both the positive and the negative regulatory mechanisms of β-cell regeneration in animal models is essential to develop novel strategies capable of inducing functional β cells in patients. Zebrafish are an attractive model system for studying β-cell regeneration due to the ease to which genetic and chemical-genetic approaches can be used as well as their high regenerative capacity. Here, we highlight the current state of β-cell regeneration studies in zebrafish with an emphasis on cell signaling mechanisms.

The melanocortin-4 receptor (MC4R) plays a critical role in homeostasis and the regulation of body weight. Polymorphisms in the mc4r gene have been discovered and linked to growth, carcass composition, and meat quality traits. Therefore, we used the CRISPR-Cas9 system to target the mc4r gene in the most important freshwater aquaculture species in the USA, channel catfish, Ictalurus punctatus. Guide RNAs were designed to direct the Cas9 to the coding sequence of the channel catfish mc4r gene. gRNA(s)-Cas9 mixtures were delivered into one-cell embryos using electroporation and microinjection. For each treatment, the nature and rate of mutations were analyzed. Hatching and survival rates were calculated. The overall mutation rates were 30.6% and 66.7–90.6% for electroporation and microinjection, respectively. Mutated fish generated via electroporation or microinjection exhibited 38% and 20% improvement in body weight, respectively, when compared with the full-sib control. The mean feed conversion ratio of the mutants was 1.18 compared with 1.57 in the control fish. The improved growth and feed conversion indicate that the generation of mc4r-edited fish could economically benefit aquaculture production.

Abstract Background Renal cell carcinoma (RCC) is the most common kidney cancer and includes several molecular and histological subtypes with different clinical characteristics. The combination of DNA methylation and gene expression data can improve the classification of tumor heterogeneity, by incorporating differences at the epigenetic level and clinical features. Methods In this study, we identified the prognostic methylation and constructed specific prognosis-subgroups based on the DNA methylation spectrum of RCC from the TCGA database. Results Significant differences in DNA methylation profiles among the seven subgroups were revealed by consistent clustering using 3389 CpGs that indicated that were significant differences in prognosis. The specific DNA methylation patterns reflected differentially in the clinical index, including TNM classification, pathological grade, clinical stage, and age. In addition, 437 CpGs corresponding to 477 genes of 151 samples were identified as specific hyper/hypomethylation sites for each specific subgroup. A total of 277 and 212 genes corresponding to DNA methylation at promoter sites were enriched in transcription factor of GKLF and RREB-1, respectively. Finally, Bayesian network classifier with specific methylation sites was constructed and was used to verify the test set of prognoses into DNA methylation subgroups, which was found to be consistent with the classification results of the train set. DNA methylation-based classification can be used to identify the distinct subtypes of renal cell carcinoma. Conclusions This study shows that DNA methylation-based classification is highly relevant for future diagnosis and treatment of renal cell carcinoma as it identifies the prognostic value of each epigenetic subtype.

Coronavirus disease-2019 (COVID-19) is a novel respiratory disease induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It remains poorly understood how the host immune system responds to the infection during disease progression. We applied microarray analysis of the whole genome transcriptome to peripheral blood mononuclear cells (PBMCs) taken from severe and mild COVID-19 patients as well as healthy controls. Functional enrichment analysis of genes associated with COVID-19 severity indicated that disease progression is featured by overactivation of myeloid cells and deficient T cell function. The upregulation of TLR6 and MMP9, which promote the neutrophils-mediated inflammatory response, and the downregulation of SKAP1 and LAG3, which regulate T cells function, were associated with disease severity. Importantly, the regulation of these four genes was absent in patients with influenza A (H1N1). And compared with stimulation with hemagglutinin (HA) of H1N1 virus, the regulation pattern of these genes was unique in PBMCs response to Spike protein of SARS-CoV-2 ex vivo. Our data also suggested that severe SARS-CoV-2 infection largely silenced the response of type I interferons (IFNs) and altered the proportion of immune cells, providing a potential mechanism for the hypercytokinemia. This study indicates that SARS-CoV-2 infection impairs inflammatory and immune signatures in patients, especially those at severe stage. The potential mechanisms underpinning severe COVID-19 progression include overactive myeloid cells, impaired function of T cells, and inadequate induction of type I IFNs signaling.

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.

