Single-cell genomics and spatial transcriptomics: Discovery of novel cell states and cellular interactions in liver physiology and disease biology

Hepatic Fibrosis and Cancer: The Silent Threats of Metabolic Syndrome

Metabolic dysfunction-associated steatotic (fatty) liver disease (MASLD), previously termed non-alcoholic fatty liver disease, is a worldwide epidemic that can lead to hepatic inflammation, fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). The disease is typically a component of the metabolic syndrome that accompanies obesity, and is often overlooked because the liver manifestations are clinically silent until late-stage disease is present (i.e., cirrhosis). Moreover, Asian populations, including Koreans, have a higher fraction of patients who are lean, yet their illness has the same prognosis or worse than those who are obese. Nonetheless, ongoing injury can lead to hepatic inflammation and ballooning of hepatocytes as classic features. Over time, fibrosis develops following activation of hepatic stellate cells, the liver's main fibrogenic cell type. The disease is usually more advanced in patients with type 2 diabetes mellitus, indicating that all diabetic patients should be screened for liver disease. Although there has been substantial progress in clarifying pathways of injury and fibrosis, there no approved therapies yet, but current research seeks to uncover the pathways driving hepatic inflammation and fibrosis, in hopes of identifying new therapeutic targets. Emerging molecular methods, especially single cell sequencing technologies, are revolutionizing our ability to clarify mechanisms underlying MASLD-associated fibrosis and HCC.

Breaks for Precision Medicine in Cancer: Development and Prospects of Spatiotemporal Transcriptomics

With the development of the social economy and the deepening understanding of cancer, cancer has become a significant cause of death, threatening human health. Although researchers have made rapid progress in cancer treatment strategies in recent years, the overall survival of cancer patients is still not optimistic. Therefore, it is essential to reveal the spatial pattern of gene expression, spatial heterogeneity of cell populations, microenvironment interactions, and other aspects of cancer. Spatiotemporal transcriptomics can help analyze the mechanism of cancer occurrence and development, greatly help precise cancer treatment, and improve clinical prognosis. Here, we review the integration strategies of single-cell RNA sequencing and spatial transcriptomics data, summarize the recent advances in spatiotemporal transcriptomics in cancer studies, and discuss the combined application of spatial multiomics, which provides new directions and strategies for the precise treatment and clinical prognosis of cancer.

Insight into Tetrabromobisphenol A-Associated Liver Transcriptional Landscape via Single Cell RNA Sequencing

In recent years, there has been growing concern over the rising incidence of liver diseases, with increasing exposure to environmental toxins as a significant contributing factor. However, the mechanisms of liver injury induced by environmental pollutants are largely unclear. Here, using tetrabromobisphenol A (TBBPA), a widely used brominated flame retardant, as an example, environmental toxin-induced liver toxicity in mice is characterized via single-cell sequencing technology. Heterogeneous gene expression profiles after exposure to TBBPA in major cell types of the liver are demonstrated. In hepatocytes, pathway analysis of differentially expressed genes reveals the enhanced interferon response and diminished metabolic processes. The disrupted endothelial functions in TBBPA-treated cells are then shown. Moreover, the activation of M2-polarization in Kupffer cells, as well as activated effector T and B cells are unveiled in TBBPA-treated cells. Finally, ligand-receptor pair analysis shows that TBBPA disrupts cell-cell communication and induces an inflammatory microenvironment. Overall, the results reveal that TBBPA-induced dysfunction of hepatocytes and endothelial cells may then activate and recruit other immune cells such as Kuffer cells, and T/NK cells into the liver, further increasing inflammatory response and liver injury. Thus, the results provide novel insight into undesiring environmental pollutant-induced liver injury.

A single-nucleus transcriptomic atlas of primate liver aging uncovers the pro-senescence role of SREBP2 in hepatocytes

Aging increases the risk of liver diseases and systemic susceptibility to aging-related diseases. However, cell type-specific changes and the underlying mechanism of liver aging in higher vertebrates remain incompletely characterized. Here, we constructed the first single-nucleus transcriptomic landscape of primate liver aging, in which we resolved cell type-specific gene expression fluctuation in hepatocytes across three liver zonations and detected aberrant cell-cell interactions between hepatocytes and niche cells. Upon in-depth dissection of this rich dataset, we identified impaired lipid metabolism and upregulation of chronic inflammation-related genes prominently associated with declined liver functions during aging. In particular, hyperactivated sterol regulatory element-binding protein (SREBP) signaling was a hallmark of the aged liver, and consequently, forced activation of SREBP2 in human primary hepatocytes recapitulated in vivo aging phenotypes, manifesting as impaired detoxification and accelerated cellular senescence. This study expands our knowledge of primate liver aging and informs the development of diagnostics and therapeutic interventions for liver aging and associated diseases.

Liver fibrosis in NAFLD/NASH: from pathophysiology towards diagnostic and therapeutic strategies

Liver fibrosis, as an excess deposition of extracellular matrix (ECM) components, results from chronic liver injury as well as persistent activation of inflammatory response and of fibrogenesis. Liver fibrosis is a major determinant for chronic liver disease (CLD) progression and in the last two decades our understanding on the major molecular and cellular mechanisms underlying the fibrogenic progression of CLD has dramatically improved, boosting pre-clinical studies and clinical trials designed to find novel therapeutic approaches. From these studies several critical concepts have emerged, starting to reveal the complexity of the pro-fibrotic microenvironment which involves very complex, dynamic and interrelated interactions between different hepatic and extrahepatic cell populations. This review will offer first a recapitulation of established and novel pathophysiological basic principles and concepts by intentionally focus the attention on NAFLD/NASH, a metabolic-related form of CLD with a high impact on the general population and emerging as a leading cause of CLD worldwide. NAFLD/NASH-related pro-inflammatory and profibrogenic mechanisms will be analysed as well as novel information on cells, mediators and signalling pathways which have taken advantage from novel methodological approaches and techniques (single cell genomics, imaging mass cytometry, novel in vitro two- and three-dimensional models, etc.). We will next offer an overview on recent advancement in diagnostic and prognostic tools, including serum biomarkers and polygenic scores, to support the analysis of liver biopsies. Finally, this review will provide an analysis of current and emerging therapies for the treatment of NAFLD/NASH patients.

SCAR: Single-cell and Spatially-resolved Cancer Resources

Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomic data from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety of tissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development.

