Multi-Omics profiling identifies aldehyde dehydrogenase 2 as a critical mediator in the crosstalk between Treg-mediated immunosuppression microenvironment and hepatocellular carcinoma.

Dysregulation of the aldehyde dehydrogenase (ALDH) family has been implicated in various pathological conditions, including cancer. However, a systematic evaluation of ALDH alterations and their therapeutic relevance in hepatocellular carcinoma (HCC) remains lacking. Herein, we found that 15 of 19 ALDHs were transcriptionally dysregulated in HCC tissues compared to normal liver tissues. A four gene signature, including ALDH2, ALDH5A1, ALDH6A1, and ALDH8A1, robustly predicted prognosis and defined a high-risk subgroup exhibiting immunosuppressive features like regulatory T cell (Tregs) infiltration. Single-cell profiling revealed selective overexpression of tumor necrosis factor receptor superfamily member 18 (TNFRSF18) on Tregs, upregulated in high-risk HCC patients. We identified ALDH2 as a tumor suppressor in HCC, with three novel phosphorylation sites mediated by protein kinase C zeta that enhanced enzymatic activity. Mechanistically, ALDH2 suppressed Tregs differentiation by inhibiting ß-catenin/TGF-ß1 signaling in HCC. Collectively, our integrated multi-omics analysis defines an ALDH-Tregs-TNFRSF18 axis that contributes to HCC pathogenesis and represents potential therapeutic targets for this aggressive malignancy.

Identification of vitamin D-related signature for predicting the clinical outcome and immunotherapy response in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common cancers globally, seriously endangering people health. Vitamin D was significantly associated with tumor progression and patients' prognosis. Integrative 10 machine learning algorithms were used to develop a Vitamin D-related signature (VRS) with one training cohort and 3 testing cohorts. The performance of VRS in predicting the immunology response was verified using several predicting approaches. The optimal VRS was constructed by stepCox + superPC algorithm. VRS acted as a risk factor for HCC patients. HCC patients with high-risk score had a poor clinical outcome and the AUCs of 1-, 3-, and 5-year ROC were 0.786, 0.755, and 0.786, respectively. A higher level of CD8 + cytotoxic T cells and B cells was obtained in HCC patients with low-risk score. There is higher PD1&CTLA4 immunophenoscore and TMB score in low-risk score in HCC patients. Lower TIDE score and tumor escape score was found in HCC cases with low-risk score. The IC50 value of camptothecin, docetaxel, crizotinib, dasatinib, and erlotinib was lower in HCC cases with high-risk score. HCC patients with high-risk score had a higher score of cancer-related hallmarks, including angiogenesis, glycolysis, and NOTCH signaling. Our study proposed a novel VRS for HCC, which served as an indicator for predicting clinical outcome and immunotherapy responses in HCC.

Interleukin-21 receptor signaling promotes metabolic dysfunction-associated steatohepatitis-driven hepatocellular carcinoma by inducing immunosuppressive IgA+ B cells.

BACKGROUND: Dysregulation of immune surveillance is tightly linked to the development of metabolic dysfunction-associated steatohepatitis (MASH)-driven hepatocellular carcinoma (HCC); however, its underlying mechanisms remain unclear. Herein, we aimed to determine the role of interleukin-21 receptor (IL-21R) in MASH-driven HCC. METHODS: The clinical significance of IL-21R was assessed in human HCC specimens using immunohistochemistry staining. Furthermore, the expression of IL-21R in mice was assessed in the STAM model. Thereafter, two different MASH-driven HCC mouse models were applied between IL-21R-deficient mice and wild type controls to explore the role of IL-21R in MASH-driven HCC. To further elucidate the potential mechanisms by which IL-21R affected MASH-driven HCC, whole transcriptome sequencing, flow cytometry and adoptive lymphocyte transfer were performed. Finally, flow cytometry, enzyme-linked immunosorbent assay, immunofluorescent staining, chromatin immunoprecipitation assay and western blotting were conducted to explore the mechanism by which IL-21R induced IgA+ B cells. RESULTS: HCC patients with high IL-21R expression exhibited poor relapse-free survival, advanced TNM stage and severe steatosis. Additionally, IL-21R was demonstrated to be upregulated in mouse liver tumors. Particularly, ablation of IL-21R impeded MASH-driven hepatocarcinogenesis with dramatically reduction of lipid accumulation. Moreover, cytotoxic CD8+ T lymphocyte activation was enhanced in the absence of IL-21R due to the reduction of immunosuppressive IgA+ B cells. Mechanistically, the IL-21R-STAT1-c-Jun/c-Fos regulatory axis was activated in MASH-driven HCC and thus promoted the transcription of Igha, resulting in the induction of IgA+ B cells. CONCLUSIONS: IL-21R plays a cancer-promoting role by inducing IgA+ B cells in MASH-driven hepatocarcinogenesis. Targeting IL-21R signaling represents a potential therapeutic strategy for cancer therapy.

