Landscape of immune microenvironment in hepatocellular carcinoma and its additional impact on histological and molecular classification

The association between tumour heterogeneity and immune evasion mechanisms in hepatocellular carcinoma and its clinical implications

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related mortality worldwide. The emergence of combination therapy, atezolizumab (anti-PDL1, immune checkpoint inhibitor) and bevacizumab (anti-VEGF) has revolutionised the management of HCC. Despite this breakthrough, the best overall response rate with first-line systemic therapy is only about 30%, owing to intra-tumoural heterogeneity, complex tumour microenvironment and the lack of predictive biomarkers. Many groups have attempted to classify HCC based on the immune microenvironment and have consistently observed better outcomes in immunologically "hot" HCC. We summarised possible mechanisms of tumour immune evasion based on the latest literature and the rationale for combination/sequential therapy to improve treatment response. Lastly, we proposed future strategies and therapies to overcome HCC immune evasion to further improve treatment outcomes of HCC.

Plexin domain-containing 1 may be a biomarker of poor prognosis in hepatocellular carcinoma patients, may mediate immune evasion

BACKGROUND

For the first time, we investigated the oncological role of plexin domain-containing 1 (PLXDC1), also known as tumor endothelial marker 7 (TEM7), in hepatocellular carcinoma (HCC).

AIM

To investigate the oncological profile of PLXDC1 in HCC.

METHODS

Based on The Cancer Genome Atlas database, we analyzed the expression of PLXDC1 in HCC. Using immunohistochemistry, quantitative real-time polymerase chain reaction (qRT-PCR), and Western blotting, we validated our results. The prognostic value of PLXDC1 in HCC was analyzed by assessing its correlation with clinicopathological features, such as patient survival, methylation level, tumor immune microenvironment features, and immune cell surface checkpoint expression. Finally, to assess the immune evasion potential of PLXDC1 in HCC, we used the tumor immune dysfunction and exclusion (TIDE) website and immunohistochemical staining assays.

RESULTS

Based on immunohistochemistry, qRT-PCR, and Western blot assays, overexpression of PLXDC1 in HCC was associated with poor prognosis. Univariate and multivariate Cox analyses indicated that PLXDC1 might be an independent prognostic factor. In HCC patients with high methylation levels, the prognosis was worse than in patients with low methylation levels. Pathway enrichment analysis of HCC tissues indicated that genes upregulated in the high-PLXDC1 subgroup were enriched in mesenchymal and immune activation signaling, and TIDE assessment showed that the risk of immune evasion was significantly higher in the high-PLXDC1 subgroup compared to the low-PLXDC1 subgroup. The high-risk group had a significantly lower immune evasion rate as well as a poor prognosis, and PLXDC1-related risk scores were also associated with a poor prognosis.

CONCLUSION

As a result of this study analyzing PLXDC1 from multiple biological perspectives, it was revealed that it is a biomarker of poor prognosis for HCC patients, and that it plays a role in determining immune evasion status.

The comprehensive roles of lncRNA FAM99A/FAM99B in hepatocellular carcinoma: Expressions, regulatory mechanisms and functional pathway analysis

AIMS

The incidence and mortality of liver hepatocellular carcinoma (LIHC) were increasing year by year. The aim of this study was to investigate the comprehensive roles of lncRNA FAM99A and FAM99B in LIHC.

MAIN METHODS

According to the data of TCGA and GTEx, the expression levels of FAM99A and FAM99B in LIHC were evaluated, and the overall survival (OS), disease-free survival (DFS), immune cell infiltration and tumor stage were analyzed. The subcellular localization of FAM99A and FAM99B in various cancer cell lines was predicted by lncATLAS database. In addition, we also used ENCORI, KEGG, LinkedOmics, Metascape and other databases. It was verified by in vivo and in vitro experiments.

KEY FINDINGS

Compared with adjacent normal tissues, FAM99A and FAM99B were down-regulated in LIHC tissues, and significantly correlated with immune cell infiltration. With the progression of tumor stage and grade, the expression of FAM99A and FAM99B showed a decreasing trend, and the prognosis of patients were also poor. In addition, the biological functions, signaling pathways and protein interactions of FAM99A and FAM99B in LIHC were enriched to study the potential molecular mechanisms. The overlapping RNA binding proteins (RBP) of FAM99A and FAM99B mainly included CSTF2T, BCCIP, RBFOX2 and SF3B4. Finally, experiments showed that overexpression of FAM99A attenuated the proliferation, invasion, colony formation and tumor growth of LIHC cells.

SIGNIFICANCE

Taken together, the above studies demonstrated that FAM99A and FAM99B had an inhibitory effect on the progression of LIHC, which might be promising diagnostic biomarkers and therapeutic targets for LIHC patients.

Applying image features of proximal paracancerous tissues in predicting prognosis of patients with hepatocellular carcinoma

BACKGROUND

Most of the methods using digital pathological image for predicting Hepatocellular carcinoma (HCC) prognosis have not considered paracancerous tissue microenvironment (PTME), which are potentially important for tumour initiation and metastasis. This study aimed to identify roles of image features of PTME in predicting prognosis and tumour recurrence of HCC patients.

METHODS

We collected whole slide images (WSIs) of 146 HCC patients from Sun Yat-sen Memorial Hospital (SYSM dataset). For each WSI, five types of regions of interests (ROIs) in PTME and tumours were manually annotated. These ROIs were used to construct a Lasso Cox survival model for predicting the prognosis of HCC patients. To make the model broadly useful, we established a deep learning method to automatically segment WSIs, and further used it to construct a prognosis prediction model. This model was tested by the samples of 225 HCC patients from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC).

RESULTS

In predicting prognosis of the HCC patients, using the image features of manually annotated ROIs in PTME achieved C-index 0.668 in the SYSM testing dataset, which is higher than the C-index 0.648 reached by the model only using image features of tumours. Integrating ROIs of PTME and tumours achieved C-index 0.693 in the SYSM testing dataset. The model using automatically segmented ROIs of PTME and tumours achieved C-index of 0.665 (95% CI: 0.556-0.774) in the TCGA-LIHC samples, which is better than the widely used methods, WSISA (0.567), DeepGraphSurv (0.593), and SeTranSurv (0.642). Finally, we found the Texture SumAverage Skew HV on immune cell infiltration and Texture related features on desmoplastic reaction are the most important features of PTME in predicting HCC prognosis. We additionally used the model in prediction HCC recurrence for patients from SYSM-training, SYSM-testing, and TCGA-LIHC datasets, indicating the important roles of PTME in the prediction.

CONCLUSIONS

Our results indicate image features of PTME is critical for improving the prognosis prediction of HCC. Moreover, the image features related with immune cell infiltration and desmoplastic reaction of PTME are the most important factors associated with prognosis of HCC.

Immunosuppressive tumor microenvironment and immunotherapy of hepatocellular carcinoma: current status and prospectives

Hepatocellular carcinoma (HCC) is a major health concern worldwide, with limited therapeutic options and poor prognosis. In recent years, immunotherapies such as immune checkpoint inhibitors (ICIs) have made great progress in the systemic treatment of HCC. The combination treatments based on ICIs have been the major trend in this area. Recently, dual immune checkpoint blockade with durvalumab plus tremelimumab has also emerged as an effective treatment for advanced HCC. However, the majority of HCC patients obtain limited benefits. Understanding the immunological rationale and exploring novel ways to improve the efficacy of immunotherapy has drawn much attention. In this review, we summarize the latest progress in this area, the ongoing clinical trials of immune-based combination therapies, as well as novel immunotherapy strategies such as chimeric antigen receptor T cells, personalized neoantigen vaccines, oncolytic viruses, and bispecific antibodies.

Treatment Options for Hepatocellular Carcinoma Using Immunotherapy: Present and Future

Hepatocellular carcinoma (HCC) is a common cancer, and the body's immune responses greatly affect its progression and the prognosis of patients. Immunological suppression and the maintenance of self-tolerance in the tumor microenvironment are essential responses, and these form part of the theoretical foundations of immunotherapy. In this review, we first discuss the tumor microenvironment of HCC, describe immunosuppression in HCC, and review the major biomarkers used to track HCC progression and response to treatment. We then examine antibody-based therapies, with a focus on immune checkpoint inhibitors (ICIs), monoclonal antibodies that target key proteins in the immune response (programmed cell death protein 1, anti-cytotoxic T-lymphocyte associated protein 4, and programmed death-ligand 1) which have transformed the treatment of HCC and other cancers. ICIs may be used alone or in conjunction with various targeted therapies for patients with advanced HCC who are receiving first-line treatments or subsequent treatments. We also discuss the use of different cellular immunotherapies, including T cell receptor (TCR) T cell therapy and chimeric antigen receptor (CAR) T cell therapy. We then review the use of HCC vaccines, adjuvant immunotherapy, and oncolytic virotherapy, and describe the goals of future research in the development of treatments for HCC.

Based on the prognosis model of immunogenes, the prognosis model was constructed to predict the invasion of immune genes and immune cells related to primary liver cancer and its experimental validation

Background

Primary liver cancer (PLC) is a prevalent malignancy of the digestive system characterized by insidious symptom onset and a generally poor prognosis. Recent studies have highlighted a significant correlation between the initiation and prognosis of liver cancer and the immune function of PLC patients.

Purpose

Revealing the expression of PLC-related immune genes and the characteristics of immune cell infiltration provides assistance for the analysis of clinical pathological parameters and prognosis of PLC patients.