Effects of silybin supplementation on growth performance, serum indexes and liver transcriptome of Peking ducks

As an emerging feed additive extracted from the traditional herb milk thistle, silybin has few applications and studies in Peking ducks. The aim of this study was to explore the practical significance of silymarin application in Peking ducks and to provide more theoretical support for the application of silymarin in livestock and poultry production. A total of 156 1-day-old healthy Peking ducks were randomly divided into four groups and supplemented with 0 mg/kg (control group), 400 mg/kg (S400), 800 mg/kg (S800) and 1,600 mg/kg (S1600) of silybin in the diets at day 14, to investigate the effects of silymarin on the growth, serum indexes and liver transcriptome of Peking ducks. The whole experiment lasted until day 42, and the sample collection was scheduled to take place in the morning. A substantial inprovement in average daily gain (ADG) and a decrease in feed conversion ratio (FCR) occurred in the S1600 group on days 14-28 compared to the control group (p < 0.05). The FCRs of other additive groups in the same period showed the same results. Supplementation of diets with silybin significantly increased serum IgA levels and when 1,600 mg/kg of silybin was given, levels of TNF-α and IL-6 were also significantly decreased (p < 0.05). In addition, we observed that the S1600 group had a significantly lower (p < 0.05) glutamine transaminase and an increased (p < 0.05) T-SOD level in the S400 group (p < 0.05). Liver transcriptome sequencing showed that 71 and 258 differentially expressed genes (DEGs) were identified in the S400 and S1600 groups, respectively, compared with the control group. DEGs related to cell composition and function, antigen processing and presentation were up-regulated, while DEGs related to insulin resistance and JAK-STAT were down-regulated. Conclusively, silybin can be used as a feed additive to improve the growth performance and health status of Peking ducks.

Spatial omics: An innovative frontier in aging research

Disentangling the impact of aging on health and disease has become critical as population aging progresses rapidly. Studying aging at the molecular level is complicated by the diverse aging profiles and dynamics. However, the examination of cellular states within aging tissues in situ is hampered by the lack of high-resolution spatial data. Emerging spatial omics technologies facilitate molecular and spatial analysis of tissues, providing direct access to precise information on various functional regions and serving as a favorable tool for unraveling the heterogeneity of aging. In this review, we summarize the recent advances in spatial omics application in multi-organ aging research, which has enhanced the understanding of aging mechanisms from multiple standpoints. We also discuss the main challenges in spatial omics research to date, the opportunities for further developing the technology, and the potential applications of spatial omics in aging and aging-related diseases.

Integration of single-cell and bulk RNA-sequencing to analyze the heterogeneity of hepatocellular carcinoma and establish a prognostic model

BACKGROUND

The highly heterogeneous nature of hepatocellular carcinoma (HCC) results in different responses and prognoses to the same treatment in patients with similar clinical stages.

AIMS

Thus, it is imperative to investigate the association between HCC tumor heterogeneity and treatment response and prognosis.

METHODS AND RESULTS

At first, we downloaded scRNA-seq, bulk RNA-seq, and clinical data from TCGA and GEO databases. We conducted quality control, normalization using SCTransform, dimensionality reduction using PCA, batch effect removal using Harmony, dimensionality reduction using UMAP, and cell annotation-based marker genes on the scRNA-seq data. We recognized tumor cells, identified tumor-related genes (TRGs), and performed cell communication analysis. Next, we developed a prognostic model using univariable Cox, LASSO, and multivariate Cox analyses. The signature was evaluated using survival analysis, ROC curves, C-index, and nomogram. Last, we studied the predictability of the signature in terms of prognosis and immunotherapeutic response for HCC, assessed a variety of drugs for clinical treatment, and used the qRT-PCR analysis to validate the mRNA expression levels of prognostic TRGs.

CONCLUSION

To conclude, this study expounded upon the influence of tumor cell heterogeneity on the prediction of treatment outcomes and prognosis in HCC. This, in turn, enhances the predictive ability of the TNM staging system and furnishes novel perspectives on the prognostic assessment and therapy of HCC.

Integrating bulk and single-cell data to predict the prognosis and identify the immune landscape in HNSCC

The complex interplay between tumour cells and the tumour microenvironment (TME) underscores the necessity for gaining comprehensive insights into disease progression. This study centres on elucidating the elusive the elusive role of endothelial cells within the TME of head and neck squamous cell carcinoma (HNSCC). Despite their crucial involvement in angiogenesis and vascular function, the mechanistic diversity of endothelial cells among HNSCC patients remains largely uncharted. Leveraging advanced single-cell RNA sequencing (scRNA-Seq) technology and the Scissor algorithm, we aimed to bridge this knowledge gap and illuminate the intricate interplay between endothelial cells and patient prognosis within the context of HNSCC. Here, endothelial cells were categorized into Scissorhigh and Scissorlow subtypes. We identified Scissor+ endothelial cells exhibiting pro-tumorigenic profiles and constructed a prognostic risk model for HNSCC. Additionally, four biomarkers also were identified by analysing the gene expression profiles of patients with HNSCC and a prognostic risk prediction model was constructed based on these genes. Furthermore, the correlations between endothelial cells and prognosis of patients with HNSCC were analysed by integrating bulk and single-cell sequencing data, revealing a close association between SHSS and the overall survival (OS) of HNSCC patients with malignant endothelial cells. Finally, we validated the prognostic model by RT-qPCR and IHC analysis. These findings enhance our comprehension of TME heterogeneity at the single-cell level and provide a prognostic model for HNSCC.

Microfluidics Coupled Mass Spectrometry for Single Cell Multi-Omics

Population-level analysis masks significant heterogeneity between individual cells, making it difficult to accurately reflect the true intricacies of life activities. Microfluidics is a technique that can manipulate individual cells effectively and is commonly coupled with a variety of analytical methods for single-cell analysis. Single-cell omics provides abundant molecular information at the single-cell level, fundamentally revealing differences in cell types and biological states among cell individuals, leading to a deeper understanding of cellular phenotypes and life activities. Herein, this work summarizes the microfluidic chips designed for single-cell isolation, manipulation, trapping, screening, and sorting, including droplet microfluidic chips, microwell arrays, hydrodynamic microfluidic chips, and microchips with microvalves. This work further reviews the studies on single-cell proteomics, metabolomics, lipidomics, and multi-omics based on microfluidics and mass spectrometry. Finally, the challenges and future application of single-cell multi-omics are discussed.

Stem Cell Therapy for Liver Diseases: Current Perspectives

Stem cell therapy offers a promising avenue for advanced liver disease cases as an alternative to liver transplantation. Clinical studies are underway to explore the potential of stem cells from various sources in treating different liver diseases. However, due to the variability among current studies, further validation is needed to ensure the safety and effectiveness of stem cell therapy. To establish a strong foundation for optimal stem cell therapy applications, selection of suitable stem cell sources, standardization of transplantation protocols, and patient criteria are vital. This review comprehensively examines existing literature on stem cell sources, transplantation methods, and patient selection. Additionally, we discuss novel strategies, including stem cell preconditioning, cell-free therapy, genetic modification of stem cells, and the use of liver organoids, addressing the limitations of current stem cell therapies. Nevertheless, these innovative approaches require further validation.

Deep learning and transfer learning identify breast cancer survival subtypes from single-cell imaging data

BACKGROUND

Single-cell multiplex imaging data have provided new insights into disease subtypes and prognoses recently. However, quantitative models that explicitly capture single-cell resolution cell-cell interaction features to predict patient survival at a population scale are currently missing.

METHODS

We quantified hundreds of single-cell resolution cell-cell interaction features through neighborhood calculation, in addition to cellular phenotypes. We applied these features to a neural-network-based Cox-nnet survival model to identify survival-associated features. We used non-negative matrix factorization (NMF) to identify patient survival subtypes. We identified atypical subpopulations of triple-negative breast cancer (TNBC) patients with moderate prognosis and Luminal A patients with poor prognosis and validated these subpopulations by label transferring using the UNION-COM method.

