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

Profiling of B cells and their subsets by whole blood gene expression analysis versus flow cytometry in multiple sclerosis

We investigated if differentially expressed mRNA targets could be used as surrogate markers for circulating B cells and subsets. In paired blood samples from patients with untreated, anti-CD20-treated, fingolimod-treated, and natalizumab-treated multiple sclerosis, whole blood expression of CD19 correlated with B cell counts determined by flow cytometry, ROR1 with transitional B cells, TCL1A and ZNF727 with naïve B cells, NEXMIF with memory B cells and BCMA with plasmablasts. CD19 expression distinguished patients with B cell repletion and may be used as an alternative to flow cytometry, but NEXMIF was unsuitable for memory B cell monitoring in rituximab-treated patients.

Nuclear Acly protects the liver from ischemia-reperfusion injury

BACKGROUND AND AIMS

Hepatic ischemia-reperfusion (IR) injury is the most common complication that occurs in liver surgery and hemorrhagic shock. ATP citrate lyase (Acly) plays a pivotal role in chromatin modification via generating acetyl-CoA for histone acetylation to influence biological processes. We aim to examine the roles of Acly, which is highly expressed in hepatocytes, in liver IR injury.

APPROACH AND RESULTS

The functions of Acly in hepatic IR injury were examined in the mouse model with a hepatocyte-specific knockout of Acly . The Acly target genes were analyzed by CUT&RUN assay and RNA sequencing. The relationship between the susceptibility of the steatotic liver to IR and Acly was determined by the gain of function studies in mice. Hepatic deficiency of Acly exacerbated liver IR injury. IR induced Acly nuclear translocation in hepatocytes, which spatially fueled nuclear acetyl-CoA. This alteration was associated with enhanced acetylation of H3K9 and subsequent activation of the Foxa2 signaling pathway. Nuclear localization of Acly enabled Foxa2-mediated protective effects after hypoxia-reperfusion in cultured hepatocytes, while cytosolic Acly demonstrated no effect. The presence of steatosis disrupted Acly nuclear translocation. In the steatotic liver, restoration of Acly nuclear localization through overexpression of Rspondin-1 or Rspondin-3 ameliorated the IR-induced injury.

CONCLUSIONS

Our results indicate that Acly regulates histone modification by means of nuclear AcCoA production in hepatic IR. Disruption of Acly nuclear translocation increases the vulnerability of the steatotic liver to IR. Nuclear Acly thus may serve as a potential therapeutic target for future interventions in hepatic IR injury, particularly in the context of steatosis.

Pyroptosis-related genes features on prediction of the prognosis in liver cancer: An integrated analysis of bulk and single-cell RNA sequencing

Objective

This study explores the impact of pyroptosis-related genes (PRG) on the prognosis of liver cancer (LC).

Methods

421 samples (371 tumor samples and 50 normal samples) from the Cancer Genome Atlas (TCGA) were included in this study. GSE14520 dataset (data of RNA expression and relevant clinicopathological features), GSE125449 dataset (single-cell data in LC) and HCCDB18 dataset (validation on the reliability of the model) were downloaded as appropriate. Download the PRG and its corresponding pathway information from the gene set enrichment analysis (GSEA) website. The consensus clustering was performed by ConsensusClusterPlus package. Differentially expressed genes (DEGs) were identified using limma package, and prognostic features were constructed using un/multivariate and Lasso Cox regression. Pathway enrichment analysis was conducted by ssGSEA method. Receiver Operating Characteristic and the survival analysis were conducted by timeROC and Survminer packages. The Seurat package was used for single-cell RNA sequencing (scRNA-seq) analysis. For cellular validation, following the quantification on the key genes via reverse-transcription quantitative PCR, the Transwell and scratch assays were applied to evaluate the in-vitro invasion and migration of LC cells Huh-7.

Results

12 prognosis-related genes were identified to be related to the progression of LC. Three subtypes including C1, C2 and C3 were categorized using the 12 prognosis-related genes and PRGs significantly related to the prognosis of LC patients. The worst and best prognosis was seen in C3 subtype and C2 subtype, respectively. Hallmark pathway enrichment analysis has shown the concurrent immunoactivation and immune escape in C3 subtype. A RiskScore model was constructed using 8 key genes (KPNA2, UCK2, FTCD, CBX2, RAB32, HMMR, S100A9 and ANXA10) from the DEGs of three subtypes. The RiskScore system as an independent prognostic factor dividing the patients into high and low risk groups, and patients of the high-risk group had poor prognosis in both test set and validation set. A nomogram model combining the risk score had the extreme higher benefit. Further, 6 subclusters were identified from scRNA-seq analysis, where the highest PYROPTOSIS score was seen in Monocytic-Macrophages. The quantification on the key genes has suggested the high expressions of KPNA2, UCK2, CBX2, RAB32, HMMR and S100A9 and the low expressions of FTCD and ANXA10 in LC cells Huh-7. Particularly, UCK2 knockdown evidently diminished the number of invaded and migrated LC cells in vitro.

Conclusion

The risk model associated with pyproptosis is crucial for the tumor immunity of LC and may serve as a prognostic indicator for patients suffering from LC. Our findings will offer new perspectives for immunotherapies targeting LC.

Spatial transcriptomic revealed intratumor heterogeneity and cancer stem cell enrichment in colorectal cancer metastasis

Metastasis is the main cause of mortality in colorectal cancer (CRC) patients. Exploring the mechanisms of metastasis is of great importance in both clinical and fundamental CRC research. CRC is a highly heterogeneous disease with variable therapeutic outcomes of treatment. In this study, we applied spatial transcriptomics (ST) to generate a tissue-wide transcriptome from two primary colorectal cancer tissues and their matched liver metastatic tissues. Spatial RNA information showed intratumoral heterogeneity (ITH) of both primary and metastatic tissues. The comparison of gene expressions across tissues revealed an apparent enrichment of cancer stem cells (CSCs) in metastatic tissues and identified FOXD1 as a novel metastatic CSC marker. Trajectory and pseudo-time analyses revealed distinct evolutionary trajectories and a dedifferentiation-differentiation process during metastasis. CellphoneDB analysis suggested a dominant interaction of CD74-MIF with tumor cells in metastatic tissues. Further analysis confirmed FOXD1 as a maker of CSCs and the predictor of patient survival, especially in metastatic diseases. Our study found ITH of primary and metastatic tissues and provides novel insights into the cellular mechanisms underlying liver metastasis of CRC and foundations for therapeutic strategies for CRC metastasis.

