Trajectory and Functional Analysis of PD-1high CD4+CD8+ T Cells in Hepatocellular Carcinoma by Single-Cell Cytometry and Transcriptome Sequencing

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Single-cell and spatial omics unravel the spatiotemporal biology of tumour border invasion and haematogenous metastasis

Solid tumours exhibit a well-defined architecture, comprising a differentiated core and a dynamic border that interfaces with the surrounding tissue. This border, characterised by distinct cellular morphology and molecular composition, serves as a critical determinant of the tumour's invasive behaviour. Notably, the invasive border of the primary tumour represents the principal site for intravasation of metastatic cells. These cells, known as circulating tumour cells (CTCs), function as 'seeds' for distant dissemination and display remarkable heterogeneity. Advancements in spatial sequencing technology are progressively unveiling the spatial biological features of tumours. However, systematic investigations specifically targeting the characteristics of the tumour border remain scarce. In this comprehensive review, we illuminate key biological insights along the tumour body-border-haematogenous metastasis axis over the past five years. We delineate the distinctive landscape of tumour invasion boundaries and delve into the intricate heterogeneity and phenotype of CTCs, which orchestrate haematogenous metastasis. These insights have the potential to explain the basis of tumour invasion and distant metastasis, offering new perspectives for the development of more complex and precise clinical interventions and treatments.

Novel Arf1 Inhibitors Drive Cancer Stem Cell Aging and Potentiate Anti-Tumor Immunity

The small G protein Arf1 has been identified as playing a selective role in supporting cancer stem cells (CSCs), making it an attractive target for cancer therapy. However, the current Arf1 inhibitors have limited translational potential due to their high toxicity and low specificity. In this study, two new potent small-molecule inhibitors of Arf1, identified as DU101 and DU102, for cancer therapy are introduced. Preclinical tumor models demonstrate that these inhibitors triggered a cascade of aging in CSCs and enhance anti-tumor immunity in mouse cancer and PDX models. Through single-cell sequencing, the remodeling of the tumor immune microenvironment induced by these new Arf1 inhibitors is analyzed and an increase in tumor-associated CD8+ CD4+ double-positive T (DPT) cells is identified. These DPT cells exhibit superior features of active CD8 single-positive T cells and a higher percentage of TCF1+PD-1+, characteristic of stem-like T cells. The frequency of tumor-infiltrating stem-like DPT cells correlates with better disease-free survival (DFS) in cancer patients, indicating that these inhibitors may offer a novel cancer immunotherapy strategy by converting the cold tumor immune microenvironment into a hot one, thus expanding the potential for immunotherapy in cancer patients.

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.

The Role of CD4+T Cells in Nonalcoholic Steatohepatitis and Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) has become the fourth leading cause of cancer-related deaths worldwide; annually, approximately 830,000 deaths related to liver cancer are diagnosed globally. Since early-stage HCC is clinically asymptomatic, traditional treatment modalities, including surgical ablation, are usually not applicable or result in recurrence. Immunotherapy, particularly immune checkpoint blockade (ICB), provides new hope for cancer therapy; however, immune evasion mechanisms counteract its efficiency. In addition to viral exposure and alcohol addiction, nonalcoholic steatohepatitis (NASH) has become a major cause of HCC. Owing to NASH-related aberrant T cell activation causing tissue damage that leads to impaired immune surveillance, NASH-associated HCC patients respond much less efficiently to ICB treatment than do patients with other etiologies. In addition, abnormal inflammation contributes to NASH progression and NASH-HCC transition, as well as to HCC immune evasion. Therefore, uncovering the detailed mechanism governing how NASH-associated immune cells contribute to NASH progression would benefit HCC prevention and improve HCC immunotherapy efficiency. In the following review, we focused our attention on summarizing the current knowledge of the role of CD4+T cells in NASH and HCC progression, and discuss potential therapeutic strategies involving the targeting of CD4+T cells for the treatment of NASH and HCC.

Mechanisms, combination therapy, and biomarkers in cancer immunotherapy resistance

Anti-programmed death 1/programmed death ligand 1 (anti-PD-1/PD-L1) antibodies exert significant antitumor effects by overcoming tumor cell immune evasion and reversing T-cell exhaustion. However, the emergence of drug resistance causes most patients to respond poorly to these immune checkpoint inhibitors (ICIs). Studies have shown that insufficient T-cell infiltration, lack of PD-1 expression, deficient interferon signaling, loss of tumor antigen presentation, and abnormal lipid metabolism are all considered to be closely associated with immunotherapy resistance. To address drug resistance in tumor immunotherapy, a lot of research has concentrated on developing combination therapy strategies. Currently, ICIs such as anti-PD-1 /PD-L1 antibody combined with chemotherapy and targeted therapy have been approved for clinical treatment. In this review, we analyze the mechanisms of resistance to anti-PD-1/PD-L1 therapy in terms of the tumor microenvironment, gut microbiota, epigenetic regulation, and co-inhibitory immune checkpoint receptors. We also discuss various promising combination therapeutic strategies to address resistance to anti-PD-1/PD-L1 drugs, including combining these therapies with traditional Chinese medicine, non-coding RNAs, targeted therapy, other ICIs, and personalized cancer vaccines. Moreover, we focus on biomarkers that predict resistance to anti-PD-1/PD-L1 therapy as well as combination therapy efficacy. Finally, we suggest ways to further expand the application of immunotherapy through personalized combination strategies using biomarker systems.

Spatial iTME analysis of KRAS mutant NSCLC and immunotherapy outcome

We conducted spatial immune tumor microenvironment (iTME) profiling using formalin-fixed paraffin-embedded (FFPE) samples of 25 KRAS-mutated non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), including 12 responders and 13 non-responders. An eleven-marker panel (CD3, CD4, CD8, FOXP3, CD68, arginase-1, CD33, HLA-DR, pan-keratin (PanCK), PD-1, and PD-L1) was used to study the tumor and immune cell compositions. Spatial features at single cell level with cellular neighborhoods and fractal analysis were determined. Spatial features and different subgroups of CD68+ cells and FOXP3+ cells being associated with response or resistance to ICIs were also identified. In particular, CD68+ cells, CD33+ and FOXP3+ cells were found to be associated with resistance. Interestingly, there was also significant association between non-nuclear expression of FOXP3 being resistant to ICIs. We identified CD68dim cells in the lung cancer tissues being associated with improved responses, which should be insightful for future studies of tumor immunity.

del Hierro A, H-Vázquez J, Cuesta-Sancho S, Bernardo D. State-of-the-art cytometry in the search of novel biomarkers in digestive cancers

Despite that colorectal and liver cancer are among the most prevalent tumours in the world, the identification of non-invasive biomarkers to aid on their diagnose and subsequent prognosis is a current unmet need that would diminish both their incidence and mortality rates. In this context, conventional flow cytometry has been widely used in the screening of biomarkers with clinical utility in other malignant processes like leukaemia or lymphoma. Therefore, in this review, we will focus on how advanced cytometry panels covering over 40 parameters can be applied on the study of the immune system from patients with colorectal and hepatocellular carcinoma and how that can be used on the search of novel biomarkers to aid or diagnose, prognosis, and even predict clinical response to different treatments. In addition, these multiparametric and unbiased approaches can also provide novel insights into the specific immunopathogenic mechanisms governing these malignant diseases, hence potentially unravelling novel targets to perform immunotherapy or identify novel mechanisms, rendering the development of novel treatments. As a consequence, computational cytometry approaches are an emerging methodology for the early detection and predicting therapies for gastrointestinal cancers.