RESULTS

The neural-network-based Cox-nnet survival model using all cellular phenotype and cell-cell interaction features is highly predictive of patient survival in the test data (Concordance Index > 0.8). We identify seven survival subtypes using the top survival features, presenting distinct profiles of epithelial, immune, and fibroblast cells and their interactions. We reveal atypical subpopulations of TNBC patients with moderate prognosis (marked by GATA3 over-expression) and Luminal A patients with poor prognosis (marked by KRT6 and ACTA2 over-expression and CDH1 under-expression). These atypical subpopulations are validated in TCGA-BRCA and METABRIC datasets.

CONCLUSIONS

This work provides an approach to bridge single-cell level information toward population-level survival prediction.

Therapeutic modulation of the liver immune microenvironment

Inflammation is a hallmark of progressive liver diseases such as chronic viral or immune-mediated hepatitis, alcohol-associated liver disease, and NAFLD. Preclinical and clinical studies have provided robust evidence that cytokines and related cellular stress sensors in innate and adaptive immunity orchestrate hepatic disease processes. Unresolved inflammation and liver injury result in hepatic scarring, fibrosis, and cirrhosis, which may culminate in HCC. Liver diseases are accompanied by gut dysbiosis and a bloom of pathobionts, fueling hepatic inflammation. Anti-inflammatory strategies are extensively used to treat human immune-mediated conditions beyond the liver, while evidence for immunomodulatory therapies and cell therapy-based strategies in liver diseases is only emerging. The development and establishment of novel immunomodulatory therapies for chronic liver diseases has been dampened by several clinical challenges, such as invasive monitoring of therapeutic efficacy with liver biopsy in clinical trials and risk of DILI in several studies. Such aspects prevented advancements of novel medical therapies for chronic inflammatory liver diseases. New concepts modulating the liver immune environment are studied and eagerly awaited to improve the management of chronic liver diseases in the future.

Defining spatiotemporal gene modules in liver regeneration using Analytical Dynamic Visual Spatial Omics Representation (ADViSOR)

BACKGROUND

The liver is the only organ with the ability to regenerate following surgical or toxicant insults, and partial hepatectomy serves as an experimental model of liver regeneration (LR). Dynamic changes in gene expression occur from the periportal to pericentral regions of the liver following partial hepatectomy; thus, spatial transcriptomics, combined with a novel computational pipeline (ADViSOR [Analytic Dynamic Visual Spatial Omics Representation]), was employed to gain insights into the spatiotemporal molecular underpinnings of LR.

METHODS

ADViSOR, comprising Time-Interval Principal Component Analysis and sliding dynamic hypergraphs, was applied to spatial transcriptomics data on 100 genes assayed serially through LR, including key components of the Wnt/β-catenin pathway at critical timepoints after partial hepatectomy.

RESULTS

This computational pipeline identified key functional modules demonstrating cell signaling and cell-cell interactions, inferring shared regulatory mechanisms. Specifically, ADViSOR analysis suggested that macrophage-mediated inflammation is a critical component of early LR and confirmed prior studies showing that Ccnd1, a hepatocyte proliferative gene, is regulated by the Wnt/β-catenin pathway. These findings were subsequently validated through protein localization, which provided further confirmation and novel insights into the spatiotemporal changes in the Wnt/β-catenin pathway during LR.

CONCLUSIONS

Thus, ADViSOR may yield novel insights in other complex, spatiotemporal contexts.

Unveiling the Role of Tumor-Infiltrating T Cells and Immunotherapy in Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC) is a rapidly rising global health concern, ranking as the third-leading cause of cancer-related mortality. Despite medical advancements, the five-year survival rate remains a dismal 18%, with a daunting 70% recurrence rate within a five-year period. Current systematic treatments, including first-line sorafenib, yield an overall response rate (ORR) below 10%. In contrast, immunotherapies have shown promise by improving ORR to approximately 30%. The IMbravel150 clinical trial demonstrates that combining atezolizumab and bevacizumab surpasses sorafenib in terms of median progression-free survival (PFS) and overall survival (OS). However, the therapeutic efficacy for HCC patients remains unsatisfactory, highlighting the urgent need for a comprehensive understanding of antitumor responses and immune evasion mechanisms in HCC. In this context, understanding the immune landscape of HCC is of paramount importance. Tumor-infiltrating T cells, including cytotoxic T cells, regulatory T cells, and natural killer T cells, are key components in the antitumor immune response. This review aims to shed light on their intricate interactions within the immunosuppressive tumor microenvironment and explores potential strategies for revitalizing dysfunctional T cells. Additionally, current immune checkpoint inhibitor (ICI)-based trials, ICI-based combination therapies, and CAR-T- or TCR-T-cell therapies for HCC are summarized, which might further improve OS and transform the management of HCC in the future.

Omics and Multi-Omics in IBD: No Integration, No Breakthroughs

The recent advent of sophisticated technologies like sequencing and mass spectroscopy platforms combined with artificial intelligence-powered analytic tools has initiated a new era of "big data" research in various complex diseases of still-undetermined cause and mechanisms. The investigation of these diseases was, until recently, limited to traditional in vitro and in vivo biological experimentation, but a clear switch to in silico methodologies is now under way. This review tries to provide a comprehensive assessment of state-of-the-art knowledge on omes, omics and multi-omics in inflammatory bowel disease (IBD). The notion and importance of omes, omics and multi-omics in both health and complex diseases like IBD is introduced, followed by a discussion of the various omics believed to be relevant to IBD pathogenesis, and how multi-omics "big data" can generate new insights translatable into useful clinical tools in IBD such as biomarker identification, prediction of remission and relapse, response to therapy, and precision medicine. The pitfalls and limitations of current IBD multi-omics studies are critically analyzed, revealing that, regardless of the types of omes being analyzed, the majority of current reports are still based on simple associations of descriptive retrospective data from cross-sectional patient cohorts rather than more powerful longitudinally collected prospective datasets. Given this limitation, some suggestions are provided on how IBD multi-omics data may be optimized for greater clinical and therapeutic benefit. The review concludes by forecasting the upcoming incorporation of multi-omics analyses in the routine management of IBD.

Like father, like daughter:Paternal cadmium exposure causes hepatic glucose metabolic disorder and phospholipids accumulation in adult female offspring

Cadmium (Cd), is a well-known reproductive toxicant. The impacts of paternal Cd exposure on offspring glucose and lipid metabolism remain unclear, despite the abundance of adverse reports following early exposure from the mother. Here, we assessed paternally acquired metabolic derailment using a mouse model. LC-MS/MS, transcriptomics and molecular experimental techniques were subsequently applied in this study to explore the potential mechanism. We found that paternal Cd exposure caused glucose intolerance, lower insulin sensitivity and abnormal hepatic glycogen storage in adult female offspring, but not in males. LC-MS/MS data showed that hepatic phospholipids accumulation was also only observed in adult female offspring after paternal Cd exposure. Gene expression data showed that the level of insulin signaling and lipid transport-related genes was decreased in Cd-treated adult female offspring livers. Meanwhile, AHR, a transcription factor that combines with phospholipids to promote insulin resistance, was increased in Cd-treated adult female offspring livers. In addition, the escalation of the afore-mentioned lipid metabolites in the liver occurred as early as fetal stages in the female pups following paternal Cd exposure, suggesting the potential for these lipid species to be selected as early markers of disease for metabolic derailment later in life. Altogether, paternal Cd exposure causes offspring glucose metabolism disorder and phospholipids accumulation in a sex-dependent manner. This study provides a theoretical framework for future understanding of paternal-originated metabolic diseases.