Integrated analysis reveals NLRC4 as a potential biomarker in sepsis pathogenesis

Sepsis remains a significant global health burden and contributor to mortality, yet the precise molecular mechanisms underlying the immune response are not fully elucidated. To gain insight into this issue, we performed a comprehensive analysis using a variety of techniques including bulk RNA sequencing, single-cell RNA sequencing, and enzyme-linked immunosorbent assay (ELISA). We performed enrichment analysis of differentially expressed genes in sepsis and healthy individuals by utilizing Gene Ontology (GO) analysis and indicated significant enrichment of immune-related response. Following Weighted Gene Co-Expression Network Analysis (WGCNA) and protein-protein interaction analysis (PPI) were used to identify key immune-related hub genes and validated by ELISA to show that NLRC4 is highly expressed in sepsis. Additionally, an analysis of scRNA-seq data from newly diagnosed sepsis, sepsis diagnosis at 6 hours, and healthy samples demonstrates a significant increase in both the expression levels and proportions of NLRC4 in sepsis monocytes and neutrophils. In addition, using pySCENIC we identified upstream transcription factors that regulate NLRC4. Our study provides valuable insights into the identification of NLRC4 in peripheral blood as a potential candidate gene for the diagnosis and treatment of sepsis.

Deubiquitinase USP18 inhibits hepatic stellate cells activation and alleviates liver fibrosis via regulation of TAK1 activity

BACKGROUND & AIMS

Activation of hepatic stellate cells (HSCs) is the key process underlying liver fibrosis. Unveiling its molecular mechanism may provide an effective target for inhibiting liver fibrosis. Protein ubiquitination is a dynamic and reversible process. Deubiquitinases (DUBs) catalyze the removal of ubiquitin chains from substrate proteins, thereby inhibiting the biological processes regulated by ubiquitination signals. However, there are few studies revealing the role of deubiquitination in the activation of HSCs.

METHODS & RESULTS

Single-cell RNA sequencing (scRNA-seq) revealed significantly decreased USP18 expression in activated HSCs when compared to quiescent HSCs. In mouse primary HSCs, continuous activation of HSCs led to a gradual decrease in USP18 expression whilst restoration of USP18 expression significantly inhibited HSC activation. Injection of USP18 lentivirus into the portal vein of a CCl4-induced liver fibrosis mouse model confirmed that overexpression of USP18 can significantly reduce the degree of liver fibrosis. In terms of mechanism, we screened some targets of USP18 in mouse primary HSCs and found that USP18 could directly bind to TAK1. Furthermore, we demonstrated that USP18 can inhibit TAK1 activity by interfering with the K63 ubiquitination of TAK1.

CONCLUSIONS

Our study demonstrated that USP18 inhibited HSC activation and alleviated liver fibrosis via modulation of TAK1 activity; this may prove to be an effective target for inhibiting liver fibrosis.

A new exploration: characterization of the differentiation trajectory of prostate cancer cells

Prostate cancer is one of the most common malignant tumors in men, and in-depth study of its gene expression patterns is crucial for understanding the formation and development of prostate cancer. Although single-cell transcriptomics has deeply explored the heterogeneous expression characteristics of prostate cancer, given that normal epithelial cells themselves have different states of differentiation, these normal differentiation characteristics may lead to confusion with heterogeneous tumor characteristics. In this study, we used single-cell data from the GEO database to analyze in detail the heterogeneity of prostate cancer tumor cells/tumor-associated epithelium cells (TAECs), with a particular focus on the differentiation state of epithelial cells in matching normal tissue. We found that after subtype pairing analysis of normal tissue and tumor tissue epithelium based on differentiation status, the characteristics identified later were not consistent with the general characteristics originally exhibited by different TAECs subpopulations. Among them, all TAECs subpopulations showed P53 enrichment and downregulation of the apoptotic pathway, and expressed higher levels of EGFR, ERBB2, interferon receptors, MIF, and cell adhesion-related signals; through transcription factor regulatory network analysis, we observed that YY1, NKX3-1, and EHF had higher transcriptional activity in TAECs subpopulations than normal epithelial cells at the same differentiation stage, while ATF3 was the opposite. Among them, YY1 may act as an upstream regulator of the MIF signaling pathway, and ATF3 is a key upstream transcriptional regulator of differentially expressed genes in the P53 and apoptotic pathways. Immune infiltration analysis showed that the above four transcription factors were significantly correlated with the infiltration of immune cells in prostate cancer, and pan-cancer analysis showed that their expression-related survival risks were widely present in different cancers. It is worth noting that this is merely a preliminary, exploratory study, which inevitably has some deficiencies and limitations. Despite this, this study is committed to bringing a novel and unique perspective to the field through this work, with the hope of opening up new levels of understanding and stimulating more in-depth research and discussion.

Hepatic immune regulation and sex disparities

Chronic liver disease is a major cause of morbidity and mortality worldwide. Epidemiology, clinical phenotype and response to therapies for gastrointestinal and liver diseases are commonly different between women and men due to sex-specific hormonal, genetic and immune-related factors. The hepatic immune system has unique regulatory functions that promote the induction of intrahepatic tolerance, which is key for maintaining liver health and homeostasis. In liver diseases, hepatic immune alterations are increasingly recognized as a main cofactor responsible for the development and progression of chronic liver injury and fibrosis. In this Review, we discuss the basic mechanisms of sex disparity in hepatic immune regulation and how these mechanisms influence and modify the development of autoimmune liver diseases, genetic liver diseases, portal hypertension and inflammation in chronic liver disease. Alterations in gut microbiota and their crosstalk with the hepatic immune system might affect the progression of liver disease in a sex-specific manner, creating potential opportunities for novel diagnostic and therapeutic approaches to be evaluated in clinical trials. Finally, we identify and propose areas for future basic, translational and clinical research that will advance our understanding of sex disparities in hepatic immunity and liver disease.