Hepatocellular carcinoma (HCC) is an immune-related tumor, that the type and number of tumor-infiltrated immune cells can serve as biomarkers for the clinical application. In this study, we constructed the immune model for diagnostic and prognostic prediction of HCC based on the systematic bioinformatics analyses on the component of immune cells from large samples transcriptome. CIBERSORT analysis found that the component of immune cells between 513 HCC and 473 adjacent normal tissues was different. M0 macrophages and regulatory T cells were mainly enriched in tumor tissues, whereas the CD8+ T cell and activated CD4+ memory T cells were the most in normal tissues. Using random forest and LASSO analyses, eleven immune cell types were mined out to construct the immune diagnostic model (IDG), which showed high efficiency in distinguishing cancer from normal tissues both in testing and validation groups. In addition, the immune prognostic model (IPG) consisting of five types of immune cells was constructed using the LASSO-Cox algorithm. It showed that HCC patients of the high-risk group had a significantly shorter survival time than those of low-risk group in testing, validation, and entire cohorts. Besides, Nomogram plots and decision curve analyses revealed that the IPG was positively associated with the HCC clinical classification of the Barcelona Clinic Liver Cancer (BCLC) stage, and showing more accuracy of prediction than independent BCLC stage. Related analyses found that IDG positively correlated with epithelial-mesenchymal transition (EMT) and cytotoxic factor-related genes and negatively correlated with immune checkpoint regulators related genes. From the GSEA analysis of the biological function of genes related to IPG, it was found that the genes of the high-risk group were enriched in some tumorigenesis related pathways, such as DNA replication, cell cycle, and PPARA. Therefore, this study identified IDG and IPG as efficient biomarkers for the diagnosis and prognosis of HCC.

Immune-related genes (IRGs) have been identified as critical drivers of the initiation and progression of hepatocellular carcinoma (HCC). This study is aimed at constructing an IRG signature for HCC and validating its prognostic value in clinical application. The prognostic signature was developed by integrating multiple IRG expression data sets from TCGA and GEO databases. The IRGs were then combined with clinical features to validate the robustness of the prognostic signature through bioinformatics tools. A total of 1039 IRGs were identified in the 657 HCC samples. Subsequently, the IRGs were subjected to univariate Cox regression and LASSO Cox regression analyses in the training set to construct an IRG signature comprising nine immune-related gene pairs (IRGPs). Functional analyses revealed that the nine IRGPs were associated with tumor immune mechanisms, including cell proliferation, cell-mediated immunity, and tumorigenesis signal pathway. Concerning the overall survival rate, the IRGPs distinctly grouped the HCC samples into the high- and low-risk groups. Also, we found that the risk score based on nine IRGPs was related to clinical and pathologic factors and remained a valid independent prognostic signature after adjusting for tumor TNM, grade, and grade in multivariate Cox regression analyses. The prognostic value of the nine IRGPs was further validated by forest and nomogram plots, which revealed that it was superior to the tumor TNM, grade, and stage. Our findings suggest that the nine-IRGP signature can be effective in determining the disease outcomes of HCC patients.

Type 2 diabetes mellitus (T2DM) is characterized by persistent hyperglycemia and is influenced by genetic and environmental factors. Optimum T2DM management involves early diagnosis and effective glucose-lowering therapies. Further research is warranted to improve our understanding of T2DM pathophysiology and reveal potential roles of genetic predisposition. We have previously developed an obesity-induced diabetic zebrafish model that shares common pathological pathways with humans and may be used to identify putative pharmacological targets of diabetes. Additionally, we have previously identified several candidate genes with altered expression in T2DM zebrafish. Here, we performed a small-scale zebrafish screening for these genes and discovered a new therapeutic target, centromere protein X (CENPX), which was further validated in a T2DM mouse model. In zebrafish, cenpx knockdown by morpholino or knockout by CRISPR/Cas9 system ameliorated overfeeding-induced hyperglycemia and upregulated insulin level. In T2DM mice, small-interfering RNA-mediated Cenpx knockdown decreased hyperglycemia and upregulated insulin synthesis in the pancreas. Gene expression analysis revealed insulin, mechanistic target of rapamycin, leptin, and insulin-like growth factor 1 pathway activation following Cenpx silencing in pancreas tissues. Thus, CENPX inhibition exerted antidiabetic effects via increased insulin expression and related pathways. Therefore, T2DM zebrafish may serve as a powerful tool in the discovery of new therapeutic gene targets.

Obesity and diabetes now considered global epidemics. The prevalence rates of diabetes are increasing in parallel with the rates of obesity and the strong connection between these two diseases has been coined as “diabesity.” The health risks of overweight or obesity include Type 2 diabetes mellitus (T2DM), coronary heart disease and cancer of numerous organs. Both obesity and diabetes are complex diseases that involve the interaction of genetics and environmental factors. The underlying pathogenesis of obesity and diabetes are not well understood and further research is needed for pharmacological and surgical management. Consequently, the use of animal models of obesity and/or diabetes is important for both improving the understanding of these diseases and to identify and develop effective treatments. Zebrafish is an attractive model system for studying metabolic diseases because of the functional conservation in lipid metabolism, adipose biology, pancreas structure, and glucose homeostasis. It is also suited for identification of novel targets associated with the risk and treatment of obesity and diabetes in humans. In this review, we highlight studies using zebrafish to model metabolic diseases, and discuss the advantages and disadvantages of studying pathologies associated with obesity and diabetes in zebrafish.