Single-cell RNA sequencing reveals the effects of capsaicin in the treatment of sepsis-induced liver injury

Sepsis is a difficult-to-treat systemic condition in which liver dysfunction acts as both regulator and target. However, the dynamic response of diverse intrahepatic cells to sepsis remains poorly characterized. Capsaicin (CAP), a multifunctional chemical derived from chilli peppers, has recently been shown to potentially possess anti-inflammatory effects, which is also one of the main approaches for drug discovery against sepsis. We performed single-cell RNA transcriptome sequencing on 86,830 intrahepatic cells isolated from normal mice, cecal ligation and puncture-induced sepsis model mice and CAP-treated mice. The transcriptional atlas of these cells revealed dynamic changes in hepatocytes, macrophages, neutrophils, and endothelial cells in response to sepsis. Among the extensive crosstalk across these major subtypes, KC_Cxcl10 shared strong potential interaction with other cells when responding to sepsis. CAP mitigated the severity of inflammation by partly reversing these pathophysiologic processes. Specific cell subpopulations in the liver act collectively to escalate inflammation, ultimately causing liver dysfunction. CAP displays its health-promoting function by ameliorating liver dysfunction induced by sepsis. Our study provides valuable insights into the pathophysiology of sepsis and suggestions for future therapeutic gain.

Hepatic inflammatory responses in liver fibrosis

Chronic liver diseases such as nonalcoholic fatty liver disease (NAFLD) or viral hepatitis are characterized by persistent inflammation and subsequent liver fibrosis. Liver fibrosis critically determines long-term morbidity (for example, cirrhosis or liver cancer) and mortality in NAFLD and nonalcoholic steatohepatitis (NASH). Inflammation represents the concerted response of various hepatic cell types to hepatocellular death and inflammatory signals, which are related to intrahepatic injury pathways or extrahepatic mediators from the gut-liver axis and the circulation. Single-cell technologies have revealed the heterogeneity of immune cell activation concerning disease states and the spatial organization within the liver, including resident and recruited macrophages, neutrophils as mediators of tissue repair, auto-aggressive features of T cells as well as various innate lymphoid cell and unconventional T cell populations. Inflammatory responses drive the activation of hepatic stellate cells (HSCs), and HSC subsets, in turn, modulate immune mechanisms via chemokines and cytokines or transdifferentiate into matrix-producing myofibroblasts. Current advances in understanding the pathogenesis of inflammation and fibrosis in the liver, mainly focused on NAFLD or NASH owing to the high unmet medical need, have led to the identification of several therapeutic targets. In this Review, we summarize the inflammatory mediators and cells in the diseased liver, fibrogenic pathways and their therapeutic implications.

Friend or foe? The elusive role of hepatic stellate cells in liver cancer

Liver fibrosis is a substantial risk factor for the development and progression of liver cancer, which includes hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). Studies utilizing cell fate mapping and single-cell transcriptomics techniques have identified quiescent perisinusoidal hepatic stellate cells (HSCs) as the primary source of activated collagen-producing HSCs and liver cancer-associated fibroblasts (CAFs) in HCC and liver metastasis, complemented in iCCA by contributions from portal fibroblasts. At the same time, integrative computational analysis of single-cell, single-nucleus and spatial RNA sequencing data have revealed marked heterogeneity among HSCs and CAFs, with distinct subpopulations displaying unique gene expression signatures and functions. Some of these subpopulations have divergent roles in promoting or inhibiting liver fibrogenesis and carcinogenesis. In this Review, we discuss the dual roles of HSC subpopulations in liver fibrogenesis and their contribution to liver cancer promotion, progression and metastasis. We review the transcriptomic and functional similarities between HSC and CAF subpopulations, highlighting the pathways that either promote or prevent fibrosis and cancer, and the immunological landscape from which these pathways emerge. Insights from ongoing studies will yield novel strategies for developing biomarkers, assessing prognosis and generating new therapies for both HCC and iCCA prevention and treatment.

The Origin and Fate of Liver Myofibroblasts

Liver fibrosis of different etiologies is a serious health problem worldwide. There is no effective therapy available for liver fibrosis except the removal of the underlying cause of injury or liver transplantation. Development of liver fibrosis is caused by fibrogenic myofibroblasts that are not present in the normal liver, but rather activate from liver resident mesenchymal cells in response to chronic toxic or cholestatic injury. Many studies indicate that liver fibrosis is reversible when the causative agent is removed. Regression of liver fibrosis is associated with the disappearance of activated myofibroblasts and resorption of the fibrous scar. In this review, we discuss the results of genetic tracing and cell fate mapping of hepatic stellate cells and portal fibroblasts, their specific characteristics, and potential phenotypes. We summarize research progress in the understanding of the molecular mechanisms underlying the development and reversibility of liver fibrosis, including activation, apoptosis, and inactivation of myofibroblasts.

Adult tissue-specific stem cell interaction: novel technologies and research advances

Adult tissue-specific stem cells play a dominant role in tissue homeostasis and regeneration. Various in vivo markers of adult tissue-specific stem cells have been increasingly reported by lineage tracing in genetic mouse models, indicating that marked cells differentiation is crucial during homeostasis and regeneration. How adult tissue-specific stem cells with indicated markers contact the adjacent lineage with indicated markers is of significance to be studied. Novel methods bring future findings. Recent advances in lineage tracing, synthetic receptor systems, proximity labeling, and transcriptomics have enabled easier and more accurate cell behavior visualization and qualitative and quantitative analysis of cell-cell interactions than ever before. These technological innovations have prompted researchers to re-evaluate previous experimental results, providing increasingly compelling experimental results for understanding the mechanisms of cell-cell interactions. This review aimed to describe the recent methodological advances of dual enzyme lineage tracing system, the synthetic receptor system, proximity labeling, single-cell RNA sequencing and spatial transcriptomics in the study of adult tissue-specific stem cells interactions. An enhanced understanding of the mechanisms of adult tissue-specific stem cells interaction is important for tissue regeneration and maintenance of homeostasis in organisms.

Deep-learning and transfer learning identify new breast cancer survival subtypes from single-cell imaging data

Quantitative models that explicitly capture single-cell resolution cell-cell interaction features to predict patient survival at population scale are currently missing. Here, we computationally extracted hundreds of features describing single-cell based cell-cell interactions and cellular phenotypes from a large, published cohort of cyto-images of breast cancer patients. We applied these features to a neural-network based Cox-nnet survival model and obtained high accuracy in predicting patient survival in test data (Concordance Index > 0.8). We identified seven survival subtypes using the top survival features, which present distinct profiles of epithelial, immune, fibroblast cells, and their interactions. We identified atypical subpopulations of TNBC patients with moderate prognosis (marked by GATA3 over-expression) and Luminal A patients with poor prognosis (marked by KRT6 and ACTA2 over-expression and CDH1 under-expression). These atypical subpopulations are validated in TCGA-BRCA and METABRIC datasets. This work provides important guidelines on bridging single-cell level information towards population-level survival prediction.