Deciphering the spatiotemporal transcriptional landscape of intestinal diseases (Review)

The intestines are the largest barrier organ in the human body. The intestinal barrier plays a crucial role in maintaining the balance of the intestinal environment and protecting the intestines from harmful bacterial invasion. Single‑cell RNA sequencing technology allows the detection of the different cell types in the intestine in two dimensions and the exploration of cell types that have not been fully characterized. The intestinal mucosa is highly complex in structure, and its proper functioning is linked to multiple structures in the proximal‑distal intestinal and luminal‑mucosal axes. Spatial localization is at the core of the efforts to explore the interactions between the complex structures. Spatial transcriptomics (ST) is a method that allows for comprehensive tissue analysis and the acquisition of spatially separated genetic information from individual cells, while preserving their spatial location and interactions. This approach also prevents the loss of fragile cells during tissue disaggregation. The emergence of ST technology allows us to spatially dissect enzymatic processes and interactions between multiple cells, genes, proteins and signals in the intestine. This includes the exchange of oxygen and nutrients in the intestine, different gradients of microbial populations and the role of extracellular matrix proteins. This regionally precise approach to tissue studies is gaining more acceptance and is increasingly applied in the investigation of disease mechanisms related to the gastrointestinal tract. Therefore, this review summarized the application of ST in gastrointestinal diseases.

Angiocrine signaling in sinusoidal homeostasis and liver diseases

The hepatic sinusoids are composed of liver sinusoidal endothelial cells (LSECs), which are surrounded by hepatic stellate cells (HSCs) and contain liver-resident macrophages called Kupffer cells, and other patrolling immune cells. All these cells communicate with each other and with hepatocytes to maintain sinusoidal homeostasis and a spectrum of hepatic functions under healthy conditions. Sinusoidal homeostasis is disrupted by metabolites, toxins, viruses, and other pathological factors, leading to liver injury, chronic liver diseases, and cirrhosis. Alterations in hepatic sinusoids are linked to fibrosis progression and portal hypertension. LSECs are crucial regulators of cellular crosstalk within their microenvironment via angiocrine signaling. This review discusses the mechanisms by which angiocrine signaling orchestrates sinusoidal homeostasis, as well as the development of liver diseases. Here, we summarise the crosstalk between LSECs, HSCs, hepatocytes, cholangiocytes, and immune cells in health and disease and comment on potential novel therapeutic methods for treating liver diseases.

Liver regeneration after injury: Mechanisms, cellular interactions and therapeutic innovations

The liver possesses a distinctive capacity for regeneration within the human body. Under normal circumstances, liver cells replicate themselves to maintain liver function. Compensatory replication of healthy hepatocytes is sufficient for the regeneration after acute liver injuries. In the late stage of chronic liver damage, a large number of hepatocytes die and hepatocyte replication is blocked. Liver regeneration has more complex mechanisms, such as the transdifferentiation between cell types or hepatic progenitor cells mediated. Dysregulation of liver regeneration causes severe chronic liver disease. Gaining a more comprehensive understanding of liver regeneration mechanisms would facilitate the advancement of efficient therapeutic approaches. This review provides an overview of the signalling pathways linked to different aspects of liver regeneration in various liver diseases. Moreover, new knowledge on cellular interactions during the regenerative process is also presented. Finally, this paper explores the potential applications of new technologies, such as nanotechnology, stem cell transplantation and organoids, in liver regeneration after injury, offering fresh perspectives on treating liver disease.

Exploring the Pathogenesis of Autoimmune Liver Diseases from the Heterogeneity of Target Cells

The incidence of autoimmune liver diseases (ALDs) and research on their pathogenesis are increasing annually. However, except for autoimmune hepatitis, which responds well to immunosuppression, primary biliary cholangitis and primary sclerosing cholangitis are insensitive to immunosuppressive therapy. Besides the known effects of the environment, genetics, and immunity on ALDs, the heterogeneity of target cells provides new insights into their pathogenesis. This review started by exploring the heterogeneity in the development, structures, and functions of hepatocytes and epithelial cells of the small and large bile ducts. For example, cytokeratin (CK) 8 and CK18 are primarily expressed in hepatocytes, while CK7 and CK19 are primarily expressed in intrahepatic cholangiocytes. Additionally, emerging technologies of single-cell RNA sequencing and spatial transcriptomic are being applied to study ALDs. This review offered a new perspective on understanding the pathogenic mechanisms and potential treatment strategies for ALDs.

Molecular mechanism of geniposide against ANIT-induced intrahepatic cholestasis by integrative analysis of transcriptomics and metabolomics

Geniposide (GE), a bioactive compound extracted from the fruit of Gardenia jasminoides Ellis, has attracted significant attention for its hepatoprotective therapeutic applications. Although GE displays a protective effect on treating intrahepatic cholestasis (IC), the underlying mechanism remains elusive. In this study, we aimed to elucidate the pharmacological mechanisms of GE in treating IC by an integrated analysis of transcriptomics and metabolomics. Firstly, we evaluated the hepatoprotective effect of GE in α-naphthylisothiocyanate (ANIT)-induced IC rats by examining biochemical indices, inflammatory factors, and oxidative stress levels. Secondly, by transcriptomics and serum metabolomics, we identified differentially expressed genes and metabolites, revealing phenotype-related metabolic pathways and gene functions. Lastly, we screened the core targets of GE in the treatment of IC by integrating transcriptomic and metabolomic data and validated these targets using western blotting. The results indicated that GE improved serum indexes and alleviated inflammation reactions and oxidative stress in the liver. The transcriptomics analysis revealed 739 differentially expressed genes after GE treatment, mainly enriched in retinol metabolism, steroid hormone synthesis, PPAR signal transduction, bile secretion metabolism, and other pathways. The metabolomics analysis identified 98 differential metabolites and 10 metabolic pathways. By constructing a "genes-targets-pathways-compounds" network, we identified two pathways: the bile secretion pathway and the glutathione pathway. Within these pathways, we discovered nine crucial targets that were subsequently validated through western blotting. The results revealed that the GE group significantly increased the expression of ABCG5, NCEH1, OAT3, and GST, compared with the ANIT group. We speculate that GE has a therapeutic effect on IC by modulating the bile secretion pathway and the glutathione pathway and regulating the expression of ABCG5, NCEH1, OAT3, and GST.

