Multiregional single-cell dissection of tumor and immune cells reveals stable lock-and-key features in liver cancer

Mtb/HIV co-infection immune microenvironment subpopulations heterogeneity

BACKGROUND

The co-infection of human immunodeficiency virus type 1 (HIV-1) and tuberculosis poses a lethal threat. Currently, our understanding of the altered immune responses and diverse immune cell subpopulations triggered by dual pathogen infections remains inadequate.

METHODS

We utilized single-cell RNA sequencing data from the Gene Expression Omnibus database and the China National GeneBank Nucleotide Sequence Archive to study peripheral blood mononuclear cells from individuals infected with HIV-1 and those co-infected with Mycobacterium tuberculosis (Mtb)/HIV. We investigated cellular components, signaling pathways, biological functions, developmental trajectories, and gene regulatory networks among different cells to determine cellular heterogeneity in the progression of Mtb/HIV co-infection.

RESULTS

We constructed a single-cell global transcriptional landscape of Mtb/HIV co-infection, revealing heterogeneity among various cell subpopulations. CD4+ T_RACK1_STAT1 subpopulation may participate in the JAK-STAT signaling pathway through RACK1-mediated transcriptional regulation of STAT1, potentially mediating the immune response in patients. Targeting CD8+ T_RACK1_TIGIT subpopulation via RACK1 may help restore the effector capacity of CD8+ T cells. Additionally, Mono_HSP90AA1 and Mono_APOBEC3A subpopulations were positioned at the endpoints of monocyte differentiation trajectories in different patients, suggesting their significant roles in distinct types of immune responses. CTL_GNLY and NK_HSPA1A subpopulations were specifically enriched in three distinct HIV-infected patient groups, indicating their crucial roles in the immune cytotoxicity associated with Mtb/HIV co-infection.

CONCLUSION

The immune system disruptions caused by HIV-1 infection are further exacerbated by co-infection with Mtb. This compounded effect leads to significant heterogeneity in immune cell subpopulations among co-infected individuals, promoting immune system dysfunction.

Potential crosstalk between Naïve CD4+ T cells and SPP1+ Macrophages is associated with clinical outcome and therapeutic response in hepatocellular carcinoma

BACKGROUND

The highly heterogeneity of the tumor microenvironment (TME) in hepatocellular carcinoma (HCC) results in diverse clinical outcomes and therapeutic responses. This study aimed to investigate potential intercellular crosstalk and its impact on clinical outcomes and therapeutic responses.

METHODS

Single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST) and bulk RNA sequencing (RNA-seq) datasets were integrated to comprehensively analyze the intercellular interactions within the TME. Multiplex immunohistochemistry was conducted to validate the intercellular interactions. A machine learning-based integrative procedure was used in bulk RNA-seq datasets to generate a risk model to predict prognosis and therapeutic responses.

RESULTS

Survival analyses based on the bulk RNA-seq datasets revealed the negative impact of the naïve Cluster of Differentiation 4+ (CD4) T cells and Secreted Phosphoprotein 1+ (SPP1) macrophages on prognosis. Furthermore, their intricate intercellular crosstalk and spatial colocalization were also observed by scRNA-seq and ST analyses. Based on this crosstalk, a machine learning model, termed the naïve CD4+ T cell and SPP1+ macrophage prognostic score (TMPS), was established in the bulk-RNA seq datasets for prognostic prediction. The TMPS achieved C-index values of 0.785, 0.715, 0.692 and 0.857, respectively, across 4 independent cohorts. A low TMPS was associated with a significantly increased survival rates, improved response to immunotherapy and reduced infiltration of immunosuppressive cells, such as. regulatory T cells. Finally, 8 potential sensitive drugs and 6 potential targets were predicted for patients based on their TMPS.

CONCLUSION

The crosstalk between naïve CD4+ T cells and SPP1+ macrophages play a crucial role in the TME. TMPS can reflect this crosstalk and serve as a valuable tool for prognostic stratification and guiding clinical decision-making.

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.

Opposing regulation of the STING pathway in hepatic stellate cells by NBR1 and p62 determines the progression of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) emerges from chronic inflammation, to which activation of hepatic stellate cells (HSCs) contributes by shaping a pro-tumorigenic microenvironment. Key to this process is p62, whose inactivation leads to enhanced hepatocarcinogenesis. Here, we show that p62 activates the interferon (IFN) cascade by promoting STING ubiquitination by tripartite motif protein 32 (TRIM32) in HSCs. p62, binding neighbor of BRCA1 gene 1 (NBR1) and STING, triggers the IFN cascade by displacing NBR1, which normally prevents the interaction of TRIM32 with STING and its subsequent activation. Furthermore, NBR1 also antagonizes STING by promoting its trafficking to the endosome-lysosomal compartment for degradation independent of autophagy. Of functional relevance, NBR1 deletion completely reverts the tumor-promoting function of p62-deficient HSCs by rescuing the inhibited STING-IFN pathway, thus enhancing anti-tumor responses mediated by CD8+ T cells. Therefore, NBR1 emerges as a synthetic vulnerability of p62 deficiency in HSCs by promoting the STING/IFN pathway, which boosts anti-tumor CD8+ T cell responses to restrain HCC progression.

Exploring MPC1 as a potential ferroptosis-linked biomarker in the cervical cancer tumor microenvironment: a comprehensive analysis

BACKGROUND

The increasing problems of drug and radiotherapy resistance in cervical cancer underscores the need for novel methods for its management. Reports indicate that the expression of MPC1 may be associated with the tumor microenvironment and the occurrence of ferroptosis in cervical cancer. The objective of this study was to visually illustrate the prognostic significance and immunological characterization of MPC1 in cervical cancer.

METHODS

The expression profile and prognostic significance of MPC1 were analyzed using various databases, including UALCAN, TIMER2, GEPIA2, and Kaplan-Meier Plotter. TISIDB, TIMER2, and immunohistochemical analysis were used to investigate the correlation between MPC1 expression and immune infiltration. GO enrichment analysis, KEGG analysis, Reactome analysis, ConsensusPathDB, and GeneMANIA were used to visualize the functional enrichment of MPC1 and signaling pathways related to MPC1. The correlation analysis was carried out to examine the relationship between MPC1 and Ferroptosis gene in TIMER 2.0, ncFO, GEPIA Database and Kaplan-Meier Plotter.

RESULTS

We demonstrated that the expression levels of MPC1 in cervical cancer tissues were lower than those in normal cervical tissues. Kaplan-Meier survival curves showed shorter overall survival in cervical cancer patients with low levels of MPC1 expression. The expression of MPC1 was related to the infiltrating levels of tumor-infiltrating immune cells in cervical cancer. Moreover, MPC1 expression was associated with the iron-mediated cell death pathway, and several important ferroptosis genes were upregulated in cervical cancer cells. Furthermore, after knocking down MPC1 in HeLa cells, the expression of these genes decreased.

CONCLUSION

These findings indicate that MPC1 functions as a prognostic indicator and plays a role in the regulation of the ferroptosis pathway in cervical cancer.

Characterization of cell states in biliary tract cancers identifies mechanisms of therapeutic resistance in a phase II trial of DKN-01/nivolumab

Biliary tract cancers demonstrate profound therapeutic resistance, and broadly effective therapies for refractory disease are lacking. We conducted a single-arm, second-line phase II trial combining DKN-01, a humanized monoclonal antibody targeting Dickkopf-1 (DKK-1), and nivolumab to treat patients with advanced biliary tract cancer (NCT04057365). No objective responses were seen. To identify mechanisms of treatment failure, we analyzed paired pre-treatment and on-treatment biopsies using scRNA-seq and constructed a detailed molecular classification of malignant and immune cells. We annotated five biliary tract cancer malignant cell states: classical, basal, mesenchymal, neural-like, and endothelial-like. Neural-like and endothelial-like states, which drive therapeutic resistance in other cancers, have not previously been described in BTC. Malignant cell states co-varied with distinct immune cell states, revealing diverse mechanisms of myeloid and T-cell mediated immune suppression, including M2 myeloid and terminally exhausted T cell programs that were induced by DKN-01/nivolumab. Here, we provide the first systematic classification of functionally annotated cell states in biliary tract cancer and provide new insight into resistance mechanisms to an immunotherapy combination that can inform the next generation of trials.

Multi-omics analysis unveils the predictive value of IGF2BP3/SPHK1 signaling in cancer stem cells for prognosis and immunotherapeutic response in muscle-invasive bladder cancer

BACKGROUND

Muscle invasive bladder cancer (MIBC) is a life-threatening malignant tumor characterized by high metastasis rates, poor prognosis, and limited treatment options. Immune checkpoint inhibitors (ICIs) targeting PD-1 and PD-L1 represent an emerging treatment for MIBC immunotherapy. However, the characteristics of patients likely to benefit from immunotherapy remain unclear.