Fluorescence imaging sheds light on the immune evasion mechanisms of hepatic stellate cells mediated by superoxide anion.

Whether and how the reactive oxygen species generated by hepatic stellate cells (HSCs) promote immune evasion of hepatocellular carcinoma (HCC) remains mysterious. Therefore, investigating the function of superoxide anion (O2•-), the firstly generated reactive oxygen species, during the immune evasion become necessary. In this work, we establish a novel in situ imaging method for visualization of O2•- changes in HSCs based on a new two-photon fluorescence probe TPH. TPH comprises recognition group for O2•- and HSCs targeting peptides. We observe that O2•- in HSCs gradually rose, impairing the infiltration of CD8+ T cells in HCC mice. Further studies reveal that the cyclin-dependent kinase 4 is deactivated by O2•-, and then cause the up-regulation of PD-L1. Our work provides molecular insights into HSC-mediated immune evasion of HCC, which may represent potential targets for HCC immunotherapy.

Identification of PANoptosis-related subtypes, construction of a prognosis signature, and tumor microenvironment landscape of hepatocellular carcinoma using bioinformatic analysis and experimental verification.

Background: Hepatocellular carcinoma (HCC) is one of the most lethal malignancies worldwide. PANoptosis is a recently unveiled programmed cell death pathway, Nonetheless, the precise implications of PANoptosis within the context of HCC remain incompletely elucidated. Methods: We conducted a comprehensive bioinformatics analysis to evaluate both the expression and mutation patterns of PANoptosis-related genes (PRGs). We categorized HCC into two clusters and identified differentially expressed PANoptosis-related genes (DEPRGs). Next, a PANoptosis risk model was constructed using LASSO and multivariate Cox regression analyses. The relationship between PRGs, risk genes, the risk model, and the immune microenvironment was studies. In addition, drug sensitivity between high- and low-risk groups was examined. The expression profiles of these four risk genes were elucidate by qRT-PCR or immunohistochemical (IHC). Furthermore, the effect of CTSC knock down on HCC cell behavior was verified using in vitro experiments. Results: We constructed a prognostic signature of four DEPRGs (CTSC, CDCA8, G6PD, and CXCL9). Receiver operating characteristic curve analyses underscored the superior prognostic capacity of this signature in assessing the outcomes of HCC patients. Subsequently, patients were stratified based on their risk scores, which revealed that the low-risk group had better prognosis than those in the high-risk group. High-risk group displayed a lower Stromal Score, Immune Score, ESTIMATE score, and higher cancer stem cell content, tumor mutation burden (TMB) values. Furthermore, a correlation was noted between the risk model and the sensitivity to 56 chemotherapeutic agents, as well as immunotherapy efficacy, in patient with. These findings provide valuable guidance for personalized clinical treatment strategies. The qRT-PCR analysis revealed that upregulated expression of CTSC, CDCA8, and G6PD, whereas downregulated expression of CXCL9 in HCC compared with adjacent tumor tissue and normal liver cell lines. The knockdown of CTSC significantly reduced both HCC cell proliferation and migration. Conclusion: Our study underscores the promise of PANoptosis-based molecular clustering and prognostic signatures in predicting patient survival and discerning the intricacies of the tumor microenvironment within the context of HCC. These insights hold the potential to advance our comprehension of the therapeutic contribution of PANoptosis plays in HCC and pave the way for generating more efficacious treatment strategies.

RRP8, associated with immune infiltration, is a prospective therapeutic target in hepatocellular carcinoma.

