Molecular Markers of Response to Anti-PD1 Therapy in Advanced Hepatocellular Carcinoma

CXCR4 antagonist-loaded nanoparticles reprogram the tumor microenvironment and enhance immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer death that has limited treatment options for advanced stages. Although PD-1 inhibitors such as nivolumab and pembrolizumab have been approved for advanced HCC treatment, their effectiveness is often hampered by the immunosuppressive tumor microenvironment (TME), which is due to hypoxia-driven CXCL12/CXCR4 axis activation. In this study, we developed 807-NPs, lipid-coated tannic acid (TA) nanoparticles that encapsulate BPRCX807, a potent CXCR4 antagonist to target HCC. 807-NPs enhance the pharmacokinetics and improve the tumor availability of BPRCX807 without causing systemic toxicity. Our findings show that 807-NPs block the CXCR4/CXCL12 pathway, inhibiting Akt and mTOR activation in HCC cells and M2 macrophages and promoting their repolarization toward the antitumor M1 phenotype. In orthotopic murine HCC models, systemic administration of 807-NPs significantly remodeled the immunosuppressive TME by reprogramming tumor-associated macrophages (TAMs) toward an immunostimulatory phenotype and promoting cytotoxic T-cell infiltration into tumors. This led to suppressed primary tumor growth and metastasis, while enhancing the efficacy of cancer immunotherapies, including PD-1 blockade and whole-cancer cell vaccines, by promoting T-cell activation. Our work demonstrates the potential of using nanotechnology to deliver CXCR4 antagonists for cancer immunotherapy.

Pharmacological activation of STAT1-GSDME pyroptotic circuitry reinforces epigenetic immunotherapy for hepatocellular carcinoma

BACKGROUND

Genomic screening uncovered interferon-gamma (IFNγ) pathway defects in tumours refractory to immune checkpoint blockade (ICB). However, its non-mutational regulation and reversibility for therapeutic development remain less understood.

OBJECTIVE

We aimed to identify ICB resistance-associated druggable histone deacetylases (HDACs) and develop a readily translatable combination approach for patients with hepatocellular carcinoma (HCC).

DESIGN

We correlated the prognostic outcomes of HCC patients from a pembrolizumab trial (NCT03419481) with tumourous cell expressions of all HDAC isoforms by single-cell RNA sequencing. We investigated the therapeutic efficacy and mechanism of action of selective HDAC inhibition in 4 ICB-resistant orthotopic and spontaneous models using immune profiling, single-cell multiomics and chromatin immunoprecipitation-sequencing and verified by genetic modulations and co-culture systems.

RESULTS

HCC patients showing higher HDAC1/2/3 expressions exhibited deficient IFNγ signalling and poorer survival on ICB therapy. Transient treatment of a selective class-I HDAC inhibitor CXD101 resensitised HDAC1/2/3high tumours to ICB therapies, resulting in CD8+T cell-dependent antitumour and memory T cell responses. Mechanistically, CXD101 synergised with ICB to stimulate STAT1-driven antitumour immunity through enhanced chromatin accessibility and H3K27 hyperacetylation of IFNγ-responsive genes. Intratumoural recruitment of IFNγ+GZMB+cytotoxic lymphocytes further promoted cleavage of CXD101-induced Gasdermin E (GSDME) to trigger pyroptosis in a STAT1-dependent manner. Notably, deletion of GSDME mimicked STAT1 knockout in abolishing the antitumour efficacy and survival benefit of CXD101-ICB combination therapy by thwarting both pyroptotic and IFNγ responses.

CONCLUSION

Our immunoepigenetic strategy harnesses IFNγ-mediated network to augment the cancer-immunity cycle, revealing a self-reinforcing STAT1-GSDME pyroptotic circuitry as the mechanistic basis for an ongoing phase-II trial to tackle ICB resistance (NCT05873244).