Hepatocellular Carcinoma and the Multifaceted Relationship with Its Microenvironment: Attacking the Hepatocellular Carcinoma Defensive Fortress

Hepatocellular carcinoma is a malignant tumor that originates from hepatocytes in an inflammatory substrate due to different degrees of liver fibrosis up to cirrhosis. In recent years, there has been growing interest in the role played by the complex interrelationship between hepatocellular carcinoma and its microenvironment, capable of influencing tumourigenesis, neoplastic growth, and its progression or even inhibition. The microenvironment is made up of an intricate network of mesenchymal cells, immune system cells, extracellular matrix, and growth factors, as well as proinflammatory cytokines and translocated bacterial products coming from the intestinal microenvironment via the enterohepatic circulation. The aim of this paper is to review the role of the HCC microenvironment and describe the possible implications in the choice of the most appropriate therapeutic scheme in the prediction of tumor response or resistance to currently applied treatments and in the possible development of future therapeutic perspectives, in order to circumvent resistance and break down the tumor's defensive fort.

Hyperactivation of β-catenin signal in hepatocellular carcinoma recruits myeloid-derived suppressor cells through PF4-CXCR3 axis

The high mutation rate of CTNNB1 (37 %) and Wnt-β-catenin signal-associated genes (54 %) has been notified in hepatocellular carcinoma (HCC). The activation of Wnt-β-catenin signal pathway was reported to be associated with an immune "desert" phenotype, but the underlying mechanism remains unclear. Here we mainly employed orthotopic HCC models to explore on it. Mass cytometry depicted the immune contexture of orthotopic HCC syngeneic grafts, unveiling that the exogenous expression of β-catenin significantly increased the percentage of myeloid-derived suppressor cells (MDSCs) and decreased the percentage of CD8+ T-cells. Flow cytometry and immunohistochemistry further confirmed the findings. The protein microarray analysis, Western blot and PCR identified PF4 as its downstream regulating cytokine. Intratumorally injection of cytokine PF4 enhanced the accumulation of MDSCs. Knockout of PF4 abolished the effect of β-catenin on recruiting MDSCs. Chromatin immunoprecipitation and luciferase reporter assay demonstrated that β-catenin increases the mRNA level of PF4 via binding to PF4's promoter region. In vitro chemotaxis assay and in vivo administration of specific inhibitors identified CXCR3 on MDSCs as receptor for recruiting PF4. Lastly, the significant correlations across β-catenin, PF4 and MDSCs and CD8+ T-cells infiltration were verified in HCC clinical samples. Our results unveiled HCC tumor cell intrinsic hyperactivation of β-catenin can recruit MDSC through PF4-CXCR3, which contributes to the formation of immune "desert" phenotype. Our study provided new insights into the development of immunotherapeutic strategy of HCC with CTNNB1 mutation. SIGNIFICANCE: This study identifies PF4-CXCR3-MDSCs as a downstream mechanism underlying CTNNB1 mutation associated immune "desert" phenotype.

Integrative single-cell analysis of LUAD: elucidating immune cell dynamics and prognostic modeling based on exhausted CD8+ T cells

Background

The tumor microenvironment (TME) plays a pivotal role in the progression and metastasis of lung adenocarcinoma (LUAD). However, the detailed characteristics of LUAD and its associated microenvironment are yet to be extensively explored. This study aims to delineate a comprehensive profile of the immune cells within the LUAD microenvironment, including CD8+ T cells, CD4+ T cells, and myeloid cells. Subsequently, based on marker genes of exhausted CD8+ T cells, we aim to establish a prognostic model for LUAD.

Method

Utilizing the Seurat and Scanpy packages, we successfully constructed an immune microenvironment atlas for LUAD. The Monocle3 and PAGA algorithms were employed for pseudotime analysis, pySCENIC for transcription factor analysis, and CellChat for analyzing intercellular communication. Following this, a prognostic model for LUAD was developed, based on the marker genes of exhausted CD8+ T cells, enabling effective risk stratification in LUAD patients. Our study included a thorough analysis to identify differences in TME, mutation landscape, and enrichment across varying risk groups. Moreover, by integrating risk scores with clinical features, we developed a new nomogram. The expression of model genes was validated via RT-PCR, and a series of cellular experiments were conducted, elucidating the potential oncogenic mechanisms of GALNT2.

Results

Our study developed a single-cell atlas for LUAD from scRNA-seq data of 19 patients, examining crucial immune cells in LUAD's microenvironment. We underscored pDCs' role in antigen processing and established a Cox regression model based on CD8_Tex-LAYN genes for risk assessment. Additionally, we contrasted prognosis and tumor environments across risk groups, constructed a new nomogram integrating clinical features, validated the expression of model genes via RT-PCR, and confirmed GALNT2's function in LUAD through cellular experiments, thereby enhancing our understanding and approach to LUAD treatment.

Conclusion

The creation of a LUAD single-cell atlas in our study offered new insights into its tumor microenvironment and immune cell interactions, highlighting the importance of key genes associated with exhausted CD8+ T cells. These discoveries have enabled the development of an effective prognostic model for LUAD and identified GALNT2 as a potential therapeutic target, significantly contributing to the improvement of LUAD diagnosis and treatment strategies.

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

Potent induction of antitumor immunity by combining cryo-thermal ablation with immune checkpoint inhibitors in hepatocellular carcinoma

BACKGROUND

The low response rate of immune checkpoint inhibitors (ICIs) prompts the exploration of novel combination therapies for patients with hepatocellular carcinoma (HCC). Here, we aimed to examine the efficiency and potential mechanism of cryo-thermal ablation (Cryo-A) combined with anti-programmed death protein 1 (αPD1) and/or cytotoxic T-lymphocyte antigen 4 (αCTLA4) inhibitors in a murine hepatoma model.

METHOD

Immunocompetent C57BL/6 mice inoculated with unilateral or bilateral H22 hepatic tumour cells were treated with Cryo-A and/or ICIs (αPD1 and/or αCTLA4). Flow cytometry, immunohistochemistry, ELISpot assay, time-of-flight cytometry, tumour rechallenging, and T-cell depletion assay were used to assess the dynamic changes of immune cell subsets following therapy.

RESULTS

We found Cryo-A resulted in immunogenic cell death of tumour cells, activation of dendritic cells, and enhancement of antitumor immunity. Cryo-A alone was insufficient to extend survival, combining Cryo-A with αPD1 and αCTLA4 further modulated the tumour microenvironment, inducing a durable antitumor immune response by tumour-reactive CD8+ T cells and significantly prolonged survival. Time-of-flight cytometry (CyTOF) data revealed that combination therapies reshaped the tumour microenvironment by the increase of intratumoral CD8+ T cells expressed higher levels of cytotoxic markers and immune checkpoint molecules, and by downregulation of intratumoral granulocytes. The combination also resulted in the eradication of remote unablated tumours (abscopal effect).

CONCLUSIONS

These findings suggested that Cryo-A turned HCC from "cold" tumours to "hot" tumours and the combination of Cryo-A with αPD1 and αCTLA4 may be a promising approach to improve the prognosis of HCC.