BACKGROUND: Ribosomal RNA Processing 8 (RRP8) is a nucleolar Rossman fold-like methyltransferase that exhibits increased expression in many malignant tumours. However, the role of RRP8 in hepatocellular carcinoma (HCC) is still uncertain. We explored the relationships between RRP8 and prognosis and immune infiltration, as well as the putative pathological function and mechanism of RRP8 in HCC. METHODS: Analysis of RRP8 expression across cancers was performed by using multiple databases. Associations between RRP8 expression and clinicopathological factors were further examined. Gene enrichment analysis was used to identify various putative biological activities and regulatory networks of RRP8 in HCC. The relationship between RRP8 expression and immune infiltration was confirmed by single-sample gene set enrichment analysis (ssGSEA). Univariate and multivariate Cox regression analyses were conducted to assess the impact of clinical variables on patient outcomes. Furthermore, a nomogram was constructed to estimate survival probability based on multivariate Cox regression analysis. Functional validation of RRP8 in HCC was performed with two different systems: doxycycline-inducible shRNA knockdown and CRISPR-Cas9 knockout. RESULTS: RRP8 was markedly overexpressed in HCC clinical specimens compared to adjacent normal tissues. Further analysis demonstrated that RRP8 was directly connected to multiple clinical characteristics and strongly associated with various immune markers in HCC. Moreover, elevated RRP8 expression indicated an unfavourable prognosis. Our functional studies revealed that both knockdown and knockout of RRP8 dramatically attenuated liver cancer cells to proliferate and migrate. Knockout of RRP8 decreased the phosphorylation of MEK1/2 and ß-catenin-(Y654) signalling pathway components; downregulated downstream signalling effectors, including Cyclin D1 and N-cadherin; and upregulated E-cadherin. CONCLUSIONS: RRP8 is strongly implicated in immune infiltration and could be a potential therapeutic target in HCC.

Epigenetic silencing of LDHB promotes hepatocellular carcinoma by remodeling the tumor microenvironment.

Lactate dehydrogenase B (LDHB) reversibly catalyzes the conversion of pyruvate to lactate or lactate to pyruvate and expressed in various malignancies. However, the role of LDHB in modulating immune responses against hepatocellular carcinoma (HCC) remains largely unknown. Here, we found that down-regulation of lactate dehydrogenase B (LDHB) was coupled with the promoter hypermethylation and knocking down the DNA methyltransferase 3A (DNMT 3A) restored LDHB expression levels in HCC cell lines. Bioinformatics analysis of the HCC cohort from The Cancer Genome Atlas revealed a significant positive correlation between LDHB expression and immune regulatory signaling pathways and immune cell infiltrations. Moreover, immune checkpoint inhibitors (ICIs) have shown considerable promise for HCC treatment and patients with higher LDHB expression responded better to ICIs. Finally, we found that overexpression of LDHB suppressed HCC growth in immunocompetent but not in immunodeficient mice, suggesting that the host immune system was involved in the LDHB-medicated tumor suppression. Our findings indicate that DNMT3A-mediated epigenetic silencing of LDHB may contribute to HCC progression through remodeling the tumor immune microenvironment, and LDHB may become a potential prognostic biomarker and therapeutic target for HCC immunotherapy.

Comprehensive Analysis of the Immunosuppressive Function of Regulatory T Cells in Human Hepatocellular Carcinoma Tissues.

BACKGROUND: Immune-based therapies are commonly employed to combat hepatocellular carcinoma (HCC). However, the presence of immune-regulating elements, especially regulatory T cells (Tregs), can dramatically impact the treatment efficacy. A deeper examination of the immune-regulation mechanisms linked to these inhibitory factors and their impact on HCC patient outcomes is warranted. METHODS: We employed multicolor fluorescence immunohistochemistry (mIHC) to stain Foxp3, cytokeratin, and nuclei on an HCC tissue microarray (TMA). Leveraging liver cancer transcriptome data from TCGA, we built a prognostic model focused on Treg-associated gene sets and represented it with a nomogram. We then sourced liver cancer single-cell RNA sequencing data (GSE140228) from the GEO database, selectively focusing on Treg subsets, and conducted further analyses, including cell-to-cell communication and pseudo-time trajectory examination. RESULTS: Our mIHC results revealed a more substantial presence of Foxp3+Tregs in HCC samples than in adjacent normal tissue samples (P < .001). An increased presence of Foxp3+Tregs in HCC samples correlated with unfavorable patient outcomes (HR = 1.722, 95% CI:1.023-2.899, P = .041). The multi-factorial prognosis model we built from TCGA liver cancer data highlighted Tregs as a standalone risk determinant for predicting outcomes (HR = 3.84, 95% CI:2.52-5.83, P < .001). Re-analyzing the scRNA-seq dataset (GSE140228) showcased distinctive gene expression patterns in Tregs from varying tissues. Interactions between Tregs and other CD4+T cell types were predominantly governed by the CXCL13/CXCR3 signaling pathway. Communication pathways between Tregs and macrophages primarily involved MIF-CD74/CXCR4, LGALS9/CD45, and PTPRC/MRC1. Additionally, macrophages could influence Tregs via HLA-class II and CD4 interactions. CONCLUSION: An elevated presence of Tregs in HCC samples correlated with negative patient outcomes. Elucidating the interplay between Tregs and other immune cells in HCC could provide insights into the modulatory role of Tregs within HCC tissues.