Methods

PLC-related differentially expressed genes (DEGs) with a median absolute deviation (MAD > 0.5) were identified from TCGA and GEO databases. These DEGs were intersected with immune-related genes (IRGs) from the ImmPort database to obtain PLC-related IRGs. The method of constructing a prognostic model through immune-related gene pairs (IRGPs) is used to obtain IRGPs and conduct the selection of central immune genes. The central immune genes obtained from the selection of IRGPs are validated in PLC. Subsequently, the relative proportions of 22 types of immune cells in different immune risk groups are evaluated, and the differential characteristics of PLC-related immune cells are verified through animal experiments.

Results

Through database screening and the construction of an IRGP prognosis model, 84 pairs of IRGPs (P < 0.001) were ultimately obtained. Analysis of these 84 IRGPs revealed 11 central immune genes related to PLC, showing differential expression in liver cancer tissues compared to normal liver tissues. Results from the CiberSort platform indicate differential expression of immune cells such as naive B cells, macrophages, and neutrophils in different immune risk groups. Animal experiments demonstrated altered immune cell proportions in H22 tumor-bearing mice, validating findings from peripheral blood and spleen homogenate analyses.

Conclusion

Our study successfully predicted and validated PLC-related IRGs and immune cells, suggesting their potential as prognostic indicators and therapeutic targets for PLC.

Cancer stem cell-immune cell crosstalk in the tumor microenvironment for liver cancer progression

Crosstalk between cancer cells and the immune microenvironment is determinant for liver cancer progression. A tumor subpopulation called liver cancer stem cells (CSCs) significantly accounts for the initiation, metastasis, therapeutic resistance, and recurrence of liver cancer. Emerging evidence demonstrates that the interaction between liver CSCs and immune cells plays a crucial role in shaping an immunosuppressive microenvironment and determining immunotherapy responses. This review sheds light on the bidirectional crosstalk between liver CSCs and immune cells for liver cancer progression, as well as the underlying molecular mechanisms after presenting an overview of liver CSCs characteristic and their microenvironment. Finally, we discuss the potential application of liver CSCs-targeted immunotherapy for liver cancer treatment.

A prognostic signature established based on genes related to tumor microenvironment for patients with hepatocellular carcinoma

BACKGROUND

Complex cellular signaling network in the tumor microenvironment (TME) could serve as an indicator for the prognostic classification of hepatocellular carcinoma (HCC) patients.

METHODS

Univariate Cox regression analysis was performed to screen prognosis-related TME-related genes (TRGs), based on which HCC samples were clustered by running non-negative matrix factorization (NMF) algorithm. Furthermore, the correlation between different molecular HCC subtypes and immune cell infiltration level was analyzed. Finally, a risk score (RS) model was established by LASSO and Cox regression analyses (CRA) using these TRGs. Functional enrichment analysis was performed using gene set enrichment analysis (GSEA).

RESULTS

HCC patients were divided into three molecular subtypes (C1, C2, and C3) based on 704 prognosis-related TRGs. HCC subtype C1 had significantly better OS than C2 and C3. We selected 13 TRGs to construct the RS model. Univariate and multivariate CRA showed that the RS could independently predict patients' prognosis. A nomogram integrating the RS and clinicopathologic features of the patients was further created. We also validated the reliability of the model according to the area under the receiver operating characteristic (ROC) curve value, concordance index (C-index), and decision curve analysis. The current findings demonstrated that the RS was significantly correlated with CD8+ T cells, monocytic lineage, and myeloid dendritic cells.

CONCLUSION

This study provided TRGs to help classify patients with HCC and predict their prognoses, contributing to personalized treatments for patients with HCC.

Potential involvement of oncostatin M in the immunosuppressive tumor immune microenvironment in hepatocellular carcinoma with vessels encapsulating tumor clusters

AIM

Vessels encapsulating tumor clusters (VETC) represents an adverse prognostic morphological feature of hepatocellular carcinoma (HCC), which is associated with an immunosuppressive tumor immune microenvironment (TIM). However, the underlying factors characterizing the TIM in HCC with a VETC pattern (VETC-positive HCC) remain uncertain. Oncostatin M (OSM), a pleiotropic cytokine of the interleukin-6 family, regulates various biological processes, including inflammation, proliferation, and invasiveness of tumor cells. We aimed to test a hypothesis that OSM is associated with the immunosuppressive TIM of VETC-positive HCC.

METHODS

A total of 397 consecutive HCC patients with curative-intent hepatectomy were included. OSM-positive cells and inflammatory cells including CD4-, CD8-, CD163-, and FOXP3-positive cells were immunohistochemically evaluated. We compared VETC-positive and VETC-negative HCCs in terms of the number of these cells.

RESULTS

We found the VETC pattern in 62 patients (15.6%). Our analysis revealed a significant decrease in the expression of arginase-1, a marker associated with mature hepatocyte differentiation, in VETC-positive HCC (p = 0.046). The number of tumor-infiltrating OSM-positive cells was significantly low in VETC-positive HCC (p = 0.0057). Notably, in VETC-positive HCC, the number of OSM-positive cells was not associated with vascular invasion, whereas in VETC-negative HCC, an increase in the number of OSM-positive cells was associated with vascular invasion (p = 0.042).

CONCLUSIONS

We identified an association between a decrease in OSM-positive cells and the VETC pattern. Additionally, our findings indicate that VETC-positive HCC is characterized by low hepatocyte differentiation and OSM-independent vascular invasion. These findings highlight the potential interaction between VETC-positive HCC cells and their TIM through the reduction of OSM-expressing cells.

Identification of Two Distinct Immune Subtypes in Hepatitis B Virus (HBV)-Associated Hepatocellular Carcinoma (HCC)

HBV is the most common risk factor for HCC development, accounting for almost 50% of cases worldwide. Despite significant advances in immunotherapy, there is limited information on the HBV-HCC tumor microenvironment (TME), which may influence the response to checkpoint inhibitors. Here, we characterize the TME in a unique series of liver specimens from HBV-HCC patients to identify who might benefit from immunotherapy. By combining an extensive immunohistochemistry analysis with the transcriptomic profile of paired liver samples (tumor vs. nontumorous tissue) from 12 well-characterized Caucasian patients with HBV-HCC, we identified two distinct tumor subtypes that we defined immune-high and immune-low. The immune-high subtype, seen in half of the patients, is characterized by a high number of infiltrating B and T cells in association with stromal activation and a transcriptomic profile featuring inhibition of antigen presentation and CTL activation. All the immune-high tumors expressed high levels of CTLA-4 and low levels of PD-1, while PD-L1 was present only in four of six cases. In contrast, the immune-low subtype shows significantly lower lymphocyte infiltration and stromal activation. By whole exome sequencing, we documented that four out of six individuals with the immune-low subtype had missense mutations in the CTNNB1 gene, while only one patient had mutations in this gene in the immune-high subtype. Outside the tumor, there were no differences between the two subtypes. This study identifies two distinctive immune subtypes in HBV-associated HCC, regardless of the microenvironment observed in the surrounding nontumorous tissue, providing new insights into pathogenesis. These findings may be instrumental in the identification of patients who might benefit from immunotherapy.

Comprehensive assessment of regulatory T-cells-related scoring system for predicting the prognosis, immune microenvironment and therapeutic response in hepatocellular carcinoma

INTRODUCTION

Regulatory T cells (Tregs) play important roles in tumor immunosuppression and immune escape. The aim of the present study was to construct a novel Tregs-associated biomarker for the prediction of tumour immune microenvironment (TIME), clinical outcomes, and individualised treatment in hepatocellular carcinoma (HCC).

METHODS

Single-cell sequencing data were obtained from the three independent cohorts. Cox and LASSO regression were utilised to develop the Tregs Related Scoring System (TRSSys). GSE140520, ICGC-LIRI and CHCC cohorts were used for the validation of TRSSys. Kaplan-Meier, ROC, and Cox regression were utilised for the evaluation of TRSSys. The ESTIMATE, TIMER 2.0, and ssGSEA algorithm were utilised to determine the value of TRSSys in predicting the TIME. GSVA, GO, KEGG, and TMB analyses were used for mechanistic exploration. Finally, the value of TRSSys in predicting drug sensitivity was evaluated based on the oncoPredict algorithm.

RESULTS

Comprehensive validation showed that TRSSys had good prognostic predictive efficacy and applicability. Additionally, ssGSEA, TIMER and ESTIMATE algorithm suggested that TRSSys could help to distinguish different TIME subtypes and determine the beneficiary population of immunotherapy. Finally, the oncoPredict algorithm suggests that TRSSys provides a basis for individualised treatment.

CONCLUSIONS

TRSSys constructed in the current study is a novel HCC prognostic prediction biomarker with good predictive efficacy and stability. Additionally, risk stratification based on TRSSys can help to identify the TIME landscape subtypes and provide a basis for individualized treatment options.

Battle of the biopsies: Role of tissue and liquid biopsy in hepatocellular carcinoma

The diagnosis and management of hepatocellular carcinoma (HCC) have improved significantly in recent years. With the introduction of immunotherapy-based combination therapy, there has been a notable expansion in treatment options for patients with unresectable HCC. Simultaneously, innovative molecular tests for early detection and management of HCC are emerging. This progress prompts a key question: as liquid biopsy techniques rise in prominence, will they replace traditional tissue biopsies, or will both techniques remain relevant? Given the ongoing challenges of early HCC detection, including issues with ultrasound sensitivity, accessibility, and patient adherence to surveillance, the evolution of diagnostic techniques is more relevant than ever. Furthermore, the accurate stratification of HCC is limited by the absence of reliable biomarkers which can predict response to therapies. While the advantages of molecular diagnostics are evident, their potential has not yet been fully harnessed, largely because tissue biopsies are not routinely performed for HCC. Liquid biopsies, analysing components such as circulating tumour cells, DNA, and extracellular vesicles, provide a promising alternative, though they are still associated with challenges related to sensitivity, cost, and accessibility. The early results from multi-analyte liquid biopsy panels are promising and suggest they could play a transformative role in HCC detection and management; however, comprehensive clinical validation is still ongoing. In this review, we explore the challenges and potential of both tissue and liquid biopsy, highlighting that these diagnostic methods, while distinct in their approaches, are set to jointly reshape the future of HCC management.

