A single cell atlas of the human liver tumor microenvironment

Spatial and Single-Cell Transcriptomics Reveals the Regional Division of the Spatial Structure of MASH Fibrosis

OBJECTIVE

To elucidate the regional distribution of metabolic dysfunction-associated steatohepatitis (MASH) fibrosis within the liver and to identify potential therapeutic targets for MASH fibrosis.

METHODS

Liver sections from healthy controls, patients with simple steatosis and MASH patients were analysed using spatial transcriptomics integrated with single-cell RNA-seq.

RESULTS

Spatial transcriptomics analysis of liver tissues revealed that the fibrotic region (Cluster 9) was primarily distributed in lobules, with some fibrosis also found in the surrounding area. Integration of the single-cell-sequencing data set (GSE189175) showed a greater proportion of inflammatory cells (Kupffer cells and T cells) and myofibroblasts in MASH. Six genes, showing high- or low-specific expression in Cluster 9, namely, ADAMTSL2, PTGDS, S100A6, PPP1R1A, ASS1 and G6PC, were identified in combination with pathology. The average expression levels of ADAMTSL2, PTGDS and S100A6 on the pathological HE staining map were positively correlated with the increase in the degree of fibrosis and aligned strongly with the distribution of fibrosis. ADAMTSL2+ myofibroblasts play a role in TNF signalling pathways and in the production of ECM structural components. Pseudotime analysis indicated that in the early stages of MASH, infiltration by T cells and Kupffer cells triggers a significant inflammatory response. Subsequently, this inflammation leads to the activation of hepatic stellate cells (HSCs), transforming them into myofibroblasts and promoting the development of liver fibrosis.

CONCLUSION

This study is the first to characterise lineage-specific changes in gene expression, subpopulation composition, and pseudotime analysis in MASH fibrosis and reveals potential therapeutic targets for this condition.

Bi-level graph learning unveils prognosis-relevant tumor microenvironment patterns in breast multiplexed digital pathology

The tumor microenvironment (TME) is widely recognized for its central role in driving cancer progression and influencing prognostic outcomes. Increasing efforts have been dedicated to characterizing it, including its analysis with modern deep learning. However, identifying generalizable biomarkers has been limited by the uninterpretable nature of their predictions. We introduce a data-driven yet interpretable approach for identifying cellular patterns in the TME associated with patient prognoses. Our method relies on constructing a bi-level graph model: a cellular graph, which models the TME, and a population graph, capturing inter-patient similarities given their respective cellular graphs. We demonstrate our approach in breast cancer, showing that the identified patterns provide a risk-stratification system with new complementary information to standard clinical subtypes, and these results are validated in two independent cohorts. Our methodology could be applied to other cancer types more generally, providing insights into the spatial cellular patterns associated with patient outcomes.

The landscape of malignant transition: Unraveling cancer cell-of-origin and heterogeneous tissue microenvironment

Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by leveraging data from 1396 samples spanning 13 major tissues. Within transitional stem-like subpopulations highly enriched in precancers and cancers, we identified 30 recurring cellular states strongly linked to malignancy, including hypoxia and epithelial senescence, revealing a high degree of plasticity in epithelial stem cells. By characterizing dynamics in stem-cell crosstalk with the microenvironment along the pseudotime axis, we found differential roles of ANXA1 at different stages of tumor development. In precancerous stages, reduced ANXA1 levels promoted monocyte differentiation toward M1 macrophages and inflammatory responses, whereas during malignant progression, upregulated ANXA1 fostered M2 macrophage polarization and cancer-associated fibroblast transformation by increasing TGF-β production. Our spatiotemporal analysis further provided insights into mechanisms responsible for immunosuppression and a potential target to control evolution of precancer and mitigate the risk for cancer development.

Molecular and immune landscape of hepatocellular carcinoma to guide therapeutic decision-making

Liver cancer, primarily HCC, exhibits highly heterogeneous histological and molecular aberrations across tumors and within individual tumor nodules. Such intertumor and intratumor heterogeneities may lead to diversity in the natural history of disease progression and various clinical disparities across the patients. Recently developed multimodality, single-cell, and spatial omics profiling technologies have enabled interrogation of the intertumor/intratumor heterogeneity in the cancer cells and the tumor immune microenvironment. These features may influence the natural history and efficacy of emerging therapies targeting novel molecular and immune pathways, some of which had been deemed undruggable. Thus, comprehensive characterization of the heterogeneities at various levels may facilitate the discovery of biomarkers that enable personalized and rational treatment decisions, and optimize treatment efficacy while minimizing the risk of adverse effects. Such companion biomarkers will also refine HCC treatment algorithms across disease stages for cost-effective patient management by optimizing the allocation of limited medical resources. Despite this promise, the complexity of the intertumor/intratumor heterogeneity and ever-expanding inventory of therapeutic agents and regimens have made clinical evaluation and translation of biomarkers increasingly challenging. To address this issue, novel clinical trial designs have been proposed and incorporated into recent studies. In this review, we discuss the latest findings in the molecular and immune landscape of HCC for their potential and utility as biomarkers, the framework of evaluation and clinical application of predictive/prognostic biomarkers, and ongoing biomarker-guided therapeutic clinical trials. These new developments may revolutionize patient care and substantially impact the still dismal HCC mortality.

The Role of Macrophages in Various Types of Tumors and the Possibility of Their Use as Targets for Antitumor Therapy

In solid tumors, tumor-associated macrophages (TAMs) are one of the most numerous populations and play an important role in the processes of tumor cell invasion, metastasis, and angiogenesis. Therefore, TAMs are considered promising diagnostic and prognostic biomarkers of tumors, and many attempts have been made to influence these cells as part of antitumor therapy. There are several key principles of action on ТАМs: the inhibition of monocyte/macrophage transition; the destruction of macrophages; the reprogramming of macrophage phenotypes (polarization of M2 macrophages to M1); the stimulation of phagocytic activity of macrophages and CAR-M therapy. Despite the large number of studies in this area, to date, there are no adequate approaches using antitumor therapy based on alterations in TAM functioning that would show high efficacy when administered in a mono-regimen for the treatment of malignant neoplasms. Studies devoted to the evaluation of the efficacy of drugs acting on TAMs are characterized by a small sample and the large heterogeneity of patient groups; in addition, in such studies, chemotherapy or immunotherapy is used, which significantly complicates the evaluation of the effectiveness of the agent acting on TAMs. In this review, we attempted to systematize the evidence on attempts to influence TAMs in malignancies such as lung cancer, breast cancer, colorectal cancer, cervical cancer, prostate cancer, gastric cancer, head and neck squamous cell cancer, and soft tissue sarcomas.

Investigation of Exome-Wide Tumor Heterogeneity on Colorectal Tissue-Based Single Cells

The progression of colorectal cancer is strongly influenced by environmental and genetic conditions. One of the key factors is tumor heterogeneity which is extensively studied by cfDNA and bulk sequencing methods; however, we lack knowledge regarding its effects at the single-cell level. Motivated by this, we aimed to employ an end-to-end single-cell sequencing workflow from tissue-derived sample isolation to exome sequencing. Our main goal was to investigate the heterogeneity patterns by laser microdissecting samples from different locations of a tissue slide. Moreover, by studying healthy colon control, tumor-associated normal, and colorectal cancer tissues, we explored tissue-specific heterogeneity motifs. For completeness, we also compared the performance of the whole-exome bulk, cfDNA, and single-cell sequencing methods based on variation at the level of a single nucleotide.