Are We There Yet? Assessing the Readiness of Single-Cell Proteomics to Answer Biological Hypotheses

Single-cell analysis is an active area of research in many fields of biology. Measurements at single-cell resolution allow researchers to study diverse populations without losing biologically meaningful information to sample averages. Many technologies have been used to study single cells, including mass spectrometry-based single-cell proteomics (SCP). SCP has seen a lot of growth over the past couple of years through improvements in data acquisition and analysis, leading to greater proteomic depth. Because method development has been the main focus in SCP, biological applications have been sprinkled in only as proof-of-concept. However, SCP methods now provide significant coverage of the proteome and have been implemented in many laboratories. Thus, a primary question to address in our community is whether the current state of technology is ready for widespread adoption for biological inquiry. In this Perspective, we examine the potential for SCP in three thematic areas of biological investigation: cell annotation, developmental trajectories, and spatial mapping. We identify that the primary limitation of SCP is sample throughput. As proteome depth has been the primary target for method development to date, we advocate for a change in focus to facilitate measuring tens of thousands of single-cell proteomes to enable biological applications beyond proof-of-concept.

Pathophysiology and therapeutic options for cirrhotic portal hypertension

Portal hypertension represents the primary non-neoplastic complication of liver cirrhosis and has life-threatening consequences, such as oesophageal variceal bleeding, ascites, and hepatic encephalopathy. Portal hypertension occurs due to increased resistance of the cirrhotic liver vasculature to portal blood flow and is further aggravated by the hyperdynamic circulatory syndrome. Existing knowledge indicates that the profibrogenic phenotype acquired by sinusoidal cells is the initial factor leading to increased hepatic vascular tone and fibrosis, which cause increased vascular resistance and portal hypertension. Data also suggest that the phenotype of hepatic cells could be further impaired due to the altered mechanical properties of the cirrhotic liver itself, creating a deleterious cycle that worsens portal hypertension in the advanced stages of liver disease. In this Review, we discuss recent discoveries in the pathophysiology and treatment of cirrhotic portal hypertension, a condition with few pharmacological treatment options.

Single-cell RNA sequencing in exploring the pathogenesis of diabetic retinopathy

Diabetic retinopathy (DR) is a leading cause of irreversible blindness in the working-age populations. Despite decades of research on the pathogenesis of DR for clinical care, a comprehensive understanding of the condition is still lacking due to the intricate cellular diversity and molecular heterogeneity involved. Single-cell RNA sequencing (scRNA-seq) has made the high-throughput molecular profiling of cells across modalities possible which has provided valuable insights into complex biological systems. In this review, we summarise the application of scRNA-seq in investigating the pathogenesis of DR, focusing on four aspects. These include the identification of differentially expressed genes, characterisation of key cell subpopulations and reconstruction of developmental 'trajectories' to unveil their state transition, exploration of complex cell‒cell communication in DR and integration of scRNA-seq with genome-wide association studies to identify cell types that are most closely related to DR risk genetic loci. Finally, we discuss the future challenges and expectations associated with studying DR using scRNA-seq. We anticipate that scRNA-seq will facilitate the discovery of mechanisms and new treatment targets in the clinical care landscape for patients with DR. KEY POINTS: Progress in scRNA-seq for diabetic retinopathy (DR) research includes studies on DR patients, non-human primates, and the prevalent mouse models. scRNA-seq facilitates the identification of differentially expressed genes, pivotal cell subpopulations, and complex cell-cell interactions in DR at single-cell level. Future scRNA-seq applications in DR should target specific patient subsets and integrate with single-cell and spatial multi-omics approaches.

Large-Scale Formation and Long-Term Culture of Hepatocyte Organoids From Streamlined In Vivo Genome-Edited GGTA1-/- Pigs for Bioartificial Liver Applications

Hepatocyte transplantation and bioartificial liver (BAL) systems hold significant promise as less invasive alternatives to traditional transplantation, providing crucial temporary support for patients with acute and chronic liver failure. Although human hepatocytes are ideal, their use is limited by ethical concerns and donor availability, leading to the use of porcine hepatocytes in BAL systems due to their functional similarities. Recent advancements in gene-editing technology have improved porcine organ xenotransplantation clinical trials by addressing immune rejection issues. Gene-edited pigs, such as alpha-1,3-galactosyltransferase (GGTA1) knockout pigs, offer a secure source of primary cells for BAL systems. Our research focuses on optimizing the safety and functionality of porcine primary hepatocytes during large-scale cultivation. We achieved this by creating GGTA1 knockout pigs through one-step delivery of CRISPR/Cas9 to pig zygotes via oviduct injection of rAAV, and enhancing hepatocyte viability and function by co-culturing hepatocytes with Roof plate-specific spondin 1 overexpressing HUVECs (R-HUVECs). Using a Rocker culture system, approximately 1010 primary porcine hepatocytes and R-HUVECs rapidly formed organoids with a diameter of 92.1 ± 28.1 µm within 24 h. These organoids not only maintained excellent functionality but also supported partial hepatocyte self-renewal during long-term culture over 28 days. Gene-edited primary porcine hepatocyte organoids will significantly advance the applications of hepatocyte transplantation and BAL systems.

A novel efficient strategy to generate liver sinusoidal endothelial cells from human pluripotent stem cells

Liver sinusoidal endothelial cells (LSECs) are highly specialized endothelial cells (ECs) that play an important role in liver development and regeneration. Additionally, it is involved in various pathological processes, including steatosis, inflammation, fibrosis and hepatocellular carcinoma. However, the rapid dedifferentiation of LSECs after culture greatly limits their use in vitro modeling for biomedical applications. In this study, we developed a highly efficient protocol to induce LSEC-like cells from human induced pluripotent stem cells (hiPSCs) in only 8 days. Using single-cell transcriptomic analysis, we identified several novel LSEC-specific markers, such as EPAS1, LIFR, and NID1, as well as several previously revealed markers, such as CLEC4M, CLEC1B, CRHBP and FCN3. These LSEC markers are specifically expressed in our LSEC-like cells. Furthermore, hiPSC-derived cells expressed LSEC-specific proteins and exhibited LSEC-related functions, such as the uptake of acetylated low density lipoprotein (ac-LDL) and immune complex endocytosis. Overall, this study confirmed that our novel protocol allowed hiPSCs to rapidly acquire an LSEC-like phenotype and function in vitro. The ability to generate LSECs efficiently and rapidly may help to more precisely mimic liver development and disease progression in a liver-specific multicellular microenvironment, offering new insights into the development of novel therapeutic strategies.