Immature stroma and high infiltration of CD15+ cells are predictive markers of poor prognosis in different subsets of patients with pancreatic cancer

Preoperative treatment is commonly carried out for borderline resectable pancreatic ductal adenocarcinoma (PDAC). However, the relationship between the combination of immune cells in the tumor microenvironment and their intratumoral heterogeneity along with their association with histological findings remains unclear, especially in patients receiving preoperative chemotherapy. We aimed to explore the therapeutic strategies for patients with PDAC with poor prognosis after receiving chemotherapy based on histological and immunological microenvironmental classifications. We investigated the correlation between the prognosis and histological immune microenvironmental factors of patients who initially underwent surgery (n = 100) and were receiving gemcitabine plus nab-paclitaxel (GEM + nabPTX) as preoperative chemotherapy (n = 103). Immune profiles were generated based on immune cell infiltration into the tumor, and their correlation with patient outcomes and histological features was analyzed. Tumor-infiltrating neutrophils (TINs) were identified as independent poor prognostic factors using multivariate analysis in both surgery-first and preoperative chemotherapy groups. The patients were further classified into four groups based on immune cell infiltration into the tumor. Patients with high CD15 infiltration into the tumor and immature stroma at the cancer margins showed the worst prognosis in the preoperative chemotherapy group. The analysis of mRNA expression and immunohistochemical features revealed that CXCR2, the receptor for CXCL8, was correlated with disease-free and overall survival. We inferred that patients with immature stroma at the margins and high infiltration of CD15+ neutrophils within the tumor showed the worst prognosis and they could particularly benefit from treatment with inhibitors targeting CXCR2 or CXCL8.

Development of a promising PPAR signaling pathway-related prognostic prediction model for hepatocellular carcinoma

The peroxisome proliferator-activated receptor (PPAR) signaling pathway plays a crucial role in systemic cell metabolism, energy homeostasis and immune response inhibition. However, its significance in hepatocellular carcinoma (HCC) has not been well documented. In our study, based on the RNA sequencing data of HCC, consensus clustering analyses were performed to identify PPAR signaling pathway-related molecular subtypes, each of which displaying varying survival probabilities and immune infiltration status. Following, a prognostic prediction model of HCC was developed by using the random survival forest method and Cox regression analysis. Significant difference in survival outcome, immune landscape, drug sensitivity and pathological features were observed between patients with different prognosis. Additionally, decision tree and nomogram models were adopted to optimize the prognostic prediction model. Furthermore, the robustness of the model was verified through single-cell RNA-sequencing data. Collectively, this study systematically elucidated that the PPAR signaling pathway-related prognostic model has good predictive efficacy for patients with HCC. These findings provide valuable insights for further research on personalized treatment approaches for HCC.

Prediction of immunocyte infiltration and prognosis in postoperative hepatitis B virus-related hepatocellular carcinoma patients using magnetic resonance imaging

Background

The immune microenvironment (IME) is closely associated with prognosis and therapeutic response of hepatitis B virus-related hepatocellular carcinoma (HBV-HCC). Multi-parametric magnetic resonance imaging (MRI) enables non-invasive assessment of IME and predicts prognosis in HBV-HCC. We aimed to construct an MRI prediction model of the immunocyte-infiltration subtypes and explore its prognostic significance.

Methods

HBV-HCC patients at the First Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) with radical surgery (between 1 October and 30 December 2021) were prospectively enrolled. Patients with pathologically proven HCC (between 1 December 2013 and 30 October 2019) were retrospectively enrolled. Pearson correlation analysis was used to examine the relationship between the immunocyte-infiltration counts and MRI parameters. An MRI prediction model of immunocyte-infiltration subtypes was constructed in prospective cohort. Kaplan-Meier survival analysis was used to analyse its prognostic significance in the retrospective cohort.

Results

Twenty-four patients were prospectively enrolled to construct the MRI prediction model. Eighty-nine patients were retrospectively enrolled to determine its prognostic significance. MRI parameters (relative enhancement, ratio of the apparent diffusion coefficient value of tumoral region to peritumoral region [rADC], T1 value) correlated significantly with the immunocyte-infiltration counts (leukocytes, T help cells, PD1+Tc cells, B lymphocytes). rADC differed significantly between high and low immunocyte-infiltration groups (1.47 ± 0.36 vs 1.09 ± 0.25, P = 0.009). The area under the curve of the MRI model was 0.787 (95% confidence interval 0.587-0.987). Based on the MRI model, the recurrence-free time was longer in the high immunocyte-infiltration group than in the low immunocyte-infiltration group (P = 0.026).

Conclusions

MRI is a non-invasive method for assessing the IME and immunocyte-infiltration subtypes, and predicting prognosis in post-operative HBV-HCC patients.

Serum amyloid A promotes glycolysis of neutrophils during PD-1 blockade resistance in hepatocellular carcinoma

The response to programmed death-1 (PD-1) blockade varies in hepatocellular carcinoma (HCC). We utilize a panel of 16 serum factors to show that a circulating level of serum amyloid A (SAA) > 20.0 mg/L has the highest accuracy in predicting anti-PD-1 resistance in HCC. Further experiments show a correlation between peritumoral SAA expression and circulating SAA levels in patients with progressive disease after PD-1 inhibition. In vitro experiments demonstrate that SAA induces neutrophils to express PD-L1 through glycolytic activation via an LDHA/STAT3 pathway and to release oncostatin M, thereby attenuating cytotoxic T cell function. In vivo, genetic or pharmacological inhibition of STAT3 or SAA eliminates neutrophil-mediated immunosuppression and enhances antitumor efficacy of anti-PD-1 treatment. This study indicates that SAA may be a critical inflammatory cytokine implicated in anti-PD-1 resistance in HCC. Targeting SAA-induced PD-L1+ neutrophils through STAT3 or SAA inhibition may present a potential approach for overcoming anti-PD1 resistance.

Novel nomograms based on microvascular invasion grade for early-stage hepatocellular carcinoma after curative hepatectomy

Microvascular invasion (MVI) is a critical risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). This study aimed to firstly develop and validate nomograms based on MVI grade for predicting recurrence, especially early recurrence, and overall survival in patients with early-stage HCC after curative resection. We retrospectively reviewed the data of patients with early-stage HCC who underwent curative hepatectomy in the First Affiliated Hospital of Fujian Medical University (FHFU) and Mengchao Hepatobiliary Hospital of Fujian Medical University (MHH). Kaplan-Meier curves and Cox proportional hazards regression models were used to analyse disease-free survival (DFS) and overall survival (OS). Nomogram models were constructed on the datasets from the 70% samples of and FHFU, which were validated using bootstrap resampling with 30% samples as internal validation and data of patients from MHH as external validation. A total of 703 patients with early-stage HCC were included to create a nomogram for predicting recurrence or metastasis (DFS nomogram) and a nomogram for predicting survival (OS nomogram). The concordance indexes and calibration curves in the training and validation cohorts showed optimal agreement between the predicted and observed DFS and OS rates. The predictive accuracy was significantly better than that of the classic HCC staging systems.

Targeting ALK averts ribonuclease 1-induced immunosuppression and enhances antitumor immunity in hepatocellular carcinoma

Tumor-secreted factors contribute to the development of a microenvironment that facilitates the escape of cancer cells from immunotherapy. In this study, we conduct a retrospective comparison of the proteins secreted by hepatocellular carcinoma (HCC) cells in responders and non-responders among a cohort of ten patients who received Nivolumab (anti-PD-1 antibody). Our findings indicate that non-responders have a high abundance of secreted RNase1, which is associated with a poor prognosis in various cancer types. Furthermore, mice implanted with HCC cells that overexpress RNase1 exhibit immunosuppressive tumor microenvironments and diminished response to anti-PD-1 therapy. RNase1 induces the polarization of macrophages towards a tumor growth-promoting phenotype through activation of the anaplastic lymphoma kinase (ALK) signaling pathway. Targeting the RNase1/ALK axis reprograms the macrophage polarization, with increased CD8+ T- and Th1- cell recruitment. Moreover, simultaneous targeting of the checkpoint protein PD-1 unleashes cytotoxic CD8+ T-cell responses. Treatment utilizing both an ALK inhibitor and an anti-PD-1 antibody exhibits enhanced tumor regression and facilitates long-term immunity. Our study elucidates the role of RNase1 in mediating tumor resistance to immunotherapy and reveals an RNase1-mediated immunosuppressive tumor microenvironment, highlighting the potential of targeting RNase1 as a promising strategy for cancer immunotherapy in HCC.

Downregulation of ST6GAL2 Correlates to Liver Inflammation and Predicts Adverse Prognosis in Hepatocellular Carcinoma

Purpose

ST6 Beta-Galactoside Alpha-2,6-Sialyltransferase 2 (ST6GAL2), a member of the sialic acid transferase family, is differentially expressed in diverse cancers. However, it remains poorly understood in tumorigenesis and impacts on immune cell infiltration (ICI) in hepatocellular carcinoma (HCC).

Patients and Methods

Herein, the expression, diagnosis, prognosis, functional enrichment, genetic alterations, immune characteristics, and targeted drugs of ST6GAL2 in HCC were researched by conducting bioinformatics analysis, in vivo, and in vitro experiments.