PNMA1 is a novel immune modulator and therapeutic target in hepatocellular carcinoma linked to bile acid metabolism

Hepatocellular carcinoma (HCC) necessitates innovative prognostic biomarkers and therapeutic targets. By investigating PNMA1 in HCC via the TCGA and GEO databases and our clinical data, we found that its overexpression is associated with worse survival. The relevance of PNMA1 extends to immune factors such as M1 macrophages, CD8+ T cells, and immune checkpoints. Mechanistically, PNMA1 shapes a suppressive tumor microenvironment strongly linked to bile acid metabolism. It promotes tumor progression via immune inhibition and PI3K-AKT pathway activation. Notably, PNMA1 has emerged as a promising therapeutic target for tyrosine kinase inhibitors, as confirmed by reduced IC50 values and molecular docking. Experimental knockdown of PNMA1 hindered HepG2 cell proliferation and migration. Furthermore, PNMA1 is a pivotal HCC biomarker and therapeutic target with a focus on cancer progression, immune modulation, and bile acid metabolism.

Single-cell dissection of multifocal bladder cancer reveals malignant and immune cells variation between primary and recurrent tumor lesions

Bladder carcinoma (BLCA) is characterized by a high rate of post-surgery recurrence and multifocality. Multifocal tumors have a higher risk of recurrence compared to single tumors, significantly impacting bladder cancer-specific mortality. However, the interregional or intraregional heterogeneity within both primary and recurrent tumors remains poorly understood. Here, we employed single-cell RNA sequencing to analyze tumor lesions from five multifocal bladder cancer patients comprising three primary tumors and two recurrent tumors. Our findings revealed that malignant cells derived from recurrent multifocal bladder cancer exhibited higher interregional transcriptional similarity and consistent cellular communication. Furthermore, our analysis uncovered that malignant cells from recurrent tumors may evade immune destruction by suppressing cytokine responses and natural killer cell activity. Notably, we identified a preference for the expression of the tryptophan metabolic enzyme IL4I1 on SPP1+ macrophages in recurrent tumors. Functional analyses have revealed that IL4I1 may promotes tumor progression in recurrent tumors by activating the aryl hydrocarbon receptor (AHR) and recruiting regulatory T cells to suppress adaptive immunity. Taken together, our study provides a comprehensive understanding of primary and recurrent multifocal bladder tumors, offering valuable resources for analyzing the multifocality and recurrence of bladder cancer.

Dynamics of liver cancer cellular taxa revealed through single-cell RNA sequencing: Advances and challenges

Liver cancer is a leading cause of death worldwide, representing a substantial public health challenge. The advent of single-cell RNA sequencing has significantly advanced our understanding of cellular dynamics from the onset of liver cancer to therapeutic intervention. This technology has unveiled profound insights into cancer heterogeneity and the tumor microenvironment (TME), enabling the identification of key molecular drivers and phenotypic landscapes of liver cancer at a single-cell resolution. This review highlights recent advancements in mapping functional cell subsets, phenotypic alterations, and the diversity of the TME. These insights are pivotal for advancing targeted therapies and developing prognostic tools. Moreover, this review covers the ongoing challenges and advances from tumor initiation to progression, offering a detailed perspective on advancing personalized treatment.

Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues

Metastasis is a leading cause of cancer-related deaths, yet understanding how metastatic tumors adapt from their origin to their target tissues remains a fundamental challenge. To address this, we assessed whether primary and metastatic tumors more closely resemble their tissues of origin or target tissues in terms of gene expression. We analyzed expression profiles from multiple cancer types and normal tissues, including single-cell and bulk RNA sequencing data from both paired and unpaired patient cohorts. Primary tumors were overall more transcriptomically similar to their tissues of origin, while metastases shifted toward their target tissues. However, pathway-level analysis highlighted critical metabolic and immune transcriptomic changes toward target tissues during metastasis in both primary and metastatic tumors. In addition, primary tumors exhibited higher activity in cancer hallmarks such as "Activating Invasion and Metastasis" when compared to metastases. This comprehensive analysis provides a transcriptome-wide view of the processes through which cancer tumors adapt to their metastatic environments before and after metastasis.

Analysis of the implication of steroid 5 alpha-reductase 3 on prognosis and immune microenvironment in Liver Hepatocellular Carcinoma

INTRODUCTION

This study combined the bioinformatics and in vitro experiment-related technologies to analyze the impact of steroid 5 alpha-reductase 3 (SRD5A3) on the prognosis and immune microenvironment of Liver Hepatocellular Carcinoma (LIHC).

METHOD

Gene expression and clinical data were obtained from public databases. The prognosis was evaluated using survival, multifactor Cox, enrichment, and mutation analyses. This was then verified through in vitro experiments.

RESULTS

The expression level of SRD5A3 in LIHC tissues was significantly higher than that in the adjacent tissues. Kaplan-Meier survival analysis showed that high SRD5A3 expression was associated with poor overall survival (OS) and short progression-free survival in patients with LIHC. Multivariate Cox regression analysis revealed that positive SRD5A3 expression was an independent risk factor for OS in patients with LIHC. Expression of SRD5A3 was negatively correlated with immune cell infiltration of CD4+ T, CD8+ T, and B cells. GO and KEGG enrichment analyses showed that SRD5A3 was significantly enriched in signaling- and tumor metastasis-related pathways. Nomogram and calibration curve showed that the predicted performance of the model was consistent with the actual results. In vitro results confirmed that SRD5A3 knockdown inhibited the migration, invasion, and proliferation of LIHC cells.

CONCLUSIONS

SRD5A3 is actively expressed in LIHC, and positive expression of SRD5A3 is an independent risk factor for different prognoses in patients with LIHC. SRD5A3 can promote the proliferation, migration, and invasion of liver cancer cells and is related to short immune infiltration in patients with LIHC.

Matrisomics: Beyond the extracellular matrix for unveiling tumor microenvironment

The matrisome, a group of proteins constituting or interacting with the extracellular matrix (ECM), has garnered attention as a potent regulator of cancer progression. An increasing number of studies have focused on cancer matrisome utilizing diverse -omics approaches. Here, we present diverse patterns of matrisomal populations within cancer tissues, exploring recent -omics studies spanning different '-omics' levels (epigenomics, genomics, transcriptomics, and proteomics), as well as newly developed sequencing techniques such as single-cell RNA sequencing and spatial transcriptomics. Some matrisome genes showed uniform patterns of upregulated or downregulated expression across various cancers, while others displayed different expression patterns according to the cancer types. This matrisomal dysregulation in cancer was further examined according to their originating cell type and spatial location in the tumor tissue. Experimental studies were also collected to demonstrate the identified roles of matrisome genes during cancer progression. Interestingly, many studies on cancer matrisome have suggested matrisome genes as effective biomarkers in cancer research. Although the specific mechanisms and clinical applications of cancer matrisome have not yet been fully elucidated, recent techniques and analyses on cancer matrisomics have emphasized their biological importance in cancer progression and their clinical implications in deciding the efficacy of cancer treatment.

Beyond Cancer Cells: How the Tumor Microenvironment Drives Cancer Progression

Liver cancer represents a substantial global health challenge, contributing significantly to worldwide morbidity and mortality. It has long been understood that tumors are not composed solely of cancerous cells, but also include a variety of normal cells within their structure. These tumor-associated normal cells encompass vascular endothelial cells, fibroblasts, and various inflammatory cells, including neutrophils, monocytes, macrophages, mast cells, eosinophils, and lymphocytes. Additionally, tumor cells engage in complex interactions with stromal cells and elements of the extracellular matrix (ECM). Initially, the components of what is now known as the tumor microenvironment (TME) were thought to be passive bystanders in the processes of tumor proliferation and local invasion. However, recent research has significantly advanced our understanding of the TME's active role in tumor growth and metastasis. Tumor progression is now known to be driven by an intricate imbalance of positive and negative regulatory signals, primarily influenced by specific growth factors produced by both inflammatory and neoplastic cells. This review article explores the latest developments and future directions in understanding how the TME modulates liver cancer, with the aim of informing the design of novel therapies that target critical components of the TME.