NOTCH1 Drives Sexually Dimorphic Immune Responses in Hepatocellular Carcinoma

Hepatocellular carcinoma presents strong sexual dimorphism, being two to three times more frequent in males than in females; however, the role of sex in response to immunotherapies in HCC remains unknown. We demonstrate that NOTCH1, an understudied oncogene in HCC, elicits sexually dimorphic antitumor immunity and response to FDA-approved immunotherapies. Surprisingly, males harboring NOTCH1-driven tumors displayed enhanced antitumor immune responses, which, in mice, were mediated by dendritic and T cells. Conversely, females harboring NOTCH1-driven tumors presented immune evasion and resistance to immunotherapies through a defect in dendritic cell (DC)-mediated priming and activation of CD8+ T cells in mice, which was restored therapeutically with CD40 agonism. Mechanistically, the sexually dimorphic immunity was mediated by genes in the sex chromosomes but not by sex hormones. Together, our study unravels an unexpected association between NOTCH1 and sex in cancer immunity and highlights the potential of restoring the DC-CD8+ T-cell axis with CD40 agonism to improve outcomes. Significance: Although HCC presents strong sexual dimorphism, the role of sex in response to immunotherapies remains elusive. With a novel HCC mouse model and validation in patients with HCC, we demonstrate that NOTCH1 disrupts antitumor immunity specifically in females through a mechanism mediated by sex chromosome genes, which is reversed with CD40 agonism. See related commentary by Zhu and Koltsova, p. 452.

Combining Radioembolization and Immune Checkpoint Inhibitors for the Treatment of Hepatocellular Carcinoma: The Quest for Synergy

Hepatocellular carcinoma is a leading and increasing contributor to cancer-related death worldwide. Recent advancements in both liver-directed therapies in the form of yttrium-90 (90Y) radioembolization (RE) and systemic therapy in the form of immune checkpoint inhibitors (ICI) have expanded treatment options for patients with an otherwise poor prognosis. Despite these gains, ICIs and 90Y-RE each have key limitations with low objective response rates and persistent hazard of out-of-field recurrence, respectively, and overall survival remains low. However, each therapy's strength may mitigate the other's weakness, making them potentially ideal partners for combination treatment strategies. This review discusses the scientific and clinical rationale for combining 90Y-RE with ICIs, highlights early clinical trial data on its safety and effectiveness, and proposes key issues to be addressed in this emerging field. With optimal strategies, combination therapies can potentially result in increasing likelihood of durable and curative outcomes in later stage patients.

Precision models in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) represents a global health challenge, and ranks among one of the most prevalent and deadliest cancers worldwide. Therapeutic advances have expanded the treatment armamentarium for patients with advanced HCC, but obstacles remain. Precision oncology, which aims to match specific therapies to patients who have tumours with particular features, holds great promise. However, its implementation has been hindered by the existence of numerous 'HCC influencers' that contribute to the high inter-patient heterogeneity. HCC influencers include tumour-related characteristics, such as genetic alterations, immune infiltration, stromal composition and aetiology, and patient-specific factors, such as sex, age, germline variants and the microbiome. This Review delves into the intricate world of HCC, describing the most innovative model systems that can be harnessed to identify precision and/or personalized therapies. We provide examples of how different models have been used to nominate candidate biomarkers, their limitations and strategies to optimize such models. We also highlight the importance of reproducing distinct HCC influencers in a flexible and modular way, with the aim of dissecting their relative contribution to therapy response. Next-generation HCC models will pave the way for faster discovery of precision therapies for patients with advanced HCC.

Human-correlated genetic models identify precision therapy for liver cancer

Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, is a leading cause of cancer-related mortality worldwide1,2. HCC occurs typically from a background of chronic liver disease, caused by a spectrum of predisposing conditions. Tumour development is driven by the expansion of clones that accumulate progressive driver mutations3, with hepatocytes the most likely cell of origin2. However, the landscape of driver mutations in HCC is broadly independent of the underlying aetiologies4. Despite an increasing range of systemic treatment options for advanced HCC, outcomes remain heterogeneous and typically poor. Emerging data suggest that drug efficacies depend on disease aetiology and genetic alterations5,6. Exploring subtypes in preclinical models with human relevance will therefore be essential to advance precision medicine in HCC7. Here we generated a suite of genetically driven immunocompetent in vivo and matched in vitro HCC models. Our models represent multiple features of human HCC, including clonal origin, histopathological appearance and metastasis. We integrated transcriptomic data from the mouse models with human HCC data and identified four common human-mouse subtype clusters. The subtype clusters had distinct transcriptomic characteristics that aligned with the human histopathology. In a proof-of-principle analysis, we verified response to standard-of-care treatment and used a linked in vitro-in vivo pipeline to identify a promising therapeutic candidate, cladribine, that has not previously been linked to HCC treatment. Cladribine acts in a highly effective subtype-specific manner in combination with standard-of-care therapy.