Current understanding on TREM-2 molecular biology and physiopathological functions

Triggering receptor expressed on myeloid cells 2 (TREM-2), a glycosylated receptor belonging to the immunoglobin superfamily and especially expressed in the myeloid cell lineage, is frequently explained as a reminiscent receptor for both adaptive and innate immunity regulation. TREM-2 is also acknowledged to influence NK cell differentiation via the PI3K and PLCγ signaling pathways, as well as the partial activation or direct inhibition of T cells. Additionally, TREM-2 overexpression is substantially linked to cell-specific functions, such as enhanced phagocytosis, reduced toll-like receptor (TLR)-mediated inflammatory cytokine production, increased transcription of anti-inflammatory cytokines, and reshaped T cell function. Whereas TREM-2-deficient cells exhibit diminished phagocytic function and enhanced proinflammatory cytokines production, proceeding to inflammatory injuries and an immunosuppressive environment for disease progression. Despite the growing literature supporting TREM-2+ cells in various diseases, such as neurodegenerative disorders and cancer, substantial facets of TREM-2-mediated signaling remain inadequately understood relevant to pathophysiology conditions. In this direction, herein, we have summarized the current knowledge on TREM-2 biology and cell-specific TREM-2 expression, particularly in the modulation of pivotal TREM-2-dependent functions under physiopathological conditions. Furthermore, molecular regulation and generic biological relevance of TREM-2 are also discussed, which might provide an alternative approach for preventing or reducing TREM-2-associated deformities. At last, we discussed the TREM-2 function in supporting an immunosuppressive cancer environment and as a potential drug target for cancer immunotherapy. Hence, summarized knowledge of TREM-2 might provide a window to overcome challenges in clinically effective therapies for TREM-2-induced diseases in humans.

Yinchen gongying decoction mitigates CCl4-induced chronic liver injury and fibrosis in mice implicated in inhibition of the FoxO1/TGF-β1/ Smad2/3 and YAP signaling pathways

ETHNOPHARMACOLOGICAL RELEVANCE

Liver fibrosis (LF) is a common reversible consequence of chronic liver damage with limited therapeutic options. Yinchen Gongying decoction (YGD) composed of two homologous plants: (Artemisia capillaris Thunb, Taraxacum monochlamydeum Hand.-Mazz.), has a traditionally application as a medicinal diet for acute icteric hepatitis. However, its impact on LF and underlying mechanisms remain unclear.

AIM OF THE STUDY

This study aims to assess the impact of YGD on a carbon tetrachloride (CCl4) induced liver fibrosis and elucidate its possible mechanisms. The study seeks to establish an experimental foundation for YGD as a candidate drug for hepatic fibrosis.

MATERIALS AND METHODS

LC-MS/MS identified 11 blood-entry components in YGD, and network pharmacology predicted their involvement in the FoxO signaling pathway, insulin resistance, and PI3K-AKT signaling pathway. Using a CCl4-induced LF mouse model, YGD's protective effects were evaluated in comparison to a positive control and a normal group. The underlying mechanisms were explored through the assessments of hepatic stellate cells (HSCs) activation, fibrotic signaling, and inflammation.

RESULTS

YGD treatment significantly improved liver function, enhanced liver morphology, and reduced liver collagen deposition in CCl4-induced LF mice. Mechanistically, YGD inhibited HSC activation, elevated MMPs/TIMP1 ratios, suppressed the FoxO1/TGF-β1/Smad2/3 and YAP pathways, and exhibited anti-inflammatory and antioxidant effects. Notably, YGD improved the insulin signaling pathway.

CONCLUSION

YGD mitigates LF in mice by modulating fibrotic and inflammatory pathways, enhancing antioxidant responses, and specifically inhibiting FoxO1/TGF-β1/Smad2/3 and YAP signal pathways.

Optimizing the design of spatial genomic studies

Spatial genomic technologies characterize the relationship between the structural organization of cells and their cellular state. Despite the availability of various spatial transcriptomic and proteomic profiling platforms, these experiments remain costly and labor-intensive. Traditionally, tissue slicing for spatial sequencing involves parallel axis-aligned sections, often yielding redundant or correlated information. We propose structured batch experimental design, a method that improves the cost efficiency of spatial genomics experiments by profiling tissue slices that are maximally informative, while recognizing the destructive nature of the process. Applied to two spatial genomics studies-one to construct a spatially-resolved genomic atlas of a tissue and another to localize a region of interest in a tissue, such as a tumor-our approach collects more informative samples using fewer slices compared to traditional slicing strategies. This methodology offers a foundation for developing robust and cost-efficient design strategies, allowing spatial genomics studies to be deployed by smaller, resource-constrained labs.

A facile single-cell patterning strategy based on harbor-like microwell microfluidics

Single-cell analysis is an effective method for conducting comprehensive heterogeneity studies ranging from cell phenotype to gene expression. The ability to arrange different cells in a predetermined pattern at single-cell resolution has a wide range of applications in cell-based analysis and plays an important role in facilitating interdisciplinary research by researchers in various fields. Most existing microfluidic microwell chips is a simple and straightforward method, which typically use small-sized microwells to accommodate single cells. However, this method imposes certain limitations on cells of various sizes, and the single-cell capture efficiency is relatively low without the assistance of external forces. Moreover, the microwells limit the spatiotemporal resolution of reagent replacement, as well as cell-to-cell communication. In this study, we propose a new strategy to prepare a single-cell array on a planar microchannel based on microfluidic flip microwells chip platform with large apertures (50 μm), shallow channels (50 μm), and deep microwells (50 μm). The combination of three configuration characteristics contributes to multi-cell trapping and a single-cell array within microwells, while the subsequent chip flipping accomplishes the transfer of the single-cell array to the opposite planar microchannel for cells adherence and growth. Further assisted by protein coating of bovine serum albumin and fibronectin on different layers, the single-cell capture efficiency in microwells is achieved at 92.1% ± 1%, while ultimately 85% ± 3.4% on planar microchannel. To verify the microfluidic flip microwells chip platform, the real-time and heterogeneous study of calcium release and apoptosis behaviours of single cells is carried out. To our knowledge, this is the first time that high-efficiency single-cell acquisition has been accomplished using a circular-well chip design that combines shallow channel, large aperture and deep microwell together. The chip is effective in avoiding the shearing force of high flow rates on cells, and the large apertures better allows cells to sedimentation. Therefore, this strategy owns the advantages of easy preparation and user-friendliness, which is especially valuable for researchers from different fields.