METHODS

We performed single-cell mass cytometry (CyTOF) analysis of 179,483 single cells to characterize potential immunotherapy-related cancer stem cells (CSCs)-like populations in the tumor microenvironment of 38 MIBC tissues. The upregulated expression of IGF2BP3 in CD274 + ALDH + CSC-like cells, which was associated with poor clinical prognosis, was analyzed by bulk RNA-sequencing data from an in-house cohort. The functional role of IGF2BP3 was determined through cell proliferation, colony formation, cell apoptosis and sphere formation assays. The regulation of SPHK1 expression by IGF2BP3 was  investigated using methylated RNA immunoprecipitation sequencing (MeRIP-seq) and bulk RNA-sequencing (bulk RNA-seq). We further utilized single-nucleus RNA sequencing (snRNA-seq) data from 67,988 cells of 25 MIBC tissues and single-cell RNA sequencing (scRNA-seq) data from MIBC patient-derived organoids to characterize the molecular features of bladder cancer cells co-expressing IGF2BP3 and SPHK1. Spatial transcriptomics (ST) and co-detection by indexing (CODEX) analysis were used to describe the spatial distribution and interactions of IGF2BP3 + SPHK1 + bladder cancer cells and immune cells.

RESULTS

A subset of CD274 + ALDH + CSC-like cells was identified, associating with immunosuppression and low survival rates in MIBC patients. IGF2BP3, an m6A reader gene, was found to be upregulated in the CD274 + ALDH + CSC-like cell population and linked to poor clinical prognosis in MIBC. Knockout of IGF2BP3 dramatically promoted cell apoptosis and reduced cell proliferation in T24 cells. By integrating MeRIP-seq and bulk RNA-seq analyses, we identified SPHK1 served as a substrate for IGF2BP3 in an m6A-dependent manner. Further snRNA-seq, scRNA-seq, ST, and CODEX analysis revealed a closer topographical distance between IGF2BP3 + SPHK1 + bladder cancer cells and exhausted CD8 + T cells, providing one explanation for the superior response to immunotherapy in IGF2BP3 + SPHK1 + bladder cancer cells-enriched patients. Finally, an ICI-associated signature was developed based on the enriched genes of IGF2BP3 + SPHK1 + bladder cancer cells, and its potential ability to predict the response to immunotherapy was validated in two independent immunotherapy cohort.

CONCLUSIONS

Our study highlighted the critical involvement of the IGF2BP3/SPHK1 signaling in maintaining the stemness of CSCs and promoting MIBC progression. Additionally, these findings suggested that the IGF2BP3/SPHK1 signaling might serve as a biomarker for prognosis and immunotherapy response in MIBC.

HCC spatial transcriptomic profiling reveals significant and potentially targetable cancer-endothelial interactions

BACKGROUND

HCC is a highly vascular tumor, and many effective drug regimens target the tumor blood vessels. Prior bulk HCC subtyping data used bulk transcriptomes, which contained a mixture of parenchymal and stromal contributions.

METHODS

We utilized computational deconvolution and cell-cell interaction analyses to cell type-specific (tumor-enriched and vessel-enriched) spatial transcriptomic data collected from 41 resected HCC tissue specimens.

RESULTS

We report that the prior Hoshida bulk transcriptional subtyping schema is driven largely by an endothelial fraction, show an alternative tumor-specific schema has potential prognostic value, and use spatially paired ligand-receptor analyses to identify known and novel (LGALS9 tumor-HAVCR2 vessel) signaling relationships that drive HCC biology in a subtype-specific and potentially targetable manner.

CONCLUSIONS

Our study leverages spatial gene expression profiling technologies to dissect HCC heterogeneity and identify heterogeneous signaling relationships between cancer cells and their endothelial cells. Future validation and expansion of these findings may validate novel cancer-endothelial cell interactions and related drug targets.

Survival benefit and spatial properties of tertiary lymphoid structures in esophageal squamous cell carcinoma with neoadjuvant therapies

Tertiary lymphoid structures (TLSs) were associated with survival in esophageal squamous cell carcinoma (ESCC) undergoing surgery alone (SA). However, their clinical relevance in neoadjuvant therapies remains less known. Here, we firstly investigated the presence, maturation and spatial distribution of TLSs in 359 ESCC patients receiving neoadjuvant chemotherapy (NCT), neoadjuvant immunotherapy (NCI), neoadjuvant chemoradiotherapy (NCRT) or SA. We found mature TLS (MTLS) was an independent prognostic factor in ESCC. NCI group had the lowest immature TLS cases. NCRT group had the lowest MTLSs. MTLSs mostly located in stromal and normal compartments; these MTLSs were positively correlated with neoadjuvant therapy outcomes. NCI group displayed the highest T cells within 150 μm proximity of TLSs among the four groups. Most T cells were dispersed up to more than 150 μm from TLSs, while B cells remained concentrated within TLSs. Innate lymphoid cells and follicular dendritic cells infiltrated and connected with survival differently in NCRT and NCI groups compared with SA group. The novel PD-L1 combined positive score, NCPS, was positively connected with MTLSs and neoadjuvant therapy efficacy. ScRNA-seq analysis revealed TLS+ tumors had increased plasma cells, B cells, Th17, Tfh and Th1, and elevated exhausted CD8+ T cells that highly expressed checkpoint molecules and granzymes. Conclusively, MTLSs favored treatment outcome in ESCC patients receiving multiple neoadjuvant therapies. The spatial distribution of MTLSs was associated with multiregional immune status modified by the neoadjuvant therapies.

Abnormal Cellular Populations Shape Thymic Epithelial Tumor Heterogeneity and Anti-Tumor by Blocking Metabolic Interactions in Organoids

A variety of abnormal epithelial cells and immature and mature immune cells in thymic epithelial tumors (TETs) affect histopathological features, the degree of malignancy, and the response to treatment. Here, gene expression, trajectory inference, and T cell antigen receptor (TCR)-based lineage tracking are profiled in TETs at single-cell resolution. An original subpopulation of KRT14+ progenitor cells with a spindle cell phenotype is shown. An abnormal infiltration of immature T cells with a TCR hyper-rearrangement state is revealed, due to the lack of CCL21+ medullary epithelial cells. For thymic carcinoma, the novel biomarkers of MSLN, CCL20, and SLC1A5 are identified and observed an elevated expression of LAG3 and HAVCR2 in malignant tumorn-infiltrating mature T cells. These common features based on the single-cell populations may inform pathological reclassification of TETs. Meanwhile, it is found that macrophages (MACs) attract thymic tumor cells through the LGALS9-SLC1A5 axis, providing them with glutamine to elicit metabolic reprogramming. This MAC-based metabolic pattern can promote malignancy progression. Additionally, an interactive immune environment in TETs is identified that correlates with the infiltration of abnormal FOXI1+ CFTR- ionocytes. Collectively, the data broaden the knowledge of TET cellular ecosystems, providing a basis for tackling histopathological diagnosis and related treatment.

HKDC1 promotes liver cancer stemness under hypoxia through stabilizing β-catenin

BACKGROUND AND AIMS

Hexokinases (HKs), a group of enzymes catalyzing the first step of glycolysis, have been shown to play important roles in liver metabolism and tumorigenesis. Our recent studies identified hexokinase domain containing 1 (HKDC1) as a top candidate associated with liver cancer metastasis. We aimed to compare its cell-type specificity with other HKs upregulated in liver cancer and investigate the molecular mechanisms underlying its involvement in liver cancer metastasis.

APPROACH AND RESULTS

We found that, compared to HK1 and HK2, the other 2 commonly upregulated HKs in liver cancer, HKDC1 was most strongly associated with the metastasis potential of tumors and organoids derived from 2 liver cancer mouse models we previously established. RNA in situ hybridization and single-cell RNA-seq analysis revealed that HKDC1 was specifically upregulated in malignant cells in HCC and cholangiocarcinoma patient tumors, whereas HK1 and HK2 were widespread across various tumor microenvironment lineages. An unbiased metabolomic profiling demonstrated that HKDC1 overexpression in HCC cells led to metabolic alterations distinct from those from HK1 and HK2 overexpression, with HKDC1 particularly impacting the tricarboxylic acid cycle. HKDC1 was prometastatic in HCC orthotopic and tail vein injection mouse models. Molecularly, HKDC1 was induced by hypoxia and bound to glycogen synthase kinase 3β to stabilize β-catenin, leading to enhanced stemness of HCC cells.

CONCLUSIONS

Overall, our findings underscore HKDC1 as a prometastatic HK specifically expressed in the malignant compartment of primary liver tumors, thereby providing a mechanistic basis for targeting this enzyme in advanced liver cancer.