Bi-level Graph Learning Unveils Prognosis-Relevant Tumor Microenvironment Patterns in Breast Multiplexed Digital Pathology

The tumor microenvironment is widely recognized for its central role in driving cancer progression and influencing prognostic outcomes. There have been increasing efforts dedicated to characterizing this complex and heterogeneous environment, including developing potential prognostic tools by leveraging modern deep learning methods. However, the identification of generalizable data-driven biomarkers has been limited, in part due to the inability to interpret the complex, black-box predictions made by these models. In this study, we introduce a data-driven yet interpretable approach for identifying patterns of cell organizations in the tumor microenvironment that are associated with patient prognoses. Our methodology relies on the construction of a bi-level graph model: (i) a cellular graph, which models the intricate tumor microenvironment, and (ii) a population graph that captures inter-patient similarities, given their respective cellular graphs, by means of a soft Weisfeiler-Lehman subtree kernel. This systematic integration of information across different scales enables us to identify patient subgroups exhibiting unique prognoses while unveiling tumor microenvironment patterns that characterize them. We demonstrate our approach in a cohort of breast cancer patients and show that the identified tumor microenvironment patterns result in a risk stratification system that provides new complementary information with respect to standard stratification systems. Our results, which are validated in two independent cohorts, allow for new insights into the prognostic implications of the breast tumor microenvironment. This methodology could be applied to other cancer types more generally, providing insights into the cellular patterns of organization associated with different outcomes.

Global research trends in the tumor microenvironment of hepatocellular carcinoma: insights based on bibliometric analysis

Objective

This study aimed to use visual mapping and bibliometric analysis to summarize valuable information on the tumor microenvironment (TME)-related research on hepatocellular carcinoma (HCC) in the past 20 years and to identify the research hotspots and trends in this field.

Methods

We screened all of the relevant literature on the TME of HCC in the Web of Science database from 2003 to 2023 and analysed the research hotspots and trends in this field via VOSviewer and CiteSpace.

Results

A total of 2,157 English studies were collected. According to the prediction, the number of papers that were published in the past three years will be approximately 1,394, accounting for 64.63%. China published the most papers (n=1,525) and had the highest total number of citations (n=32,253). Frontiers In Immunology published the most articles on the TME of HCC (n=75), whereas, Hepatology was the journal with the highest total number of citations (n=4,104) and average number of citations (n=91). The four clusters containing keywords such as "cancer-associated fibroblasts", "hepatic stellate cells", "immune cells", "immunotherapy", "combination therapy", "landscape", "immune infiltration", and "heterogeneity" are currently hot research topics in this field. The keywords "cell death", "ferroptosis", "biomarkers", and "prognostic features" have emerged relatively recently, and these research directions are becoming increasingly popular.

Conclusions

We identified four key areas of focus in the study of the TME in HCC: the main components and roles in the TME, immunotherapy, combination therapy, and the microenvironmental landscape. Moreover, the result of our study indicate that effect of ferroptosis on the TME in HCC may become a future research trend.

Liver metastasis and resistance to immunotherapy in microsatellite stable colorectal cancer. A literature review

Background

Microsatellite stable (MSS) metastatic colorectal cancer (CRC) remains predominantly managed with chemotherapy. The use of immunotherapy, whether alone or in combination with other systemic or local treatments, displays limited success, especially in the context of active liver metastases (LM). The mechanisms responsible for this resistance are not fully understood.

Methods

We conducted a comprehensive search across electronic databases such as Medline, PubMed, Google Scholar and ScienceDirect. This search targeted translational studies evaluating the liver tumour immune microenvironment and immune tolerance mechanisms in CRC with LM and prospective studies that assessed immunotherapy either as a standalone treatment or in combination with other systemic or local therapies for patients diagnosed with MSS CRC. Our primary objectives included elucidating the mechanisms of resistance originating from LM in a non-systematic literature review and presenting a summary of the outcomes observed in prospective trials utilising immune checkpoint inhibitors (ICIs), with a focus on the presence of LM.

Findings

There were 16 prospective trials evaluating immunotherapy for metastatic CRC comprising 1,713 patients. Response rates to immunotherapy inpatients with colorectal liver metastases (CRLM) varied from 0% to 23%. Overall, reduced or null responses to immunotherapy in the presence of liver metastasis in comparison to patients without liver involvement were observed.

Conclusion

Studies consistently show the resistance derived from classical ICI, both alone and in combination with other systemic treatments in patients with CRLM. The design of upcoming trials using immunotherapy should consider LM as a stratification factor or contemplate excluding patients with liver involvement.

Efficacy and safety of first-line treatments for advanced hepatocellular carcinoma patients: a systematic review and network meta-analysis

Background

The first-line treatment for advanced hepatocellular carcinoma has evolved significantly. This study aimed to identify the most beneficial regimen.

Methods

A systematic search was conducted from July 2012 to August 2024 across the following four databases: PubMed, Embase, Cochrane Library, and ClinicalTrials.gov. This search focused on phase III prospective randomized controlled trials that compared first-line treatment for advanced hepatocellular carcinoma.

Results

Seventeen studies involving 10322 patients were included in this network meta-analysis. Of the studies we included, twelve studies were global multicenter clinical studies, four were initiated in China, and one was initiated in Korea. The results of our statistical analysis suggest that Hepatic artery infusion chemotherapy with oxaliplatin plus fluorouracil (HAIC-FO) demonstrated significant overall survival (OS) benefits compared with most treatments, including various immune checkpoint inhibitors (ICIs) and anti-vascular endothelial growth factor tyrosine kinase inhibitors (VEGF-TKIs). In terms of OS, HAIC had shown similar efficacy with sorafenib plus FOLFOX (HR, 0.88; 95% CI: 0.37-2.09) and transcatheter arterial chemoembolization (TACE) combined with lenvatinib (HR, 0.69; 95% CI: 0.30-1.56). Notably, immune-related treatments, such as ICIs combined with anti-VEGF therapies, also showed improved OS compared with anti-VEGF-TKIs alone. In terms of progression-free survival (PFS), HAIC-FO outperformed anti-VEGF-TKI monotherapy, ICI monotherapy, and several ICI combinations. However, it was not superior to lenvatinib plus TACE or lenvatinib plus pembrolizumab. Based on the Surface Under the Cumulative Ranking Curve (SUCRA) values, HAIC-FO was ranked the most effective in terms of OS (SUCRA = 0.961) and objective response rate (ORR) (SUCRA = 0.971). The results of the subgroup analysis suggested that HAIC-FO achieved the best OS benefit in the macrovascular invasion (MVI) and extrahepatic spread (EHS) subgroup (SUCRA = 0.99) and that tremelimumab combined with durvalumab achieved the best OS benefit in the Asian subgroup (SUCRA = 0.88).

Conclusion

This systematic review and network meta-analysis suggest that HAIC-based therapies may become a potential first-line treatment option for advanced HCC, especially for patients in Mainland China with MVI and EHS. Additionally, immune-related treatments may be more suitable for Asian populations.