STATEMENT OF TRANSLATIONAL RELEVANCE

Our findings from a breast cancer population cohort demonstrate the clinical utility of using the single-cell level imaging mass cytometry (IMC) data as a new type of patient prognosis prediction marker. Not only did the prognosis prediction achieve high accuracy with a Concordance index score greater than 0.8, it also enabled the discovery of seven survival subtypes that are more distinguishable than the molecular subtypes. These new subtypes present distinct profiles of epithelial, immune, fibroblast cells, and their interactions. Most importantly, this study identified and validated atypical subpopulations of TNBC patients with moderate prognosis (GATA3 over-expression) and Luminal A patients with poor prognosis (KRT6 and ACTA2 over-expression and CDH1 under-expression), using multiple large breast cancer cohorts.

Integrative analysis of single-cell RNA-seq and ATAC-seq reveals heterogeneity of induced pluripotent stem cell-derived hepatic organoids

To gain deeper insights into transcriptomes and epigenomes of organoids, liver organoids from two states (expandable and more differentiated) were subjected to single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq (scATAC-seq) analyses. Mitochondrial gene expression was higher in differentiated than in non-differentiated hepatocytes, with ATAC-seq peaks increasing near the mitochondrial control region. Differentiation of liver organoids resulted in the expression of transcription factors that act as enhancers and repressors. In addition, epigenetic mechanisms regulating the expression of alpha-fetoprotein (AFP) and albumin (ALB) differed in liver organoids and adult liver. Knockdown of PDX1, an essential transcription factor for pancreas development, led to the hepatic maturation of liver organoids through regulation of AFP and ALB expression. This integrative analysis of the transcriptomes and epigenomes of liver organoids at the single-cell level may contribute to a better understanding of the regulatory networks during liver development and the further development of mature in vitro human liver models.

The multifaceted role of macrophages during acute liver injury

The liver is situated at the interface of the gut and circulation where it acts as a filter for blood-borne and gut-derived microbes and biological molecules, promoting tolerance of non-invasive antigens while driving immune responses against pathogenic ones. Liver resident immune cells such as Kupffer cells (KCs), a subset of macrophages, maintain homeostasis under physiological conditions. However, upon liver injury, these cells and others recruited from circulation participate in the response to injury and the repair of tissue damage. Such response is thus spatially and temporally regulated and implicates interconnected cells of immune and non-immune nature. This review will describe the hepatic immune environment during acute liver injury and the subsequent wound healing process. In its early stages, the wound healing immune response involves a necroinflammatory process characterized by partial depletion of resident KCs and lymphocytes and a significant infiltration of myeloid cells including monocyte-derived macrophages (MoMFs) complemented by a wave of pro-inflammatory mediators. The subsequent repair stage includes restoring KCs, initiating angiogenesis, renewing extracellular matrix and enhancing proliferation/activation of resident parenchymal and mesenchymal cells. This review will focus on the multifaceted role of hepatic macrophages, including KCs and MoMFs, and their spatial distribution and roles during acute liver injury.

Non-alcoholic fatty liver disease and diabetes mellitus as growing aetiologies of hepatocellular carcinoma

Obesity-related complications such as non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D) are well-established risk factors for the development of hepatocellular carcinoma (HCC). This review provides insights into the molecular mechanisms that underlie the role of steatosis, hyperinsulinemia and hepatic inflammation in HCC development and progression. We focus on recent findings linking intracellular pathways and transcription factors that can trigger the reprogramming of hepatic cells. In addition, we highlight the role of enzymes in dysregulated metabolic activity and consequent dysfunctional signalling. Finally, we discuss the potential uses and challenges of novel therapeutic strategies to prevent and treat NAFLD/T2D-associated HCC.

Lineage Plasticity and Stemness Phenotypes in Prostate Cancer: Harnessing the Power of Integrated "Omics" Approaches to Explore Measurable Metrics

Prostate cancer (PCa), the most frequent and second most lethal cancer type in men in developed countries, is a highly heterogeneous disease. PCa heterogeneity, therapy resistance, stemness, and lethal progression have been attributed to lineage plasticity, which refers to the ability of neoplastic cells to undergo phenotypic changes under microenvironmental pressures by switching between developmental cell states. What remains to be elucidated is how to identify measurements of lineage plasticity, how to implement them to inform preclinical and clinical research, and, further, how to classify patients and inform therapeutic strategies in the clinic. Recent research has highlighted the crucial role of next-generation sequencing technologies in identifying potential biomarkers associated with lineage plasticity. Here, we review the genomic, transcriptomic, and epigenetic events that have been described in PCa and highlight those with significance for lineage plasticity. We further focus on their relevance in PCa research and their benefits in PCa patient classification. Finally, we explore ways in which bioinformatic analyses can be used to determine lineage plasticity based on large omics analyses and algorithms that can shed light on upstream and downstream events. Most importantly, an integrated multiomics approach may soon allow for the identification of a lineage plasticity signature, which would revolutionize the molecular classification of PCa patients.

Applying quantitative spatial phenotypes analysis to the investigation of peltate glandular trichomes development pattern in Perilla frutescens

BACKGROUND

Glandular trichomes, often referred to as "phytochemical factories", plays a crucial role in plant growth and metabolism. As the site for secretion and storage, the development of glandular trichomes is related to the dynamic biosynthesis of specialised metabolites. The study aims to explore the relationship between spatial phenotype and dynamic metabolism of glandular trichomes, and establish a novel approach for the exploration and study of the regulatory mechanism governing the development of glandular trichomes.

RESULTS

In this study, we proposed a technical route based on the relative deviation value to distinguish the peltate glandular trichomes (PGTs) from the background tissues and extract their spatial phenotype. By defining glandular trichome developmental stages based on the leaf vein growth axis, we found that young PGTs were densely distributed near the proximal end of growth axis of the leaf veins, where perillaketone, a primary metabolite of PGTs, is predominantly accumulated. Conversely, mature PGTs are typically found near the distal end of the mid-vein growth axis and the lateral end of the secondary vein growth axis, where the accumulation rate of isoegomaketone and egomaketone exceeds that of perillaketone in PGTs. We further identified spatial phenotypic parameters, Lsum and d, as independent variables to construct a linear regression model that illustrates the relationship between the spatial phenotypes and metabolite content of PGTs, including perillaketone (R2 = 0.698), egomaketone (R2 = 0.593), isoegomaketone (R2 = 0.662) and the sum of the amount (R2 = 0.773).

CONCLUSIONS

This model proved that the development of PGTs was correlated with the growth of the entire leaf, and the development stage of PGTs can be identifined by spatial phenotypes based on the leaf veins. In conclusion, the findings of this study enhance our understanding of correlation between spatial phenotype and development of glandular trichomes and offer a new approach to explore and study the regulatory mechanism of glandular trichome development.