Results

ST6GAL2 was remarkably decreased in HCC compared to non-tumor tissues, portending a poor prognosis associated with high DNA methylation levels. Functional enrichment and GSVA analyses revealed that ST6GAL2 might function through the extracellular matrix, PI3K-Akt signaling pathways, and tumor inflammation signature. We found that ST6GAL2 expression was proportional to ICI, immunostimulator, and immune subtypes. ST6GAL2 expression first increased and then decreased during the progression of liver inflammation to HCC. The dysfunctional experiment indicated that ST6GAL2 might exert immunosuppressive effects during HCC progression through regulating ICI. Several broad-spectrum anticancer drugs were obtained by drug sensitivity prediction analysis of ST6GAL2.

Conclusion

In conclusion, ST6GAL2 was a reliable prognostic biomarker strongly associated with ICI, and could be a potential immunotherapeutic target for HCC.

Molecular diagnostics of hepatobiliary and pancreatic neoplasias

Neoplasias of the hepatopancreatobiliary tract are growing in numbers, have the poorest prognosis of all major cancer entities, and thus represent a rising clinical problem. Their molecular diagnostic has dramatically improved, contributing to tumor subtyping, definition of malignancy, and uncovering cases with hereditary predisposition. Most of all, predictive molecular testing allows to identify cases amenable to treatment with the rising number of approved targeted drugs, immune-oncological treatment, and clinical trials. In this review, the current state of molecular testing and its contribution to clinical decision-making are outlined.

Immune characteristics of dedifferentiated retroperitoneal liposarcomas and the reliability of regional samples in evaluating their tumor immune microenvironments

BACKGROUND

Tumor immunotherapy is a new treatment breakthrough for retroperitoneal liposarcoma (RPLS), which is highly invasive and has few effective treatment options other than tumor resection. However, the heterogeneity of the tumor immune microenvironment (TIME) leads to missed clinical diagnosis and inappropriate treatment. Therefore, it is crucial to evaluate whether the TIME of a certain part of the tumor reliably represents the whole tumor, particularly for very large tumors, such as RPLS.

METHODS

We conducted a prospective study to evaluate the TIME in different regions of dedifferentiated RPLS (DDRPLS) by detecting the expressions of markers such as CD4+, CD8+, Foxp3+, CD20+, CD68+, LAMP3+, PD-1+ tumor-infiltrating lymphocytes (TILs), and PD-L1 in tumors and corresponding paratumor tissues via immunohistochemistry and RNA sequencing.

RESULTS

In DDRPLS, very few TILs were observed. Differentially expressed genes were significantly enriched in cell part and cell functions, as well as the metabolic pathway and PI3K-Akt signaling pathway. In addition, for most tumors (70-80%), the TIME was similar in different tumor regions.

CONCLUSIONS

For most tumors (70-80%), the TIME in any region of the tumor reliably represents the whole tumor. DDRPLS may regulate cell functions by modulating the metabolic and PI3K-Akt signaling pathways to promote its malignant behavior.

Single-cell disulfidptosis regulator patterns guide intercellular communication of tumor microenvironment that contribute to kidney renal clear cell carcinoma progression and immunotherapy

Background

Disulfidptosis, an emerging type of programmed cell death, plays a pivotal role in various cancer types, notably impacting the progression of kidney renal clear cell carcinoma (KIRC) through the tumor microenvironment (TME). However, the specific involvement of disulfidptosis within the TME remains elusive.

Methods

Analyzing 41,784 single cells obtained from seven samples of KIRC through single-cell RNA sequencing (scRNA-seq), this study employed nonnegative matrix factorization (NMF) to assess 24 disulfidptosis regulators. Pseudotime analysis, intercellular communication mapping, determination of transcription factor activities (TFs), and metabolic profiling of the TME subgroup in KIRC were conducted using Monocle, CellChat, SCENIC, and scMetabolism. Additionally, public cohorts were utilized to predict prognosis and immune responses within the TME subgroup of KIRC.

Results

Through NMF clustering and differential expression marker genes, fibroblasts, macrophages, monocytes, T cells, and B cells were categorized into four to six distinct subgroups. Furthermore, this investigation revealed the correlation between disulfidptosis regulatory factors and the biological traits, as well as the pseudotime trajectories of TME subgroups. Notably, disulfidptosis-mediated TME subgroups (DSTN+CD4T-C1 and FLNA+CD4T-C2) demonstrated significant prognostic value and immune responses in patients with KIRC. Multiple immunohistochemistry (mIHC) assays identified marker expression within both cell clusters. Moreover, CellChat analysis unveiled diverse and extensive interactions between disulfidptosis-mediated TME subgroups and tumor epithelial cells, highlighting the TNFSF12-TNFRSF12A ligand-receptor pair as mediators between DSTN+CD4T-C1, FLNA+CD4T-C2, and epithelial cells.

Conclusion

Our study sheds light on the role of disulfidptosis-mediated intercellular communication in regulating the biological characteristics of the TME. These findings offer valuable insights for patients with KIRC, potentially guiding personalized immunotherapy approaches.

BCLAF1 is Expressed as a Potential Anti-oncogene in Bile Duct Cancer

Validating the role of BCLAF1 in the development of Bile Duct Cancer. Differential expression of BCLAF1 in Bile Duct Cancer and normal tissues was analyzed bioinformatically, and immuno-infiltration analysis was performed by R. We also derived the correlation between the expression of BCLAF1 and HIF-1α by bioinformatics analysis and validated it by Western Blotting, qRT-PCR and scratch assays before and after hypoxia. Through bioinformatics analysis, we found that BCLAF1 mRNA was significantly higher in the tumor tissues of Bile Duct Cancer. The high expression of BCLAF1 implied a more advanced stage but a lower mortality rate. KEGG and GO enrichment analysis showed that BCLAF1 overexpression in Bile Duct Cancer was mainly associated with histone modification, peptidyl lysine modification, and macromolecular methylation. We used the TIMER algorithm to show that BCLAF1 expression in Bile Duct Cancer is associated with immune cell infiltration, which affects tumor progression and patient prognosis. We confirmed by normoxia and hypoxia qRT-PCR, Western Blotting and scratch assays that BCLAF1 and HIF-1α expression are positively correlated and that BCLAF1 may be expressed as anti-oncogene in Bile Duct Cancer. These findings demonstrate that BCLAF1 may act as anti-oncogene in Bile Duct Cancer and may be involved in immune cell infiltration in Bile Duct Cancer, suppressing the expression of HIF-1α.

PD1 and TIM3 Expression is Associated with Very Early Hepatocellular Carcinoma Recurrence After Percutaneous Thermal Ablation

Purpose

Percutaneous thermal ablation (PTA) is a cornerstone in the management of early-stage hepatocellular carcinoma (HCC). However, intrahepatic distant recurrence (IDR) occurs in the majority of patients after PTA. The aim of this study was to evaluate the immune signature associated with very early IDR.

Patients and Methods

Thirty-one patients (26 men, 5 women; mean age:72.4 ± 8.6; age range:57-86 years) who underwent PTA for HCC were included in this study. After PTA for HCC, patients were followed and later divided into two groups: a "very early recurrence" group in case of IDR within 12 months after PTA, and a "prolonged recurrence-free" group in case of no recurrence before 12 months of follow-up. Freshly harvested intratumoral and nontumoral liver tissues and peripheral blood were obtained before PTA and explored by multiparametric flow cytometry.

Results

The frequency of PD1+CD4+ T cells was higher in the early recurrence group than in the prolonged recurrence-free group in the peripheral blood (24.3%, IQR: 22.3-36.5 vs 14.0%, IQR: 11.5-16.4, p<0.0001), in the nontumoral liver (37.9%, IQR: 36.0-50.0 vs 22.5%, IQR: 18.0-29.9, p=0.0004), and in the tumor (37.6%, IQR: 32.3-39.3 vs 24.0%, IQR: 20.0-30.3, p=0.0137). Similarly, the frequency of TIM+CD8+ T cells was higher in the very early recurrence group in the peripheral blood (p=0.0021), non-tumoral liver (p=0.0012), and tumor (p=0.0239).

Conclusion

The expression of immune checkpoint molecules, such as PD1 and TIM3 on T cells identified HCC patients at risk of very early IDR after PTA who would likely benefit from adjuvant immunotherapy. Thus, our study contributes to a better understanding of the potential association of PTA with adjuvant immunotherapies.

PRMT1 Integrates Immune Microenvironment and Fatty Acid Metabolism Response in Progression of Hepatocellular Carcinoma

Background

Protein arginine methyltransferase (PRMT) family members have important roles in cancer processes. However, its functions in the regulation of cancer immunotherapy of hepatocellular carcinoma (HCC) are incompletely understood. This study aimed to investigate the roles of PRMT1 in HCC.

Methods

Single-cell RNA sequencing (scRNA-seq) and clinicopathological data were obtained and used to explore the diagnostic and prognostic value, cellular functions and roles in immune microenvironment regulation of PRMT1 in HCC. The functions of PRMT1 were explored using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO), as well as gene set enrichment analysis (GSEA). TIMER and CIBERSORT were used to analyze the relationships between PRMT1 expression and immune cell infiltration. The STRING database was used to construct a protein-protein interaction (PPI) network.

Results

PRMT1 was aberrantly expressed in HCC, which high expression was associated with tumor progression, worse overall survival (OS) and disease-free survival (DFS) of patients with HCC. PRMT1 was also associated with immune cell infiltration. Moreover, it was specifically expressed in immune cells, including exhausted CD8 T cells, B cells, and mono/macro cells in patients with immunotherapy. The expression of immune checkpoints was significantly increased in the high-PRMT1 expression groups of HCC patients. Regarding biological mechanisms, cell viability, migration and invasion, and the expression of genes related to fatty acid metabolism were suppressed in PRMT1 knockdown HCC cells. Moreover, genes co-expressed with PRMT1 were involved in the fatty acid metabolic process and enriched in fatty and drug-induced liver disease.