Predicting effect of anti-PD-1/PD-L1 inhibitors therapy for hepatocellular carcinoma by detecting plasma metabolite based on UHPLC-MS.

Introduction: Anti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. Methods: Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. Results: A partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. Discussion: This study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

The pattern of tumor progression on first-line immune checkpoint inhibitor-based systemic therapy for Chinese advanced hepatocellular carcinoma -CLEAP 004 study.

Background: For decades, stratification criteria for first-line clinical studies have been highly uniform. However, there is no principle or consensus for restratification after systemic treatment progression based on immune checkpoint inhibitors (ICIs). The aim of this study was to assess the patterns of disease progression in patients with advanced hepatocellular carcinoma (HCC) who are not eligible for surgical intervention, following the use of immune checkpoint inhibitors. Methods: This is a retrospective study that involved patients with inoperable China liver stage (CNLC) IIIa and/or IIIb. The patients were treated at eight centers across China between January 2017 and October 2022. All patients received at least two cycles of first-line treatment containing immune checkpoint inhibitors. The patterns of disease progression were assessed using RECIST criteria 1.1. Different progression modes have been identified based on the characteristics of imaging progress. The study's main outcome measures were post-progression survival (PPS) and overall survival (OS). Survival curves were plotted using the Kaplan-Meier method to compare the difference among the four groups. Subgroup analysis was conducted to compare the efficacy of different immunotherapy combinations. Variations in the efficacy of immunotherapy have also been noted across patient groups exhibiting alpha-fetoprotein (AFP) levels equal to or exceeding 400ng/mL, in contrast to those with AFP levels below 400ng/mL. Results: The study has identified four distinct patterns of progress, namely p-IIb, p-IIIa, p-IIIb, and p-IIIc. Diverse patterns of progress demonstrate notable variations in both PPS and OS. The group p-IIb had the longest PPS of 12.7m (95% 9.3-16.1) and OS 19.6m (95% 15.6-23.5), the remaining groups exhibited p-IIIb at PPS 10.5 months (95%CI: 7.9-13.1) and OS 19.2 months (95%CI 15.1-23.3). Similarly, p-IIIc at PPS 5.7 months (95%CI: 4.2-7.2) and OS 11.0 months (95%CI 9.0-12.9), while p-IIIa at PPS 3.4 months (95%CI: 2.7-4.1) and OS 8.2 months (95%CI 6.8-9.5) were also seen. Additional stratified analysis was conducted and showed there were no differences of immunotherapy alone or in combination in OS (HR= 0.92, 95%CI: 0.59-1.43, P=0.68) and PPS (HR= 0.88, 95%CI: 0.57-1.36, P=0.54); there was no significant difference in PPS (HR=0.79, 95% CI: 0.55-1.12, P=0.15) and OS (HR=0.86, 95% CI: 0.61-1.24, P=0.39) for patients with AFP levels at or over 400ng/mL. However, it was observed that patients with AFP levels above 400ng/mL experienced a shorter median progression of PPS (8.0 months vs. 5.0 months) after undergoing immunotherapy. Conclusion: In this investigation of advanced hepatocellular carcinoma among Chinese patients treated with immune checkpoint inhibitors, we identified four distinct progression patterns (p-IIb, p-IIIa, p-IIIb and p-IIIc) that showed significant differences in PPS and OS. These findings demonstrate the heterogeneity of disease progression and prognosis after immunotherapy failure. Further validation in large cohorts is necessary to develop prognostic models that integrate distinct progression patterns to guide subsequent treatment decisions. Additionally, post-immunotherapy progression in patients with AFP levels ≥400ng/mL indicates a shortened median PPS. These findings provide valuable insights for future personalized treatment decisions.