Spatial single-cell profiling and neighbourhood analysis reveal the determinants of immune architecture connected to checkpoint inhibitor therapy outcome in hepatocellular carcinoma

BACKGROUND

The determinants of the response to checkpoint immunotherapy in hepatocellular carcinoma (HCC) remain poorly understood. The organisation of the immune response in the tumour microenvironment (TME) is expected to govern immunotherapy outcomes but spatial immunotypes remain poorly defined.

OBJECTIVE

We hypothesised that the deconvolution of spatial immune network architectures could identify clinically relevant immunotypes in HCC.

DESIGN

We conducted highly multiplexed imaging mass cytometry on HCC tissues from 101 patients. We performed in-depth spatial single-cell analysis in a discovery and validation cohort to deconvolute the determinants of the heterogeneity of HCC immune architecture and develop a spatial immune classification that was tested for the prediction of immune checkpoint inhibitor (ICI) therapy.

RESULTS

Bioinformatic analysis identified 23 major immune, stroma, parenchymal and tumour cell types in the HCC TME. Unsupervised neighbourhood detection based on the spatial interaction of immune cells identified three immune architectures with differing involvement of immune cells and immune checkpoints dominated by either CD8 T-cells, myeloid immune cells or B- and CD4 T-cells. We used these to define three major spatial HCC immunotypes that reflect a higher level of intratumour immune cell organisation: depleted, compartmentalised and enriched. Progression-free survival under ICI therapy differed significantly between the spatial immune types with improved survival of enriched patients. In patients with intratumour heterogeneity, the presence of one enriched area governed long-term survival.

Stromal architecture and fibroblast subpopulations with opposing effects on outcomes in hepatocellular carcinoma

Dissecting the spatial heterogeneity of cancer-associated fibroblasts (CAFs) is vital for understanding tumor biology and therapeutic design. By combining pathological image analysis with spatial proteomics, we revealed two stromal archetypes in hepatocellular carcinoma (HCC) with different biological functions and extracellular matrix compositions. Using paired single-cell RNA and epigenomic sequencing with Stereo-seq, we revealed two fibroblast subsets CAF-FAP and CAF-C7, whose spatial enrichment strongly correlated with the two stromal archetypes and opposing patient prognosis. We discovered two functional units, one is the intratumor inflammatory hub featured by CAF-FAP plus CD8_PDCD1 proximity and the other is the marginal wound-healing hub with CAF-C7 plus Macrophage_SPP1 co-localization. Inhibiting CAF-FAP combined with anti-PD-1 in orthotopic HCC models led to improved tumor regression than either monotherapy. Collectively, our findings suggest stroma-targeted strategies for HCC based on defined stromal archetypes, raising the concept that CAFs change their transcriptional program and intercellular crosstalk according to the spatial context.

Clinical Applications of Artificial Intelligence (AI) in Human Cancer: Is It Time to Update the Diagnostic and Predictive Models in Managing Hepatocellular Carcinoma (HCC)?

In recent years, novel findings have progressively and promisingly supported the potential role of Artificial intelligence (AI) in transforming the management of various neoplasms, including hepatocellular carcinoma (HCC). HCC represents the most common primary liver cancer. Alarmingly, the HCC incidence is dramatically increasing worldwide due to the simultaneous "pandemic" spreading of metabolic dysfunction-associated steatotic liver disease (MASLD). MASLD currently constitutes the leading cause of chronic hepatic damage (steatosis and steatohepatitis), fibrosis, and liver cirrhosis, configuring a scenario where an HCC onset has been reported even in the early disease stage. On the other hand, HCC represents a serious plague, significantly burdening the outcomes of chronic hepatitis B (HBV) and hepatitis C (HCV) virus-infected patients. Despite the recent progress in the management of this cancer, the overall prognosis for advanced-stage HCC patients continues to be poor, suggesting the absolute need to develop personalized healthcare strategies further. In this "cold war", machine learning techniques and neural networks are emerging as weapons, able to identify the patterns and biomarkers that would have normally escaped human observation. Using advanced algorithms, AI can analyze large volumes of clinical data and medical images (including routinely obtained ultrasound data) with an elevated accuracy, facilitating early diagnosis, improving the performance of predictive models, and supporting the multidisciplinary (oncologist, gastroenterologist, surgeon, radiologist) team in opting for the best "tailored" individual treatment. Additionally, AI can significantly contribute to enhancing the effectiveness of metabolomics-radiomics-based models, promoting the identification of specific HCC-pathogenetic molecules as new targets for realizing novel therapeutic regimens. In the era of precision medicine, integrating AI into routine clinical practice appears as a promising frontier, opening new avenues for liver cancer research and treatment.