Emerging and potential use of CRISPR in human liver disease

CRISPR is a gene editing tool adapted from naturally occurring defense systems from bacteria. It is a technology that is revolutionizing the interrogation of gene functions in driving liver disease, especially through genetic screens and by facilitating animal knockout and knockin models. It is being used in models of liver disease to identify which genes are critical for liver pathology, especially in genetic liver disease, hepatitis, and in cancer initiation and progression. It holds tremendous promise in treating human diseases directly by editing DNA. It could disable gene function in the case of expression of a maladaptive protein, such as blocking transthyretin as a therapy for amyloidosis, or to correct gene defects, such as restoring the normal functions of liver enzymes fumarylacetoacetate hydrolase or alpha-1 antitrypsin. It is also being studied for treatment of hepatitis B infection. CRISPR is an exciting, evolving technology that is facilitating gene characterization and discovery in liver disease and holds the potential to treat liver diseases safely and permanently.

Deciphering gastric inflammation-induced tumorigenesis through multi-omics data and AI methods

Gastric cancer (GC), the fifth most common cancer globally, remains the leading cause of cancer deaths worldwide. Inflammation-induced tumorigenesis is the predominant process in GC development; therefore, systematic research in this area should improve understanding of the biological mechanisms that initiate GC development and promote cancer hallmarks. Here, we summarize biological knowledge regarding gastric inflammation-induced tumorigenesis, and characterize the multi-omics data and systems biology methods for investigating GC development. Of note, we highlight pioneering studies in multi-omics data and state-of-the-art network-based algorithms used for dissecting the features of gastric inflammation-induced tumorigenesis, and we propose translational applications in early GC warning biomarkers and precise treatment strategies. This review offers integrative insights for GC research, with the goal of paving the way to novel paradigms for GC precision oncology and prevention.

An invasive zone in human liver cancer identified by Stereo-seq promotes hepatocyte-tumor cell crosstalk, local immunosuppression and tumor progression

Dissecting and understanding the cancer ecosystem, especially that around the tumor margins, which have strong implications for tumor cell infiltration and invasion, are essential for exploring the mechanisms of tumor metastasis and developing effective new treatments. Using a novel tumor border scanning and digitization model enabled by nanoscale resolution-SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we identified a 500 µm-wide zone centered around the tumor border in patients with liver cancer, referred to as "the invasive zone". We detected strong immunosuppression, metabolic reprogramming, and severely damaged hepatocytes in this zone. We also identified a subpopulation of damaged hepatocytes with increased expression of serum amyloid A1 and A2 (referred to collectively as SAAs) located close to the border on the paratumor side. Overexpression of CXCL6 in adjacent malignant cells could induce activation of the JAK-STAT3 pathway in nearby hepatocytes, which subsequently caused SAAs' overexpression in these hepatocytes. Furthermore, overexpression and secretion of SAAs by hepatocytes in the invasive zone could lead to the recruitment of macrophages and M2 polarization, further promoting local immunosuppression, potentially resulting in tumor progression. Clinical association analysis in additional five independent cohorts of patients with primary and secondary liver cancer (n = 423) showed that patients with overexpression of SAAs in the invasive zone had a worse prognosis. Further in vivo experiments using mouse liver tumor models in situ confirmed that the knockdown of genes encoding SAAs in hepatocytes decreased macrophage accumulation around the tumor border and delayed tumor growth. The identification and characterization of a novel invasive zone in human cancer patients not only add an important layer of understanding regarding the mechanisms of tumor invasion and metastasis, but may also pave the way for developing novel therapeutic strategies for advanced liver cancer and other solid tumors.

LiverQuant: An Improved Method for Quantitative Analysis of Liver Pathology

Current means to quantify cells, gene expression, and fibrosis of liver histological slides are not standardized in the research community and typically rely upon data acquired from a selection of random regions identified in each slide. As such, analyses are subject to selection bias as well as limited subsets of available data elements throughout the slide. A whole-slide analysis of cells and fibrosis would provide for a more accurate and complete quantitative analysis, along with minimization of intra- and inter-experimental variables. Herein, we present LiverQuant, a method for quantifying whole-slide scans of digitized histologic images to render a more comprehensive analysis of presented data elements. After loading images and preparing the project in the QuPath program, researchers are provided with one to two scripts per analysis that generate an average intensity threshold for their staining, automated tissue annotation, and downstream detection of their anticipated cellular matrices. When compared with two standard methodologies for histological quantification, LiverQuant had two significant advantages: increased speed and a 50-fold greater tissue area coverage. Using publicly available open-source code (GitHub), LiverQuant improves the reliability and reproducibility of experimental results while reducing the time scientists require to perform bulk analysis of liver histology. This analytical process is readily adaptable by most laboratories, requires minimal optimization, and its principles and code can be optimized for use in other organs. Graphical overview.

ScRNA-seq and spatial transcriptomics: exploring the occurrence and treatment of coronary-related diseases starting from development

Single-cell RNA sequencing (scRNA-seq) is a new technology that can be used to explore molecular changes in complex cell clusters at the single-cell level. Single-cell spatial transcriptomic technology complements the cell-space location information lost during single-cell sequencing. Coronary artery disease is an important cardiovascular disease with high mortality rates. Many studies have explored the physiological development and pathological changes in coronary arteries from the perspective of single cells using single-cell spatial transcriptomic technology. This article reviews the molecular mechanisms underlying coronary artery development and diseases as revealed by scRNA-seq combined with spatial transcriptomic technology. Based on these mechanisms, we discuss the possible new treatments for coronary diseases.

3D bioprinted liver tissue and disease models: Current advances and future perspectives

Three-dimensional (3D) bioprinting is a promising technology for fabricating complex tissue constructs with biomimetic biological functions and stable mechanical properties. In this review, the characteristics of different bioprinting technologies and materials are compared, and development in strategies for bioprinting normal and diseased hepatic tissue are summarized. In particular, features of bioprinting and other bio-fabrication strategies, such as organoids and spheroids are compared to demonstrate the strengths and weaknesses of 3D printing technology. Directions and suggestions, such as vascularization and primary human hepatocyte culture, are provided for the future development of 3D bioprinting.

Novel CH25H+ and OASL+ microglia subclusters play distinct roles in cerebral ischemic stroke

BACKGROUND

Microglial polarization is one of the most promising therapeutic targets for multiple central nervous system (CNS) disorders, including ischemic stroke. However, detailed transcriptional alteration of microglia following cerebral ischemic stroke remains largely unclear.

METHODS

Focal cerebral ischemia was induced by transient middle cerebral artery occlusion (tMCAO) for 60 min in mice. Single-cell RNA sequencing (scRNA-seq) was performed using ischemic brain tissues from tMCAO and sham mice 3 days after surgery. Ch25h^-/- mice were used to investigate the role of specific microglia subcluster on post-stroke infarct volume and neuroinflammation.