Primary liver cancer organoids and their application to research and therapy

Primary liver cancer is a leading cause of death worldwide. To create advanced treatments for primary liver cancer, studies have utilized models such as 2D cell culture and in vivo animal models. Recent developments in cancer organoids have created the possibility for 3D in vitro cultures that recapitulates the cancer cell structure and operation as well as the tumor microenvironment (TME). However, before organoids can be directly translated to clinical use, tissue processing and culture medium must be standardized with unified protocols to decrease variability in results. Herein, we present the wide variety of published methodologies used to derive liver cancer organoids from patient tumor tissues. Additionally, we summarize validation methodologies for organoids in terms of marker expression levels with immunohistochemistry as well as the presence of mutations and variants through RNA-sequencing. Primary liver cancer organoids have exciting applications allowing for faster drug testing at a larger scale. Primary liver cancer organoids also assisit in uncovering new mechanisms. Through the coculture of different immune cells and cancer organoids, organoids are now better able to recapitulate the liver cancer TME. In addition, it further aids in the investigation of drug development and drug resistance. Lastly, we posit that the usage of liver cancer organoids in animal models provides researchers a methodology to overcome the current limitations of culture systems.

Single-cell transcriptomics reveals tumor microenvironment remodeling in hepatocellular carcinoma with varying tumor subclonal complexity

Introduction

The complexity of tumor cell subclonal structure has been extensively investigated in hepatocellular carcinoma. However, the role of subclonal complexity in reshaping the tumor microenvironment (TME) remains poorly understood.

Methods

We integrated single-cell transcriptome sequencing data from four independent HCC cohorts, involving 30 samples, to decode the associations between tumor subclonal complexity and the TME. We proposed a robust metric to accurately quantify the degree of subclonal complexity for each sample based on discrete copy number variations (CNVs) profiles.

Results

We found that tumor cells in the high-complexity group originated from the cell lineage with FGB overexpression and exhibited high levels of transcription factors associated with poor survival. In contrast, tumor cells in low-complexity patients showed activation of more hallmark signaling pathways, more active cell-cell communications within the TME and a higher immune activation status. Additionally, cytokines signaling activity analysis suggested a link between HMGB1 expressed by a specific endothelial subtype and T cell proliferation.

Discussion

Our study sheds light on the intricate relationship between the complexity of subclonal structure and the TME, offering novel insights into potential therapeutic targets for HCC.

Innovative aspects and applications of single cell technology for different diseases

Recent developments in single-cell technologies have provided valuable insights from cancer genomics to complex microbial communities. Single-cell technologies including the RNA-seq, next-generation sequencing (NGS), epigenomics, genomics, and transcriptomics can be used to uncover the single cell nature and molecular characterization of individual cells. These technologies also reveal the cellular transition states, evolutionary relationships between genes, the complex structure of single-cell populations, cell-to-cell interaction leading to biological discoveries and more reliable than traditional bulk technologies. These technologies are becoming the first choice for the early detection of inflammatory biomarkers affecting the proliferation and progression of tumor cells in the tumor microenvironment and improving the clinical efficacy of patients undergoing immunotherapy. These technologies also hold a central position in the detection of checkpoint inhibitors and thus determining the signaling pathways evoked by tumor invasion. This review addressed the emerging approaches of single cell-based technologies in cancer immunotherapies and different human diseases at cellular and molecular levels and the emerging role of sequencing technologies leading to drug discovery. Advancements in these technologies paved for discovering novel diagnostic markers for better understanding the pathological and biochemical mechanisms also for controlling the rate of different diseases.

CD74 facilitates immunotherapy response by shaping the tumor microenvironment of hepatocellular carcinoma

BACKGROUND

CD74 is ectopically expressed in many tumors and can regulate tumor immunity. However, there are many gaps in the study of the prognostic value of CD74 expression and immune infiltration in hepatocellular carcinoma (HCC).

METHODS

An online tumor database was searched to obtain data on gene/protein expression. Immune infiltration analysis was performed using the Tumor Immune Estimation Resource and Comprehensive Analysis on Multi-Omics of Immunotherapy in Pan-cancer databases. Single-cell data were obtained from the Tissue-specific Gene Expression and Regulation, Single-cell Transcriptomes of Tumor Immune Microenvironment and Tumor Immune Single-cell Hub 2 databases.

RESULTS

CD74 was highly expressed in HCC patients. HCC patients with high CD74 expression who consumed alcohol or were negative for hepatitis virus had a better prognosis than patients with low CD74 expression. CD74 was mainly enriched in immune response regulation pathways. Both copy number variations in CD74 and CD74 expression patterns affected the infiltration levels of immune cells. Interestingly, CD74 regulated the differentiation of myeloid cells. CD74 in macrophages and dendritic cells (DCs) forms complex networks with malignant cells and hepatic progenitor cell (HPC)-like cells, respectively. High CD74 expression in HPC-like cells and malignant cells significantly decreased the fraction of C-type lectin domain family 9 A (CLEC9A)-cDC1+ DCs and IL-1B+ macrophages, respectively. Their crosstalk subsequently shaped the tumor microenvironment of HCC, possibly through the CD74-MIF axis. Importantly, patients with high CD74 expression presented higher immune scores and achieved good outcomes after receiving immunotherapy.

CONCLUSION

High CD74 expression is associated with the abundance of a variety of immune cell types, mediating interactions among tumor and immune cells and shaping the malignant behavior of HCC. In summary, CD74 may be a hallmark for determining the prognosis and immune cell infiltration levels of HCC patients.

POSTN+ cancer-associated fibroblasts determine the efficacy of immunotherapy in hepatocellular carcinoma

OBJECTIVE

Hepatocellular carcinoma (HCC) poses a significant clinical challenge because the long-term benefits of immune checkpoint blockade therapy are limited. A comprehensive understanding of the mechanisms underlying immunotherapy resistance in HCC is imperative for improving patient prognosis.

DESIGN

In this study, to systematically investigate the characteristics of cancer-associated fibroblast (CAF) subsets and the dynamic communication among the tumor microenvironment (TME) components regulated by CAF subsets, we generated an HCC atlas by compiling single-cell RNA sequencing (scRNA-seq) datasets on 220 samples from six datasets. We combined spatial transcriptomics with scRNA-seq and multiplexed immunofluorescence to identify the specific CAF subsets in the TME that determine the efficacy of immunotherapy in HCC patients.

RESULTS

Our findings highlight the pivotal role of POSTN+ CAFs as potent immune response barriers at specific tumor locations, as they hinder effective T-cell infiltration and decrease the efficacy of immunotherapy. Additionally, we elucidated the interplay between POSTN+ CAFs and SPP1+ macrophages, whereby the former recruits the latter and triggers increased SPP1 expression via the IL-6/STAT3 signaling pathway. Moreover, we demonstrated a spatial correlation between POSTN+ CAFs and SPP1+ macrophages, revealing an immunosuppressive microenvironment that limits the immunotherapy response. Notably, we found that patients with elevated expression levels of both POSTN+ CAFs and SPP1+ macrophages achieved less therapeutic benefit in an immunotherapy cohort.

CONCLUSION

Our research elucidates light on the role of a particular subset of CAFs in immunotherapy resistance, emphasizing the potential benefits of targeting specific CAF subpopulations to improve clinical responses to immunotherapy.

A single-cell pan-cancer analysis to show the variability of tumor-infiltrating myeloid cells in immune checkpoint blockade

Myeloid cells are vital components of the immune system and have pivotal functions in orchestrating immune responses. Understanding their functions within the tumor microenvironment and their interactions with tumor-infiltrating lymphocytes presents formidable challenges across diverse cancer types, particularly with regards to cancer immunotherapies. Here, we explore tumor-infiltrating myeloid cells (TIMs) by conducting a pan-cancer analysis using single-cell transcriptomics across eight distinct cancer types, encompassing a total of 192 tumor samples from 129 patients. By examining gene expression patterns and transcriptional activities of TIMs in different cancer types, we discern notable alterations in abundance of TIMs and kinetic behaviors prior to and following immunotherapy. We also identify specific cell-cell interaction targets in immunotherapy; unique and shared regulatory profiles critical for treatment response; and TIMs associated with survival outcomes. Overall, our study illuminates the heterogeneity of TIMs and improves our understanding of tissue-specific and cancer-specific myeloid subsets within the context of tumor immunotherapies.

The tumor immune microenvironment remodeling and response to HER2-targeted therapy in HER2-positive advanced gastric cancer

Combination therapy with anti-HER2 agents and immunotherapy has demonstrated significant clinical benefits in gastric cancer (GC), but the underlying mechanism remains unclear. In this study, we used multiplex immunohistochemistry to assess the changes of the tumor microenvironment in 47 advanced GC patients receiving anti-HER2 therapy. Additionally, we performed single-cell transcriptional sequencing to investigate potential cell-to-cell communication and molecular mechanisms in four HER2-positive GC baseline samples. We observed that post-treated the infiltration of NK cells, CD8+ T cells, and B lymphocytes were significantly higher in patients who benefited from anti-HER2 treatment than baseline. Further spatial distribution analysis demonstrated that the interaction scores between NK cells and CD8+ T cells, B lymphocytes and M2 macrophages, B lymphocytes and Tregs were also significantly higher in benefited patients. Cell-cell communication analysis from scRNA sequencing showed that NK cells utilized CCL3/CCL4-CCR5 to recruit CD8+ T cell infiltration. B lymphocytes employed CD74-APP/COPA/MIF to interact with M2 macrophages, and utilized TNF-FAS/ICOS/TNFRSR1B to interact with Tregs. These cell-cell interactions contribute to inhibit the immune resistance of M2 macrophages and Tregs. Our research provides potential guidance for the use of anti-HER2 therapy in combination with immune therapy.