Peripheral Lymphocytes in Primary Liver Cancers: Elevated NK and CD8+ T Cells and Dysregulated Selenium Metabolism

Peripheral blood lymphocytes (PBLs), which play a pivotal role in orchestrating the immune system, garner minimal attention in hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). The impact of primary liver cancers on PBLs remains unexplored. In this study, flow cytometry facilitated the quantification of cell populations, while transcriptome of PBLs was executed utilizing 10× single-cell sequencing technology. Additionally, pertinent cases were curated from the GEO database. Subsequent bioinformatics and statistical analyses were conducted utilizing R (4.2.1) software. Elevated counts of NK cells and CD8+ T cells were observed in both ICC and HCC when compared to benign liver disease (BLD). In the multivariate Cox model, NK cells and CD8+ T cells emerged as independent risk factors for recurrence-free survival. Single-cell sequencing of PBLs uncovered the downregulation of TGFβ signaling in tumor-derived CD8+ T cells. Pathway enrichment analysis, based on differential expression profiling, highlighted aberrations in selenium metabolism. Proteomic analysis of preoperative and postoperative peripheral blood samples from patients undergoing tumor resection revealed a significant upregulation of SELENBP1 and a significant downregulation of SEPP1. Primary liver cancer has a definite impact on PBLs, manifested by alterations in cellular quantities and selenoprotein metabolism.

T-cell receptor sequencing reveals hepatocellular carcinoma immune characteristics according to Barcelona Clinic liver cancer stages within liver tissue and peripheral blood

Analysis of T-cell receptor (TCR) repertoires in different stages of hepatocellular carcinoma (HCC) might help to elucidate its pathogenesis and progression. This study aimed to investigate TCR profiles in liver biopsies and peripheral blood mononuclear cells (PBMCs) in different Barcelona Clinic liver cancer (BCLC) stages of HCC. Ten patients in early stage (BCLC_A), 10 patients in middle stage (BCLC_B), and 10 patients in late stage (BCLC_C) cancer were prospectively enrolled. The liver tumor tissues, adjacent tissues, and PBMCs of each patient were collected and examined by TCR β sequencing. Based on the ImMunoGeneTics (IMGT) database, we aligned the V, D, J, and C gene segments and identified the frequency of CDR3 sequences and amino acids sequence. Diversity of TCR in PBMCs was higher than in both tumor tissues and adjacent tissues, regardless of BCLC stage and postoperative recurrence. TCR clonality was increased in T cells from peripheral blood in advanced HCC, compared with the early and middle stages. No statistical differences were observed between different BCLC stages, either in tumors or adjacent tissues. TCR clonality revealed no significant difference between recurrent tumor and non-recurrent tumor, therefore PBMCs was better to be representative of TCR characteristics in different stages of HCC compared to tumor tissues. Clonal expansion of T cells was associated with low risk of recurrence in HCC patients.

MAIT cells confer resistance to Lenvatinib plus anti-PD1 antibodies in hepatocellular carcinoma through TNF-TNFRSF1B pathway

The combination of antiangiogenic agents and immune checkpoint inhibitors is more efficient than monotherapy in the management of hepatocellular carcinoma (HCC). Lenvatinib plus anti-PD1 antibodies have become the mainstay in HCC treatment. However, more than half the patients with HCC are non-responsive, and the mechanisms underlying drug resistance are unknown. To address this issue, we performed single-cell sequencing on samples from six HCC patients, aiming to explore cellular signals and molecular pathways related to the effect of lenvatinib plus anti-PD1 antibody treatment. GSVA analysis revealed that treatment with lenvatinib plus anti-PD1 antibody led to an increase in the TNF-NFKB pathway across all immune cell types, as compared to the non-treatment group. Mucosal-associated invariant T (MAIT) cells were found to secrete TNF, which activates TNFRSF1B on regulatory T cells, thereby promoting immunosuppression. Additionally, TNFSF9 was highly expressed in anticancer immune cells, including CD8+ effector T cells, MAIT, and γδ T cells in the treatment group. We also detected CD3+ macrophages in both HCC and pan-cancer tissues. Overall, our findings shed light on the potential mechanisms behind the effectiveness of lenvatinib plus anti-PD1 antibody treatment in HCC patients. By understanding these mechanisms better, we may be able to develop more effective treatment strategies for patients who do not respond to current therapies.

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

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

Single-cell analysis technologies for cancer research: from tumor-specific single cell discovery to cancer therapy

Single-cell sequencing (SCS) technology is changing our understanding of cellular components, functions, and interactions across organisms, because of its inherent advantage of avoiding noise resulting from genotypic and phenotypic heterogeneity across numerous samples. By directly and individually measuring multiple molecular characteristics of thousands to millions of single cells, SCS technology can characterize multiple cell types and uncover the mechanisms of gene regulatory networks, the dynamics of transcription, and the functional state of proteomic profiling. In this context, we conducted systematic research on SCS techniques, including the fundamental concepts, procedural steps, and applications of scDNA, scRNA, scATAC, scCITE, and scSNARE methods, focusing on the unique clinical advantages of SCS, particularly in cancer therapy. We have explored challenging but critical areas such as circulating tumor cells (CTCs), lineage tracing, tumor heterogeneity, drug resistance, and tumor immunotherapy. Despite challenges in managing and analyzing the large amounts of data that result from SCS, this technique is expected to reveal new horizons in cancer research. This review aims to emphasize the key role of SCS in cancer research and promote the application of single-cell technologies to cancer therapy.

Platinum-Chimeric Carrier Cells for Ultratrace Cell Analysis in Mass Cytometry

Mass cytometry by time-of-flight (CyTOF), a high-dimensional single-cell analysis platform, detects up to 50 biomarkers at single-cell resolution. However, CyTOF analysis of biological samples with a minimal number of available cells or rare cell subsets remains a major technical challenge due to the extensive loss of cells during cell recovery, staining, and acquisition. Here, we introduce a platinum-chimeric carrier cell strategy for mass cytometry profiling of ultratrace cell samples. Cisplatin can rapidly enter broken plasma membranes of dead cells and form a chimeric interaction with cellular proteins, peptides, and amino acids. Thus, 198Pt-cisplatin is adopted to tag carrier cells in the pretreatment stage. We investigated 8 cell lines that are commonly accessible in laboratories for their potential as carrier cells to preserve rare target cells for CyTOF analysis. We designed a panel of 35 protein biomarkers to evaluate the comprehensive single-cell subtype classification capability with or without the carrier cell strategy. We further demonstrated the detection and analysis of as few as 1 × 104 immune cells using our method. The proposed method thus allows CyTOF analysis on precious clinical samples with less abundant cells.

Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma

Background

This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response.

Methods

Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients.

Results

Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients.

Conclusion

Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.