Spatial genomics: mapping human steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD, formerly known as non-alcoholic fatty liver disease) is a leading cause of chronic liver disease worldwide. MASLD can progress to metabolic dysfunction-associated steatohepatitis (MASH, formerly known as non-alcoholic steatohepatitis) with subsequent liver cirrhosis and hepatocellular carcinoma formation. The advent of current technologies such as single-cell and single-nuclei RNA sequencing have transformed our understanding of the liver in homeostasis and disease. The next frontier is contextualizing this single-cell information in its native spatial orientation. This understanding will markedly accelerate discovery science in hepatology, resulting in a further step-change in our knowledge of liver biology and pathobiology. In this Review, we discuss up-to-date knowledge of MASLD development and progression and how the burgeoning field of spatial genomics is driving exciting new developments in our understanding of human liver disease pathogenesis and therapeutic target identification.

In vivo interaction screening reveals liver-derived constraints to metastasis

It is estimated that only 0.02% of disseminated tumour cells are able to seed overt metastases1. While this suggests the presence of environmental constraints to metastatic seeding, the landscape of host factors controlling this process remains largely unclear. Here, combining transposon technology2 and fluorescence niche labelling3, we developed an in vivo CRISPR activation screen to systematically investigate the interactions between hepatocytes and metastatic cells. We identify plexin B2 as a critical host-derived regulator of liver colonization in colorectal and pancreatic cancer and melanoma syngeneic mouse models. We dissect a mechanism through which plexin B2 interacts with class IV semaphorins on tumour cells, leading to KLF4 upregulation and thereby promoting the acquisition of epithelial traits. Our results highlight the essential role of signals from the liver parenchyma for the seeding of disseminated tumour cells before the establishment of a growth-promoting niche. Our findings further suggest that epithelialization is required for the adaptation of CRC metastases to their new tissue environment. Blocking the plexin-B2-semaphorin axis abolishes metastatic colonization of the liver and therefore represents a therapeutic strategy for the prevention of hepatic metastases. Finally, our screening approach, which evaluates host-derived extrinsic signals rather than tumour-intrinsic factors for their ability to promote metastatic seeding, is broadly applicable and lays a framework for the screening of environmental constraints to metastasis in other organs and cancer types.

Estrogen Receptor Blockade Potentiates Immunotherapy for Liver Metastases by Altering the Liver Immunosuppressive Microenvironment

Liver metastases (LM) remain a major cause of cancer-related death and are a major clinical challenge. LM and the female sex are predictors of a poorer response to immunotherapy but the underlying mechanisms remain unclear. We previously reported on a sexual dimorphism in the control of the tumor microenvironment (TME) of colorectal carcinoma liver metastases (CRCLM) and identified estrogen as a regulator of an immunosuppressive TME in the liver. Here we aimed to assess the effect of estrogen deprivation on the cytokine/chemokine profile associated with CRCLM, using a multiplex cytokine array and the RNAscope technology, and its effects on the innate and adaptive immune responses in the liver. We also evaluated the benefit of combining the selective estrogen-receptor degrader Fulvestrant with immune checkpoint blockade for the treatment of CRCLM. We show that estrogen depletion altered the cytokine/chemokine repertoire of the liver, decreased macrophage polarization, as reflected in reduced accumulation of tumor infiltrating M2 macrophages and increased the accumulation of CCL5+/CCR5+ CD8+ T and NKT cells in the liver TME. Similar results were obtained in a murine pancreatic ductal adenocarcinoma model. Importantly, treatment with Fulvestrant also increased the accumulation of CD8+CCL5+, CD8+CCR5+ T and NK cells in the liver TME and enhanced the therapeutic benefit of anti-PD1 immunotherapy, resulting in a significant reduction in the outgrowth of LM. Taken together, our results show that estrogen regulates immune cell recruitment to the liver and suggest that inhibition of estrogen action could potentiate the tumor-inhibitory effect of immunotherapy in hormone-independent and immunotherapy-resistant metastatic cancer.

SIGNIFICANCE

The immune microenvironment of the liver plays a major role in controlling the expansion of hepatic metastases and is regulated by estrogen. We show that treatment of tumor-bearing mice with an estrogen receptor degrader potentiated an anti-metastatic effect of immunotherapy. Our results provide mechanistic insight into clinical findings and a rationale for evaluating the efficacy of combination anti-estrogen and immunotherapy for prevention and/or treatment of hepatic metastases in female patients.

Metastasis and basement membrane-related signature enhances hepatocellular carcinoma prognosis and diagnosis by integrating single-cell RNA sequencing analysis and immune microenvironment assessment

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and second leading cause of cancer-related deaths worldwide. The heightened mortality associated with HCC is largely attributed to its propensity for metastasis, which cannot be achieved without remodeling or loss of the basement membrane (BM). Despite advancements in targeted therapies and immunotherapies, resistance and limited efficacy in late-stage HCC underscore the urgent need for better therapeutic options and early diagnostic biomarkers. Our study aimed to address these gaps by investigating and evaluating potential biomarkers to improve survival outcomes and treatment efficacy in patients with HCC.

METHOD

In this study, we collected the transcriptome sequencing, clinical, and mutation data of 424 patients with HCC from The Cancer Genome Atlas (TCGA) and 240 from the International Cancer Genome Consortium (ICGC) databases. We then constructed and validated a prognostic model based on metastasis and basement membrane-related genes (MBRGs) using univariate and multivariate Cox regression analyses. Five immune-related algorithms (CIBERSORT, QUANTISEQ, MCP counter, ssGSEA, and TIMER) were then utilized to examine the immune landscape and activity across high- and low-risk groups. We also analyzed Tumor Mutation Burden (TMB) values, Tumor Immune Dysfunction and Exclusion (TIDE) scores, mutation frequency, and immune checkpoint gene expression to evaluate immune treatment sensitivity. We analyzed integrin subunit alpha 3 (ITGA3) expression in HCC by performing single-cell RNA sequencing (scRNA-seq) analysis using the TISCH 2.0 database. Lastly, wound healing and transwell assays were conducted to elucidate the role of ITGA3 in tumor metastasis.

RESULTS

Patients with HCC were categorized into high- and low-risk groups based on the median values, with higher risk scores indicating worse overall survival. Five immune-related algorithms revealed that the abundance of immune cells, particularly T cells, was greater in the high-risk group than in the low-risk group. The high-risk group also exhibited a higher TMB value, mutation frequency, and immune checkpoint gene expression and a lower tumor TIDE score, suggesting the potential for better immunotherapy outcomes. Additionally, scRNA-seq analysis revealed higher ITGA3 expression in tumor cells compared with normal hepatocytes. Wound healing scratch and transwell cell migration assays revealed that overexpression of the MBRG ITGA3 enhanced migration of HCC HepG2 cells.

CONCLUSION

This study established a direct molecular correlation between metastasis and BM, encompassing clinical features, tumor microenvironment, and immune response, thereby offering valuable insights for predicting clinical outcomes and immunotherapy responses in HCC.

Cell atlas of the regenerating human liver after portal vein embolization

The liver has the remarkable capacity to regenerate. In the clinic, regeneration is induced by portal vein embolization, which redirects portal blood flow, resulting in liver hypertrophy in locations with increased blood supply, and atrophy of embolized segments. Here, we apply single-cell and single-nucleus transcriptomics on healthy, hypertrophied, and atrophied patient-derived liver samples to explore cell states in the regenerating liver. Our data unveils pervasive upregulation of genes associated with developmental processes, cellular adhesion, and inflammation in post-portal vein embolization liver, disrupted portal-central hepatocyte zonation, and altered cell subtype composition of endothelial and immune cells. Interlineage crosstalk analysis reveals mesenchymal cells as an interaction hub between immune and endothelial cells, and highlights the importance of extracellular matrix proteins in liver regeneration. Moreover, we establish tissue-scale iterative indirect immunofluorescence imaging for high-dimensional spatial analysis of perivascular microenvironments, uncovering changes to tissue architecture in regenerating liver lobules. Altogether, our data is a rich resource revealing cellular and histological changes in human liver regeneration.