Spatial Dynamics of T- and B-Cell Responses Predicts Clinical Outcome of Resectable and Unresectable Hepatocellular Carcinoma

PURPOSE

Immunotherapies have led to a paradigm shift in the treatment of hepatocellular carcinoma (HCC). Studies have revealed the single-cell catalogs of tumor-infiltrating immune cells and the trajectories of their differentiation. Nevertheless, the spatial distribution of these immune cells with distinct phenotypes in the tumor microenvironment and their clinicopathologic significance in resectable and unresectable HCCs are still largely unclear.

EXPERIMENTAL DESIGN

We analyzed the spatial dynamics of intratumoral CD4 and CD8 T cells and their association with B and plasma cells using 283 surgically resected HCC samples, 58 unresectable HCC samples before combined immunotherapy [atezolizumab plus bevacizumab (Atezo + Bev)], and autopsy specimens from 50 cases of advanced-stage HCC through multiplex IHC combined with transcriptomic and driver gene mutation analyses. Classification based on the spatial dynamics of T- and B-cell responses (refined immunosubtype) was developed, and its clinicopathologic significance was analyzed.

RESULTS

We found that stem-like CD4 and CD8 T cells were mainly observed in T-cell aggregates and T-cell zone of tertiary lymphoid structure (TLS). The differentiation of T follicular helper cells was associated with the development of TLS, whereas the differentiation of CXCL13-expressing CD4 TCXCL13 cells with a phenotype resembling T peripheral helper cells was associated with the development of the lymphoplasmacytic microenvironment. The refined immunosubtype could predict clinical outcomes of resectable HCC after surgery and unresectable HCC after Atezo + Bev therapy. The immune microenvironment of metastatic lesions tended to reflect those of primary lesions.

CONCLUSIONS

We revealed the spatial dynamics of T- and B-cell responses in HCC, which is closely associated with the clinical outcome after surgical resection or Atezo + Bev therapy.

Immune checkpoint inhibitors and the liver: balancing therapeutic benefit and adverse events

Immune checkpoint inhibitors (ICI) have led to breakthrough improvements in the management of malignancy including hepatocellular (HCC) and biliary tract cancer, improving decades-old standards of care and increasing patient survival. In both liver tumour types, which commonly arise in the context of liver inflammation and underlying functional impairment, the lack of validated predictors of response underscores the need to balance predicted gains in survival with risk of treatment-related hepatoxicity and decompensation of underlying chronic liver disease.In addition, the liver is implicated in the toxicity associated with ICI therapy for non-liver cancers, which exhibits a high degree of variability in presentation and severity. An accurate assessment is mandatory for the diagnosis and management of ICI-induced liver injury.In this Recent Advances article, we provide an overview of the mechanisms of efficacy and toxicity of anticancer immunotherapy in liver tumours and liver toxicity in extrahepatic malignancies.We compare and contrast characteristics, management strategies and outcomes from immune-related liver injury in patients with chronic hepatitis/cirrhosis or with an underlying healthy liver and discuss the latest findings on how toxicity and decompensation may impact the outlook of patients with liver tumours and extrahepatic malignancies offering insights into the future directions of clinical research and practice in the field.

A multi-task deep learning model based on comprehensive feature integration and self-attention mechanism for predicting response to anti-PD1/PD-L1

BACKGROUND

Immune checkpoint inhibitor (ICI) has been widely used in the treatment of advanced cancers, but predicting their efficacy remains challenging. Traditional biomarkers are numerous but exhibit heterogeneity within populations. For comprehensively utilizing the ICI-related biomarkers, we aim to conduct multidimensional feature selection and deep learning model construction.