Spatial Patterning Analysis of Cellular Ensembles (SPACE) discovers complex spatial organization at the cell and tissue levels

Spatial patterns of cells and other biological elements drive both physiologic and pathologic processes within tissues. While many imaging and transcriptomic methods document tissue organization, discerning these patterns is challenging, especially when they involve multiple elements in complex arrangements. To address this challenge, we present Spatial Patterning Analysis of Cellular Ensembles (SPACE), an R package for analysis of high-plex spatial data. SPACE is compatible with any data collection modality that records values (i.e., categorical cell/structure types or quantitative expression levels) at fixed spatial coordinates (i.e., 2d pixels or 3d voxels). SPACE detects not only broad patterns of co-occurrence but also context-dependent associations, quantitative gradients and orientations, and other organizational complexities. Via a robust information theoretic framework, SPACE explores all possible ensembles of tissue elements - single elements, pairs, triplets, and so on - and ranks the most strongly patterned ensembles. For single images, rankings reflect patterns that differ from random assortment. For sets of images, rankings reflect patterns that differ across sample groups (e.g., genotypes, treatments, timepoints, etc.). Further tools then thoroughly characterize the nature of each pattern for intuitive interpretation. We validate SPACE and demonstrate its advantages using murine lymph node images for which ground truth has been defined. We then use SPACE to detect new patterns across varied datasets, including tumors and tuberculosis granulomas.

Accurately deciphering spatial domains for spatially resolved transcriptomics with stCluster

Spatial transcriptomics provides valuable insights into gene expression within the native tissue context, effectively merging molecular data with spatial information to uncover intricate cellular relationships and tissue organizations. In this context, deciphering cellular spatial domains becomes essential for revealing complex cellular dynamics and tissue structures. However, current methods encounter challenges in seamlessly integrating gene expression data with spatial information, resulting in less informative representations of spots and suboptimal accuracy in spatial domain identification. We introduce stCluster, a novel method that integrates graph contrastive learning with multi-task learning to refine informative representations for spatial transcriptomic data, consequently improving spatial domain identification. stCluster first leverages graph contrastive learning technology to obtain discriminative representations capable of recognizing spatially coherent patterns. Through jointly optimizing multiple tasks, stCluster further fine-tunes the representations to be able to capture complex relationships between gene expression and spatial organization. Benchmarked against six state-of-the-art methods, the experimental results reveal its proficiency in accurately identifying complex spatial domains across various datasets and platforms, spanning tissue, organ, and embryo levels. Moreover, stCluster can effectively denoise the spatial gene expression patterns and enhance the spatial trajectory inference. The source code of stCluster is freely available at https://github.com/hannshu/stCluster.

Novel immune classification based on machine learning of pathological images predicts early recurrence of hepatocellular carcinoma

Introduction

Immune infiltration within the tumor microenvironment (TME) plays a significant role in the onset and progression of hepatocellular carcinoma (HCC). Machine learning applied to pathological images offers a practical means to explore the TME at the cellular level. Our former research employed a transfer learning procedure to adapt a convolutional neural network (CNN) model for cell recognition, which could recognize tumor cells, lymphocytes, and stromal cells autonomously and accurately within the images. This study introduces a novel immune classification system based on the modified CNN model.

Method

Patients with HCC from both Beijing Hospital and The Cancer Genome Atlas (TCGA) database were included in this study. Additionally, least absolute shrinkage and selection operator (LASSO) analyses, along with logistic regression, were utilized to develop a prognostic model. We proposed an immune classification based on the percentage of lymphocytes, with a threshold set at the median lymphocyte percentage.

Result

Patients were categorized into high or low infiltration subtypes based on whether their lymphocyte percentages were above or below the median, respectively. Patients with different immune infiltration subtypes exhibited varying clinical features and distinct TME characteristics. The low-infiltration subtype showed a higher incidence of hypertension and fatty liver, more advanced tumor stages, downregulated immune-related genes, and higher infiltration of immunosuppressive cells. A reliable prognostic model for predicting early recurrence of HCC based on clinical features and immune classification was established. The area under the curve (AUC) of the receiver operating characteristic (ROC) curves was 0.918 and 0.814 for the training and test sets, respectively.

Discussion

In conclusion, we proposed a novel immune classification system based on cell information extracted from pathological slices, provides a novel tool for prognostic evaluation in HCC.

Drug repurposing in MASLD and MASH-cirrhosis: Targets and treatment approaches based on pathways analysis

Designing and predicting novel drug targets to accelerate drug discovery for treating metabolic dysfunction-associated steatohepatitis (MASH)-cirrhosis is a challenging task. The presence of superimposed (nested) and co-occurring clinical and histological phenotypes, namely MASH and cirrhosis, may partly explain this. Thus, in this scenario, each sub-phenotype has its own set of pathophysiological mechanisms, triggers, and processes. Here, we used gene/protein and set enrichment analysis to predict druggable pathways for the treatment of MASH-cirrhosis. Our findings indicate that the pathogenesis of MASH-cirrhosis can be explained by perturbations in multiple, simultaneous, and overlapping molecular processes. In this scenario, each sub-phenotype has its own set of pathophysiological mechanisms, triggers, and processes. Therefore, we used systems biology modeling to provide evidence that MASH and cirrhosis paradoxically present unique and distinct as well as common disease mechanisms, including a network of molecular targets. More importantly, pathway analysis revealed straightforward results consistent with modulation of the immune response, cell cycle control, and epigenetic regulation. In conclusion, the selection of potential therapies for MASH-cirrhosis should be guided by a better understanding of the underlying biological processes and molecular perturbations that progressively damage liver tissue and its underlying structure. Therapeutic options for patients with MASH may not necessarily be of choice for MASH cirrhosis. Therefore, the biology of the disease and the processes associated with its natural history must be at the forefront of the decision-making process.