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.

Immune landscape of hepatocellular carcinoma: From dysregulation of the immune responses to the potential immunotherapies

Hepatocellular carcinoma (HCC) presents a considerable global health burden due to its late diagnosis and high morbidity. The liver's specific anatomical and physiological features expose it to various antigens, requiring precise immune regulation. To the best of our knowledge, this is the first time that a comprehensive overview of the interactions between the immune system and gut microbiota in the development of HCC, as well as the relevant therapeutic approaches are discussed. Dysregulation of immune compartments within the liver microenvironment drives HCC pathogenesis, characterized by elevated regulatory cells such as regulatory T cells (Tregs), myeloid-derived suppressor cells, and M2 macrophages as well as suppressive molecules, alongside reduced number of effector cells like T cells, natural killer cells, and M1 macrophages. Dysbiosis of gut microbiota also contributes to HCC by disrupting intestinal barrier integrity and triggering overactivated immune responses. Immunotherapy approaches, particularly immune checkpoint inhibitors, have exhibited promise in HCC management, yet adoptive cell therapy and cancer vaccination research are in the early steps with relatively less favorable outcomes. Further understanding of immune dysregulation, gut microbiota involvement, and therapeutic combination strategies are essential for advancing precision immunotherapy in HCC.

Collagen in hepatocellular carcinoma: A novel biomarker and therapeutic target

HCC is globally recognized as a major health threat. Despite significant progress in the development of treatment strategies for liver cancer, recurrence, metastasis, and drug resistance remain key factors leading to a poor prognosis for the majority of liver cancer patients. Thus, there is an urgent need to develop effective biomarkers and therapeutic targets for HCC. Collagen, the most abundant and diverse protein in the tumor microenvironment, is highly expressed in various solid tumors and plays a crucial role in the initiation and progression of tumors. Recent studies have shown that abnormal expression of collagen in the tumor microenvironment is closely related to the occurrence, development, invasion, metastasis, drug resistance, and treatment of liver cancer, making it a potential therapeutic target and a possible diagnostic and prognostic biomarker for HCC. This article provides a comprehensive review of the structure, classification, and origin of collagen, as well as its role in the progression and treatment of HCC and its potential clinical value, offering new insights into the diagnosis, treatment, and prognosis assessment of liver cancer.

Liver cancer from the perspective of single-cell sequencing: a review combined with bibliometric analysis

BACKGROUND

Liver cancer (LC) is a prevalent malignancy and a leading cause of cancer-related mortality worldwide. Extensive research has been conducted to enhance patient outcomes and develop effective prevention strategies, ranging from molecular mechanisms to clinical interventions. Single-cell sequencing, as a novel bioanalysis technology, has significantly contributed to the understanding of the global cognition and dynamic changes in liver cancer. However, there is a lack of bibliometric analysis in this specific research area. Therefore, the objective of this study is to provide a comprehensive overview of the knowledge structure and research hotspots in the field of single-cell sequencing in liver cancer research through the use of bibliometrics.

METHOD

Publications related to the application of single-cell sequencing technology to liver cancer research as of December 31, 2023, were searched on the web of science core collection (WoSCC) database. VOSviewers, CiteSpace, and R package "bibliometrix" were used to conduct this bibliometric analysis.

RESULTS

A total of 331 publications from 34 countries, primarily led by China and the United States, were included in this study. The research focuses on the application of single cell sequencing technology to liver cancer, and the number of related publications has been increasing year by year. The main research institutions involved in this field are Fudan University, Sun Yat-Sen University, and the Chinese Academy of Sciences. Frontiers in Immunology and Nature Communications is the most popular journal in this field, while Cell is the most frequently co-cited journal. These publications are authored by 2799 individuals, with Fan Jia and Zhou Jian having the most published papers, and Llovet Jm being the most frequently co-cited author. The use of single cell sequencing to explore the immune microenvironment of liver cancer, as well as its implications in immunotherapy and chemotherapy, remains the central focus of this field. The emerging research hotspots are characterized by keywords such as 'Gene-Expression', 'Prognosis', 'Tumor Heterogeneity', 'Immunoregulation', and 'Tumor Immune Microenvironment'.

CONCLUSION

This is the first bibliometric study that comprehensively summarizes the research trends and developments on the application of single cell sequencing in liver cancer. The study identifies recent research frontiers and hot directions, providing a valuable reference for researchers exploring the landscape of liver cancer, understanding the composition of the immune microenvironment, and utilizing single-cell sequencing technology to guide and enhance the prognosis of liver cancer patients.

Precise recognition of benzonitrile derivatives with supramolecular macrocycle of phosphorylated cavitand by co-crystallization method

The importance of molecular docking in drug discovery lies in the precise recognition between potential drug compounds and their target receptors, which is generally based on the computational method. However, it will become quite interesting if the rigid cavity structure of supramolecular macrocycles can precisely recognize a series of guests with specific fragments by mimicking molecular docking through co-crystallization experiments. Herein, we report a phenylphosphine oxide-bridged aromatic supramolecular macrocycle, F[3]A1-[P(O)Ph]3, which precisely recognizes benzonitrile derivatives through non-covalent interactions to form key-lock complexes by co-crystallization method. A total of 15 various benzonitrile derivatives as guest molecules are specifically bound by F[3]A1-[P(O)Ph]3 in co-crystal structures, respectively. Notably, among them, crisaborole (anti-dermatitis) and alectinib (anti-cancer) with the benzonitrile fragment, which are two commercial drug molecules approved by the U.S. Food and Drug Administration (FDA), could also form a key-lock complex with F[3]A1-[P(O)Ph]3 in the crystal state, respectively.

S100A16 is a potential target for reshaping the tumor microenvironment in the hypoxic context of liver cancer

BACKGROUND

The research on the S100 family has garnered significant attention; however, there remains a dearth of understanding regarding the precise role of S100A16 in the tumor microenvironment of liver cancer.

METHOD

Comprehensive analysis was conducted on the expression of S100A16 in tumor tissues and its correlation with hypoxia genes. Furthermore, an investigation was carried out to examine the association between S100A16 and infiltration of immune cells in tumors as well as immunotherapy. Relevant findings were derived from the analysis of single cell sequencing data, focusing on the involvement of S100A16 in both cellular differentiation and intercellular communication. Finally, we validated the expression of S100A16 in liver cancer by Wuhan cohort and multiplexed immunofluorescence to investigate the correlation between S100A16 and hypoxia.

RESULT

Tumor tissues displayed a notable increase in the expression of S100A16. A significant correlation was observed between S100A16 and genes associated with hypoxic genes. Examination of immune cell infiltration revealed an inverse association between T cell infiltration and the level of S100A16 expression. The high expression group of S100A16 exhibited a decrease in the expression of genes related to immune cell function. Single-cell sequencing data analysis revealed that non-immune cells predominantly expressed S100A16, and its expression levels increased along with the trajectory of cell differentiation. Additionally, there were significant variations observed in hypoxia genes as cells underwent differentiation. Cellular communication identified non-immune cells interacting with immune cells through multiple signaling pathways. The Wuhan cohort verified that S100A16 expression was increased in liver cancer. The expression of S100A16 and HIF was simultaneously elevated in endothelial cells.

CONCLUSION

The strong association between S100A16 and immune cell infiltration is observed in the context of hypoxia, indicating its regulatory role in shaping the hypoxic tumor microenvironment in liver cancer.

Macrophage and fibroblast trajectory inference and crosstalk analysis during myocardial infarction using integrated single-cell transcriptomic datasets

BACKGROUND

Cardiac fibrosis after myocardial infarction (MI) has been considered an important part of cardiac pathological remodeling. Immune cells, especially macrophages, are thought to be involved in the process of fibrosis and constitute a niche with fibroblasts to promote fibrosis. However, the diversity and variability of fibroblasts and macrophages make it difficult to accurately depict interconnections.

METHODS

We collected and reanalyzed scRNA-seq and snRNA-seq datasets from 12 different studies. Differentiation trajectories of these subpopulations after MI injury were analyzed by using scVelo, PAGA and Slingshot. We used CellphoneDB and NicheNet to infer fibroblast-macrophage interactions. Tissue immunofluorescence staining and in vitro experiments were used to validate our findings.

RESULTS

We discovered two subsets of ECM-producing fibroblasts, reparative cardiac fibroblasts (RCFs) and matrifibrocytes, which appeared at different times after MI and exhibited different transcriptional profiles. We also observed that CTHRC1+ fibroblasts represent an activated fibroblast in chronic disease states. We identified a macrophage subset expressing the genes signature of SAMs conserved in both human and mouse hearts. Meanwhile, the SPP1hi macrophages were predominantly found in the early stages after MI, and cell communication analysis indicated that SPP1hi macrophage-RCFs interactions are mainly involved in collagen deposition and scar formation.