METHODS

We used statistical and machine learning methods to map features of different levels to next-generation sequencing gene expression. We integrated genes from different sources into the feature input of a deep learning model, by means of self-attention mechanism.

RESULTS

We performed feature selection at the single-cell sequencing level, PD-L1 (CD274) analysis level, tumor mutational burden (TMB)/mismatch repair (MMR) level, and somatic copy number alteration (SCNA) level, obtaining 96 feature genes. Based on the pan-cancer dataset, we trained a multi-task deep learning model. We tested the model in the bladder urothelial carcinoma testing set 1 (AUC = 0.62, n = 298), bladder urothelial carcinoma testing set 2 (AUC = 0.66, n = 89), non-small cell lung cancer testing set (AUC = 0.85, n = 27), and skin cutaneous melanoma testing set (AUC = 0.71, n = 27).

CONCLUSION

Our study demonstrates the potential of the deep learning model for integrating multidimensional features in predicting the outcome of ICI. Our study also provides a potential methodological case for medical scenarios requiring the integration of multiple levels of features.

Specific features of ß-catenin-mutated hepatocellular carcinomas

CTNNB1, encoding the ß-catenin protein, is a key oncogene contributing to liver carcinogenesis. Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer in adult, representing the third leading cause of cancer-related death. Aberrant activation of the Wnt/ß-catenin pathway, mainly due to mutations of the CTNNB1 gene, is observed in a significant subset of HCC. In this review, we first resume the major recent advances in HCC classification with a focus on CTNNB1-mutated HCC subclass. We present the regulatory mechanisms involved in β-catenin stabilisation, transcriptional activity and binding to partner proteins. We then describe specific phenotypic characteristics of CTNNB1-mutated HCC thanks to their unique gene expression patterns. CTNNB1-mutated HCC constitute a full-fledged subclass of HCC with distinct pathological features such as well-differentiated cells with low proliferation rate, association to cholestasis, metabolic alterations, immune exclusion and invasion. Finally, we discuss therapeutic approaches to target ß-catenin-mutated liver tumours and innovative perspectives for future drug developments.

Development of mutated β-catenin gene signature to identify CTNNB1 mutations from whole and spatial transcriptomic data in patients with HCC

Background & Aims

Patients with β-catenin (encoded by CTNNB1)-mutated hepatocellular carcinoma (HCC) demonstrate heterogenous responses to first-line immune checkpoint inhibitors (ICIs). Precision-medicine based treatments for this subclass are currently in clinical development. Here, we report derivation of the Mutated β-catenin Gene Signature (MBGS) to predict CTNNB1-mutational status in patients with HCC for future application in personalized medicine treatment regimens.

Methods

Co-expression of mutant-Nrf2 and hMet ± mutant-β-catenin in murine livers in mice led to HCC development. The MBGS was derived using bulk RNA-seq and intersectional transcriptomic analysis of β-catenin-mutated and non-mutated HCC models. Integrated RNA/whole-exome-sequencing and spatial transcriptomic data from multiple cohorts of patients with HCC was assessed to address the ability of MBGS to detect CTNNB1 mutation, the tumor immune microenvironment, and/or predict therapeutic responses.

Results

Bulk RNA-seq comparing HCC specimens in mutant β-catenin-Nrf2, β-catenin-Met and β-catenin-Nrf2-Met to Nrf2-Met HCC model yielded 95 common upregulated genes. In The Cancer Genome Atlas (TCGA)-LIHC dataset, differential gene expression analysis with false discovery rate (FDR) = 0.05 and log2(fold change) >1.5 on the 95 common genes comparing CTNNB1-mutated vs. wild-type patients narrowed the gene panel to a 13-gene MBGS. MBGS predicted CTNNB1-mutations in TCGA (n = 374) and French (n = 398) patient cohorts with AUCs of 0.90 and 0.94, respectively. Additionally, a higher MBGS expression score was associated with lack of significant improvement in overall survival or progression-free survival in the atezolizumab-bevacizumab arm vs. the sorafenib arm in the IMbrave150 cohort. MBGS performed comparable or superior to other CTNNB1-mutant classifiers. MBGS overlapped with Hoshida S3, Boyault G5/G6, and Chiang CTNNB1 subclass tumors in TCGA and in HCC spatial transcriptomic datasets visually depicting these tumors to be situated in an immune excluded tumor microenvironment.