Predictive value of a stemness-based classifier for prognosis and immunotherapy response of hepatocellular carcinoma based on bioinformatics and machine-learning strategies.

Objective: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therapy, which continues to be challenging. Cancer stem cells (CSCs) are involved in the oncogenesis, drug resistance, and invasion, as well as metastasis of HCC cells. Therefore, in this study, we aimed to create an mRNA expression-based stemness index (mRNAsi) model to predict the response of patients with HCC to immunotherapy. Methods: We retrieved gene expression and clinical data of patients with HCC from the GSE14520 dataset and the Cancer Genome Atlas (TCGA) database. Next, we used the "one-class logistic regression (OCLR)" algorithm to obtain the mRNAsi of patients with HCC. We performed "unsupervised consensus clustering" to classify patients with HCC based on the mRNAsi scores and stemness subtypes. The relationships between the mRNAsi model, clinicopathological features, and genetic profiles of patients were compared using various bioinformatic methods. We screened for differentially expressed genes to establish a stemness-based classifier for predicting the patient's prognosis. Next, we determined the effect of risk scores on the tumor immune microenvironment (TIME) and the response of patients to immune checkpoint blockade (ICB). Finally, we used qRT-PCR to investigate gene expression in patients with HCC. Results: We screened CSC-related genes using various bioinformatics tools in patients from the TCGA-LIHC cohort. We constructed a stemness classifier based on a nine-gene (PPARGC1A, FTCD, CFHR3, MAGEA6, CXCL8, CABYR, EPO, HMMR, and UCK2) signature for predicting the patient's prognosis and response to ICBs. Further, the model was validated in an independent GSE14520 dataset and performed well. Our model could predict the status of TIME, immunogenomic expressions, congenic pathway, and response to chemotherapy drugs. Furthermore, a significant increase in the proportion of infiltrating macrophages, Treg cells, and immune checkpoints was observed in patients in the high-risk group. In addition, tumor cells in patients with high mRNAsi scores could escape immune surveillance. Finally, we observed that the constructed model had a good expression in the clinical samples. The HCC tumor size and UCK2 genes expression were significantly alleviated and decreased, respectively, by treatments of anti-PD1 antibody. We also found knockdown UCK2 changed expressions of immune genes in HCC cell lines. Conclusion: The novel stemness-related model could predict the prognosis of patients and aid in creating personalized immuno- and targeted therapy for patients in HCC.

DNA methylation regulator-based molecular subtyping and tumor microenvironment characterization in hepatocellular carcinoma.

Backgroud: Although recent studies have reported the regulation of the immune response in hepatocellular carcinoma (HCC) through DNA methylation, the comprehensive impact methylation modifications on tumor microenvironment characteristics and immunotherapy efficacy has not been fully elucidated. Methods: In this research, we conducted a comprehensive assessment of the patterns of DNA methylation regulators and the profiles of the tumor microenvironment (TME) in HCC, focusing on 21 specific DNA methylation regulators. We subsequently developed a unique scoring system, a DNA methylation score (DMscore), to assess the individual DNA methylation modifications among the three distinct methylation patterns for differentially expressed genes (DEGs). Results: Three distinct methylation modification patterns were identified with distinct TME infiltration characteristics. We demonstrated that the DMscore could predict patient subtype, TME infiltration, and patient prognosis. A low DMscore, characterized by an elevated tumor mutation burden (TMB), hepatitis B virus (HBV)/hepatitis C virus (HCV) infection, and immune activation, indicates an inflamed tumor microenvironment phenotype with a 5-year survival rate of 7.8%. Moreover, a low DMscore appeared to increase the efficacy of immunotherapy in the anti-CTLA-4/PD-1/PD-L1 cohort. Conclusions: In brief, this research has enhanced our understanding of the correlation between modifications in DNA methylation patterns and the profile of the tumor microenvironment in individuals diagnosed with HCC. The DMscore may serve as an alternative biomarker for survival and efficacy of immunotherapy in patients with HCC.

Comprehensive study of the interplay between immunological and metabolic factors in hepatic steatosis.