Conclusion

Taken together, these results indicate that PRMT1 might exert its oncogenic effects via immune microenvironment regulation and fatty acid metabolism in HCC. Our finding will provide a foundation for further studies and indicate a potential clinical therapeutic target for liver cancer.

Role of immune related genes in predicting prognosis and immune response in patients with hepatocellular carcinoma

Immunotherapy has developed rapidly in recent years. This study aimed to establish a prognostic signature for immune-related genes (IRGs) and explore related potential immunotherapies. The RNA-seq transcriptome profiles and clinicopathological information of patients were obtained from The Cancer Genome Atlas. Differentially expressed IRGs in tumors and normal tissues were screened and a risk score signature was constructed to predict the prognosis in patients with hepatocellular carcinoma (HCC). Receiver operating characteristic curves, survival analyses, and correlation analyses were used to explore the clinical application of this model. We further analyzed the differences in clinical characteristics, immune infiltration, somatic mutations, and treatment sensitivity between the high- and low-risk populations characterized by the prognostic models. The immune cell infiltration score and immune-related pathway activity were calculated using the single sample gene set enrichment analysis (ssGSEA) set enrichment analysis. Gene ontology (GO), Kyoto encyclopedia of genes and genomes, and GSEA were used to explore the underlying mechanisms. We constructed a nine-IRG formula to predict the prognosis in HCC patients. The higher the risk score, the higher the malignancy of the tumor and the worse the prognosis. There were significant differences in immune related processes between the high- and low-risk groups. TP53 and CTNNB1 mutations were significantly different between different risk groups. The expression of model gene was closely related to the sensitivity of tumor cells to chemotherapeutic drugs. This risk score model, which is helpful for the individualized treatment of patients with different risk factors, could be a reliable prognostic tool for HCC patients.

Research progress in nano-drug delivery systems based on the characteristics of the liver cancer microenvironment

The liver cancer has microenvironmental features such as low pH, M2 tumor-associated macrophage enrichment, low oxygen, rich blood supply and susceptibility to hematotropic metastasis, high chemokine expression, enzyme overexpression, high redox level, and strong immunosuppression, which not only promotes the progression of the disease, but also seriously affects the clinical effectiveness of traditional therapeutic approaches. However, nanotechnology, due to its unique advantages of size effect and functionalized modifiability, can be utilized to develop various responsive nano-drug delivery system (NDDS) by using these characteristic signals of the liver cancer microenvironment as a source of stimulation, which in turn can realize the intelligent release of the drug under the specific microenvironment, and significantly increase the concentration of the drug at the target site. Therefore, researchers have designed a series of stimuli-responsive NDDS based on the characteristics of the liver cancer microenvironment, such as hypoxia, weak acidity, and abnormal expression of proteases, and they have been widely investigated for improving anti-tumor therapeutic efficacy and reducing the related side effects. This paper provides a review of the current application and progress of NDDS developed based on the response and regulation of the microenvironment in the treatment of liver cancer, compares the effects of the microenvironment and the NDDS, and provides a reference for building more advanced NDDS.

Serum CXCL10 levels at the start of the second course of atezolizumab plus bevacizumab therapy predict therapeutic efficacy in patients with advanced BCLC stage C hepatocellular carcinoma: A multicenter analysis

BACKGROUND & AIMS

Relationships of serum C-C motif chemokine ligand 5 (CCL5) and C-X-C motif chemokine ligand 10 (CXCL10) levels with hot immune features have been reported in patients with hepatocellular carcinoma (HCC). Therefore, we examined the utility of their levels for predicting the efficacy of atezolizumab plus bevacizumab (Atez/Bev) in patients with HCC.

DESIGN

In total, 98 patients with HCC treated with Atez/Bev were enrolled, and their initial responses were evaluated at least once via dynamic computed tomography or magnetic resonance imaging. Serum CCL5 and CXCL10 levels were assessed by enzyme-linked immunosorbent assay before treatment and at the start of the second course of Atez/Bev therapy, and their relationships with treatment efficacy were determined.

RESULTS

No analyzed factor was associated with the initial therapeutic response. Among the 56 patients with Barcelona Clinic Liver Cancer (BCLC) stage C, serum CXCL10 levels at the beginning of course two (CXCL10-2c) tended to be higher in responders than in non-responders in the initial evaluation, and its optimal cutoff level of 690 pg/mL could be used to stratify patients regarding overall survival (OS; high vs. low: not reached vs. 17.6 months, p = 0.034) and progression-free survival (high vs. low: 13.6 vs. 5.1 months, p = 0.014). In multivariate analysis, high CXCL10 levels and neutrophil-to-lymphocyte ratios at the start of course two and Child-Pugh stage A at baseline were independent predictive factors of improved OS.

CONCLUSIONS

Serum CXCL10-2c levels were predictive of Atez/Bev efficacy in patients with BCLC stage C HCC.

Current status of vaccine immunotherapy for gastrointestinal cancers

Recent advances in tumor immunology and molecular drug development have ushered in a new era of cancer immunotherapy. Immunotherapy has shown promising results for several types of tumors, such as advanced melanoma, non-small cell lung cancer, renal cell carcinoma, bladder cancers, and refractory Hodgkin's lymphoma. Similarly, efforts have been made to develop immunotherapies such as adoptive T-cell transplantation, peptide vaccines, and dendritic cell vaccines, specifically for gastrointestinal tumors. However, before the advent of immune checkpoint inhibitors, immunotherapy did not work as well as expected. In this article, we review immunotherapy, focusing on cancer vaccines for gastrointestinal tumors, which generally target eliciting tumor-specific CD8 + cytotoxic T lymphocytes (CTLs). We also review various vaccine therapies and describe the relationship between vaccines and adjuvants. Finally, we discuss prospects for the combination of immunotherapy with immune checkpoint inhibitors.

The value of CDC42 effector protein 2 as a novel prognostic biomarker in liver hepatocellular carcinoma: a comprehensive data analysis

BACKGROUND

The prognostic significance of CDC42 effector protein 2 (CDC42EP2) and its association with tumor-infiltrating immune cells (TIICs) have not been explored in liver hepatocellular carcinoma (LIHC). This study aims to assess the potential prognostic value of CDC42EP2 by conducting a comprehensive analysis of online databases pertaining to LIHC.

METHODS

We evaluated the potential of CDC42EP2 as a prognostic biomarker by utilizing online databases such as TIMER, GEPIA2, KM, OSlihc, HPA, and LinkedOmics.

RESULTS

In LIHC, we observed that the mRNA and protein expression of CDC42EP2 were upregulated compared to normal tissues. Upregulated CDC42EP2 expression was associated with a worse prognosis based on the clinicopathological characteristics of patients with LIHC. Furthermore, CDC42EP2 was positively associated with TIICs. In the co-expression and functional enrichment analyses of CDC42EP2, 11,416 genes showed positive associations with CDC42EP2 while 8,008 genes showed negative associations. CDC42EP2-related co-expression genes were involved in protein localization to the endoplasmic reticulum, translational initiation, and RNA catabolic processes in gene set enrichment analysis-Gene Ontology (GSEAGO), and regulated the ribosome, spliceosome, and primary immune deficiency in the GSEAKyoto Encyclopedia of Genes and Genomes (KEGG) pathway. In a survival map, 23 and 17 genes that exhibited positive associations with CDC42EP2 showed a significant hazard ratio (HR) for overall survival and disease-free survival, respectively.

CONCLUSION

Our findings demonstrated that CDC42EP2 is a novel prognostic biomarker and a potential tumor immune therapeutic target in patients with LIHC.

Recurrence risk stratification of hepatocellular carcinomas based on immune gene expression and features extracted from pathological images

BACKGROUND

Immune-based therapy is a promising type of treatment for hepatocellular carcinoma (HCC) but has only been partially successful due to the high heterogeneity in HCC tumor. The differences in the degree of tumor cell progression and in the activity of tumor immune microenvironment could lead to varied clinical outcome. Accurate subgrouping for recurrence risk is an approach to address the issue of such heterogeneity. It remains under investigation as whether integrating quantitative whole slide image (WSI) features with the expression profile of immune marker genes can improve the risk stratification, and whether clinical outcome prediction can assist in understanding molecular biology that drives the outcome.

METHODS

We included a total of 231 patients from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) project. For each patient, we extracted 18 statistical metrics corresponding to a global region of interest and 135 features regarding nucleus shape from WSI. A risk score was developed using these image features with high-dimensional survival modeling. We also introduced into the model the expression profile of 66 representative marker genes relevant to currently available immunotherapies. We stratified all patients into higher and lower-risk subgroup based on the final risk score selected from multiple models generated, and further investigated underlying molecular mechanisms associated with the risk stratification.

RESULTS

One WSI feature and three immune marker genes were selected into the final recurrence-free survival (RFS) prediction model following the best integrated modeling framework. The resultant score showed a significantly improved prediction performance on the test dataset (mean time-dependent AUCs = 0.707) as compared to those of other types (e.g: mean time-dependent AUCs of AJCC tumor stage = 0.525) of input data integration. To assess that the risk score could provide a higher-resolution risk stratification, a lower-risk subgroup (or a higher-risk subgroup) was arbitrarily assigned according to score falling below (or above) the median score. The lower risk subgroup had significantly longer median RFS time than that of the higher-risk patients (median RFS = 903 vs. 265 days, log-rank test p-value< 0.0001). Additionally, the higher-risk subgroup, in contrast to the lower-risk patients were characterized with a significant downregulation of immune checkpoint genes, suppressive signal in tumor immune response pathways, and depletion of CD8 T cells. These observations for the higher-risk subgroup suggest that new targets for adoptive or checkpoint-based combined systemic therapies may be useful.