CONCLUSIONS

Overall, this study comprehensively analyzed the dynamics of fibroblast and macrophage subsets after MI and identified specific subsets of fibroblasts and macrophages involved in scar formation and collagen deposition.

Integrated Analysis of scRNA-Seq and Bulk RNA-Seq Reveals Metabolic Reprogramming of Liver Cancer and Establishes a Prognostic Risk Model

Liver cancer manifests as a profoundly heterogeneous malignancy, posing significant challenges in terms of both therapeutic intervention and prognostic evaluation. Given that the liver is the largest metabolic organ, a prognostic risk model grounded in single-cell transcriptome analysis and a metabolic perspective can facilitate precise prevention and treatment strategies for liver cancer. Hence, we identified 11 cell types in a scRNA-seq profile comprising 105,829 cells and found that the metabolic activity of malignant cells increased significantly. Subsequently, a prognostic risk model incorporating tumor heterogeneity, cell interactions, tumor cell metabolism, and differentially expressed genes was established based on eight genes; this model can accurately distinguish the survival outcomes of liver cancer patients and predict the response to immunotherapy. Analyzing the immune status and drug sensitivity of the high- and low-risk groups identified by the model revealed that the high-risk group had more active immune cell status and greater expression of immune checkpoints, indicating potential risks associated with liver cancer-targeted drugs. In summary, this study provides direct evidence for the stratification and precise treatment of liver cancer patients, and is an important step in establishing reliable predictors of treatment efficacy in liver cancer patients.

Expression and clinical significance of interleukin-6 pathway in cholangiocarcinoma

Background

Cholangiocarcinoma (CCA) is a typical inflammation-induced malignancy, and elevated serum interleukin-6 (IL-6) levels have been reported to be linked to the onset and progression of CCA. We aim to investigate the potential prognostic value of the IL-6 pathway for CCA.

Methods

We detected the expressions of IL-6, IL-6R, glycoprotein (gp130), C-reactive protein (CRP), Janus kinase 2 (JAK2), and signal transducer and activator of transcription 3 (STAT3) in CCA tissue microarray using multiplex immunofluorescence. Furthermore, the clinical associations and prognostic values were assessed. Finally, single-cell transcriptome analysis was performed to evaluate the expression level of IL-6 pathway genes in CCA.

Results

The results revealed that the expression of IL-6 was lower, while the expression of STAT3 was higher in tumor tissues compared to normal tissues. Especially in tumor microenvironment, the expression of IL-6 pathway genes was generally downregulated. Importantly, gp130 was strongly correlated with JAK2 in tumor tissues, while it was moderately correlated with JAK2 in normal tissue. Although none of the gene expressions were directly associated with overall survival and disease-free survival, our study found that IL-6, IL-6R, CRP, gp130, and JAK2 were inversely correlated with vascular invasion, which is a risk factor for poor prognosis in patients with CCA.

Conclusion

The findings from this study suggest that the IL-6 signaling pathway may have a potential prognostic value for CCA. Further investigation is needed to understand the underlying molecular mechanisms of the IL-6 pathway in CCA.

Single-Cell RNA Sequencing Identifies Crucial Genes Influencing the Polarization of Tumor-Associated Macrophages in Liver Cancer

Background

In the context of hepatocellular carcinoma (HCC), tumor-associated macrophages (TAMs) are pivotal for the immunosuppressive nature of the tumor microenvironment (TME). This investigation delves into the functional transformations of TAMs within the TME by leveraging single-cell transcriptomics to pinpoint critical genes influencing TAM subset polarization.

Methods

We procured single-cell and bulk transcriptomic data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), implementing quality assurance, dimensional reduction, clustering, and annotation on the single-cell sequencing data. To examine cellular interactions, CellChat was utilized, while single-cell regulatory network inference and clustering (SCENIC) was applied to deduce transcription factors (TFs) and their associated targets. Through gene enrichment, survival, and immune infiltration correlation analyses, we sought to pinpoint and validate influential genes. A TAM model under HCC conditions was then established to confirm the expression levels of these key genes.

Results

Our analysis encompassed 74,742 cells and 23,110 genes. Through postdimensional reduction and clustering, we identified seven distinct cell types and nine TAM subtypes. Analysis via CellChat highlighted a predominance of M2-phenotype-inclined TAM subsets within the tumor's core. SCENIC pinpointed the transcription factor PRDM1 and its target genes as pivotal in this region. Further analysis indicated these genes' involvement in macrophage polarization. Employing trajectory analysis, survival analysis, and immune infiltration correlation, we scrutinized and validated genes likely directing M2 polarization. Experimental validation confirmed PRDM1's heightened expression in TAMs conditioned by HCC.

Conclusions

Our findings suggest the PRDM1 gene is a key regulator of M2 macrophage polarization, contributing to the immunosuppressive TME in HCC.

Integration of Single-Cell RNA Sequencing and Bulk RNA Sequencing to Identify an Immunogenic Cell Death-Related 5-Gene Prognostic Signature in Hepatocellular Carcinoma

Introduction

Immunogenic cell death (ICD) can enhance the potency of immunotherapy in cancer treatment. Nevertheless, it is ambiguous how ICD-related genes (ICDRGs) contribute to hepatocellular carcinoma (HCC).

Methods

Single-cell RNA sequencing (scRNA-seq) data were used to distinguish malignant cells from normal cells in the HCC tumor microenvironment(TME). Bulk RNA sequencing data was employed to acquire the landscape of the 33 ICDRGs. Unsupervised clustering identified two ICD molecular subtypes. The cellular infiltration characteristics and biological behavior in different subtypes were analyzed by ssGSEA. Subsequently, differentially expressed genes (DEGs) between the two subtypes were determined, based on which patients were classified into three gene clusters. Then, the prognostic model was constructed by Lasso-Cox analysis. Finally, we investigated the expression of risk genes in cancer cell line encyclopedia (CCLE) and validated the function of NKX3-2 in vitro experiments.

Results

ICD scores and ICDRGs expression in malignant cells were significantly lower than in normal cells by scRNA-seq analysis. ICD-high subtype was characterized by ICD-related gene overexpression and high levels of immune infiltration abundance and immune checkpoints; Three DEGs-related gene clusters were likewise strongly linked to stromal and immunological activation. In the ICD-related prognostic model consisting of NKX3-2, CHODL, MMP1, NR0B1, and CTSV, the low-risk group patients had a better endpoint and displayed increased susceptibility to immunotherapy and chemotherapeutic drugs like 5-Fluorouracil, afatinib, bortezomib, cediratinib, lapatinib, dasatinib, gefitinib and crizotinib. Moreover, NKX3-2 amplification in HCC samples has been verified by experiments, and its disruption suppressed the proliferation and invasion of tumor cells.

Conclusion

Our study highlighted the potential of the ICDRGs risk score as a prognostic indicator to aid in the accurate diagnosis and immunotherapy sensitivity of HCC.

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.

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine - cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.

A prognostic and immune related risk model based on zinc homeostasis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. The dysfunction of zinc homeostasis participates in the early and advancing malignancy of HCC. However, the prognostic ability of zinc homeostasis in HCC has not been clarified yet. Here, we showed a zinc-homeostasis related risk model in HCC. Five signature genes including ADAMTS5, PLOD2, PTDSS2, KLRB1, and UCK2 were screened out via survival analyses and regression algorithms to construct the nomogram with clinical characteristics. Experimental researches indicated that UCK2 participated in the progression of HCC. Patients with higher risk scores always had worse outcomes and were more associated with immune suppression according to the analyses of immune related-pathway activation, cell infiltration, and gene expression. Moreover, these patients were likely to exhibit more sensitivity to sorafenib and other antitumor drugs. This study highlights the significant prognostic role of zinc homeostasis and suggests potential treatment strategies in HCC.

Alcohol-associated liver cancer

Heavy alcohol intake induces a wide spectrum of liver diseases ranging from steatosis, steatohepatitis, cirrhosis, and HCC. Although alcohol consumption is a well-known risk factor for the development, morbidity, and mortality of HCC globally, alcohol-associated hepatocellular carcinoma (A-HCC) is poorly characterized compared to viral hepatitis-associated HCC. Most A-HCCs develop after alcohol-associated cirrhosis (AC), but the direct carcinogenesis from ethanol and its metabolites to A-HCC remains obscure. The differences between A-HCC and HCCs caused by other etiologies have not been well investigated in terms of clinical prognosis, genetic or epigenetic landscape, molecular mechanisms, and heterogeneity. Moreover, there is a huge gap between basic research and clinical practice due to the lack of preclinical models of A-HCC. In the current review, we discuss the pathogenesis, heterogeneity, preclinical approaches, epigenetic, and genetic profiles of A-HCC, and discuss the current insights into and the prospects for future research on A-HCC. The potential effect of alcohol on cholangiocarcinoma and liver metastasis is also discussed.