The pathophysiology of hepatic steatosis is thoroughly reviewed in this comprehensive report, with particular attention to the complex interactions between inflammatory pathways, insulin resistance, lipid metabolism, metabolic dysregulation, and immunological responses in the liver including non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), and hepatocellular carcinoma (HCC). The study highlights the role of immune cell regulation in disease progression and explores the potential of immune cell-specific treatments for treating hepatic disorders. The development of liver disorders is significantly influenced by immune cells, including dendritic cells, T cells, and natural killer cells. Clinical investigations show that immune cell-specific treatments can effectively reduce liver fibrosis and inflammation. Future research should focus on finding new immunological targets for therapeutic interventions, as well as addressing the management challenges associated with NAFLD/NASH. Hepatic immune microorganisms also impact liver homeostasis and disorders. Improvements in immune cell regulation and liver transplantation methods give patients hope for better prognoses. Important phases include optimizing the selection of donors for malignancy of the liver, using machine perfusion for organ preservation, and fine-tuning immunosuppressive strategies. For focused treatments in hepatic steatosis, it is imperative to understand the intricate interactions between immune and metabolic variables. Understanding the liver's heterogeneous immune profile, encompassing a range of immune cell subpopulations, is crucial for formulating focused therapeutic interventions. To improve patient care and outcomes in hepatic illnesses, there is an urgent need for further research and innovation. Therefore, to effectively treat hepatic steatosis, it is important to enhance therapeutic techniques and maximize liver transplantation strategies.

Association between ascites Gustave Roussy immune score and the intratumoural microbiome in malignant ascites secondary to hepatocellular carcinoma.

BACKGROUNDS: The Gustave Roussy Immune (GRIm) score predicts survival outcomes in several cancers. However, the prognostic significance of the GRIm score in patients with malignant ascites has not yet been investigated. METHODS: Clinical samples were collected from a cohort of patients with malignant ascites secondary to hepatocellular carcinoma (HCC). We calculated serum GRIm (sGRIm) and ascites GRIm (aGRIm) scores and divided the samples into low and high GRIm score groups. Survival analysis was used to compare the prognostic significance of the sGRIm and aGRIm scores. 16S rRNA sequencing was performed to determine the profiles of the intratumoral microbiota in the groups. A fluorescent multiplex immunohistochemistry (mIHC) assay was used to detect the expression of different immune cells by labeling seven markers of malignant ascites. RESULTS: 155 patients with HCC and malignant ascites were enrolled in this study. Survival analysis revealed that the aGRIm score showed a superior prognostic significance compared to the sGRIm score. Microbial analysis demonstrated that the bacterial richness and diversity were higher in the low aGRIm score group than in the high aGRIm score group. LefSe analysis revealed that certain bacteria were correlated with high aGRIm scores. Fluorescent mIHC displayed the tumor microenvironment of malignant ascites and found that the density of CD8 + T cells was significantly higher in the low aGRIm score group than in the high aGRIm score group. CONCLUSIONS: Our present study identified a novel scoring system (aGRIm score) that can predict the survival outcome of patients with malignant ascites secondary to HCC.

Prognostic impact of CD68+ tumor-associated macrophages in hepatocellular carcinoma: A meta-analysis.

BACKGROUND: Evidence from clinical research suggests that the tumor-associated macrophages (TAMs) were associated with prognosis in hepatocellular carcinoma (HCC). The aim of the present meta-analysis was to conduct a qualitative analysis to explore the prognostic value of CD68 + TAMs in HCC. METHODS: This study conducted a systematic search in Pubmed, Embase, the Cochrane Library and China National Knowledge Internet from inception of the databases to November 2023. The hazard ratio (HR) and 95% confidence interval (CI) were calculated employing fixed-effect or random-effect models depending on the heterogeneity of the included trials. The Newcastle-Ottawa Scale was used to evaluate the risk of prejudice. RESULTS: We analyzed 4362 HCC patients. The present research indicated that the expression levels Of CD68 + TAMs were significantly associated with overall survival (OS) (HR = 1.55, 95% CI: 1.30-1.84) and disease-free survival (DFS) (HR = 1.44, 95% CI: 1.17-1.78). Subgroup analysis based on cutoff values showed that the "Median" subgroup showed a pooled HR of 1.66 with a 95% CI ranging from 1.32 to 2.08, which was slightly higher than the "Others" subgroup that exhibited a pooled HR of 1.40 and a 95% CI of 1.07 to 1.84. The "PT" subgroup had the highest pooled HR of 1.68 (95% CI: 1.19-2.37), indicating a worse OS compared to the "IT" (pooled HR: 1.50, 95% CI: 1.13-2.01) and "Mix" (pooled HR: 1.52, 95% CI: 1.03-2.26) subgroups. Moreover, in the sample size-based analysis, studies with more than 100 samples (>100) exhibited a higher pooled HR of 1.57 (95% CI: 1.28 to 1.93) compared to studies with fewer than 100 samples (<100), which had a pooled HR of 1.45 (95% CI: 1.00-2.10). CONCLUSIONS: The analysis suggests that CD68 + TAMs were significantly associated with unfavorable OS and DFS in HCC patients, and may be served as a promising prognostic biomarker in HCC. However, more large-scale trials are needed to study the clinical value of TAMs in HCC.