RESULTS

We identified a relatively homeostatic subcluster with enhanced antigen processing and three "ischemic stroke associated microglia" (ISAM): MKI67⁺, CH25H⁺ and OASL⁺ subclusters. We found the MKI67⁺ subcluster undergo proliferation and differentiation into CH25H⁺ and OASL⁺ subclusters. CH25H⁺ microglia was a critical subcluster of ISAM that exhibited increased phagocytosis and neuroprotective property after stroke. Ch25h^-/- mice developed significantly increased infarct volume following ischemic stroke compared to Ch25h^+/-. Meanwhile, the OASL⁺ subcluster accumulated in the ischemic brain and was associated with the evolving of neuroinflammation after stroke, which was further aggravated in the aged mice brain.

CONCLUSIONS

Our data reveal previously unrecognized roles of the newly defined CH25H⁺ and OASL⁺ microglia subclusters following ischemic stroke, with novel insights for precise microglia modulation towards stroke therapy.

Toll-like receptor 2 activation in monocytes contributes to systemic inflammation and alcohol-associated liver disease in humans

BACKGROUND AND RATIONALE

In the context of gut leakiness and translocation of microbial products in alcohol-associated liver disease (ALD), it is possible that systemic and liver inflammation involve the activation of circulating monocyte through gut-derived factors. We explored the association between monocytes, microbial translocation, systemic inflammation, and ALD.

METHODS

Patients with alcohol use disorder following a rehabilitation program were compared with healthy controls. We determined the circulating number and proportion of monocyte subsets by FACS. The activation of signaling pathways by gut-derived microbes was analyzed by quantitative PCR in isolated monocytes. Cytokines secretion by monocytes and phagocytosis were assessed in vitro. Serum microbial translocation markers and cytokines were measured by ELISA and multiplex assay, respectively. ALD severity and liver inflammatory responses were analyzed in liver biopsies by various methods.

RESULTS

In patients with alcohol use disorder, the number of blood monocytes increased compared with controls. Monocytes from patients with alcohol use disorder upregulated IL-1β and IL-8 together with toll-like receptor 2 and downstream AP-1, while fungal sensor CARD9 was downregulated. IL-1β and IL-8 were actively secreted upon stimulation in vitro with the toll-like receptor 2 ligand peptidoglycan. Exposure with Escherichia coli confirmed preserved bacterial phagocytic activity. In contrast, Candida albicans stimulation leads to downregulation of IL-1β and TNFα compared with controls. Systemic cytokines and monocyte changes correlated with microbial translocation. Hepatic IL-1β and IL-8 increased with ALD severity together with liver macrophage activation and upregulation of chemokines involved in monocyte attraction.

CONCLUSIONS

Our results point to the contribution of activated monocytes to systemic inflammation and ALD. Monocytes likely infiltrate the liver, transform into monocyte-derived macrophages and release IL-1β and IL-8 in response to peptidoglycan and toll-like receptor 2 activation.

Monitoring Cultured Rat Hepatocytes Using RNA-Seq In Vitro

Compared to other techniques, RNA sequencing (RNA-Seq) has the advantage of having details of the expression abundance of all transcripts in a single run. In this study, we used RNA-Seq to monitor the maturity and dynamic characteristics of in vitro hepatocyte cultures. Hepatocytes, including mature hepatocytes and small hepatocytes, were analyzed in vitro using RNA-Seq and quantitative polymerase chain reaction (qPCR). The results demonstrated that the gene expression profiles measured by RNA-Seq showed a similar trend to the expression profiles measured by qPCR, and can be used to infer the success of in vitro hepatocyte cultures. The results of the differential analysis, which compared mature hepatocytes against small hepatocytes, revealed 836 downregulated and 137 upregulated genes. In addition, the success of the hepatocyte cultures could be explained by the gene list screened from the adopted gene enrichment test. In summary, we demonstrated that RNA-Seq could become an effective method for monitoring the whole transcriptome of hepatocyte cultures and provide a more comprehensive list of factors related to the differentiation of small hepatocytes into mature hepatocytes. This monitoring system not only shows high potential in medical applications but may also be a novel method for the clinical diagnosis of liver-related diseases.

Single-cell and spatial transcriptomics: Advances in heart development and disease applications

Current transcriptomics technologies, including bulk RNA-seq, single-cell RNA sequencing (scRNA-seq), single-nucleus RNA-sequencing (snRNA-seq), and spatial transcriptomics (ST), provide novel insights into the spatial and temporal dynamics of gene expression during cardiac development and disease processes. Cardiac development is a highly sophisticated process involving the regulation of numerous key genes and signaling pathways at specific anatomical sites and developmental stages. Exploring the cell biological mechanisms involved in cardiogenesis also contributes to congenital heart disease research. Meanwhile, the severity of distinct heart diseases, such as coronary heart disease, valvular disease, cardiomyopathy, and heart failure, is associated with cellular transcriptional heterogeneity and phenotypic alteration. Integrating transcriptomic technologies in the clinical diagnosis and treatment of heart diseases will aid in advancing precision medicine. In this review, we summarize applications of scRNA-seq and ST in the cardiac field, including organogenesis and clinical diseases, and provide insights into the promise of single-cell and spatial transcriptomics in translational research and precision medicine.

De-novo reconstruction and identification of transcriptional gene regulatory network modules differentiating single-cell clusters

Single-cell RNA sequencing (scRNA-seq) technology provides an unprecedented opportunity to understand gene functions and interactions at single-cell resolution. While computational tools for scRNA-seq data analysis to decipher differential gene expression profiles and differential pathway expression exist, we still lack methods to learn differential regulatory disease mechanisms directly from the single-cell data. Here, we provide a new methodology, named DiNiro, to unravel such mechanisms de novo and report them as small, easily interpretable transcriptional regulatory network modules. We demonstrate that DiNiro is able to uncover novel, relevant, and deep mechanistic models that not just predict but explain differential cellular gene expression programs. DiNiro is available at https://exbio.wzw.tum.de/diniro/.

Spatial transcriptomics analysis of zone-dependent hepatic ischemia-reperfusion injury murine model

Hepatic ischemia-reperfusion (I/R) injury is a common complication in liver transplantation. The connection between I/R-induced injury response and liver heterogeneity has yet to be fully understood. In this study, we converge histopathological examination with spatial transcriptomics to dissect I/R injury patterns and their associated molecular changes, which reveal that the pericentral zones are most sensitive to I/R injury in terms of histology, transcriptomic changes, and cell type dynamics. Bioinformatic analysis of I/R injury-related pathways predicts that celastrol can protect against liver I/R injury by inducing ischemic pre-conditioning, which is experimentally validated. Mechanistically, celastrol likely implements its protective effect against I/R injury by activating HIF1α signaling and represents a potential strategy for resolving liver I/R.

Single-Cell Analysis of Primary Liver Cancer in Mouse Models

Primary liver cancer (PLC), consisting mainly of hepatocellular carcinoma and intrahepatic cholangiocarcinoma, is one of the major causes of cancer-related mortality worldwide. The curative therapy for PLC is surgical resection and liver transplantation, but most PLCs are inoperable at diagnosis. Even after surgery, there is a high rate of tumor recurrence. There is an unmet clinical need to discover more effective treatment options for advanced PLCs. Pre-clinical mouse models in PLC research have played a critical role in identifying key oncogenic drivers and signaling pathways in hepatocarcinogenesis. Furthermore, recent advances in single-cell RNA sequencing (scRNA-seq) have provided an unprecedented degree of resolution in such characterization. In this review, we will summarize the recent studies that utilized pre-clinical mouse models with the combination of scRNA-seq to provide an understanding of different aspects of PLC. We will focus particularly on the potentially actionable targets regarding the cellular and molecular components. We anticipate that the findings in mouse models could complement those in patients. With more defined etiological background, mouse models may provide valuable insights.