Perturbed liver gene zonation in a mouse model of non-alcoholic steatohepatitis

Liver zonation characterizes the separation of metabolic pathways along the lobules and is required for optimal hepatic function. Wnt signaling is a master regulator of spatial liver zonation. A perivenous-periportal Wnt activity gradient orchestrates metabolic zonation by activating gene expression in perivenous hepatocytes, while suppressing gene expression in their periportal counterparts. However, the understanding as to the liver gene zonation and zonation regulators in diseases is limited. Non-alcoholic steatohepatitis (NASH) is a chronic liver disease characterized by fat accumulation, inflammation, and fibrosis. Here, we investigated the perturbation of liver gene zonation in a mouse NASH model by combining spatial transcriptomics, bulk RNAseq and in situ hybridization. Wnt-target genes represented a major subset of genes showing altered spatial expression in the NASH liver. The altered Wnt-target gene expression levels and zonation spatial patterns were in line with the up regulation of Wnt regulators and the augmentation of Wnt signaling. Particularly, we found that the Wnt activator Rspo3 expression was restricted to the perivenous zone in control liver but expanded to the periportal zone in NASH liver. AAV8-mediated RSPO3 overexpression in controls resulted in zonation changes, and further amplified the disturbed zonation of Wnt-target genes in NASH, similarly Rspo3 knockdown in Rspo3+/- mice resulted in zonation changes of Wnt-target genes in both chow and HFD mouse. Interestingly, there were no impacts on steatosis, inflammation, or fibrosis NASH pathology from RSPO3 overexpression nor Rspo3 knockdown. In summary, our study demonstrated the alteration of Wnt signaling in a mouse NASH model, leading to perturbed liver zonation.

Single-cell RNA sequencing to explore cancer-associated fibroblasts heterogeneity: "Single" vision for "heterogeneous" environment

Cancer-associated fibroblasts (CAFs), a phenotypically and functionally heterogeneous stromal cell, are one of the most important components of the tumour microenvironment. Previous studies have consolidated it as a promising target against cancer. However, variable therapeutic efficacy-both protumor and antitumor effects have been observed not least owing to the strong heterogeneity of CAFs. Over the past 10 years, advances in single-cell RNA sequencing (scRNA-seq) technologies had a dramatic effect on biomedical research, enabling the analysis of single cell transcriptomes with unprecedented resolution and throughput. Specifically, scRNA-seq facilitates our understanding of the complexity and heterogeneity of diverse CAF subtypes. In this review, we discuss the up-to-date knowledge about CAF heterogeneity with a focus on scRNA-seq perspective to investigate the emerging strategies for integrating multimodal single-cell platforms. Furthermore, we summarized the clinical application of scRNA-seq on CAF research. We believe that the comprehensive understanding of the heterogeneity of CAFs form different visions will generate innovative solutions to cancer therapy and achieve clinical applications.

Spatial metabolomics and its application in the liver

Hepatocytes work in highly structured, repetitive hepatic lobules. Blood flow across the radial axis of the lobule generates oxygen, nutrient, and hormone gradients, which result in zoned spatial variability and functional diversity. This large heterogeneity suggests that hepatocytes in different lobule zones may have distinct gene expression profiles, metabolic features, regenerative capacity, and susceptibility to damage. Here, we describe the principles of liver zonation, introduce metabolomic approaches to study the spatial heterogeneity of the liver, and highlight the possibility of exploring the spatial metabolic profile, leading to a deeper understanding of the tissue metabolic organization. Spatial metabolomics can also reveal intercellular heterogeneity and its contribution to liver disease. These approaches facilitate the global characterization of liver metabolic function with high spatial resolution along physiological and pathological time scales. This review summarizes the state of the art for spatially resolved metabolomic analysis and the challenges that hinder the achievement of metabolome coverage at the single-cell level. We also discuss several major contributions to the understanding of liver spatial metabolism and conclude with our opinion on the future developments and applications of these exciting new technologies.

Inflammation in Alcohol-Associated Hepatitis: Pathogenesis and Therapeutic Targets

Alcohol-associated hepatitis (AH) is an acute-on-chronic liver injury that occurs in patients with chronic alcohol-associated liver disease (ALD). Patients with severe AH have high short-term mortality and lack effective pharmacologic therapies. Inflammation is believed to be one of the key factors promoting AH progression and has been actively investigated as therapeutic targets over the last several decades, but no effective inflammatory targets have been identified so far. In this review, we discuss how inflammatory cells and the inflammatory mediators produced by these cells contribute to the development and progression of AH, with focus on neutrophils and macrophages. The crosstalk between inflammatory cells and liver nonparenchymal cells in the pathogenesis of AH is elaborated. We also deliberate the application of recent cutting-edge technologies in characterizing liver inflammation in AH. Finally, the potential therapeutic targets of inflammatory mediators for AH are briefly summarized.

Gut-liver axis: Recent concepts in pathophysiology in alcohol-associated liver disease

The growing recognition of the role of the gut microbiome's impact on alcohol-associated diseases, especially in alcohol-associated liver disease, emphasizes the need to understand molecular mechanisms involved in governing organ-organ communication to identify novel avenues to combat alcohol-associated diseases. The gut-liver axis refers to the bidirectional communication and interaction between the gut and the liver. Intestinal microbiota plays a pivotal role in maintaining homeostasis within the gut-liver axis, and this axis plays a significant role in alcohol-associated liver disease. The intricate communication between intestine and liver involves communication between multiple cellular components in each organ that enable them to carry out their physiological functions. In this review, we focus on novel approaches to understanding how chronic alcohol exposure impacts the microbiome and individual cells within the liver and intestine, as well as the impact of ethanol on the molecular machinery required for intraorgan and interorgan communication.