Legend or Truth: Mature CD4+CD8+ Double-Positive T Cells in the Periphery in Health and Disease

The expression of CD4 and CD8 co-receptors defines two distinct T cell populations with specialized functions. While CD4+ T cells support and modulate immune responses through different T-helper (Th) and regulatory subtypes, CD8+ T cells eliminate cells that might threaten the organism, for example, virus-infected or tumor cells. However, a paradoxical population of CD4+CD8+ double-positive (DP) T cells challenging this paradigm has been found in the peripheral blood. This subset has been observed in healthy as well as pathological conditions, suggesting unique and well-defined functions. Furthermore, DP T cells express activation markers and exhibit memory-like features, displaying an effector memory (EM) and central memory (CM) phenotype. A subset expressing high CD4 (CD4bright+) and intermediate CD8 (CD8dim+) levels and a population of CD8bright+CD4dim+ T cells have been identified within DP T cells, suggesting that this small subpopulation may be heterogeneous. This review summarizes the current literature on DP T cells in humans in health and diseases. In addition, we point out that strategies to better characterize this minor T cell subset's role in regulating immune responses are necessary.

Immune landscape and immunotherapy of hepatocellular carcinoma: focus on innate and adaptive immune cells

Hepatocellular carcinoma (HCC) is responsible for roughly 90% of all cases of primary liver cancer, and the cases are on the rise. The treatment of advanced HCC is a serious challenge. Immune checkpoint inhibitor (ICI) therapy has marked a watershed moment in the history of HCC systemic treatment. Atezolizumab in combination with bevacizumab has been approved as a first-line treatment for advanced HCC since 2020; however, the combination therapy is only effective in a limited percentage of patients. Considering that the tumor immune microenvironment (TIME) has a great impact on immunotherapies for HCC, an in-depth understanding of the immune landscape in tumors and the current immunotherapeutic approaches is extremely necessary. We elaborate on the features, functions, and cross talk of the innate and adaptive immune cells in HCC and highlight the benefits and drawbacks of various immunotherapies for advanced HCC, as well as future projections. HCC consists of a heterogeneous group of cancers with distinct etiologies and immune microenvironments. Almost all the components of innate and adaptive immune cells in HCC have altered, showing a decreasing trend in the number of tumor suppressor cells and an increasing trend in the pro-cancer cells, and there is also cross talk between various cell types. Various immunotherapies for HCC have also shown promising efficacy and application prospect. There are multilayered interwoven webs among various immune cell types in HCC, and emerging evidence demonstrates the promising prospect of immunotherapeutic approaches for HCC.

The Era of Immunotherapy in Hepatocellular Carcinoma: The New Mission and Challenges of Magnetic Resonance Imaging

In recent years, significant advancements in immunotherapy for hepatocellular carcinoma (HCC) have shown the potential to further improve the prognosis of patients with advanced HCC. However, in clinical practice, there is still a lack of effective biomarkers for identifying the patient who would benefit from immunotherapy and predicting the tumor response to immunotherapy. The immune microenvironment of HCC plays a crucial role in tumor development and drug responses. However, due to the complexity of immune microenvironment, currently, no single pathological or molecular biomarker can effectively predict tumor responses to immunotherapy. Magnetic resonance imaging (MRI) images provide rich biological information; existing studies suggest the feasibility of using MRI to assess the immune microenvironment of HCC and predict tumor responses to immunotherapy. Nevertheless, there are limitations, such as the suboptimal performance of conventional MRI sequences, incomplete feature extraction in previous deep learning methods, and limited interpretability. Further study needs to combine qualitative features, quantitative parameters, multi-omics characteristics related to the HCC immune microenvironment, and various deep learning techniques in multi-center research cohorts. Subsequently, efforts should also be undertaken to construct and validate a visual predictive tool of tumor response, and assess its predictive value for patient survival benefits. Additionally, future research endeavors must aim to provide an accurate, efficient, non-invasive, and highly interpretable method for predicting the effectiveness of immune therapy.

Reprogramming of Treg cells in the inflammatory microenvironment during immunotherapy: a literature review

Regulatory T cells (Treg), as members of CD4+ T cells, have garnered extensive attention in the research of tumor progression. Treg cells have the function of inhibiting the immune effector cells, preventing tissue damage, and suppressing inflammation. Under the stimulation of the tumor inflammatory microenvironment (IM), the reprogramming of Treg cells enhances their suppression of immune responses, ultimately promoting tumor immune escape or tumor progression. Reducing the number of Treg cells in the IM or lowering the activity of Treg cells while preventing their reprogramming, can help promote the body's anti-tumor immune responses. This review introduces a reprogramming mechanism of Treg cells in the IM; and discusses the regulation of Treg cells on tumor progression. The control of Treg cells and the response to Treg inflammatory reprogramming in tumor immunotherapy are analyzed and countermeasures are proposed. This work will provide a foundation for downregulating the immunosuppressive role of Treg in the inflammatory environment in future tumor immunotherapy.

Dissecting the tumor ecosystem of liver cancers in the single-cell era

Primary liver cancers (PLCs) are a broad class of malignancies that include HCC, intrahepatic cholangiocarcinoma, and combined hepatocellular and intrahepatic cholangiocarcinoma. PLCs are often associated with a poor prognosis due to their high relapse and low therapeutic response rates. Importantly, PLCs exist within a dynamic and complex tumor ecosystem, which includes malignant, immune, and stromal cells. It is critical to dissect the PLC tumor ecosystem to uncover the underlying mechanisms associated with tumorigenesis, relapse, and treatment resistance to facilitate the discovery of novel therapeutic targets. Single-cell and spatial multi-omics sequencing techniques offer an unprecedented opportunity to elucidate spatiotemporal interactions among heterogeneous cell types within the complex tumor ecosystem. In this review, we describe the latest advances in single-cell and spatial technologies and review their applications with respect to dissecting liver cancer tumor ecosystems.

Identification of molecular subtypes based on PANoptosis-related genes and construction of a signature for predicting the prognosis and response to immunotherapy response in hepatocellular carcinoma

Background

Previous studies have demonstrated that PANoptosis is strongly correlated with cancer immunity and progression. This study aimed to develop a PANoptosis-related signature (PANRS) to explore its potential value in predicting the prognosis and immunotherapy response of hepatocellular carcinoma (HCC).

Methods

Based on the expression of PANoptosis-related genes, three molecular subtypes were identified. To construct a signature, the differentially expressed genes between different molecular subtypes were subjected to multivariate least absolute shrinkage and selection operator Cox regression analyses. The risk scores of patients in the training set were calculated using the signature. The patients were classified into high-risk and low-risk groups based on the median risk scores. The predictive performance of the signature was evaluated using Kaplan-Meier plotter, receiving operating characteristic curves, nomogram, and calibration curve. The results were validated using external datasets. Additionally, the correlation of the signature with the immune landscape and drug sensitivity was examined. Furthermore, the effect of LPCAT1 knockdown on HCC cell behavior was verified using in vitro experiments.

Results

This study developed a PANRS. The risk score obtained by using the PANRS was an independent risk factor for the prognosis of patients with HCC and exhibited good prognostic predictive performance. The nomogram constructed based on the risk score and clinical information can accurately predicted the survival probability of patients with HCC. Patients with HCC in the high-risk groups have high immune scores and tend to generate an immunosuppressive microenvironment. They also exhibited a favorable response to immunotherapy, as evidenced by high tumor mutational burden, high immune checkpoint gene expression, high human leukocyte antigen gene expression, low tumor immune dysfunction and low exclusion scores. Additionally, the PANRS enabled the identification of 15 chemotherapeutic agents, including sorafenib, for patients with HCC with different risk levels, guiding clinical treatment. The signature gene LPCAT1 was upregulated in HCC cell lines. LPCAT1 knockdown markedly decreased HCC cell proliferation and migration.