Single-cell data revealed exhaustion of characteristic NK cell subpopulations and T cell subpopulations in hepatocellular carcinoma.

BACKGROUND: The treatment and prognosis of patients with advanced hepatocellular carcinoma (HCC) have been a major medical challenge. Unraveling the landscape of tumor immune infiltrating cells (TIICs) in the immune microenvironment of HCC is of great significance to probe the molecular mechanisms. METHODS: Based on single-cell data of HCC, the cell landscape was revealed from the perspective of TIICs. Special cell subpopulations were determined by the expression levels of marker genes. Differential expression analysis was conducted. The activity of each subpopulation was determined based on the highly expressed genes. CTLA4+ T-cell subpopulations affecting the prognosis of HCC were determined based on survival analysis. A single-cell regulatory network inference and clustering analysis was also performed to determine the transcription factor regulatory networks in the CTLA4+ T cell subpopulations. RESULTS: 10 cell types were identified and NK cells and T cells showed high abundance in tumor tissues. Two NK cells subpopulations were present, FGFBP2+ NK cells, B3GNT7+ NK cells. Four T cells subpopulations were present, LAG3+ T cells, CTLA4+ T cells, RCAN3+ T cells, and HPGDS+ Th2 cells. FGFBP2+ NK cells, and CTLA4+ T cells were the exhaustive subpopulation. High CTLA4+ T cells contributed to poor prognostic outcomes and promoted tumor progression. Finally, a network of transcription factors regulated by NR3C1, STAT1, and STAT3, which were activated, was present in CTLA4+ T cells. CONCLUSION: CTLA4+ T cell subsets in HCC exhibited functional exhaustion characteristics that probably inhibited T cell function through a transcription factor network dominated by NR3C1, STAT1, and STAT3.

The predictive value of next generation sequencing for matching advanced hepatocellular carcinoma patients to targeted and immunotherapy.

Background: Targeted and Immunotherapy has emerged as a new first-line treatment for advanced hepatocellular carcinoma (aHCC). To identify the appropriate targeted and immunotherapy, we implemented next generation sequencing (NGS) to provide predictive and prognostic values for aHCC patients. Methods: Pretreatment samples from 127 HCC patients were examined for genomic changes using 680-gene NGS, and PD-L1 expression was detected by immunohistochemistry. Demographic and treatment data were included for analyses of links among treatment outcomes, drug responses, and genetic profiles. A prognostic index model for predicting benefit from treatment was constructed, taking into account of biomarkers, including TP53, TERT, PD-L1, and tumor mutation burden (TMB) as possible independent prognostic factors. Results: The multivariate Cox regression analyses showed that PD-L1≥1% (HR 25.07, 95%CI 1.56 - 403.29, p=0.023), TMB≥5Mb (HR 86.67, 95% CI 4.00 - 1876.48, p=0.004), TERT MU (HR 84.09, 95% CI 5.23 - 1352.70, p=0.002) and TP53 WT (HR 0.01, 95%CI 0.00 - 0.47, p=0.022) were independent risk factors for overall survival (OS), even after adjusting for various confounders. A prognostic nomogram for OS was developed, with an area under the ROC curve of 0.91, 0.85, and 0.98 at 1-, 2-, and 3- year, respectively, and a prognostic index cutoff of 1.2. According to the cutoff value, the patients were divided into the high-risk group (n=29) and low-risk group (n=98). The benefit of targeted and immunotherapy in the low-risk group was not distinguishable according to types of agents. However, treatment of Atezolizumab and Bevacizumab appeared to provide longer OS in the high-risk group (12 months vs 9.2, 9, or 5 months for other treatments, p<0.001). Conclusion: The prognostic model constructed by PD-L1, TMB, TERT, and TP53 can identify aHCC patients who would benefit from targeted and immunotherapy, providing insights for the personalized treatment of HCC.