Conclusions

MBGS will aid in patient stratification to guide precision medicine therapeutics for CTNNB1-mutated HCC subclass as a companion diagnostic, as anti-β-catenin therapies become available.

Impact and implications

As precision medicine for liver cancer treatment becomes a reality, diagnostic tools are needed to help classify patients into groups for the best treatment choices. We have developed a molecular signature that could serve as a companion diagnostic and uses bulk or spatial transcriptomic data to identify a unique subclass of liver tumors. This subgroup of liver cancer patients derive limited benefit from the current standard of care and are expected to benefit from specialized directed therapies that are on the horizon.

The role of artificial intelligence in the management of liver diseases

Universal neonatal hepatitis B virus (HBV) vaccination and the advent of direct-acting antivirals (DAA) against hepatitis C virus (HCV) have reshaped the epidemiology of chronic liver diseases. However, some aspects of the management of chronic liver diseases remain unresolved. Nucleotide analogs can achieve sustained HBV DNA suppression but rarely lead to a functional cure. Despite the high efficacy of DAAs, successful antiviral therapy does not eliminate the risk of hepatocellular carcinoma (HCC), highlighted the need for cost-effective identification of high-risk populations for HCC surveillance and tailored HCC treatment strategies for these populations. The accessibility of high-throughput genomic data has accelerated the development of precision medicine, and the emergence of artificial intelligence (AI) has led to a new era of precision medicine. AI can learn from complex, non-linear data and identify hidden patterns within real-world datasets. The combination of AI and multi-omics approaches can facilitate disease diagnosis, biomarker discovery, and the prediction of treatment efficacy and prognosis. AI algorithms have been implemented in various aspects, including non-invasive tests, predictive models, image diagnosis, and the interpretation of histopathology findings. AI can support clinicians in decision-making, alleviate clinical burdens, and curtail healthcare expenses. In this review, we introduce the fundamental concepts of machine learning and review the role of AI in the management of chronic liver diseases.

Spatial mapping of the HCC landscape identifies unique intratumoral perivascular-immune neighborhoods

BACKGROUND

HCC develops in the context of chronic inflammation; however, the opposing roles the immune system plays in both the development and control of tumors are not fully understood. Mapping immune cell interactions across the distinct tissue regions could provide greater insight into the role individual immune populations have within tumors.

METHODS

A 39-parameter imaging mass cytometry panel was optimized with markers targeting immune cells, stromal cells, endothelial cells, hepatocytes, and tumor cells. We mapped the immune landscape of tumor, invasive margin, and adjacent nontumor regions across 16 resected tumors comprising 144 regions of interest. X-shift clustering and manual gating were used to characterize cell subsets, and Spectre quantified the spatial environment to identify cellular neighborhoods. Ligand-receptor communication was quantified on 2 single-cell RNA-sequencing data sets and 1 spatial transcriptomic data set.

RESULTS

We show immune cell densities remain largely consistent across these 3 regions, except for subsets of monocyte-derived macrophages, which are enriched within the tumors. Mapping cellular interactions across these regions in an unbiased manner identifies immune neighborhoods comprised of tissue-resident T cells, dendritic cells, and various macrophage populations around perivascular spaces. Importantly, we identify multiple immune cells within these neighborhoods interacting with VEGFA+ perivascular macrophages. VEGFA was further identified as a ligand for communication between perivascular macrophages and CD34+ endothelial cells.

CONCLUSIONS

Immune cell neighborhood interactions, but not cell densities, differ between intratumoral and adjacent nontumor regions in HCC. Unique intratumoral immune neighborhoods around the perivascular space point to an altered landscape within tumors. Enrichment of VEGFA+ perivascular macrophages within these tumors could play a key role in angiogenesis and vascular permeability.