Conclusion

PANRS can accurately predict the prognosis and immunotherapy response of patients with HCC and consequently guide individualized treatment.

Single-cell RNA-seq and bulk RNA-seq explore the prognostic value of exhausted T cells in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains a worldwide health problem. Mounting evidence indicates that exhausted T cells play a critical role in the progress and treatment of HCC. Therefore, a detailed characterisation of exhausted T cells and their clinical significance warrants further investigation in HCC. Based on the GSE146115, we presented a comprehensive single-cell Atlas in HCC. Pseudo-time analysis revealed that tumour heterogeneity progressively increased, and the exhausted T cells gradually appeared during tumour progression. Functional enrichment analysis revealed that the evolutionary process of exhausted T cells mainly contained the pathway of cadherin binding, proteasome, cell cycle, and T cell receptor regulation of apoptosis. In the International Cancer Genome Consortium database, we divided patients into three clusters with the T cell evolution-associated genes. We found that the exhausted T cells are significantly related to poor outcomes through immunity and survival analysis. In The Cancer Genome Atlas database, the authors enrolled weighted gene co-expression network analysis, univariate Cox analysis, and Lasso Cox analysis, then screened the 19 core genes in T cells evolution and built a robust prognostic model. This study offers a fresh view on evaluating the patients' outcomes from an exhausted T cells perspective and might help clinicians develop therapeutic systems.

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

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

A Novel Prognostic Signature of comprising Nine NK Cell signatures Based on Both Bulk RNA Sequencing and Single-Cell RNA Sequencing for Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) has limited prognostic prediction due to its heterogeneity. Understanding the role of natural killer (NK) cells in HCC is vital for prognosis and immunotherapy guidance. We aimed to identify NK cell marker genes through scRNA-seq and develop a prognostic signature for HCC. Methods: We analyzed scRNA-seq data (GSE149614) from 10 patients and bulk RNA-seq data from 786 patients with clinicopathological information. NK cell marker genes were identified using clustering and marker finding functions. A predictive risk signature was constructed using LASSO-COX algorithm. Functional annotations and immune cell infiltration analysis were performed, and the nomogram's performance was evaluated. Results: We identified 79 NK cell marker genes associated with NK cell-mediated cytotoxicity, apoptosis, and immune response. The multigene signature significantly correlated with overall survival (OS) in TCGA-LIHC cohort and was validated in other cohorts. Low-risk patients exhibited higher immune cell infiltration, including CD8+ T cells. The risk signature was an independent prognostic factor for OS (HR > 1, p < 0.001). The nomogram combining the risk signature and clinical predictors demonstrated robust prognostic ability. Conclusion: We developed a nine-gene signature prognostic model based on NK cell marker genes to accurately assess the prognostic risk of HCC. This model can be a valuable tool for personalized evaluation post-surgery. Our study underscores the potential of NK cells in HCC prognosis and highlights the importance of scRNA-seq analysis in identifying prognostic markers.

Double Positive CD4+CD8+ (DP) T-Cells Display Distinct Exhaustion Phenotype in Chronic Hepatitis C

In chronic hepatitis C (CHC), characterized by exhaustion of T-cell function, increased frequencies of double-positive (DP) (CD4⁺CD8⁺) cells are present in peripheral blood. We compared the exhaustion phenotype between DP and single positive (SP) T-cells, including HCV-specific cells, and assessed the effect of successful HCV treatment on inhibitory receptors expression. Blood samples from 97 CHC patients were collected before and six months post-treatment. PD-1 (programmed cell death protein 1) and Tim-3 (T-cell immunoglobulin and mucin domain-containing molecule-3) expression was assessed by flow cytometry. DP T-cells displayed significantly higher PD-1 expression, lower Tim-3 expression than CD8⁺ SP T-cells and lower percentages of PD-1^-Tim-3^- cells than CD4⁺ SP T-cells, both before and after treatment. PD-1⁺Tim-3⁺ DP T-cells decreased following treatment. HCV-specific cells were more frequent among DP than SP T-cells, both before and after treatment. HCV-specific DP T-cells were characterized by lower PD-1 expression, higher PD-1 and Tim-3 co-expression, and lower percentages of PD-1^-Tim-3^- cells (both before and after treatment) and higher post-treatment Tim-3 than HCV-specific SP T-cells. Their percentages decreased following treatment, but the exhaustion phenotype remained unchanged. DP T-cells in CHC exhibit a distinct exhaustion phenotype from SP T-cells, and these changes mostly persist following successful treatment.

Navigating the immunometabolic heterogeneity of B cells in murine hepatocellular carcinoma at single cell resolution

Induction of antitumor immunity is critical for the therapeutic efficacy of hepatocellular carcinoma (HCC) immunotherapy. The cellular metabolic state underpins the effector function of immune cells, yet our understanding of the phenotypic and metabolic heterogeneity of B cells within HCC microenvironment is poorly developed. Herein, we investigated the composition, distribution, phenotype, function and metabolic profiles of B-cell subsets in HCC and adjacent liver tissues from an orthotopic HCC mouse model using single-cell RNA sequencing (scRNA-seq). Our results identified six B-cell clusters, which can be classified into plasma cells and activated and exhausted B cells according to marker expression, functional and temporal distribution. Exhausted B cells exhibited low metabolic activities and impaired effector functions. Activated B and plasma cells showed higher metabolic activity than exhausted B cells, but there were clear differences in their metabolic profiles. In addition, we found that the effector function of exhausted B cells was further diminished in HCC tissues compared with adjacent liver tissues, but their metabolic activity was significantly enhanced. Collectively, we comprehensively characterized the metabolic profile and alterations in B-cell subsets in HCC, which contributes to the understanding of B-cell immunology in HCC and lays the foundation for exploring novel targets in HCC immunotherapy.

Comparison of survival benefit between salvage surgery after conversion therapy versus surgery alone for hepatocellular carcinoma with portal vein tumor thrombosis: a propensity score analysis

BACKGROUND

Salvage surgery after conversion therapy with a combination of tyrosine kinase inhibitor and anti-programmed death-1 antibody has shown improved survival benefits in patients with hepatocellular carcinoma (HCC) with portal vein tumor thrombosis (PVTT). We aimed to compare the survival benefits in a retrospective cohort of patients with HCC with PVTT who underwent salvage surgery after conversion therapy and surgery alone.

METHODS

From January 2015 to October 2021, we selected patients diagnosed with HCC with PVTT who underwent liver resection at Chinese PLA General Hospital. The primary endpoint in the comparison of survival benefits between conversion therapy and surgery-alone groups was recurrence-free survival. Propensity score matching was applied to reduce any potential bias in the study.

RESULTS

The 6-, 12-, and 24-month recurrence-free survival rates in the conversion and surgery alone groups were 80.3% vs 36.5%, 65.4% vs 29.4%, and 56% vs 21%, respectively. On multivariable Cox regression analyses, conversion therapy significantly reduced HCC-related mortality and HCC recurrence rates compared with surgery alone.

CONCLUSIONS

For patients with HCC with PVTT, surgery after conversion therapy is in relationship with increased survival in comparison with surgery alone.