Cauchy hyper-graph Laplacian nonnegative matrix factorization for single-cell RNA-sequencing data analysis

Many important biological facts have been found as single-cell RNA sequencing (scRNA-seq) technology has advanced. With the use of this technology, it is now possible to investigate the connections among individual cells, genes, and illnesses. For the analysis of single-cell data, clustering is frequently used. Nevertheless, biological data usually contain a large amount of noise data, and traditional clustering methods are sensitive to noise. However, acquiring higher-order spatial information from the data alone is insufficient. As a result, getting trustworthy clustering findings is challenging. We propose the Cauchy hyper-graph Laplacian non-negative matrix factorization (CHLNMF) as a unique approach to address these issues. In CHLNMF, we replace the measurement based on Euclidean distance in the conventional non-negative matrix factorization (NMF), which can lessen the influence of noise, with the Cauchy loss function (CLF). The model also incorporates the hyper-graph constraint, which takes into account the high-order link among the samples. The CHLNMF model's best solution is then discovered using a half-quadratic optimization approach. Finally, using seven scRNA-seq datasets, we contrast the CHLNMF technique with the other nine top methods. The validity of our technique was established by analysis of the experimental outcomes.

Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer (Review)

Gastric cancer (GC) is a prominent contributor to global cancer-related mortalities, and a deeper understanding of its molecular characteristics and tumor heterogeneity is required. Single-cell omics and spatial transcriptomics (ST) technologies have revolutionized cancer research by enabling the exploration of cellular heterogeneity and molecular landscapes at the single-cell level. In the present review, an overview of the advancements in single-cell omics and ST technologies and their applications in GC research is provided. Firstly, multiple single-cell omics and ST methods are discussed, highlighting their ability to offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns and cellular location in tissues. Furthermore, a summary is provided of key findings from previous research on single-cell omics and ST methods used in GC, which have provided valuable insights into genetic alterations, tumor diagnosis and prognosis, tumor microenvironment analysis, and treatment response. In summary, the application of single-cell omics and ST technologies has revealed the levels of cellular heterogeneity and the molecular characteristics of GC, and holds promise for improving diagnostics, personalized treatments and patient outcomes in GC.

Myeloid-Mas Signaling Modulates Pathogenic Crosstalk among MYC+CD63+ Endothelial Cells, MMP12+ Macrophages, and Monocytes in Acetaminophen-Induced Liver Injury

Acetaminophen overdose is a leading cause of acute liver failure (ALF). Despite the pivotal role of the inflammatory microenvironment in the progression of advanced acetaminophen-induced liver injury (AILI), a comprehensive understanding of the underlying cellular interactions and molecular mechanisms remains elusive. Mas is a G protein-coupled receptor highly expressed by myeloid cells; however, its role in the AILI microenvironment remains to be elucidated. A multidimensional approach, including single-cell RNA sequencing, spatial transcriptomics, and hour-long intravital imaging, is employed to characterize the microenvironment in Mas1 deficient mice at the systemic and cell-specific levels. The characteristic landscape of mouse AILI models involves reciprocal cellular communication among MYC+CD63+ endothelial cells, MMP12+ macrophages, and monocytes, which is maintained by enhanced glycolysis and the NF-κB/TNF-α signaling pathway due to myeloid-Mas deficiency. Importantly, the pathogenic microenvironment is delineated in samples obtained from patients with ALF, demonstrating its clinical relevance. In summary, these findings greatly enhance the understanding of the microenvironment in advanced AILI and offer potential avenues for patient stratification and identification of novel therapeutic targets.

Ductular Reactions in Liver Injury, Regeneration, and Disease Progression-An Overview

Ductular reaction (DR) is a complex cellular response that occurs in the liver during chronic injuries. DR mainly consists of hyper-proliferative or reactive cholangiocytes and, to a lesser extent, de-differentiated hepatocytes and liver progenitors presenting a close spatial interaction with periportal mesenchyme and immune cells. The underlying pathology of DRs leads to extensive tissue remodeling in chronic liver diseases. DR initiates as a tissue-regeneration mechanism in the liver; however, its close association with progressive fibrosis and inflammation in many chronic liver diseases makes it a more complicated pathological response than a simple regenerative process. An in-depth understanding of the cellular physiology of DRs and their contribution to tissue repair, inflammation, and progressive fibrosis can help scientists develop cell-type specific targeted therapies to manage liver fibrosis and chronic liver diseases effectively.

Integrating single-cell RNA sequencing data to genome-wide association analysis data identifies significant cell types in influenza A virus infection and COVID-19

With the global pandemic of COVID-19, the research on influenza virus has entered a new stage, but it is difficult to elucidate the pathogenesis of influenza disease. Genome-wide association studies (GWASs) have greatly shed light on the role of host genetic background in influenza pathogenesis and prognosis, whereas single-cell RNA sequencing (scRNA-seq) has enabled unprecedented resolution of cellular diversity and in vivo following influenza disease. Here, we performed a comprehensive analysis of influenza GWAS and scRNA-seq data to reveal cell types associated with influenza disease and provide clues to understanding pathogenesis. We downloaded two GWAS summary data, two scRNA-seq data on influenza disease. After defining cell types for each scRNA-seq data, we used RolyPoly and LDSC-cts to integrate GWAS and scRNA-seq. Furthermore, we analyzed scRNA-seq data from the peripheral blood mononuclear cells (PBMCs) of a healthy population to validate and compare our results. After processing the scRNA-seq data, we obtained approximately 70 000 cells and identified up to 13 cell types. For the European population analysis, we determined an association between neutrophils and influenza disease. For the East Asian population analysis, we identified an association between monocytes and influenza disease. In addition, we also identified monocytes as a significantly related cell type in a dataset of healthy human PBMCs. In this comprehensive analysis, we identified neutrophils and monocytes as influenza disease-associated cell types. More attention and validation should be given in future studies.

Mapping human tissues with highly multiplexed RNA in situ hybridization

In situ transcriptomic techniques promise a holistic view of tissue organization and cell-cell interactions. There has been a surge of multiplexed RNA in situ mapping techniques but their application to human tissues has been limited due to their large size, general lower tissue quality and high autofluorescence. Here we report DART-FISH, a padlock probe-based technology capable of profiling hundreds to thousands of genes in centimeter-sized human tissue sections. We introduce an omni-cell type cytoplasmic stain that substantially improves the segmentation of cell bodies. Our enzyme-free isothermal decoding procedure allows us to image 121 genes in large sections from the human neocortex in <10 h. We successfully recapitulated the cytoarchitecture of 20 neuronal and non-neuronal subclasses. We further performed in situ mapping of 300 genes on a diseased human kidney, profiled >20 healthy and pathological cell states, and identified diseased niches enriched in transcriptionally altered epithelial cells and myofibroblasts.

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.