Applications of single-cell multi-omics in liver cancer

Primary liver cancer, more specifically hepatocellular carcinoma (HCC), remains a significant global health problem associated with increasing incidence and mortality. Clinical, biological, and molecular heterogeneity are well-known hallmarks of cancer and HCC is considered one of the most heterogeneous tumour types, displaying substantial inter-patient, intertumoural and intratumoural variability. This heterogeneity plays a pivotal role in hepatocarcinogenesis, metastasis, relapse and drug response or resistance. Unimodal single-cell sequencing techniques have already revolutionised our understanding of the different layers of molecular hierarchy in the tumour microenvironment of HCC. By highlighting the cellular heterogeneity and the intricate interactions among cancer, immune and stromal cells before and during treatment, these techniques have contributed to a deeper comprehension of tumour clonality, hematogenous spreading and the mechanisms of action of immune checkpoint inhibitors. However, major questions remain to be elucidated, with the identification of biomarkers predicting response or resistance to immunotherapy-based regimens representing an important unmet clinical need. Although the application of single-cell multi-omics in liver cancer research has been limited thus far, a revolution of individualised care for patients with HCC will only be possible by integrating various unimodal methods into multi-omics methodologies at the single-cell resolution. In this review, we will highlight the different established single-cell sequencing techniques and explore their biological and clinical impact on liver cancer research, while casting a glance at the future role of multi-omics in this dynamic and rapidly evolving field.

Single-cell transcriptional profiling of clear cell renal cell carcinoma reveals a tumor-associated endothelial tip cell phenotype

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of renal cancer, accounting for over 75% of cases. The asymptomatic nature of the disease contributes to late-stage diagnoses and poor survival. Highly vascularized and immune infiltrated microenvironment are prominent features of ccRCC, yet the interplay between vasculature and immune cells, disease progression and response to therapy remains poorly understood. Using droplet-based single-cell RNA sequencing we profile 50,236 transcriptomes from paired tumor and healthy adjacent kidney tissues. Our analysis reveals significant heterogeneity and inter-patient variability of the tumor microenvironment. Notably, we discover a previously uncharacterized vasculature subpopulation associated with epithelial-mesenchymal transition. The cell-cell communication analysis reveals multiple modes of immunosuppressive interactions within the tumor microenvironment, including clinically relevant interactions between tumor vasculature and stromal cells with immune cells. The upregulation of the genes involved in these interactions is associated with worse survival in the TCGA KIRC cohort. Our findings demonstrate the role of tumor vasculature and stromal cell populations in shaping the ccRCC microenvironment and uncover a subpopulation of cells within the tumor vasculature that is associated with an angiogenic phenotype.

Comprehensively analysis of IL33 in hepatocellular carcinoma prognosis, immune microenvironment and biological role

IL33 plays an important role in cancer. However, the role of liver cancer remains unclear. Open-accessed data was obtained from the Cancer Genome Atlas, Xena, and TISCH databases. Different algorithms and R packages are used to perform various analyses. Here, in our comprehensive study on IL33 in HCC, we observed its differential expression across cancers, implicating its role in cancer development. The single-cell analysis highlighted its primary expression in endothelial cells, unveiling correlations within the HCC microenvironment. Also, the expression level of IL33 was correlated with patients survival, emphasizing its potential prognostic value. Biological enrichment analyses revealed associations with stem cell division, angiogenesis, and inflammatory response. IL33's impact on the immune microenvironment showcased correlations with diverse immune cells. Genomic features and drug sensitivity analyses provided insights into IL33's broader implications. In a pan-cancer context, IL33 emerged as a potential tumour-inhibitor, influencing immune-related molecules. This study significantly advances our understanding of IL33 in cancer biology. IL33 exhibited differential expression across cancers, particularly in endothelial cells within the HCC microenvironment. IL33 is correlated with the survival of HCC patients, indicating potential prognostic value and highlighting its broader implications in cancer biology.

Mapping of mitogen and metabolic sensitivity in organoids defines requirements for human hepatocyte growth

Mechanisms underlying human hepatocyte growth in development and regeneration are incompletely understood. In vitro, human fetal hepatocytes (FH) can be robustly grown as organoids, while adult primary human hepatocyte (PHH) organoids remain difficult to expand, suggesting different growth requirements between fetal and adult hepatocytes. Here, we characterize hepatocyte organoid outgrowth using temporal transcriptomic and phenotypic approaches. FHs initiate reciprocal transcriptional programs involving increased proliferation and repressed lipid metabolism upon initiation of organoid growth. We exploit these insights to design maturation conditions for FH organoids, resulting in acquisition of mature hepatocyte morphological traits and increased expression of functional markers. During PHH organoid outgrowth in the same culture condition as for FHs, the adult transcriptomes initially mimic the fetal transcriptomic signatures, but PHHs rapidly acquire disbalanced proliferation-lipid metabolism dynamics, resulting in steatosis and halted organoid growth. IL6 supplementation, as emerged from the fetal dataset, and simultaneous activation of the metabolic regulator FXR, prevents steatosis and promotes PHH proliferation, resulting in improved expansion of the derived organoids. Single-cell RNA sequencing analyses reveal preservation of their fetal and adult hepatocyte identities in the respective organoid cultures. Our findings uncover mitogen requirements and metabolic differences determining proliferation of hepatocytes changing from development to adulthood.

Impact of metabolic dysfunction-associated steatotic liver disease on the efficacy of immunotherapy in patients with chronic hepatitis B-related hepatocellular carcinoma

OBJECTIVE

To investigate the impact of metabolic dysfunction-associated steatotic liver disease (MASLD) on the efficacy of immune checkpoint inhibitor (ICI)-based therapy in patients with chronic hepatitis B (CHB)-related hepatocellular carcinoma (HCC).

METHODS

A total of 155 patients with CHB-related HCC who received ICI-based therapy (in the Department of Hepatology, Tianjin Second People's Hospital and Department of Hepatobiliary Oncology, Tianjin Medical University Cancer Institute & Hospital) between April 2021 and December 2023 were evaluated. Patients were divided into two groups: MASLD concurrent with CHB [MASLD-CHB] (n = 38), and CHB (n = 117).

RESULTS

The median progression-free survival (PFS, 6.9 months vs. 9.3 months; P = 0.001), progressive disease (57.89% vs. 37.61%; P = 0.028), and disease control rate (42.11% vs. 62.39%; P = 0. 028) in the MASLD-CHB group were significantly worse than the CHB group. The median overall survival was not attained. The percentage of CD4+PD1+ (17. 56% vs. 8.89%; P < 0.001) and CD8+PD1+ T cells (10.50% vs. 7.42%; P = 0.005) in patient samples from the MASLD-CHB group were significantly higher than the CHB group. Concurrent MASLD [hazard ratio (HR) = 1.921; 95% CI, 1.138-3.245; P = 0.015] and alpha-fetoprotein levels after 3 months of treatment (HR = 2.412; 95% CI, 1.360-4.279; P = 0.003) were independent risk factors for PFS in all patients.

CONCLUSIONS

ICI-based therapy in patients with CHB-related HCC and concurrent MASLD resulted in poorer efficacy and shorter PFS compared to patients with CHB-related HCC alone.