A Botanical Drug Extracted From Antrodia cinnamomea: A First-in-human Phase I Study in Healthy Volunteers

LEAC-102 is an emerging drug extracted from the medicinal fungus Antrodia cinnamomea (AC), which is traditionally used to ameliorate fatigue and liver disorders arising from excessive alcohol consumption. AC has been used as a health product with an immunomodulatory function, but its anticancer effect has not been applied in clinical therapy as a drug. This first-in-human study examined the safety and tolerability of LEAC-102 as a new drug in healthy adults.

This standard 3 + 3 dose-escalation study included 18 participants administered LEAC-102 at doses of 597.6, 1195.2, 1792.8, 2390.4, or 2988 mg/day for 1 month plus 7 days of safety follow-up. The maximum planned dose was 2988 mg. Dose-limiting toxicity (DLT) was monitored from the start of LEAC-102 administration up to the final visit. The dose of LEAC-102 was escalated to the subsequent cohort as long as there was no DLT in the previous cohort. Tolerability, clinical status, safety (by laboratory parameters), and adverse event occurrence were documented weekly during the treatment and 1 week after the conclusion of the treatment.

All clinical biochemistry profiles were in the normal range, and no serious adverse effects were observed. The maximum tolerated dose of LEAC-102 was determined to be 2988 mg/day because one participant experienced urticaria. Additionally, our exploratory objectives revealed that LEAC-102 significantly elevated natural killer, natural killer T, and dendritic cells in a dose-dependent manner, activated effector T cells, and upregulated programmed cell death-1 expression.

The outcomes suggested that LEAC-102 was well tolerated and safe in healthy adults and exhibited potential immunomodulatory function.

Supplemental data for this article is available online at https://doi.org/10.1080/07315724.2022.2032868 .

Transcriptome analysis creates a new era of precision medicine for managing recurrent hepatocellular carcinoma

The high incidence of hepatocellular carcinoma (HCC) recurrence negatively impacts outcomes of patients treated with curative intent despite advances in surgical techniques and other locoregional liver-targeting therapies. Over the past few decades, the emergence of transcriptome analysis tools, including real-time quantitative reverse transcription PCR, microarrays, and RNA sequencing, has not only largely contributed to our knowledge about the pathogenesis of recurrent HCC but also led to the development of outcome prediction models based on differentially expressed gene signatures. In recent years, the single-cell RNA sequencing technique has revolutionized our ability to study the complicated crosstalk between cancer cells and the immune environment, which may benefit further investigations on the role of different immune cells in HCC recurrence and the identification of potential therapeutic targets. In the present article, we summarized the major findings yielded with these transcriptome methods within the framework of a causal model consisting of three domains: primary cancer cells; carcinogenic stimuli; and tumor microenvironment. We provided a comprehensive review of the insights that transcriptome analyses have provided into diagnostics, surveillance, and treatment of HCC recurrence.

The role of spatial interplay patterns between PD-L1-positive tumor cell and T cell in recurrence of locally advanced non-small cell lung cancer

PURPOSE

To explore the relationship between the spatial interaction of programmed death-ligand 1(PD-L1)-positive tumor cell and T cell with specific functions and the recurrence of non-small cell lung cancer (NSCLC) and optimize prognostic stratification.

MATERIALS AND METHODS

This study retrospectively included 104 patients with locally advanced NSCLC who underwent radical surgery. Tissue microarrays were constructed including tumor center (TC) and invasion margin (IM), and CK/CD4/CD8/PD-L1/programmed death-1 (PD-1) was labeled using multiplex immunofluorescence to decipher the counts and spatial distribution of tumor cells and T cells. The immune microenvironment and recurrence stratification were characterized using the Mann-Whitney U test and Cox proportional hazards model.

RESULT

Compared with the IM, the proportion of tumor cells (especially PD-L1⁺) was increased in the TC, while T cells (especially PD-1⁺) were decreased. An increase in TC PD-1⁺ CD8 T cells promoted relapse (HR = 2.183), while PD-L1⁺ tumor cells alone or in combination with T cells had no predictive value for relapse. In addition, in both TC and IM, CD8 were on average closer to PD-L1⁺ tumor cells than CD4, especially exhausted CD8. The effective density and percentage of PD-1⁺ CD4 T cells interacting with PD-L1⁺ tumor cells in the IM were both associated with recurrence, and the HRs increased sequentially (HRs were 2.809 and 4.063, respectively). Patients with low PD-1⁺CD4 count combined high PD-1⁺CD4 effective density showed significantly poorer RFS compared to those with high PD-1⁺CD4 count combined low PD-1⁺CD4 effective density, in both the TC and IM regions (HRs were 5.810 and 8.709, respectively).

CONCLUSION

Assessing the relative spatial proximity of PD-1/PD-L1 contributes to a deeper understanding of tumor immune escape and generates prognostic information in locally advanced NSCLC patients.

Clinicopathological and predictive value of MAIT cells in non-small cell lung cancer for immunotherapy

BACKGROUND

Immune-checkpoint inhibitors (ICIs) remain ineffective in a large group of non-small cell lung cancer (NSCLC) patients. Mucosal-associated invariant T (MAIT) cells, a population of unconventional innate-like T lymphocytes abundant in the human body, play important roles in human malignancies. Little is known about the immune characteristics of MAIT cells in NSCLC and correlation with prognosis and response rate of ICIs treatment.

METHODS

To investigate the distribution, activation status, and function of MAIT cells in NSCLC patients and their correlations with anti-PD-1 immunotherapy, MAIT cells in peripheral blood, tumor and paratumor samples from NSCLC patients with or without anti-PD-1 immunotherapy were analyzed using flow cytometry and single-cell RNA-sequencing.

RESULTS

MAIT cells were enriched in the tumor lesions of NSCLC patients migrating from peripheral blood via the CCR6-CCL20 axis. Both peripheral and tumor-infiltrating MAIT cells displayed an exhausted phenotype with upregulated PD-1, TIM-3, and IL-17A while less IFN-γ. Anti-PD-1 therapy reversed the function of circulating MAIT cells with higher expression of IFN-γ and granzyme B. Subcluster MAIT-17s (defined as cells highly expressing exhausted and Th17-related genes) mainly infiltrated in the non-responsive tissues, while the subcluster MAIT-IFNGRs (cells expressing genes related to cytotoxic function) were mainly enriched in responsive tissues. Moreover, we found predictive value of circulating MAIT cells for anti-PD-1 immunotherapy in NSCLC patients.

CONCLUSIONS

MAIT cells shifted to an exhausted tumor-promoting phenotype in NSCLC patients and the circulating MAIT subset could be a predictor for patients who respond to anti-PD-1 immunotherapy.