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.

Revealing the role of necroptosis microenvironment: FCGBP + tumor-associated macrophages drive primary liver cancer differentiation towards cHCC-CCA or iCCA

Previous research has demonstrated that the conversion of hepatocellular carcinoma (HCC) to intrahepatic cholangiocarcinoma (iCCA) can be stimulated by manipulating the tumor microenvironment linked with necroptosis. However, the specific cells regulating the necroptosis microenvironment have not yet been identified. Additionally, further inquiry into the mechanism of how the tumor microenvironment regulates necroptosis and its impact on primary liver cancer(PLC) progression may be beneficial for precision therapy. We recruited a single-cell RNA sequencing dataset (scRNA-seq) with 34 samples from 4 HCC patients and 3 iCCA patients, and a Spatial Transcriptomic (ST) dataset including one each of HCC, iCCA, and combined hepatocellular-cholangiocarcinoma (cHCC-CCA). Quality control, dimensionality reduction and clustering were based on Seurat software (v4.2.2) process and batch effects were removed by harmony (v0.1.1) software. The pseudotime analysis (also known as cell trajectory) in the single cell dataset was performed by monocle2 software (v2.24.0). Calculation of necroptosis fraction was performed by AUCell (v1.16.0) software. Switch gene analysis was performed by geneSwitches(v0.1.0) software. Dimensionality reduction, clustering, and spatial image in ST dataset were performed by Seurat (v4.0.2). Tumor cell identification, tumor subtype characterization, and cell type deconvolution in spot were performed by SpaCET (v1.0.0) software. Immunofluorescence and immunohistochemistry experiments were used to prove our conclusions. Analysis of intercellular communication was performed using CellChat software (v1.4.0). ScRNA-seq analysis of HCC and iCCA revealed that necroptosis predominantly occurred in the myeloid cell subset, particularly in FCGBP + SPP1 + tumor-associated macrophages (TAMs), which had the highest likelihood of undergoing necroptosis. The existence of macrophages undergoing necroptosis cell death was further confirmed by immunofluorescence. Regions of HCC with poor differentiation, cHCC-CCA with more cholangiocarcinoma features, and the tumor region of iCCA shared spatial colocalization with FCGBP + macrophages, as confirmed by spatial transcriptomics, immunohistochemistry and immunofluorescence. Pseudotime analysis showed that premalignant cells could progress into two directions, one towards HCC and the other towards iCCA and cHCC-CCA. Immunofluorescence and immunohistochemistry experiments demonstrated that the number of macrophages undergoing necroptosis in cHCC-CCA was higher than in iCCA and HCC, the number of macrophages undergoing necroptosis in cHCC-CCA with cholangiocarcinoma features was more than in cHCC-CCA with hepatocellular carcinoma features. Further investigation showed that myeloid cells with the highest necroptosis score were derived from the HCC_4 case, which had a severe inflammatory background on pathological histology and was likely to progress towards iCCA and cHCC-CCA. Switchgene analysis indicated that S100A6 may play a significant role in the progression of premalignant cells towards iCCA and cHCC-CCA. Immunohistochemistry confirmed the expression of S100A6 in PLC, the more severe inflammatory background of the tumor area, the more cholangiocellular carcinoma features of the tumor area, S100A6 expression was higher. The emergence of necroptosis microenvironment was found to be significantly associated with FCGBP + SPP1 + TAMs in PLC. In the presence of necroptosis microenvironment, premalignant cells appeared to transform into iCCA or cHCC-CCA. In contrast, without a necroptosis microenvironment, premalignant cells tended to develop into HCC, exhibiting amplified stemness-related genes (SRGs) and heightened malignancy.

Characterization of tumor evolution by functional clonality and phylogenetics in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a molecularly heterogeneous solid malignancy, and its fitness may be shaped by how its tumor cells evolve. However, ability to monitor tumor cell evolution is hampered by the presence of numerous passenger mutations that do not provide any biological consequences. Here we develop a strategy to determine the tumor clonality of three independent HCC cohorts of 524 patients with diverse etiologies and race/ethnicity by utilizing somatic mutations in cancer driver genes. We identify two main types of tumor evolution, i.e., linear, and non-linear models where non-linear type could be further divided into classes, which we call shallow branching and deep branching. We find that linear evolving HCC is less aggressive than other types. GTF2IRD2B mutations are enriched in HCC with linear evolution, while TP53 mutations are the most frequent genetic alterations in HCC with non-linear models. Furthermore, we observe significant B cell enrichment in linear trees compared to non-linear trees suggesting the need for further research to uncover potential variations in immune cell types within genomically determined phylogeny types. These results hint at the possibility that tumor cells and their microenvironment may collectively influence the tumor evolution process.

Tumor Microenvironment Activatable Nanoprodrug System for In Situ Fluorescence Imaging and Therapy of Liver Cancer

The development of new imaging and treatment nanoprodrug systems is highly demanded for diagnosis and therapy of liver cancer, a severe disease characterized by a high recurrence rate. Currently, available small molecule drugs are not possible for cancer diagnosis because of the fast diffusion of imaging agents and low efficacy in treatment due to poor water solubility and significant toxic side effects. In this study, we report the development of a tumor microenvironment activatable nanoprodrug system for the diagnosis and treatment of liver cancer. This nanoprodrug system can accumulate in the tumor site and be selectively activated by an excess of hydrogen peroxide (H2O2) in the tumor microenvironment, releasing near-infrared solid-state organic fluorescent probe (HPQCY-1) and phenylboronic acid-modified camptothecin (CPT) prodrug. Both HPQCY-1 and CPT prodrugs can be further activated in tumor sites for achieving more precise in situ near-infrared (NIR) fluorescence imaging and treatment while reducing the toxic effects of drugs on normal tissues. Additionally, the incorporation of hydrophilic multivalent chitosan as a carrier effectively improved the water solubility of the system. This research thus provides a practical new approach for the diagnosis and treatment of liver cancer.

Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication

BACKGROUND

Liver cancer is one of the deadliest malignant tumors worldwide. Immunotherapy has provided hope to patients with advanced liver cancer, but only a small fraction of patients benefit from this treatment due to individual differences. Identifying immune-related gene signatures in liver cancer patients not only aids physicians in cancer diagnosis but also offers personalized treatment strategies, thereby improving patient survival rates. Although several methods have been developed to predict the prognosis and immunotherapeutic efficacy in patients with liver cancer, the impact of cell-cell interactions in the tumor microenvironment has not been adequately considered.

AIM

To identify immune-related gene signals for predicting liver cancer prognosis and immunotherapy efficacy.

METHODS

Cell grouping and cell-cell communication analysis were performed on single-cell RNA-sequencing data to identify highly active cell groups in immune-related pathways. Highly active immune cells were identified by intersecting the highly active cell groups with B cells and T cells. The significantly differentially expressed genes between highly active immune cells and other cells were subsequently selected as features, and a least absolute shrinkage and selection operator (LASSO) regression model was constructed to screen for diagnostic-related features. Fourteen genes that were selected more than 5 times in 10 LASSO regression experiments were included in a multivariable Cox regression model. Finally, 3 genes (stathmin 1, cofilin 1, and C-C chemokine ligand 5) significantly associated with survival were identified and used to construct an immune-related gene signature.

RESULTS

The immune-related gene signature composed of stathmin 1, cofilin 1, and C-C chemokine ligand 5 was identified through cell-cell communication. The effectiveness of the identified gene signature was validated based on experimental results of predictive immunotherapy response, tumor mutation burden analysis, immune cell infiltration analysis, survival analysis, and expression analysis.

CONCLUSION

The findings suggest that the identified gene signature may contribute to a deeper understanding of the activity patterns of immune cells in the liver tumor microenvironment, providing insights for personalized treatment strategies.

Lineage and ecology define liver tumor evolution in response to treatment

A tumor ecosystem constantly evolves over time in the face of immune predation or therapeutic intervention, resulting in treatment failure and tumor progression. Here, we present a single-cell transcriptome-based strategy to determine the evolution of longitudinal tumor biopsies from liver cancer patients by measuring cellular lineage and ecology. We construct a lineage and ecological score as joint dynamics of tumor cells and their microenvironments. Tumors may be classified into four main states in the lineage-ecological space, which are associated with clinical outcomes. Analysis of longitudinal samples reveals the evolutionary trajectory of tumors in response to treatment. We validate the lineage-ecology-based scoring system in predicting clinical outcomes using bulk transcriptomic data of additional cohorts of 716 liver cancer patients. Our study provides a framework for monitoring tumor evolution in response to therapeutic intervention.