Prognostic value of CD8+T cells related genes and exhaustion regulation of Notch signaling pathway in hepatocellular carcinoma.

Immunotherapy has emerged as the primary treatment modality for patients with advanced Hepatocellular carcinoma (HCC). However, its clinical efficacy remains limited, benefiting only a subset of patients, while most exhibit immune tolerance and face a grim prognosis. The infiltration of immune cells plays a pivotal role in tumor initiation and progression. In this study, we conducted an analysis of immune cell infiltration patterns in HCC patients and observed a substantial proportion of CD8+T cells. Leveraging the weighted gene co-expression network analysis (WGCNA), we identified 235 genes associated with CD8+T cell and constructed a risk prediction model. In this model, HCC patients were stratified into a high-risk and low-risk group. Patients in the high-risk group exhibited a lower survival rate, predominantly presented with intermediate to advanced stages of cancer, displayed compromised immune function, showed limited responsiveness to immunotherapy, and demonstrated elevated expression levels of the Notch signaling pathway. Further examination of clinical samples demonstrated an upregulation of the Notch1+CD8+T cell exhaustion phenotype accompanied by impaired cytotoxicity and cytokine secretion functions that worsened with increasing Notch activation levels. Our study not only presents a prognostic model but also highlights the crucial involvement of the Notch pathway in CD8+T cell exhaustion-a potential target for future immunotherapeutic interventions.

Immunotherapy and drug sensitivity predictive roles of a novel prognostic model in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most significant causes of cancer-related deaths in the worldwide. Currently, predicting the survival of patients with HCC and developing treatment drugs still remain a significant challenge. In this study, we employed prognosis-related genes to develop and externally validate a predictive risk model. Furthermore, the correlation between signaling pathways, immune cell infiltration, immunotherapy response, drug sensitivity, and risk score was investigated using different algorithm platforms in HCC. Our results showed that 11 differentially expressed genes including UBE2C, PTTG1, TOP2A, SPP1, FCN3, SLC22A1, ADH4, CYP2C8, SLC10A1, F9, and FBP1 were identified as being related to prognosis, which were integrated to construct a prediction model. Our model could accurately predict patients' overall survival using both internal and external datasets. Moreover, a strong correlation was revealed between the signaling pathway, immune cell infiltration, immunotherapy response, and risk score. Importantly, a novel potential drug candidate for HCC treatment was discovered based on the risk score and also validated through ex vivo experiments. Our finds offer a novel perspective on prognosis prediction and drug exploration for cancer patients.

Mast Cells in the Microenvironment of Hepatocellular Carcinoma Confer Favorable Prognosis: A Retrospective Study using QuPath Image Analysis Software.

The insights provided by in-situ detection of immune cells within hepatocellular carcinoma (HCC) might present information on patient outcomes. Studies investigating the expression and localization of immune cells within tumor tissues are associated with several challenges, including a lack of precise annotation for tumor regions and random selection of microscopic fields of view. QuPath is an open-source, user-friendly software that could meet the growing need for digital pathology in whole-slide image (WSI) analysis. The infiltration of HCC and adjacent tissues by CD1a+ immature dendritic cells (iDCs), CD117+ mast cells, and NKp46+ natural killer cells (NKs) cells was assessed immunohistochemically in representative specimens of 67 patients with HCC who underwent curative resection. The area fraction (AF) of positively stained cells was assessed automatically in WSIs using QuPath in the tumor center (TC), inner margin (IM), outer margin (OM), and peritumor (PT) area. The prognostic significance of immune cells was evaluated for time to recurrence (TTR), disease-free survival (DFS), and overall survival (OS). The AF of mast cells was significantly greater than the AF of NKs, and the AF of iDCs was significantly lower compared to NKs in each region of interest. High AFs of mast cells in the IM and PT areas were associated with longer DFS. In addition, high AF of mast cells in IM was associated with longer OS. Computer-assisted analysis using this software is a suitable tool for obtaining prognostic information for tumor-infiltrating immune cells (iDCs, mast cells, and NKs) in different regions of HCC after resection. Mast cells displayed the greatest AF in all regions of interest (ROIs). Mast cells in the peritumor region and IM showed a positive prognostic significance.