Macrophages Orchestrate the Liver Tumor Microenvironment

Liver cancer is one of the leading causes of cancer-related mortality. Hepatocellular carcinoma and cholangiocarcinoma are the most common types, and despite numerous advances, therapeutic options still remain poor for these cancer patients. Tumor development and progression strictly depend on a supportive tumor microenvironment (TME). Tumor-associated macrophages (TAMs) are the most abundant immune cells population within a tumorigenic liver; they sustain cancer cells' growth and invasiveness, and their presence is correlated with a poor prognosis. Furthermore, TAM cross-talk with cells and components of the TME promotes immunosuppression, a desmoplastic response, and angiogenesis. In this review, we summarize the latest advances in understanding TAM heterogeneity and function, with a particular focus on TAM modulation of the TME. We also discuss the potential of targeting macrophage subpopulations and how this is now being exploited in current clinical trials for the treatment of liver cancer.

Emerging Roles of Spatial Transcriptomics in Liver Research

Spatial transcriptomics, leveraging sequencing- and imaging-based techniques, has emerged as a groundbreaking technology for mapping gene expression within the complex architectures of tissues. This approach provides an in-depth understanding of cellular and molecular dynamics across various states of healthy and diseased livers. Through the integration of sophisticated bioinformatics strategies, it enables detailed exploration of cellular heterogeneity, transitions in cell states, and intricate cell-cell interactions with remarkable precision. In liver research, spatial transcriptomics has been particularly revelatory, identifying distinct zonated functions of hepatocytes that are crucial for understanding the metabolic and detoxification processes of the liver. Moreover, this technology has unveiled new insights into the pathogenesis of liver diseases, such as the role of lipid-associated macrophages in steatosis and endothelial cell signals in liver regeneration and repair. In the domain of liver cancer, spatial transcriptomics has proven instrumental in delineating intratumor heterogeneity, identifying supportive microenvironmental niches and revealing the complex interplay between tumor cells and the immune system as well as susceptibility to immune checkpoint inhibitors. In conclusion, spatial transcriptomics represents a significant advance in hepatology, promising to enhance our understanding and treatment of liver diseases.

Fibroblast-Derived Lysyl Oxidase Increases Oxidative Phosphorylation and Stemness in Cholangiocarcinoma

BACKGROUND & AIMS

Metabolic and transcriptional programs respond to extracellular matrix-derived cues in complex environments, such as the tumor microenvironment. Here, we demonstrate how lysyl oxidase (LOX), a known factor in collagen crosslinking, contributes to the development and progression of cholangiocarcinoma (CCA).

METHODS

Transcriptomes of 209 human CCA tumors, 143 surrounding tissues, and single-cell data from 30 patients were analyzed. The recombinant protein and a small molecule inhibitor of the LOX activity were used on primary patient-derived CCA cultures to establish the role of LOX in migration, proliferation, colony formation, metabolic fitness, and the LOX interactome. The oncogenic role of LOX was further investigated by RNAscope and in vivo using the AKT/NICD genetically engineered murine CCA model.

RESULTS

We traced LOX expression to hepatic stellate cells and specifically hepatic stellate cell-derived inflammatory cancer-associated fibroblasts and found that cancer-associated fibroblast-driven LOX increases oxidative phosphorylation and metabolic fitness of CCA, and regulates mitochondrial function through transcription factor A, mitochondrial. Inhibiting LOX activity in vivo impedes CCA development and progression. Our work highlights that LOX alters tumor microenvironment-directed transcriptional reprogramming of CCA cells by facilitating the expression of the oxidative phosphorylation pathway and by increasing stemness and mobility.

CONCLUSIONS

Increased LOX is driven by stromal inflammatory cancer-associated fibroblasts and correlates with diminished survival of patients with CCA. Modulating the LOX activity can serve as a novel tumor microenvironment-directed therapeutic strategy in bile duct pathologies.

Heterogeneity in Liver Cancer Immune Microenvironment: Emerging Single-Cell and Spatial Perspectives

Primary liver cancer is a solid malignancy with a high mortality rate. The success of immunotherapy has shown great promise in improving patient care and highlights a crucial need to understand the complexity of the liver tumor immune microenvironment (TIME). Recent advances in single-cell and spatial omics technologies, coupled with the development of systems biology approaches, are rapidly transforming the landscape of tumor immunology. Here we review the cellular landscape of liver TIME from single-cell and spatial perspectives. We also discuss the cellular interaction networks within the tumor cell community in regulating immune responses. We further highlight the challenges and opportunities with implications for biomarker discovery, patient stratification, and combination immunotherapies.

Unravelling immune microenvironment features underlying tumor progression in the single-cell era

The relationship between the immune cell and tumor occurrence and progression remains unclear. Profiling alterations in the tumor immune microenvironment (TIME) at high resolution is crucial to identify factors influencing cancer progression and enhance the effectiveness of immunotherapy. However, traditional sequencing methods, including bulk RNA sequencing, exhibit varying degrees of masking the cellular heterogeneity and immunophenotypic changes observed in early and late-stage tumors. Single-cell RNA sequencing (scRNA-seq) has provided significant and precise TIME landscapes. Consequently, this review has highlighted TIME cellular and molecular changes in tumorigenesis and progression elucidated through recent scRNA-seq studies. Specifically, we have summarized the cellular heterogeneity of TIME at different stages, including early, late, and metastatic stages. Moreover, we have outlined the related variations that may promote tumor occurrence and metastasis in the single-cell era. The widespread applications of scRNA-seq in TIME will comprehensively redefine the understanding of tumor biology and furnish more effective immunotherapy strategies.

Single-cell Landscape of Malignant Transition: Unraveling Cancer Cell-of-Origin and Heterogeneous Tissue Microenvironment

Understanding disease progression and sophisticated tumor ecosystems is imperative for investigating tumorigenesis mechanisms and developing novel prevention strategies. Here, we dissected heterogeneous microenvironments during malignant transitions by leveraging data from 1396 samples spanning 13 major tissues. Within transitional stem-like subpopulations highly enriched in precancers and cancers, we identified 30 recurring cellular states strongly linked to malignancy, including hypoxia and epithelial senescence, revealing a high degree of plasticity in epithelial stem cells. By characterizing dynamics in stem-cell crosstalk with the microenvironment along the pseudotime axis, we found differential roles of ANXA1 at different stages of tumor development. In precancerous stages, reduced ANXA1 levels promoted monocyte differentiation toward M1 macrophages and inflammatory responses, whereas during malignant progression, upregulated ANXA1 fostered M2 macrophage polarization and cancer-associated fibroblast transformation by increasing TGF-β production. Our spatiotemporal analysis further provided insights into mechanisms responsible for immunosuppression and a potential target to control evolution of precancer and mitigate the risk for cancer development.

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.

PANoptosis-related molecule CASP2 affects the immune microenvironment and immunotherapy response of hepatocellular carcinoma

Background

The involvement of molecules associated with PANoptosis in hepatocellular carcinoma (HCC) is still not well understood.

Methods

Various R packages were utilized to analyze within the R software. Data that was freely accessible was obtained from the databases of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC).

Results

Here, we comprehensively explored the role of PANoptosis-related genes in HCC. The caspase 2 (CASP2) was identified as the interest gene for further analysis. We found that CASP2 is related to the poor prognosis and worse clinical features of HCC patients. Moreover, we explored the biological pathway CASP2 is involved in and found that CASP2 is associated with multiple carcinogenic pathways. Also, we noticed that CASP2 can significantly reshape the HCC immune microenvironment and affect the response rate of immunotherapy. Analysis of drug sensitivity suggested that individuals exhibiting elevated CASP2 levels may display increased susceptibility to doxorubicin and vorinostat while demonstrating resistance towards erlotinib, lapatinib, sunitinib, and temsirolimus. Meanwhile, we explored the single-cell distribution of CASP2 in the HCC microenvironment. To enhance the clinical application of CASP2 in HCC, we constructed a prognosis model using the molecules derived from CASP2, which demonstrated good efficiency in predicting patients prognosis. Moreover, in vitro experiments indicated that CASP2 can significantly inhibits cell proliferation, invasion and migration ability of HCC cells.