SOX2-positive retinal stem cells are identified in adult human pars plicata by single-cell transcriptomic analyses

Stem cell therapy is a promising strategy to rescue visual impairment caused by retinal degeneration. Previous studies have proposed controversial theories about whether in situ retinal stem cells (RSCs) are present in adult human eye tissue. Single-cell RNA sequencing (scRNA-seq) has emerged as one of the most powerful tools to reveal the heterogeneity of tissue cells. By using scRNA-seq, we explored the cell heterogeneity of different subregions of adult human eyes, including pars plicata, pars plana, retinal pigment epithelium (RPE), iris, and neural retina (NR). We identified one subpopulation expressing SRY-box transcription factor 2 (SOX2) as RSCs, which were present in the pars plicata of the adult human eye. Further analysis showed the identified subpopulation of RSCs expressed specific markers aquaporin 1 (AQP1) and tetraspanin 12 (TSPAN12). We, therefore, isolated this subpopulation using these two markers by flow sorting and found that the isolated RSCs could proliferate and differentiate into some retinal cell types, including photoreceptors, neurons, RPE cells, microglia, astrocytes, horizontal cells, bipolar cells, and ganglion cells; whereas, AQP1- TSPAN12- cells did not have this differentiation potential. In conclusion, our results showed that SOX2-positive RSCs are present in the pars plicata and may be valuable for treating human retinal diseases due to their proliferation and differentiation potential.

Optimizing the design of spatial genomic studies

Spatially-resolved genomic technologies have shown promise for studying the relationship between the structural arrangement of cells and their functional behavior. While numerous sequencing and imaging platforms exist for performing spatial transcriptomics and spatial proteomics profiling, these experiments remain expensive and labor-intensive. Thus, when performing spatial genomics experiments using multiple tissue slices, there is a need to select the tissue cross sections that will be maximally informative for the purposes of the experiment. In this work, we formalize the problem of experimental design for spatial genomics experiments, which we generalize into a problem class that we call structured batch experimental design. We propose approaches for optimizing these designs in two types of spatial genomics studies: one in which the goal is to construct a spatially-resolved genomic atlas of a tissue and another in which the goal is to localize a region of interest in a tissue, such as a tumor. We demonstrate the utility of these optimal designs, where each slice is a two-dimensional plane, on several spatial genomics datasets.

Characterization and microRNA Expression Analysis of Serum-Derived Extracellular Vesicles in Severe Liver Injury from Chronic HBV Infection

BACKGROUND

Extracellular vesicle (EV) microRNAs have been documented in several studies to have significantly different expressions in hepatitis B virus (HBV)-related liver diseases, such as hepatocellular carcinoma (HCC). The current work aimed to observe the characteristics of EVs and EV miRNA expressions in patients with severe liver injury chronic hepatitis B (CHB) and patients with HBV-associated decompensated cirrhosis (DeCi).

METHODS

The characterization of the EVs in the serum was carried out for three different groups, namely, patients with severe liver injury-CHB, patients with DeCi, and healthy controls. EV miRNAs were analyzed using miRNA-seq and RT-qPCR arrays. Additionally, we assessed the predictive and observational values of the miRNAs with significant differential expressions in serum EVs.

RESULTS

Patients with severe liver injury-CHB had the highest EV concentrations when compared to the normal controls (NCs) and patients with DeCi (p < 0.001). The miRNA-seq of the NC and severe liver injury-CHB groups identified 268 differentially expressed miRNAs (|FC| > 2, p < 0.05). In this case, 15 miRNAs were verified using RT-qPCR, and it was found that novel-miR-172-5p and miR-1285-5p in the severe liver injury-CHB group showed marked downregulation in comparison to the NC group (p < 0.001). Furthermore, compared with the NC group, three EV miRNAs (novel-miR-172-5p, miR-1285-5p, and miR-335-5p) in the DeCi group showed various degrees of downregulated expression. However, when comparing the DeCi group with the severe liver injury-CHB group, only the expression of miR-335-5p in the DeCi group decreased significantly (p < 0.05). For the severe liver injury-CHB and DeCi groups, the addition of miR-335-5p improved the predictive accuracy of the serological levels, while miR-335-5p was significantly correlated with ALT, AST, AST/ALT, GGT, and AFP. Conclusions: The patients with severe liver injury-CHB had the highest number of EVs. The combination of novel-miR-172-5p and miR-1285-5p in serum EVs helped in predicting the progression of the NCs to severe liver injury-CHB, while the addition of EV miR-335-5p improved the serological accuracy of predicting the progression of severe liver injury-CHB to DeCi.

Murine breast cancers disorganize the liver transcriptome in a zonated manner

The spatially organized gene expression program within the liver specifies hepatocyte functions according to their relative distances to the bloodstream (i.e., zonation), contributing to liver homeostasis. Despite the knowledge that solid cancers remotely disrupt liver homeostasis, it remains unexplored whether solid cancers affect liver zonation. Here, using spatial transcriptomics, we thoroughly investigate the abundance and zonation of hepatic genes in cancer-bearing mice. We find that breast cancers affect liver zonation in various distinct manners depending on biological pathways. Aspartate metabolism and triglyceride catabolic processes retain relatively intact zonation patterns, but the zonation of xenobiotic catabolic process genes exhibits a strong disruption. The acute phase response is induced in zonated manners. Furthermore, we demonstrate that breast cancers activate innate immune cells in particular neutrophils in distinct zonated manners, rather than in a uniform fashion within the liver. Collectively, breast cancers disorganize hepatic transcriptomes in zonated manners, thereby disrupting zonated functions of the liver.

Advances in Recellularization of Decellularized Liver Grafts with Different Liver (Stem) Cells: Towards Clinical Applications

Liver transplantation is currently the only curative therapy for patients with acute or chronic liver failure. However, a dramatic gap between the number of available liver grafts and the number of patients on the transplantation waiting list emphasizes the need for valid liver substitutes. Whole-organ engineering is an emerging field of tissue engineering and regenerative medicine. It aims to generate transplantable and functional organs to support patients on transplantation waiting lists until a graft becomes available. It comprises two base technologies developed in the last decade; (1) organ decellularization to generate a three-dimensional (3D) extracellular matrix scaffold of an organ, and (2) scaffold recellularization to repopulate both the parenchymal and vascular compartments of a decellularized organ. In this review article, recent advancements in both technologies, in relation to liver whole-organ engineering, are presented. We address the potential sources of hepatocytes and non-parenchymal liver cells for repopulation studies, and the role of stem-cell-derived liver progeny is discussed. In addition, different cell seeding strategies, possible graft modifications, and methods used to evaluate the functionality of recellularized liver grafts are outlined. Based on the knowledge gathered from recent transplantation studies, future directions are summarized.