CONCLUSION

We developed a novel prognostic model to predict RFS for HCC patients, using one feature that can be automatically extracted from routine histopathological images, as well as the expression profiles of three immune marker genes. The methodology used in this paper demonstrates the feasibility of developing prognostic models that provide both useful risk stratification along with valuable biological insights into the underlying characteristics of the subgroups identified.

Immune activity score to assess the prognosis, immunotherapy and chemotherapy response in gastric cancer and experimental validation

Background

Gastric cancer (GC) is an extremely heterogeneous malignancy with a complex tumor microenvironment (TME) that contributes to unsatisfactory prognosis.

Methods

The overall activity score for assessing the immune activity of GC patients was developed based on cancer immune cycle activity index in the Tracking Tumor Immunophenotype (TIP). Genes potentially affected by the overall activity score were screened using weighted gene co-expression network analysis (WGCNA). Based on the expression profile data of GC in The Cancer Genome Atlas (TCGA) database, COX analysis was applied to create an immune activity score (IAS). Differences in TME activity in the IAS groups were analyzed. We also evaluated the value of IAS in estimating immunotherapy and chemotherapy response based on immunotherapy cohort. Gene expression in IAS model and cell viability were determined by real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) and Cell Counting Kit-8 (CCK-8) assay, respectively.

Results

WGCAN analysis screened 629 overall activity score-related genes, which were mainly associated with T cell response and B cell response. COX analysis identified AKAP5, CTLA4, LRRC8C, AOAH-IT1, NPC2, RGS1 and SLC2A3 as critical genes affecting the prognosis of GC, based on which the IAS was developed. Further RT-qPCR analysis data showed that the expression of AKAP5 and CTLA4 was downregulated, while that of LRRC8C, AOAH-IT1, NPC2, RGS1 and SLC2A3 was significantly elevated in GC cell lines. Inhibition of AKAP5 increased cell viability but siAOAH-IT1 promoted viability of GC cells. IAS demonstrated excellent robustness in predicting immunotherapy outcome and GC prognosis, with low-IAS patients having better prognosis and immunotherapy. In addition, resistance to Erlotinib, Rapamycin, MG-132, Cyclopamine, AZ628, and Sorafenib was reduced in patients with low IAS.

Conclusion

IAS was a reliable prognostic indicator. For GC patients, IAS showed excellent robustness in predicting GC prognosis, immune activity status, immunotherapy response, and chemotherapeutic drug resistance. Our study provided novel insights into the prognostic assessment in GC.

Development and validation of a disulfidptosis and M2 TAM-related classifier for bladder cancer to explore tumor subtypes, immune landscape and drug treatment

BACKGROUND

Disulfidptosis, as a new mode of programmed cell death, is closely associated with tumorigenesis. Meanwhile, M2 tumor-associated macrophage (TAM) plays an important role in tumor progression. Here, we propose to combine these two perspectives to detect novel disulfidptosis and M2 TAM-related biomarkers in bladder cancer (BCa) to identify various tumor subtypes, construct prognostic features, reveal immune and somatic mutational landscapes, and screen for drugs in BCa.

METHODS

We used weighted gene co-expression network analysis (WGCNA) to mine M2 TAM-related genes. Consensus unsupervised clustering was performed to identify potential tumor subtypes. The least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses were utilized to build the risk model. We then explored the immune cell, immune function, immune checkpoint expression patterns and somatic mutational landscape in clusters and risk groups. In addition, we performed sensitivity analysis for anti-cancer drugs.

RESULTS

We identified 3057 M2 TAM-related genes and intersected them with disulfidptosis-related genes to obtain 95 disulfidptosis and M2 TAM-related genes (DMRGs). In terms of tumor subtypes, two molecular clusters were identified. Cluster 1 showed stronger immunogenicity and higher tumor mutational burden (TMB). We also predicted 50 drugs with high sensitivity in cluster 1. On the basis of risk grouping, the high-risk group had poor overall survival in the training, test, and validation groups. Ten screened anti-cancer drugs were more sensitive in the high-risk group. A nomogram predicting survival of BCa patients was also established.

CONCLUSION

By combining two hotspot perspectives, disulfidptosis and M2 TAM, we provide a valuable risk score signature for establishing individualized treatment regimens and drug choices. The risk score may serve as an independent risk factor for BCa patients.

Unlocking the potential of the tumor microenvironment for cancer therapy

The tumor microenvironment (TME) holds a crucial role in the progression of cancer. Epithelial-derived tumors share common traits in shaping the TME. The Warburg effect is a notable phenomenon wherein tumor cells exhibit resistance to apoptosis and an increased reliance on anaerobic glycolysis for energy production. Recognizing the pivotal role of the TME in controlling tumor growth and influencing responses to chemotherapy, researchers have focused on developing potential cancer treatment strategies. A wide array of therapies, including immunotherapies, antiangiogenic agents, interventions targeting cancer-associated fibroblasts (CAF), and therapies directed at the extracellular matrix, have been under investigation and have demonstrated efficacy. Additionally, innovative techniques such as tumor tissue explants, "tumor-on-a-chip" models, and multicellular tumor spheres have been explored in laboratory research. This comprehensive review aims to provide insights into the intricate cross-talk between cancer-associated signaling pathways and the TME in cancer progression, current therapeutic approaches targeting the TME, the immune landscape within solid tumors, the role of the viral TME, and cancer cell metabolism.

Characterization of stem cell subtypes and prognostic signature in hepatocellular carcinoma

BACKGROUND

Cancer stem cells (CSCs) were linked to cancer aggressiveness and poor prognosis in patients with hepatocellular carcinoma (HCC).

METHODS

We integrated two external HCC cohorts to develop the stem cell subtypes according to unsupervised clustering with 26 stem cell gene sets. Between the subtypes, differences in prognosis, clinical characteristics, recognized HCC subtypes, metabolic profile, immune-related features, somatic mutation, and drug sensitivity were examined. The prognostic signature was created, and validated by numerous cohorts, and used to assess the efficacy of immunotherapy and transcatheter arterial chemoembolization (TACE) treatment. The nomogram was developed based on the signature and clinical features. We further examined the function of KIF20A in HCC and proved that KIF20A had the potential to regulate the stemness of HCC cells through western blot.

RESULTS

Low stem cell patterns, a good prognosis, positive clinical features, specific molecular subtypes, low metastatic characteristics, and an abundance of metabolic and immunological aspects were associated with Cluster 1, whereas Cluster 2 was the reverse. Chemotherapy and immunotherapy were more effective in Cluster 1. Cluster 1 and CTNNB1 and ALB mutation were more closely. Additionally, the prognosis, immunotherapeutic, and TACE therapy responses were all worse in the high-risk group. The nomogram could predict the survival probability of HCC patients. KIF20A was discovered to be overexpressed in HCC and was revealed to be connected to the stemness of the HepG2 cell line.

CONCLUSIONS

Two stem cell subgroups with different prognoses, metabolic, and immunological characteristics in HCC patients were identified. We also created a 7-gene prognostic signature and a nomogram to estimate the survival probability. The function of KIF20A in HCC stemness was initially examined.

Tumor steatosis and glutamine synthetase expression in patients with advanced hepatocellular carcinoma receiving atezolizumab plus bevacizumab therapy

AIM

The anti-programmed death-ligand 1 antibody atezolizumab and vascular endothelial growth factor-neutralizing antibody bevacizumab in combination (Atezo + Bev) have become the first-line therapy in advanced hepatocellular carcinoma (HCC). Distinct types of tumor immune microenvironment (TIME) and their associations with specific molecular subclasses and driver gene mutations have been identified in HCC; however, these insights are mainly based on surgically resected early-stage tumors. The current study aimed to reveal the biology and TIME of advanced HCC and their significance in predicting clinical outcomes of Atezo + Bev therapy.

METHODS

Thirty-three patients with advanced HCC who were scheduled for treatment with Atezo + Bev therapy were included in this study. Pretreatment tumor biopsy, pre- and posttreatment diffusion-weighted magnetic resonance imaging (MRI) with nine b values (0-1500 s/mm2 ), and other clinicopathologic factors were analyzed.

RESULTS

Compared with resectable HCC, advanced HCC was characterized by higher proliferative activity, a higher frequency of Wnt/β-catenin-activated HCC, and lower lymphocytic infiltration. Prognostically, two metabolism-related factors, histopathologically determined tumor steatosis and/or glutamine synthetase (GS) expression, and MRI-determined tumor steatosis, were the most significant prognostic indicators for progression-free survival (PFS) and overall survival after Atezo + Bev therapy. Furthermore, changes in the pre- and posttreatment true diffusion coefficients on MRI, which might reflect changes in TIME after treatment, were significantly associated with better PFS.

CONCLUSIONS

The biology and TIME of HCC were strikingly different in advanced HCC compared with those of surgically resected HCC. Two metabolism-related factors, pathologically determined tumor steatosis and/or GS expression, and MRI-determined tumor steatosis, were found to be the most significant prognostic indicators for Atezo + Bev therapy in advanced HCC.