Conclusions

Our study comprehensively explored the role of PANoptosis-related molecule CASP2 in HCC, which can provide directions for future studies.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

A spatial map of hepatic mitochondria uncovers functional heterogeneity shaped by nutrient-sensing signaling

In the liver, mitochondria are exposed to different concentrations of nutrients due to their spatial positioning across the periportal and pericentral axis. How the mitochondria sense and integrate these signals to respond and maintain homeostasis is not known. Here, we combine intravital microscopy, spatial proteomics, and functional assessment to investigate mitochondrial heterogeneity in the context of liver zonation. We find that periportal and pericentral mitochondria are morphologically and functionally distinct; beta-oxidation is elevated in periportal regions, while lipid synthesis is predominant in the pericentral mitochondria. In addition, comparative phosphoproteomics reveals spatially distinct patterns of mitochondrial composition and potential regulation via phosphorylation. Acute pharmacological modulation of nutrient sensing through AMPK and mTOR shifts mitochondrial phenotypes in the periportal and pericentral regions, linking nutrient gradients across the lobule and mitochondrial heterogeneity. This study highlights the role of protein phosphorylation in mitochondrial structure, function, and overall homeostasis in hepatic metabolic zonation. These findings have important implications for liver physiology and disease.

Granzyme B+ B cells detected by single-cell sequencing are associated with prognosis in patients with intrahepatic cholangiocarcinoma following liver transplantation

B cells possess anti-tumor functions mediated by granzyme B, in addition to their role in antigen presentation and antibody production. However, the variations in granzyme B+ B cells between tumor and non-tumor tissues have been largely unexplored. Therefore, we integrated 25 samples from the Gene Expression Omnibus database and analyzed the tumor immune microenvironment. The findings uncovered significant inter- and intra-tumoral heterogeneity. Notably, single-cell data showed higher proportions of granzyme B+ B cells in tumor samples compared to control samples, and these levels were positively associated with disease-free survival. The elevated levels of granzyme B+ B cells in tumor samples resulted from tumor cell chemotaxis through the MIF- (CD74 + CXCR4) signaling pathway. Furthermore, the anti-tumor function of granzyme B+ B cells in tumor samples was adversely affected, potentially providing an explanation for tumor progression. These findings regarding granzyme B+ B cells were further validated in an independent clinic cohort of 40 liver transplant recipients with intrahepatic cholangiocarcinoma. Our study unveils an interaction between granzyme B+ B cells and intrahepatic cholangiocarcinoma, opening up potential avenues for the development of novel therapeutic strategies against this disease.

An atlas of cell-type-specific interactome networks across 44 human tumor types

BACKGROUND

Biological processes are controlled by groups of genes acting in concert. Investigating gene-gene interactions within different cell types can help researchers understand the regulatory mechanisms behind human complex diseases, such as tumors.

METHODS

We collected extensive single-cell RNA-seq data from tumors, involving 563 patients with 44 different tumor types. Through our analysis, we identified various cell types in tumors and created an atlas of different immune cell subsets across different tumor types. Using the SCINET method, we reconstructed interactome networks specific to different cell types. Diverse functional data was then integrated to gain biological insights into the networks, including somatic mutation patterns and gene functional annotation. Additionally, genes with prognostic relevance within the networks were also identified. We also examined cell-cell communications to investigate how gene interactions modulate cell-cell interactions.

RESULTS

We developed a data portal called CellNetdb for researchers to study cell-type-specific interactome networks. Our findings indicate that these networks can be used to identify genes with topological specificity in different cell types. We also found that prognostic genes can deconvolved into cell types through analyzing network connectivity. Additionally, we identified commonalities and differences in cell-type-specific networks across different tumor types. Our results suggest that these networks can be used to prioritize risk genes.

CONCLUSIONS

This study presented CellNetdb, a comprehensive repository featuring an atlas of cell-type-specific interactome networks across 44 human tumor types. The findings underscore the utility of these networks in delineating the intricacies of tumor microenvironments and advancing the understanding of molecular mechanisms underpinning human tumors.

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.

The nuclear factor ID3 endows macrophages with a potent anti-tumour activity

Macrophage activation is controlled by a balance between activating and inhibitory receptors1-7, which protect normal tissues from excessive damage during infection8,9 but promote tumour growth and metastasis in cancer7,10. Here we report that the Kupffer cell lineage-determining factor ID3 controls this balance and selectively endows Kupffer cells with the ability to phagocytose live tumour cells and orchestrate the recruitment, proliferation and activation of natural killer and CD8 T lymphoid effector cells in the liver to restrict the growth of a variety of tumours. ID3 shifts the macrophage inhibitory/activating receptor balance to promote the phagocytic and lymphoid response, at least in part by buffering the binding of the transcription factors ELK1 and E2A at the SIRPA locus. Furthermore, loss- and gain-of-function experiments demonstrate that ID3 is sufficient to confer this potent anti-tumour activity to mouse bone-marrow-derived macrophages and human induced pluripotent stem-cell-derived macrophages. Expression of ID3 is therefore necessary and sufficient to endow macrophages with the ability to form an efficient anti-tumour niche, which could be harnessed for cell therapy in cancer.

Highly Accurate Estimation of Cell Type Abundance in Bulk Tissues Based on Single-Cell Reference and Domain Adaptive Matching

Accurately identifies the cellular composition of complex tissues, which is critical for understanding disease pathogenesis, early diagnosis, and prevention. However, current methods for deconvoluting bulk RNA sequencing (RNA-seq) typically rely on matched single-cell RNA sequencing (scRNA-seq) as a reference, which can be limiting due to differences in sequencing distribution and the potential for invalid information from single-cell references. Hence, a novel computational method named SCROAM is introduced to address these challenges. SCROAM transforms scRNA-seq and bulk RNA-seq into a shared feature space, effectively eliminating distributional differences in the latent space. Subsequently, cell-type-specific expression matrices are generated from the scRNA-seq data, facilitating the precise identification of cell types within bulk tissues. The performance of SCROAM is assessed through benchmarking against simulated and real datasets, demonstrating its accuracy and robustness. To further validate SCROAM's performance, single-cell and bulk RNA-seq experiments are conducted on mouse spinal cord tissue, with SCROAM applied to identify cell types in bulk tissue. Results indicate that SCROAM is a highly effective tool for identifying similar cell types. An integrated analysis of liver cancer and primary glioblastoma is then performed. Overall, this research offers a novel perspective for delivering precise insights into disease pathogenesis and potential therapeutic strategies.

TET2-mediated tumor cGAS triggers endothelial STING activation to regulate vasculature remodeling and anti-tumor immunity in liver cancer

Induction of tumor vascular normalization is a crucial measure to enhance immunotherapy efficacy. cGAS-STING pathway is vital for anti-tumor immunity, but its role in tumor vasculature is unclear. Herein, using preclinical liver cancer models in Cgas/Sting-deficient male mice, we report that the interdependence between tumor cGAS and host STING mediates vascular normalization and anti-tumor immune response. Mechanistically, TET2 mediated IL-2/STAT5A signaling epigenetically upregulates tumor cGAS expression and produces cGAMP. Subsequently, cGAMP is transported via LRRC8C channels to activate STING in endothelial cells, enhancing recruitment and transendothelial migration of lymphocytes. In vivo studies in male mice also reveal that administration of vitamin C, a promising anti-cancer agent, stimulates TET2 activity, induces tumor vascular normalization and enhances the efficacy of anti-PD-L1 therapy alone or in combination with IL-2. Our findings elucidate a crosstalk between tumor and vascular endothelial cells in the tumor immune microenvironment, providing strategies to enhance the efficacy of combinational immunotherapy for liver cancer.