T cell exhaustion assessment algorism in tumor microenvironment predicted clinical outcomes and immunotherapy effects in glioma

Despite the recent increase in the use of immune checkpoint blockade (ICB), no ICB medications have been approved or are undergoing large-scale clinical trials for glioma. T cells, the main mediators of adaptive immunity, are important components of the tumor immune microenvironment. Depletion of T cells in tumors plays a key role in assessing the sensitivity of patients to immunotherapy. In this study, the bioinformatics approach was applied to construct T cell depletion-related risk assessment to investigate the impact of T cell depletion on prognosis and ICB response in glioma patients. The Cancer Genome Atlas (TCGA) and GSE108474 glioma cohorts and IMvigor210 immunotherapy datasets were collected, including complete mRNA expression profiles and clinical information. We used cell lines to verify the gene expression and the R 3.6.3 tool and GraphPad for bioinformatics analysis and mapping. T cell depletion in glioma patients displayed significant heterogeneity. The T cell depletion-related prognostic model was developed based on seven prognostic genes (HSPB1, HOXD10, HOXA5, SEC61G, H19, ANXA2P2, HOXC10) in glioma. The overall survival of patients with a high TEXScore was significantly lower than that of patients with a low TEXScore. In addition, high TEXScore scores were followed by intense immune responses and a more complex tumor immune microenvironment. The “hot tumors” were predominantly enriched in the high-risk group, which patients expressed high levels of suppressive immune checkpoints, such as PD1, PD-L1, and TIM3. However, patients with a low TEXScore had a more significant clinical response to immunotherapy. In addition, HSPB1 expression was higher in the U251 cells than in the normal HEB cells. In conclusion, the TEXScore related to T cell exhaustion combined with other pathological profiles can effectively assess the clinical status of glioma patients. The TEXScore constructed in this study enables the effective assessment of the immunotherapy response of glioma patients and provides therapeutic possibilities.

Emerging Insights on Immunotherapy in Liver Cancer

Significance: Hepatocellular carcinoma (HCC) is a liver malignancy with high mortality rate, limited treatment options, and poor prognosis. Sorafenib has been the only systemic treatment option for patients with advanced HCC for more than a decade. HCC is a typical inflammation-related tumor with a distinct immunosuppressive microenvironment especially the upregulation of immune checkpoints. Recent Advances: Immunotherapy has shown persistent and powerful efficacy in HCC treatment. Several preclinical and clinical studies have prompted the application of immunotherapy in first-line, second-line, and postline treatment of HCC, which has profoundly shifted the paradigm for advanced HCC treatment in the past few years. Critical Issues and Future Directions: Major unaddressed challenges in HCC immunotherapy include the discovery and validation of biological markers that predict the efficacy, the application of immunotherapy in patients with impaired liver function and nonalcoholic steatohepatitis-associated HCC, and the exploration of immunotherapy combinations with better effectiveness. This review provides the latest advances in the research of immune microenvironment and immunotherapy in HCC. Antioxid. Redox Signal. 37, 1325-1338.

T lymphocyte subsets and PD-1 expression on lymphocytes in peripheral blood of patients with non-small cell lung cancer

The incidence rate and mortality rate of lung cancer (LC) are very high. This study aimed to analyze the T lymphocyte subsets and programmed death-1 (PD-1) expression on lymphocytes in the peripheral blood of non-small cell lung cancer (NSCLC) patients and explore whether there were changes in cellular immunity in NSCLC. Peripheral blood samples were collected from newly diagnosed NSCLC patients and healthy individuals. The T lymphocyte subsets and PD-1 expression were evaluated using flow cytometry. Single-sample gene set enrichment analysis (ssGSEA) was performed to explore the correlations of PD-1 expression with infiltration patterns for tumor-infiltrating T immune cells. By flow cytometry, two populations of lymphocytes in NSCLC patients were observed. Apart from a population of normal volume lymphocytes (Lym1), the other population had larger volume and more particles (Lym2). Compared with the healthy group, the proportion of CD4+ T cells and PD-1 expression on Lym1 was higher, and that of CD8+ T cells was lower in the NSCLC group. In the NSCLC group, the proportions of CD3+ T cells, CD8+ T cells, CD4+CD8+ T (DPT) cells, and PD-1 expression were higher on Lym2 than those on Lym1 (P < .05). ssGSEA showed that tumor infiltrating immune T cells were positively correlated with PD-1 expression. The PD-1 expression on lymphocytes increased in recurrent patients who treated with PD-1 inhibitor. Lym2 may be tumor-infiltrating lymphocytes (TILs) which upregulated PD-1 expression in NSCLC. PD-1 expression on lymphocytes may be used as a recurrence indicator for NSCLC patients treated with PD-1 inhibitors.

Advances in single-cell sequencing technology in the field of hepatocellular carcinoma

Tumors are a class of diseases characterized by altered genetic information and uncontrolled growth. Sequencing technology provide researchers with a better way to explore specific tumor pathogenesis. In recent years, single-cell sequencing technology has shone in tumor research, especially in the study of liver cancer, revealing phenomena that were unexplored by previous studies. Single-cell sequencing (SCS) is a technique for sequencing the cellular genome, transcriptome, epigenome, proteomics, or metabolomics after dissociation of tissues into single cells. Compared with traditional bulk sequencing, single-cell sequencing can dissect human tumors at single-cell resolution, finely delineate different cell types, and reveal the heterogeneity of tumor cells. In view of the diverse pathological types and complex pathogenesis of hepatocellular carcinoma (HCC), the study of the heterogeneity among tumor cells can help improve its clinical diagnosis, treatment and prognostic judgment. On this basis, SCS has revolutionized our understanding of tumor heterogeneity, tumor immune microenvironment, and clonal evolution of tumor cells. This review summarizes the basic process and development of single-cell sequencing technology and its increasing role in the field of hepatocellular carcinoma.

Mitochondrial fragmentation in liver cancer: Emerging player and promising therapeutic opportunities

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related death worldwide. Enhanced mitochondrial fragmentation (MF) is associated with poor prognosis in HCC patients. However, its molecular mechanism in HCC remains elusive. Although enhanced MF activates effector T cells and dendritic cells, it induces immunoescape by decreasing the number and cytotoxicity of natural killer cells in the HCC immune microenvironment. Therefore, the influence of MF on the activity of different immune cells is a great challenge. Enhanced MF contributes to maintaining stemness by promoting the asymmetric division of liver cancer stem cells (LCSCs), suggesting that MF may become a potential target for HCC recurrence, metastasis, and chemotherapy resistance. Moreover, mechanistic studies suggest that MF may promote tumour progression through autophagy, oxidative stress, and metabolic reprogramming. Human-induced hepatocyte organoids are a recently developed system that can be genetically manipulated to mimic cancer initiation and identify potential preventive treatments. We can use it to screen MF-related candidate inhibitors of HCC progression and further explore the role of MF in hepatocarcinogenesis. We herein describe the mechanisms by which MF contributes to HCC development, discuss potential therapeutic approaches, and highlight the possibility that MF modulation has a synergistic effect with immunotherapy.