Clinico-histological and molecular features of hepatocellular carcinoma from nonalcoholic fatty liver disease

Patients with nonalcoholic fatty liver disease (NAFLD) continue to increase with the epidemics of obesity, and NAFLD is estimated to become the most prevalent etiology of hepatocellular carcinoma (HCC). Recently, NAFLD-HCC has been recognized to have clinico-histologically and molecularly distinct features from those from other etiologies, including a lower incidence rate of HCC and less therapeutic efficacy to immune checkpoint inhibitors (ICIs). Consistent with the clinical observations that up to 50% of NAFLD-HCC occurs in the absence of cirrhosis, the imbalance of pro- and antitumorigenic hepatic stellate cells termed as myHSC and cyHSC can contribute to the creation of an HCC-prone hepatic environment, independent of the absolute fibrosis abundance. Immune deregulations by accumulated metabolites in NAFLD-affected livers, such as a fatty-acid-induced loss of cytotoxic CD4 T cells serving for immune surveillance and "auto-aggressive" CXCR6+ CD8 T cells, may promote hepatocarcinogenesis and diminish therapeutic response to ICIs. Steatohepatitic HCC (SH-HCC), characterized by the presence of fat accumulation in tumor cells, ballooned tumor cells, Mallory-Denk body, interstitial fibrosis, and intratumor immune cell infiltration, may represent a metabolic reprogramming for adapting to a lipid-rich tumor microenvironment by downregulating CPT2 and leveraging its intermediates as an "oncometabolite." Genome-wide analyses suggested that SH-HCC may be more responsive to ICIs given its mutual exclusiveness with β-catenin mutation/activation that promotes immune evasion. Thus, further understanding of NAFLD-specific hepatocarcinogenesis and HCC would enable us to improve the current daily practice and eventually the prognoses of patients with NAFLD.

An immune and epigenetics-related scoring model and drug candidate prediction for hepatic carcinogenesis via dynamic network biomarker analysis and connectivity mapping

Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality. This study aimed to build a prognostic signature for HCC patients based on immune-related genes (IRGs) and epigenetics-related genes (EPGs). RNA-seq data from Gene Expression Omnibus were used for dynamic network biomarker (DNB) analysis to identify 56 candidate IRG-EPG-DNBs and their first-neighbor genes. These genes were screened using LASSO-Cox regression analysis to finally obtain five candidate genes-RNF2, YBX1, EZH2, CAD, and PSMD1-which constituted the prognostic signature panel. According to this panel, patients in The Cancer Genome Atlas and International Cancer Genome Consortium were divided into high- and low-risk groups. The prognosis, clinicopathological features, and immune cell infiltration significantly differed between the two risk groups. The prognostic ability of the signature panel and expression profiling were further validated using online databases. We used an independent cohort of patients to validate the expression profiles of the five genes using reverse transcription-PCR. CMap and CellMiner predicted four small molecule drug-protein pairs based on the five prognostic genes. Of them, two market drugs approved by the Food and Drug Administration (AT-13387 and KU-55933) have emerged as candidates for HCC study. This new signature panel may serve as a potential prognostic marker, engendering the possibility of novel personalized therapy with classification of HCC patients.

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.

CT radiomics for noninvasively predicting NQO1 expression levels in hepatocellular carcinoma

Using noninvasive radiomics to predict pathological biomarkers is an innovative work worthy of exploration. This retrospective cohort study aimed to analyze the correlation between NAD(P)H quinone oxidoreductase 1 (NQO1) expression levels and the prognosis of patients with hepatocellular carcinoma (HCC) and to construct radiomic models to predict the expression levels of NQO1 prior to surgery. Data of patients with HCC from The Cancer Genome Atlas (TCGA) and the corresponding arterial phase-enhanced CT images from The Cancer Imaging Archive were obtained for prognosis analysis, radiomic feature extraction, and model development. In total, 286 patients with HCC from TCGA were included. According to the cut-off value calculated using R, patients were divided into high-expression (n = 143) and low-expression groups (n = 143). Kaplan-Meier survival analysis showed that higher NQO1 expression levels were significantly associated with worse prognosis in patients with HCC (p = 0.017). Further multivariate analysis confirmed that high NQO1 expression was an independent risk factor for poor prognosis (HR = 1.761, 95% CI: 1.136-2.73, p = 0.011). Based on the arterial phase-enhanced CT images, six radiomic features were extracted, and a new bi-regional radiomics model was established, which could noninvasively predict higher NQO1 expression with good performance. The area under the curve (AUC) was 0.9079 (95% CI 0.8127-1.0000). The accuracy, sensitivity, and specificity were 0.86, 0.88, and 0.84, respectively, with a threshold value of 0.404. The data verification of our center showed that this model has good predictive efficiency, with an AUC of 0.8791 (95% CI 0.6979-1.0000). In conclusion, there existed a significant correlation between the CT image features and the expression level of NQO1, which could indirectly reflect the prognosis of patients with HCC. The predictive model based on arterial phase CT imaging features has good stability and diagnostic efficiency and is a potential means of identifying the expression level of NQO1 in HCC tissues before surgery.

Single-cell and genetic multi-omics analysis combined with experiments confirmed the signature and potential targets of cuproptosis in hepatocellular carcinoma

Background: Cuproptosis, as a recently discovered type of programmed cell death, occupies a very important role in hepatocellular carcinoma (HCC) and provides new methods for immunotherapy; however, the functions of cuproptosis in HCC are still unclear. Methods: We first analyzed the transcriptome data and clinical information of 526 HCC patients using multiple algorithms in R language and extensively described the copy number variation, prognostic and immune infiltration characteristics of cuproptosis related genes (CRGs). Then, the hub CRG related genes associated with prognosis through LASSO and Cox regression analyses and constructed a prognostic prediction model including multiple molecular markers and clinicopathological parameters through training cohorts, then this model was verified by test cohorts. On the basis of the model, the clinicopathological indicators, immune infiltration and tumor microenvironment characteristics of HCC patients were further explored via bioinformation analysis. Then, We further explored the key gene biological function by single-cell analysis, cell viability and transwell experiments. Meantime, we also explored the molecular docking of the hub genes. Results: We have screened 5 hub genes associated with HCC prognosis and constructed a prognosis prediction scoring model. And the model results showed that patients in the high-risk group had poor prognosis and the expression levels of multiple immune markers, including PD-L1, CD276 and CTLA4, were higher than those patients in the low-risk group. We found a significant correlation between risk score and M0 macrophages and memory CD4+ T cells. And the single-cell analysis and molecular experiments showed that BEX1 were higher expressed in HCC tissues and deletion inhibited the proliferation, invasion and migration and EMT pathway of HCC cells. Finally, it was observed that BEX1 could bind to sorafenib to form a stable conformation. Conclusion: The study not only revealed the multiomics characteristics of CRGs in HCC but also constructed a new high-accuracy prognostic prediction model. Meanwhile, BEX1 were also identified as hub genes that can mediate the cuproptosis of hepatocytes as potential therapeutic targets for HCC.

Prediction of prognosis, immune infiltration, and personalized treatment of hepatocellular carcinoma by analysis of cuproptosis-related long noncoding RNAs and verification in vitro

Background

The correlations between cuproptosis and long noncoding RNAs (lncRNAs) with the tumor microenvironment (TME), immunotherapy, and some other characteristics of hepatocellular carcinoma (HCC) remain unclear.

Methods

Sixteen cuproptosis regulators and 356 cuproptosis-related lncRNAs (CRLnc) were identified from 374 HCC profiles in The Cancer Genome Atlas (TCGA) database. Six differentially expressed CRLnc were selected, and a prognostic risk model based on the CRLnc signature (CRLncSig) was constructed. The prognostic power of the model was verified. Moreover, a cuproptosis-related gene cluster (CRGC) was generated based on six lncRNAs and differentially expressed genes. The relationship between immune cell infiltration in the TME, immunotherapy, CRLncSig, and CRGC was demonstrated through various algorithms, Tumor Immune Dysfunction and Exclusion (TIDE), tumor mutational burden (TMB), etc. Potential drugs and sensitivity to those agents were evaluated for the risk model. LncRNA AL158166.1 was selected and verified in HCC tissues and cell lines, the impact of its knockdown and overexpression in HCC cells was examined, and the copper (Cu) concentration and the cuproptosis-related gene expression were detected.

Results

A CRLncSig prognostic risk model with good predictive ability was constructed. The low-risk group had a longer overall survival (OS), lower tumor purity, more extensive immune cell infiltration, higher immune score, enrichment in immune-activated pathways, and more positive response to immunotherapy versus the high-risk group. CRGC-B exhibited the best OS and the lowest tumor stage; the immune cell infiltration analysis was similar to the low-risk group in CRLncSig. CRGC-B belonged to the "immune-high" group of the TME. The low-risk group had a higher TIDE score and susceptibility to antitumor drugs. The lncRNA AL158166.1 had the highest hazard ratio. The levels of AL158166.1 were higher in HCC tissues versus healthy tissues. Knockdown of AL158166.1 could lead to an increase in intracellular Cu concentration, induce DLAT low expression, and inhibit the proliferation and migration of HCC cells, whereas overexpression of AL158166.1 exerted the reverse effect.

Conclusion

Overall, a new CRLncSig prognostic risk model and a cuproptosis-related molecular signature were constructed and evaluated. The model and signature were associated with the prognosis, immune infiltration, and immunotherapy of HCC. Inhibiting the lncRNA AL158166.1 may induce cuproptosis and showed potential for the inhibition of tumors. Evaluation of the CRLnc, CRLncSig, and CRGC may enhance our understanding of the TME, determine the effectiveness of immunotherapy, and act as a marker for the prognosis of HCC.

An immune-related biomarker index for predicting the effectiveness of immunotherapy and prognosis in hepatocellular carcinoma

OBJECTIVE

Currently, there are no recognized biomarkers for predicting the immunotherapy response and prognosis of hepatocellular carcinoma (HCC). This study aimed to establish an immune-related gene prognostic index (IRGPI) for HCC, and to investigate the clinical, immune, molecular, and microenvironmental characteristics of the IRGPI subgroups, as well as their impact on the effectiveness of immune checkpoint inhibitors (ICIs) therapy and patients' prognosis.

METHODS

We analyzed the LIHC dataset (n = 424) from the The Cancer Genome Atlas (TCGA) database and the GSE10140 dataset (n = 84) from the Gene Expression Omnibus (GEO) database using weighted gene co-expression network analysis (WGCNA) and univariate/multivariate Cox regression analysis to identify immune-related hub genes with prognostic significance. Subsequently, The IRGPI was then established with these special genes obtained, and the molecular, immune, and clinicopathological characteristics of the IRGPI subgroups, along with their predictive role in ICIs treatment and HCC prognosis, were investigated.