Gemcitabine and synthesized silver nanoparticles impact on chemically induced hepatocellular carcinoma in male rats

Objective: Gemcitabine (GEM) is a deoxycytidine analog chemotherapeutic drug widely used to treat many cancers. Silver nanoparticles (AgNPs) are important nanomaterials used to treat many diseases. Using gamma radiation in nanoparticle preparation is a new eco-friendly method. This study aims to evaluate the efficiency of co-treating gemcitabine and silver nanoparticles in treating hepatocellular carcinoma. Method: The AgNPs were characterized using UV-visible spectroscopy, XRD, TEM, and EDX. The MTT cytotoxicity in vitro assay of gemcitabine, doxorubicin, and cyclophosphamide was assessed against Wi38 normal fibroblast and HepG2 HCC cell lines. After HCC development, rats received (10 µg/g b.wt.) of AgNPs three times a week for 4 weeks and/or GEM (5 mg/kg b.wt.) twice weekly for 4 weeks. Liver function enzymes were investigated. Cytochrome P450 and miR-21 genes were studied. Apoptosis was determined by using flow cytometry, and apoptotic modifications in signaling pathways were evaluated via Bcl-2, Bax, Caspase-9, and SMAD-4. Results: The co-treatment of GEM and AgNPs increased apoptosis by upregulating Bax and caspase 9 while diminishing Bcl2 and SMAD4. It also improved cytochrome P450 m-RNA relative expression. The results also proved the cooperation between GEM and AgNPs in deactivating miR21. The impact of AgNPs as an adjuvant treatment with GEM was recognized. Conclusions: The study showed that co-treating AgNPs and GEM can improve the efficiency of GEM alone in treating HCC. This is achieved by enhancing intrinsic and extrinsic apoptotic pathways while diminishing some drawbacks of using GEM alone.

Interspecies transcriptomic comparison identifies a potential porto-sinusoidal vascular disorder rat model suitable for in vivo drug testing

BACKGROUND

Porto-sinusoidal vascular disorder (PSVD) involves a group of rare vascular liver diseases of unknown aetiology that may lead to the development of portal hypertension and its life-threatening complications. Its pathophysiology is not well understood, and animal models described to date do not fully recapitulate human disease.

METHODS

We developed three different PSVD rat models by either immunosensitization (repetitive intraportal LPS or intramuscular spleen extract injections) or toxic (Selfox: combination of FOLFOX and a selenium-enriched diet) treatment and characterized them at haemodynamic, histological, biochemical and transcriptional levels. We compared these results to human data.

RESULTS

All three models developed significant portal hypertension, while only the LPS and the Selfox models displayed PSVD-specific and nonspecific histological alterations in the absence of cirrhosis. Transcriptional comparison between rat models and human data showed that both LPS and Selfox models recapitulate the main transcriptional alterations observed in humans, especially regarding haemostasis, oxidative phosphorylation and cell cycle regulation. Reproducibility and feasibility was higher for the Selfox model.

CONCLUSIONS

The Selfox rat model faithfully reproduces the main alterations described in PSVD. Its use as a preclinical model for drug testing in progressing PSVD can be a significant step forward towards the development of new therapeutic targets for this rare condition.

Multidimensional Analysis of PANoptosis-Related Molecule CASP8: Prognostic Significance, Immune Microenvironment Effect, and Therapeutic Implications in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) presents significant challenges in diagnosis and treatment. Understanding the role of PANoptosis-related molecules in HCC is crucial for advancing therapeutic strategies.

Methods

We conducted a comprehensive analysis using public data from the Cancer Genome Atlas, Human Protein Atlas, Tumor Immune Single Cell Hub, and STRING databases. Techniques included Kaplan-Meier survival curves, Cox regression, LASSO analysis, and various computational methods for understanding the tumor microenvironment. We also employed ClueGO, gene set enrichment analysis, and other algorithms for biological enrichment analysis.

Results

CASP8 emerged as a significant molecule in HCC, correlated with poor survival outcomes. Its expression was predominant in the nucleoplasm and cytosol and varied across different cancer types. Biological enrichment analysis revealed CASP8's association with critical cellular activities and immune responses. In the tumor microenvironment, CASP8 showed correlations with various immune cell types. A nomogram plot was developed for better clinical prognostication. Mutation analysis indicated a higher frequency of TP53 mutations in patients with elevated CASP8 expression. In addition, CASP8 was found to regulate YEATS2 in HCC, highlighting a potential pathway in tumor progression.

Conclusions

Our study underscores the multifaceted role of CASP8 in HCC, emphasizing its prognostic and therapeutic significance. The regulatory relationship between CASP8 and YEATS2 opens new avenues for understanding HCC pathogenesis and treatment strategies.

Hierarchical and automated cell-type annotation and inference of cancer cell of origin with Census

MOTIVATION

Cell-type annotation is a time-consuming yet critical first step in the analysis of single-cell RNA-seq data, especially when multiple similar cell subtypes with overlapping marker genes are present. Existing automated annotation methods have a number of limitations, including requiring large reference datasets, high computation time, shallow annotation resolution, and difficulty in identifying cancer cells or their most likely cell of origin.

RESULTS

We developed Census, a biologically intuitive and fully automated cell-type identification method for single-cell RNA-seq data that can deeply annotate normal cells in mammalian tissues and identify malignant cells and their likely cell of origin. Motivated by the inherently stratified developmental programs of cellular differentiation, Census infers hierarchical cell-type relationships and uses gradient-boosted \decision trees that capitalize on nodal cell-type relationships to achieve high prediction speed and accuracy. When benchmarked on 44 atlas-scale normal and cancer, human and mouse tissues, Census significantly outperforms state-of-the-art methods across multiple metrics and naturally predicts the cell-of-origin of different cancers. Census is pretrained on the Tabula Sapiens to classify 175 cell-types from 24 organs; however, users can seamlessly train their own models for customized applications.

AVAILABILITY AND IMPLEMENTATION

Census is available at Zenodo https://zenodo.org/records/7017103 and on our Github https://github.com/sjdlabgroup/Census.

SAMD13 serves as a useful prognostic biomarker for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common form of liver cancer and the 5-year relative overall survival (OS) rate is less than 20%. Since there are no specific symptoms, most patients with HCC are diagnosed in an advanced stage with poor prognosis. Therefore, identifying novel prognostic biomarkers to improve the survival of patients with HCC is urgently needed. In the present study, we attempted to identify SAMD13 (Sterile Alpha Motif Domain-Containing Protein 13) as a novel biomarker associated with the prognosis of HCC using various bioinformatics tools. SAMD13 was found to be highly expressed pan-cancer; however, the SAMD13 expression was significantly correlated with the worst prognosis in HCC. Clinicopathological analysis revealed that SAMD13 upregulation was significantly associated with advanced HCC stage and high-grade tumor type. Simultaneously, high SAMD13 expression resulted in association with various immune markers in the immune cell subsets by TIMER databases and efficacy of immunotherapy. Methylation analysis showed SAMD13 was remarkably associated with prognosis. Furthermore, a six-hub gene signature associated with poor prognosis was correlated with the cell cycle, transcription, and epigenetic regulation and this analysis may support the connection between SAMD13 expression and drug-resistance. Our study illustrated the characteristics of SAMD13 role in patients with HCC using various bioinformatics tools and highlights its potential role as a therapeutic target and promising biomarker for prognosis in HCC.