Translational research on drug development and biomarker discovery for hepatocellular carcinoma

Translational research plays a key role in drug development and biomarker discovery for hepatocellular carcinoma (HCC). However, unique challenges exist in this field because of the limited availability of human tumor samples from surgery, the lack of homogenous oncogenic driver mutations, and the paucity of adequate experimental models. In this review, we provide insights into these challenges and review recent advancements, with a particular focus on the two main agents currently used as mainstream therapies for HCC: anti-angiogenic agents and immunotherapy. First, we examine the pre-clinical and clinical studies to highlight the challenges of determining the optimal therapeutic combinations with biologically effective dosage for HCC. Second, we discuss biomarker studies focusing on anti-PD1/anti-PD-L1-based combination therapy. Finally, we discuss the progress made in our collective understanding of tumor immunology and in multi-omics analysis technology, which enhance our understanding of the mechanisms underlying immunotherapy, characterize different patient subgroups, and facilitate the development of novel combination approaches to improve treatment efficacy. In summary, this review provides a comprehensive overview of efforts in translational research aiming at advancing our understanding of and improving the treatment of HCC.

T-cell infiltration and its regulatory mechanisms in cancers: insights at single-cell resolution

Tumor-infiltrating T cells recognize, attack, and clear tumor cells, playing a central role in antitumor immune response. However, certain immune cells can impair this response and help tumor immune escape. Therefore, exploring the factors that influence T-cell infiltration is crucial to understand tumor immunity and improve therapeutic effect of cancer immunotherapy. The use of single-cell RNA sequencing (scRNA-seq) allows the high-resolution analysis of the precise composition of immune cells with different phenotypes and other microenvironmental factors, including non-immune stromal cells and the related molecules in the tumor microenvironment of various cancer types. In this review, we summarized the research progress on T-cell infiltration and the crosstalk of other stromal cells and cytokines during T-cell infiltration using scRNA-seq to provide insights into the mechanisms regulating T-cell infiltration and contribute new perspectives on tumor immunotherapy.

Development and Validation of a Novel Nomogram Integrated with Hypoxic and Lactate Metabolic Characteristics for Prognosis Prediction in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Accumulating evidence indicates that hypoxia and lactate metabolism play critical roles in tumor progression and therapeutic efficacy. This study aimed to construct a hypoxia- and lactate metabolism-related prognostic model (HLPM) to evaluate survival and treatment responses for HCC patients and develop a nomogram integrated with HLPM and clinical characteristics for prognosis prediction in HCC.

Methods

Expression profile and clinical data of HCC were obtained from TCGA and ICGC databases. The univariate, LASSO and stepwise multivariate Cox analyses were used to identify the hypoxia- and lactate metabolism-related biomarkers, whose expression levels were then validated in 14 pairs tissue samples and single-cell RNA sequencing dataset. Kaplan-Meier survival curves were utilized to assess the prognostic values of biomarkers or models. Analyses of ImmuCellAI, TIDE and drug sensitivity were conducted to evaluate the therapeutic responses of patients. Furthermore, the nomogram integrated with hypoxic and lactate metabolic characteristics was established through univariate and multivariate Cox analyses. ROC curves, C-index, and calibration curves were depicted to evaluate the performance of the nomogram.

Results

Five hypoxia- and lactate metabolism-related biomarkers (KIF20A, IRAK1, ADM, PPARGC1A and EPO) were used to construct HLPM. The expression of five prognostic biomarkers was validated in 14 pairs tissue samples and single-cell RNA sequencing dataset. Analyses of ImmuCellAI, TIDE and drug sensitivity implied that patients with low-risk score were more sensitive to immunotherapy and major chemotherapeutic agents. The nomogram that contained age, histological grade and risk score of HLPM was developed and exhibited a better capacity in prognosis prediction than HLPM only.

Conclusion

A novel nomogram integrated with hypoxic and lactate metabolic characteristics was developed and validated for prognosis prediction in HCC, providing insight into personalized decision-making in clinical management.

Deciphering the immune modulation through deep transcriptomic profiling and therapeutic implications of DNA damage repair pattern in hepatocellular carcinoma

AIMS

DNA damage repair (DDR) plays a pivotal role in hepatocellular carcinoma (HCC), driving oncogenesis, progression, and therapeutic response. However, the mechanisms of DDR mediated immune cells and immuno-modulatory pathways in HCC are yet ill-defined.

METHODS

Our study introduces an innovative deep machine learning framework for precise DDR assessment, utilizing single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data. Single-cell RNA sequencing data were obtained and in total 85,628 cells of primary or post-immunotherapy cases were analyzed. Large-scale HCC datasets, including 1027 patients in house together with public datasets, were used for 101 machine-learning models and a novel DDR feature was derived at single-cell resolution (DDRscore). Druggable targets were predicted using the reverse phase protein array (RPPA) proteomic profiling of 169 HCC patients and RNA-seq data from 22 liver cancer cell lines.

RESULTS

Our investigation reveals a dynamic interplay of DDR with natural killer cells and B cells in the primary HCC microenvironment, shaping a tumor-promoting immune milieu through metabolic programming. Analysis of HCC post-immunotherapy demonstrates elevated DDR levels that induces epithelial-mesenchymal transition and fibroblast-like transformation, reshaping the fibrotic tumor microenvironment. Conversely, attenuated DDR promotes antigen cross-presentation by dendritic cells and CD8+ T cells, modulating the inflammatory tumor microenvironment. Regulatory network analysis identifies the CXCL10-CXCR3 axis as a key determinant of immunotherapeutic response in low DDR HCC, potentially regulated by transcription factors GATA3, REL, and TBX21. Using machine learning techniques by combining bulk RNA-seq data in house together with public datasets, we introduce DDRscore, a robust consensus DDR scoring system to predict overall survival and resistance to PD-1 therapy in HCC patients. Finally, we identify BRAF as a potential therapeutic target for high DDRscore patients.

CONCLUSION

Our comprehensive findings advance our understanding of DDR and the tumor microenvironment in HCC, providing insights into immune regulatory mechanisms mediated via DDR pathways.

Single-cell Technologies Provide Novel Insights into Liver Physiology and Pathology

The liver is the largest glandular organ in the body and has a unique distribution of cells and biomolecules. However, the treatment outcome of end-stage liver disease is extremely poor. Single-cell sequencing is a new advanced and powerful technique for identifying rare cell populations and biomolecules by analyzing the characteristics of gene expression between individual cells. These cells and biomolecules might be used as potential targets for immunotherapy of liver diseases and contribute to the development of precise individualized treatment. Compared to whole-tissue RNA sequencing, single-cell RNA sequencing (scRNA-seq) or other single-cell histological techniques have solved the problem of cell population heterogeneity and characterize molecular changes associated with liver diseases with higher accuracy and resolution. In this review, we comprehensively summarized single-cell approaches including transcriptomic, spatial transcriptomic, immunomic, proteomic, epigenomic, and multiomic technologies, and described their application in liver physiology and pathology. We also discussed advanced techniques and recent studies in the field of single-cell; our review might provide new insights into the pathophysiological mechanisms of the liver to achieve precise and individualized treatment of liver diseases.

Noncanonical TRAIL Signaling Promotes Myeloid-Derived Suppressor Cell Abundance and Tumor Growth in Cholangiocarcinoma

BACKGROUND & AIMS

Proapoptotic tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) signaling as a cause of cancer cell death is a well-established mechanism. However, TRAIL-receptor (TRAIL-R) agonists have had very limited anticancer activity in human beings, challenging the concept of TRAIL as a potent anticancer agent. Herein, we aimed to define mechanisms by which TRAIL+ cancer cells can leverage noncanonical TRAIL signaling in myeloid-derived suppressor cells (MDSCs) promoting their abundance in murine cholangiocarcinoma (CCA).

METHODS

Multiple immunocompetent syngeneic, orthotopic models of CCA were used. Single-cell RNA sequencing and cellular indexing of transcriptomes and epitopes by sequencing of CD45+ cells in murine tumors from the different CCA models was conducted.

RESULTS

In multiple immunocompetent murine models of CCA, implantation of TRAIL+ murine cancer cells into Trail-r-/- mice resulted in a significant reduction in tumor volumes compared with wild-type mice. Tumor-bearing Trail-r-/- mice had a significant decrease in the abundance of MDSCs owing to attenuation of MDSC proliferation. Noncanonical TRAIL signaling with consequent nuclear factor-κB activation in MDSCs facilitated enhanced MDSC proliferation. Single-cell RNA sequencing and cellular indexing of transcriptomes and epitopes by sequencing of immune cells from murine tumors showed enrichment of a nuclear factor-κB activation signature in MDSCs. Moreover, MDSCs were resistant to TRAIL-mediated apoptosis owing to enhanced expression of cellular FLICE inhibitory protein, an inhibitor of proapoptotic TRAIL signaling. Accordingly, cellular FLICE inhibitory protein knockdown sensitized murine MDSCs to TRAIL-mediated apoptosis. Finally, cancer cell-restricted deletion of Trail significantly reduced MDSC abundance and murine tumor burden.