RESULTS

The IRGPI was composed of nine genes, namely CHGA, GAL, CCR3, MMP7, STC1, UCN, OXT, SOCS2, and GCG. The IRGPI-high group exhibited a worse prognosis in both the TCGA and GEO databases compared to the IRGPI-low group. The IRGPI-high group was primarily associated with adaptive immune response and cell-cell interaction pathways and exhibited a higher frequency of gene mutations (such as TP53 and CTNNB1), higher expression of PD-L1 and CTLA4, a higher proportion of macrophages M0 and follicular helper T cells, and a higher APC_co_inhibition and T_cell_co-inhibition immune score. Furthermore, the IRGPI-high group was associated with worse immune subtypes, clinicopathological characteristics, immunotherapy response, and clinical prognosis.

CONCLUSION

IRGPI is a biomarker with significant potential for predicting the immunotherapy response and prognosis of HCC patients, and is closely related to the immunosuppressive microenvironment and poorer clinicopathological characteristics.

Development and validation of a nomogram to predict the recurrence of hepatocellular carcinoma patients with dynamic changes in AFP undergoing locoregional treatments

Background

Serum alpha-fetoprotein (AFP) is an important clinical indicator for screening, diagnosis, and prognosis of primary hepatocellular carcinoma (HCC). Our team's previous study showed that patients with negative AFP at baseline and positive AFP at relapse had a worse prognosis (N-P). Therefore, the aim of our study was to develop and validate a nomogram for this group of patients.

Methods

A total of 513 patients with HCC who received locoregional treatments at Beijing You'an Hospital, Capital Medical University, from January 2012 to December 2019 were prospectively enrolled. Patients admitted from 2012 to 2015 were assigned to the training cohort (n = 335), while 2016 to 2019 were in the validation cohort (n =183). The clinical and pathological features of patients were collected, and independent risk factors were identified using univariate and multivariate Cox regression analysis as a basis for developing a nomogram. The performance of the nomogram was evaluated by C-index, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) curves in the training and validation cohorts.

Results

The content of the nomogram includes gender, tumor number, tumor size, lymphocyte, direct bilirubin (DBIL), gamma-glutamyl transferase (GGT), and prealbumin. The C-index (0.717 and 0.752) and 1-, 3-, and 5-year AUCs (0.721, 0.825, 0.845, and 0.740, 0.868, 0.837) of the training and validation cohorts proved the good predictive performance of the nomogram. Calibration curves and DCA curves suggested accuracy and net clinical benefit rates. The nomogram enabled to classify of patients with dynamic changes in AFP into three groups according to the risk of recurrence: low risk, intermediate risk, and high risk. There was a statistically significant difference in RFS between the three groups in the training and validation cohorts (P<0.001).

Conclusion

The nomogram developed and validated in this study had good predictive power for patients with dynamic changes in AFP.

ATP6V1F is a novel prognostic biomarker and potential immunotherapy target for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the deadliest malignancies worldwide, with late detection, ineffective treatment and poor overall survival. Immunotherapy, including immune checkpoint inhibitor (ICI) therapy, holds great potential for treatment of HCC. Although some patients respond well to ICIs, many fail to obtain a significant benefit. It is therefore of great interest to find appropriate markers to stratify patient responses to immunotherapy and to explore suitable targets for modulating the TME and immune cell infiltration. ATP6V1F encodes a constituent of vacuolar ATPase (V-ATPase). V-ATPase-mediated acidification of organelles is required for intracellular processes such as zymogen activation, receptor-mediated endocytosis, protein sorting and synaptic vesicle proton gradient generation. In this study, we confirmed for the first time that ATP6V1F is overexpressed in HCC and related to poor prognosis in these patients. We identified that overexpression of ATP6V1F is associated with infiltration of some immune cells and expression of several immune checkpoints. Furthermore, we explored the possible mechanisms of action of ATP6V1F. Finally, we conducted in vitro experiments, including wound healing, Transwell invasion, and apoptosis assays, to verify that ATP6V1F promotes development of HCC by promoting migration and invasion and inhibiting apoptosis of HCC cells. Our findings will contribute to providing precise immunotherapy to patients with HCC.

Integrated analysis revealing a novel stemness-metabolism-related gene signature for predicting prognosis and immunotherapy response in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a malignant lethal tumor and both cancer stem cells (CSCs) and metabolism reprogramming have been proven to play indispensable roles in HCC. This study aimed to reveal the connection between metabolism reprogramming and the stemness characteristics of HCC, established a new gene signature related to stemness and metabolism and utilized it to assess HCC prognosis and immunotherapy response. The clinical information and gene expression profiles (GEPs) of 478 HCC patients came from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA). The one-class logistic regression (OCLR) algorithm was employed to calculate the messenger ribonucleic acid expression-based stemness index (mRNAsi), a new stemness index quantifying stemness features. Differentially expressed analyses were done between high- and low-mRNAsi groups and 74 differentially expressed metabolism-related genes (DEMRGs) were identified with the help of metabolism-related gene sets from Molecular Signatures Database (MSigDB). After integrated analysis, a risk score model based on the three most efficient prognostic DEMRGs, including Recombinant Phosphofructokinase Platelet (PFKP), phosphodiesterase 2A (PDE2A) and UDP-glucuronosyltransferase 1A5 (UGT1A5) was constructed and HCC patients were divided into high-risk and low-risk groups. Significant differences were found in pathway enrichment, immune cell infiltration patterns, and gene alterations between the two groups. High-risk group patients tended to have worse clinical outcomes and were more likely to respond to immunotherapy. A stemness-metabolism-related model composed of gender, age, the risk score model and tumor-node-metastasis (TNM) staging was generated and showed great discrimination and strong ability in predicting HCC prognosis and immunotherapy response.

MHC class I loss is associated with biliary/progenitor cell features and "cold" tumor-immune microenvironment in hepatocellular carcinoma

Hepatocellular carcinomas (HCCs) with biliary/progenitor cell features frequently show increased programmed death-ligand 1 (PD-L1) expression, but their response to immunotherapy is not high. One possible explanation for this phenomenon could be the loss of major histocompatibility complex (MHC) class I expression on tumor cells, which impairs the presentation of tumor antigens to cytotoxic T cells. However, the potential correlation between MHC class I loss, biliary/progenitor cell features, and the tumor-immune microenvironment remains largely unexplored. Herein, we hypothesized that MHC class I loss could be associated with biliary/progenitor cell features and potentially impact the tumor-immune microenvironment. To evaluate this hypothesis and gain insight into the characteristics of tumor cells and the tumor-immune microenvironment in HCCs with MHC class I loss, we examined a consecutive series of 397 HCC cases. MHC class I loss was observed in 32 HCCs (8.1%). Lipid-less cytologic morphology was significantly associated with MHC class I loss (P = 0.02). CK19 expression and decreased ARG1 expression, both known as biliary/progenitor cell features, were significantly associated with MHC class I loss (P < 0.05). PD-L1 expression was irrelevant to the MHC class I status. HCCs with MHC class I loss exhibited significantly lower infiltration of CD8+, CD4+, CD20+, and FOXP3+ cells than those with intact MHC class I (all Ps < 0.01). Our study reveals an association between MHC class I loss, biliary/progenitor cell features, and a "cold" tumor-immune microenvironment in HCCs. These insights highlight the potential impact of MHC class I loss on tumor cells and the tumor-immune microenvironment.

Spatial immunophenotypes predict clinical outcome in intrahepatic cholangiocarcinoma

Background & Aims

Intrahepatic cholangiocarcinoma (iCCA) is a severe malignant tumour that shows only modest responses to immunotherapy. We aimed to identify the spatial immunophenotypes of iCCA and delineate potential immune escape mechanisms.

Method

Multiplex immunohistochemistry (mIHC) was performed to quantitatively evaluate the distribution of 16 immune cell subsets in intratumour, invasive margin and peritumour areas in a cohort of 192 treatment-naïve patients with iCCA. Multiregion unsupervised clustering was used to determine three spatial immunophenotypes, and multiomics analyses were carried out to explore functional differences.Results: iCCA displayed a region-specific distribution of immune cell subsets with abundant CD15⁺ neutrophil infiltration in intratumour areas. Three spatial immunophenotypes encompassing inflamed (35%), excluded (35%) and ignored (30%) phenotypes were identified. The inflamed phenotype showed characteristics of abundant immune cell infiltration in intratumour areas, increased PD-L1 expression and relatively favourable overall survival. The excluded phenotype with a moderate prognosis was characterized by immune cell infiltration restricted to the invasive margin or peritumour areas and upregulation of activated hepatic stellate cells, extracellular matrix and Notch signalling pathways. The ignored phenotype, with scarce immune cell infiltration across all subregions, was associated with MAPK signalling pathway elevation and a poor prognosis. The excluded and ignored phenotypes, constituting non-inflamed phenotypes, shared features of an increased angiogenesis score, TGF-β and Wnt-β catenin pathway upregulation and were enriched for BAP1 mutations and FGFR2 fusions.

Conclusion

We identified three spatial immunophenotypes with different overall prognoses in iCCA. Tailored therapies based on the distinct immune evasion mechanisms of the spatial immunophenotypes are needed.

Impact and implications

The contribution of immune cell infiltration in the invasive margin and peritumour areas has been proved. We explored the multiregional immune contexture of 192 patients to identify three spatial immunophenotypes in intrahepatic cholangiocarcinoma (iCCA). By integrating genomic and transcriptomic data, phenotype-specific biological behaviours and potential immune escape mechanisms were analysed. Our findings provide a rationale to develop personalized therapies for iCCA.