Integrated Analysis of Tumor Mutation Burden and Immune Infiltrates in Hepatocellular Carcinoma

Tumor mutation burdens (TMBs) act as an indicator of immunotherapeutic responsiveness in various tumors. However, the relationship between TMBs and immune cell infiltrates in hepatocellular carcinoma (HCC) is still obscure. The present study aimed to explore the potential diagnostic markers of TMBs for HCC and analyze the role of immune cell infiltration in this pathology. We used OA datasets from The Cancer Genome Atlas database. First, the “maftools” package was used to screen the highest mutation frequency in all samples. R software was used to identify differentially expressed genes (DEGs) according to mutation frequency and perform functional correlation analysis. Then, the gene ontology (GO) enrichment analysis was performed with “clusterProfiler”, “enrichplot”, and “ggplot2” packages. Finally, the correlations between diagnostic markers and infiltrating immune cells were analyzed, and CIBERSORT was used to evaluate the infiltration of immune cells in HCC tissues. As a result, we identified a total of 359 DEGs in this study. These DEGs may affect HCC prognosis by regulating fatty acid metabolism, hypoxia, and the P53 pathway. The top 15 genes were selected as the hub genes through PPI network analysis. SRSF1, SNRPA1, and SRSF3 showed strong similarities in biological effects, NCBP2 was demonstrated as a diagnostic marker of HCC, and high NCBP2 expression was significantly correlated with poor over survival (OS) in HCC. In addition, NCBP2 expression was correlated with the infiltration of B cells (r = 0.364, p = 3.30 × 10⁻¹²), CD8⁺ T cells (r = 0.295, p = 2.71 × 10⁻⁸), CD4⁺ T cells, (r = 0.484, p = 1.37 × 10⁻²¹), macrophages (r = 0.551, p = 1.97 × 10⁻²⁸), neutrophils (r = 0.457, p = 3.26 × 10⁻¹⁹), and dendritic cells (r = 0.453, p = 1.97 × 10⁻¹⁸). Immune cell infiltration analysis revealed that the degree of central memory T-cell (Tcm) infiltration may be correlated with the HCC process. In conclusion, NCBP2 can be used as diagnostic markers of HCC, and immune cell infiltration plays an important role in the occurrence and progression of HCC.

Reshaping the systemic tumor immune environment (STIE) and tumor immune microenvironment (TIME) to enhance immunotherapy efficacy in solid tumors

The development of combination immunotherapy based on the mediation of regulatory mechanisms of the tumor immune microenvironment (TIME) is promising. However, a deep understanding of tumor immunology must involve the systemic tumor immune environment (STIE) which was merely illustrated previously. Here, we aim to review recent advances in single-cell transcriptomics and spatial transcriptomics for the studies of STIE, TIME, and their interactions, which may reveal heterogeneity in immunotherapy responses as well as the dynamic changes essential for the treatment effect. We review the evidence from preclinical and clinical studies related to TIME, STIE, and their significance on overall survival, through different immunomodulatory pathways, such as metabolic and neuro-immunological pathways. We also evaluate the significance of the STIE, TIME, and their interactions as well as changes after local radiotherapy and systemic immunotherapy or combined immunotherapy. We focus our review on the evidence of lung cancer, hepatocellular carcinoma, and nasopharyngeal carcinoma, aiming to reshape STIE and TIME to enhance immunotherapy efficacy.

Characteristics of changes in double positive CD4+CD8+ T cells in liver transplantation

Although double positive CD4⁺CD8⁺ T (DPT) cells has been reported to be involved in some diseases, their trajectory and function as associated with liver transplantation (LT) remain unclear. In the present study, we found that the number of DPT cells was increased in the blood and liver tissue of LT patients. Meanwhile, we compared the distribution of DPT cells in peripheral blood samples and in penetrating liver tissue between liver rejection versus non-rejection patients, as well as the proportion of DPT cells as a function of the extent of liver rejection. The number of DPT cells in the rejection group was significantly increased. An analysis of the spatial distance and correlations between DPT and Treg cells, revealed that these cells showed a high degree of contiguity. In a mouse liver transplant model, the number of DPT cells were significantly increased in liver tissue, and the number of CD8⁺ T cells gradually increased, while CD4⁺ T cells decreased as a function of time post-transplantation. Expression level of PD-1 in DPT cells also increased in a temporally-dependent manner post liver transplantation and the changes of PD-1⁺ DPT cells were related to the degree of liver transplant rejection. In DPT cells interacting with Treg, there was an increased expression of PD-1, which enhanced cellular exhaustion. In conclusion, the capacity for DPT cells to induce immune tolerance may represent a new and important protocol for use in targeting treatments for the prevention of liver transplant rejection.

Landscape of Immune Cells Heterogeneity in Liver Transplantation by Single-Cell RNA Sequencing Analysis

Rejection is still a critical barrier to the long-term survival of graft after liver transplantation, requiring clinicians to unveil the underlying mechanism of liver transplant rejection. The cellular diversity and the interplay between immune cells in the liver graft microenvironment remain unclear. Herein, we performed single-cell RNA sequencing analysis to delineate the landscape of immune cells heterogeneity in liver transplantation. T cells, NK cells, B cells, and myeloid cell subsets in human liver and blood were enriched to characterize their tissue distribution, gene expression, and functional modules. The proportion of CCR6+CD4+ T cells increased within an allograft, suggesting that there are more memory CD4+ T cells after transplantation, in parallel with exhausted CTLA4+CD8+ T and actively proliferating MKI67+CD8+ T cells increased significantly, where they manifested heterogeneity, distinct function, and homeostatic proliferation. Remarkably, the changes of CD1c+ DC, CADM+ DC, MDSC, and FOLR3+ Kupffer cells increase significantly, but the proportion of CD163+ Kupffer, APOE+ Kupffer, and GZMA+ Kupffer decreased. Furthermore, we identified LDLR as a novel marker of activated MDSC to prevent liver transplant rejection. Intriguingly, a subset of CD4+CD8+FOXP3+ T cells included in CTLA4+CD8+ T cells was first detected in human liver transplantation. Furthermore, intercellular communication and gene regulatory analysis implicated the LDLR+ MDSC and CTLA4+CD8+ T cells interact through TIGIT-NECTIN2 signaling pathway. Taken together, these findings have gained novel mechanistic insights for understanding the immune landscape in liver transplantation, and it outlines the characteristics of immune cells and provides potential therapeutic targets in liver transplant rejection.

An immunosuppressive scoring system to predict recurrence and assist in decision regarding postoperative adjuvant treatment in gastric cancer

Inhibition of the immune microenvironment is the main cause of tumor recurrence after surgery in patients with gastric cancer (GC). In this study, immunohistochemistry and multiple immunofluorescence staining were used to evaluate immunosuppressive indicators and immune biomarkers in 825 patients with gastric cancer from three centers. We constructed an immunosuppressive recurrence score (IRS) using LASSO Cox regression based on the expression of six immunosuppressive indicators and found that the IRS and IRS-based nomogram were significantly accurate and reliable in predicting recurrence. Moreover, an elevated IRS was associated with locoregional recurrence and postoperative adjuvant chemotherapy failure. Furthermore, an increase in IRS indicated inhibition of the antitumor effect of CD8⁺ tumor-infiltrating lymphocytes in the invasive margin. Thus, we propose that the IRS can predict the recurrence outcome of patients with GC by distinguishing the immunosuppressive status, which is helpful in the selection of individualized adjuvant treatment plans.

Single-Cell Transcriptomics of Liver Cancer: Hype or Insights?

Hepatocellular carcinoma (HCC) is characterized by its high degrees of both inter- and intratumoral heterogeneity. Its complex tumor microenvironment is also crucial in promoting tumor progression. Recent advances in single-cell RNA sequencing provide an important highway to characterize the underlying pathogenesis and heterogeneity of HCC in an unprecedented degree of resolution. This review discusses the up-to-date discoveries from the latest studies of HCC with respect to the strength of single-cell RNA sequencing. We discuss its use in the dissection of the landscape of the intricate HCC ecosystem and highlight the major features at cellular levels, including the malignant cells, different immune cell types, and the various cell-cell interactions, which are crucial for developing effective immunotherapies. Finally, its translational applications will be discussed. Altogether, these explorations may give us some hints at the tumor growth and progression and drug resistance and recurrence, particularly in this era of personalized medicine.