The complex role of immune cells in antigen presentation and regulation of T-cell responses in hepatocellular carcinoma: progress, challenges, and future directions

Hepatocellular carcinoma (HCC) is a prevalent form of liver cancer that poses significant challenges regarding morbidity and mortality rates. In the context of HCC, immune cells play a vital role, especially concerning the presentation of antigens. This review explores the intricate interactions among immune cells within HCC, focusing on their functions in antigen presentation and the modulation of T-cell responses. We begin by summarizing the strategies that HCC uses to escape immune recognition, emphasizing the delicate equilibrium between immune surveillance and evasion. Next, we investigate the specific functions of various types of immune cells, including dendritic cells, natural killer (NK) cells, and CD8+ T cells, in the process of antigen presentation. We also examine the impact of immune checkpoints, such as cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and the pathways involving programmed cell death protein 1 (PD-1) and programmed death ligand 1 (PD-L1), on antigen presentation, while taking into account the clinical significance of checkpoint inhibitors. The review further emphasizes the importance of immune-based therapies, including cancer vaccines and CAR-T cell therapy, in improving antigen presentation. In conclusion, we encapsulate the latest advancements in research, propose future avenues for exploration, and stress the importance of innovative technologies and customized treatment strategies. By thoroughly analyzing the interactions of immune cells throughout the antigen presentation process in HCC, this review provides an up-to-date perspective on the field, setting the stage for new therapeutic approaches.

Clinicogenomic predictors of outcomes in patients with hepatocellular carcinoma treated with immunotherapy

INTRODUCTION

Immune checkpoint inhibitor (ICI) combinations extend overall survival (OS) while anti-PD-1/L1 monotherapy is non-inferior to sorafenib in treatment-naïve, patients with advanced hepatocellular carcinoma (HCC). Clinicogenomic features are posited to influence patient outcomes.

METHODS

The primary objective of this retrospective study was to define the clinical, pathologic, and genomic factors associated with outcomes to ICI therapy in patients with HCC. Patients with histologically confirmed advanced HCC treated with ICI at Memorial Sloan Kettering Cancer Center from 2012 to 2022 were included. Association between clinical, pathological, and genomic characteristics were assessed with univariable and multivariable Cox regression model for progression-free survival (PFS) and OS.

RESULTS

Two-hundred and forty-two patients were treated with ICI-based therapy. Patients were predominantly male (82%) with virally mediated HCC (53%) and Child Pugh A score (70%). Median follow-up was 28 months (0.5-78.4). Median PFS for those treated in 1st line, 2nd line and ≥ 3rd line was 4.9 (range: 2.9-6.2), 3.1 (2.3-4.0), and 2.5 (2.1-4.0) months, respectively. Median OS for those treated in 1st line, 2nd line, and ≥ 3rd line was 16 (11-22), 7.5 (6.4-11), and 6.4 (4.6-26) months, respectively. Poor liver function and performance status associated with worse PFS and OS, while viral hepatitis C was associated with favorable outcome. Genetic alterations were not associated with outcomes.

CONCLUSION

Clinicopathologic factors were the major determinates of outcomes for patients with advanced HCC treated with ICI. Molecular profiling did not aid in stratification of ICI outcomes. Future studies should explore alternative biomarkers such as the level of immune activation or the pretreatment composition of the immune tumor microenvironment.

Immunotherapy for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a major global healthcare challenge, with >1 million patients predicted to be affected annually by 2025. In contrast to other cancers, both incidence and mortality rates continue to rise, and HCC is now the third leading cause of cancer-related death worldwide. Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape for advanced HCC, with trials demonstrating a superior overall survival benefit compared to sorafenib in the first-line setting. Combination therapy with either atezolizumab (anti-PD-L1) and bevacizumab (anti-VEGF) or durvalumab (anti-PD-L1) and tremelimumab (anti-CTLA-4) is now recognised as standard of care for advanced HCC. More recently, two phase III studies of ICI-based combination therapy in the early and intermediate disease settings have successfully met their primary end points of improved recurrence- and progression-free survival, respectively. Despite these advances, and in contrast to other tumour types, there remain no validated predictive biomarkers of response to ICIs in HCC. Ongoing research efforts are focused on further characterising the tumour microenvironment in order to select patients most likely to benefit from ICI and identify novel therapeutic targets. Herein, we review the current understanding of the immune landscape in which HCC develops and the evidence for ICI-based therapeutic strategies in HCC. Additionally, we describe the state of biomarker development and novel immunotherapy approaches in HCC which have progressed beyond the pre-clinical stage and into early-phase trials.