CONCLUSIONS

Our findings highlight the therapeutic potential of targeting TRAIL+ cancer cells for treatment of a poorly immunogenic cancer.

Identification of Novel Cuproptosis-Related Genes Mediating the Prognosis and Immune Microenvironment in Cholangiocarcinoma

BACKGROUND

Cuproptosis is a novel type of mediated cell death strongly associated with the progression of several cancers and has been implicated as a potential therapeutic target. However, the role of cuproptosis in cholangiocarcinoma for prognostic prediction, subgroup classification, and therapeutic strategies remains largely unknown.

METHODS

A systematic analysis was conducted among 146 cuproptosis-related genes and clinical information based on independent mRNA and protein datasets to elucidate the potential mechanisms and prognostic prediction value of cuproptosis-related genes. A 10-cuproptosis-related gene prediction model was constructed, and its effects on cholangiocarcinoma prognosis were significantly connected to poor patient survival. Additionally, the expression patterns of our model included genes that were validated with several cholangiocarcinoma cancer cell lines and a normal biliary epithelial cell line.

RESULTS

First, a 10-cuproptosis-related gene signature (ADAM9, ADAM17, ALB, AQP1, CDK1, MT2A, PAM, SOD3, STEAP3, and TMPRSS6) displayed excellent predictive performance for the overall survival of cholangiocarcinoma. The low-cuproptosis group had a significantly better prognosis than the high-cuproptosis group with transcriptome and protein cohorts. Second, compared with the high-risk and low-risk groups, the 2 groups displayed distinct tumor microenvironments, reduced proportions of endothelial cells, and increased levels of cancer-associated fibroblasts based on CIBERSORTx and EPIC analyses. Third, patients' sensitivities to chemotherapeutic drugs and immune checkpoints revealed distinctive differences between the 2 groups. Finally, in replicating the expression patterns of the 10 genes, these results were validated with quantitative real-time polymerase chain reaction results validating the abnormal expression pattern of the target genes in cholangiocarcinoma.

CONCLUSIONS

Collectively, we established and verified an effective prognostic model that could separate cholangiocarcinoma patients into 2 heterogeneous cuproptosis subtypes based on the molecular or protein characteristics of 10 cuproptosis-related genes. These findings may provide potential benefits for unveiling molecular characteristics and defining subgroups could improve the early diagnosis and individualized treatment of cholangiocarcinoma patients.

Exploration of a screening model for intrahepatic cholangiocarcinoma patients prone to cuproptosis and mechanisms of the susceptibility of CD274-knockdown intrahepatic cholangiocarcinoma cells to cuproptosis

Intrahepatic cholangiocarcinoma (ICC) is a form of liver cancer with poor long-term survival rates that requires novel therapeutic methods. Our team's previous research found that ICC patients prone to cuproptosis possessed a more satisfactory long-term prognosis and a more sensitive response to copper carrier Elesclomol. Thus, we aimed to identify new diagnostic and treatment strategies for ICC patients prone to cuproptosis and further explore the associated intracellular and extracellular mechanisms of ICC cells prone to cuproptosis. We employed FU-ICC (n = 255) as the training dataset, and validated our findings using SRRSH-ICC (from our center, n = 65), GSE26566 (n = 104), E-MTAB-6389 (n = 78), and scRNA-seq (n = 14) datasets. Single sample gene set enrichment analysis and subsequent unsupervised cluster analysis was conducted on the training dataset for the pan-programmed cell death gene set (including apoptosis, autophagy, ferroptosis, pyroptosis, necroptosis, and cuproptosis) to define and screen ICC patients prone to cuproptosis. We constructed a nomogram model using weighted gene co-expression network analysis and machine learning algorithms to predict ICC patients prone to cuproptosis, then explored its clinical value with multi-center transcriptome profiling. Furthermore, we validated the hub genes with in vitro and animal experiments to define ICC cells prone to cuproptosis. Ultimately, bulk and single-cell transcriptome profiling were utilized to explore the immune microenvironment of ICC cells prone to cuproptosis. Our nomogram model could help predict ICC patients prone to cuproptosis and possessed excellent prediction efficiency and clinical significance via internal and external verification. In vitro experiments demonstrated that ICC cells with siRNA-mediated knockdown of CD274 (PD-L1) and stimulation with elescomol-CuCl2 were prone to cuproptosis, and CD274-negative ICC cells could be defined as ICC cells prone to cuproptosis. The safety and feasibility of lenti-sh CD274+Elesclomol-CuCl2 as a therapeutic approach for ICC were verified using bioinformatics analysis and animal experiments. Bulk and single-cell transcriptome profiling indicated that the interactions between ICC cells prone to cuproptosis and monocytes/macrophages were particularly relevant. In conclusion, this study systematically and comprehensively explored cuproptosis in ICC for the first time. We constructed precise diagnostic and treatment strategies for ICC patients prone to cuproptosis and further explored the intracellular and extracellular mechanisms of ICC cells prone to cuproptosis. Further work with large prospective cohorts will help verify these conclusions.

Comprehensive analysis of scRNA-Seq and bulk RNA-Seq data reveals dynamic changes in tumor-associated neutrophils in the tumor microenvironment of hepatocellular carcinoma and leads to the establishment of a neutrophil-related prognostic model

BACKGROUND

Analysis of hepatocellular carcinoma (HCC) single-cell sequencing data was conducted to explore the role of tumor-associated neutrophils in the tumor microenvironment.

METHODS

Analysis of single-cell sequencing data from 12 HCC tumor cores and five HCC paracancerous tissues identified cellular subpopulations and cellular marker genes. The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were used to establish and validate prognostic models. xCELL, TIMER, QUANTISEQ, CIBERSORT, and CIBERSORT-abs analyses were performed to explore immune cell infiltration. Finally, the pattern of tumor-associated neutrophil roles in tumor microenvironmental components was explored.

RESULTS

A total of 271 marker genes for tumor-associated neutrophils were identified based on single-cell sequencing data. Prognostic models incorporating eight genes were established based on TCGA data. Immune cell infiltration differed between the high- and low-risk groups. The low-risk group benefited more from immunotherapy. Single-cell analysis indicated that tumor-associated neutrophils were able to influence macrophage, NK cell, and T-cell functions through the IL16, IFN-II, and SPP1 signaling pathways.

CONCLUSION

Tumor-associated neutrophils regulate immune functions by influencing macrophages and NK cells. Models incorporating tumor-associated neutrophil-related genes can be used to predict patient prognosis and immunotherapy responses.

Immunogenomics of cholangiocarcinoma

The development of cholangiocarcinoma spans years, if not decades, during which the immune system becomes corrupted and permissive to primary tumor development and metastasis. This involves subversion of local immunity at tumor sites, as well as systemic immunity and the wider host response. While immune dysfunction is a hallmark of all cholangiocarcinoma, the specific steps of the cancer-immunity cycle that are perturbed differ between patients. Heterogeneous immune functionality impacts the evolutionary development, pathobiological behavior, and therapeutic response of these tumors. Integrative genomic analyses of thousands of primary tumors have supported a biological rationale for immune-based stratification of patients, encompassing immune cell composition and functionality. However, discerning immune alterations responsible for promoting tumor initiation, maintenance, and progression from those present as bystander events remains challenging. Functionally uncoupling the tumor-promoting or tumor-suppressing roles of immune profiles will be critical for identifying new immunomodulatory treatment strategies and associated biomarkers for patient stratification. This review will discuss the immunogenomics of cholangiocarcinoma, including the impact of genomic alterations on immune functionality, subversion of the cancer-immunity cycle, as well as clinical implications for existing and novel treatment strategies.

Biomarkers for immunotherapy of hepatocellular carcinoma

Immune-checkpoint inhibitors (ICIs) are now widely used for the treatment of patients with advanced-stage hepatocellular carcinoma (HCC). Two different ICI-containing regimens, atezolizumab plus bevacizumab and tremelimumab plus durvalumab, are now approved standard-of-care first-line therapies in this setting. However, and despite substantial improvements in survival outcomes relative to sorafenib, most patients with advanced-stage HCC do not derive durable benefit from these regimens. Advances in genome sequencing including the use of single-cell RNA sequencing (both of tumour material and blood samples), as well as immune cell identification strategies and other techniques such as radiomics and analysis of the microbiota, have created considerable potential for the identification of novel predictive biomarkers enabling the accurate selection of patients who are most likely to derive benefit from ICIs. In this Review, we summarize data on the immunology of HCC and the outcomes in patients receiving ICIs for the treatment of this disease. We then provide an overview of current biomarker use and developments in the past 5 years, including gene signatures, circulating tumour cells, high-dimensional flow cytometry, single-cell RNA sequencing as well as approaches involving the microbiome, radiomics and clinical markers. Novel concepts for further biomarker development in HCC are then discussed including biomarker-driven trials, spatial transcriptomics and integrated 'big data' analysis approaches. These concepts all have the potential to better identify patients who are most likely to benefit from ICIs and to promote the development of new treatment approaches.