Image-Guided Liver Biopsy: Perspectives from Interventional Radiology

Liver biopsy is a crucial aspect of interventional radiology and plays a significant role in the management of hepatobiliary diseases. Radiologists commonly perform two major image-guided liver biopsy techniques: percutaneous and transjugular approaches. It is essential for radiologists to understand the role of liver biopsy in diagnosing and treating hepatobiliary conditions, the procedural details involved, and how to manage potential complications. This article reviews the indications, contraindications, techniques, and efficacy of image-guided liver biopsy, with a focus on both percutaneous and transjugular methods.

Biomarkers for Immunotherapy Efficacy in Advanced Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC), the most common primary liver malignancy and the sixth most common cancer globally, remains fatal for many patients with inappropriate responses to treatment. Recent advancements in immunotherapy have transformed the treatment landscape for advanced HCC. However, variability in patient responses to immunotherapy highlights the need for biomarkers that can predict treatment outcomes. This manuscript comprehensively reviews the evolving role of biomarkers in immunotherapy efficacy, spanning from blood-derived indicators-alpha-fetoprotein, inflammatory markers, cytokines, circulating tumor cells, and their DNA-to tissue-derived indicators-programmed cell death ligand 1 expression, tumor mutational burden, microsatellite instability, and tumor-infiltrating lymphocytes. The current body of evidence suggests that these biomarkers hold promise for improving patient selection and predicting immunotherapy outcomes. Each biomarker offers unique insights into disease biology and the immune landscape of HCC, potentially enhancing the precision of treatment strategies. However, challenges such as methodological variability, high costs, inconsistent findings, and the need for large-scale validation in well-powered two-arm trial studies persist, making them currently unsuitable for integration into standard care. Addressing these challenges through standardized techniques and implementation of further studies will be critical for the future incorporation of these biomarkers into clinical practice for advanced HCC.

Current research status of transarterial therapies for hepatocellular carcinoma

With continuous advancements in interventional radiology, considerable progress has been made in transarterial therapies for hepatocellular carcinoma (HCC) in recent years, and an increasing number of research papers on transarterial therapies for HCC have been published. In this editorial, we comment on the article by Ma et al published in the recent issue of the World Journal of Gastro intestinal Oncology: "Efficacy and predictive factors of transarterial chemoembolization combined with lenvatinib plus programmed cell death protein-1 inhibition for unresectable HCC". We focus specifically on the current research status and future directions of transarterial therapies. In the future, more studies are needed to determine the optimal transarterial local treatment for HCC. With the emergence of checkpoint immunotherapy modalities, it is expected that the results of trials of transarterial local therapy combined with systemic therapy will bring new hope to HCC patients.

Recent developments in molecular targeted therapies for hepatocellular carcinoma in the genomic era

INTRODUCTION

Primary liver cancer is a major health problem being the sixth most frequent cancer in the world and the third cause of cancer-related death in the world. The most common histological type of liver cancer is hepatocellular carcinoma (HCC, 75-80%).

AREAS COVERED

Based on primary literature, this review provides an updated analysis of studies of genetic characterization of HCC at the level of gene mutation profiling, copy number alterations, and gene expression, with the definition of molecular subgroups and the identification of some molecular biomarkers and therapeutic targets. Recent therapeutic developments are also highlighted.

EXPERT OPINION

Deepening the understanding of the molecular complexity of HCC is progressively paving the way for the development of more personalized treatment approaches. Two important strategies involve the definition and validation of molecularly defined therapeutic targets in a subset of HCC patients and the identification of suitable biomarkers for approved systematic therapies (multikinase inhibitors and immunotherapies). The extensive molecular characterization of patients at the genomic and transcriptomic levels and the inclusion of detailed and relevant translational studies in clinical trials will represent a fundamental tool for improving the benefit of systemic therapies in HCC.

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.

Immunological Checkpoint Blockade in Anal Squamous Cell Carcinoma: Dramatic Responses Tempered By Frequent Resistance

PURPOSE OF REVIEW

Squamous cell carcinoma of the anus (SCCA) is an HPV-associated malignancy that has limited treatment options. Immunotherapy has expanded these options and here we review current and emerging immunotherapeutic approaches.

RECENT FINDINGS

Multiple studies of single-agent anti-PD1/PD-L1 immunotherapy have demonstrated a modest response rate of approximately 10% to 15%. While a minority of patients (~5%) with SCCA experience durable complete responses, most advanced SCCAs are resistant to anti-PD1/PD-L1 monotherapy. Given the need for more broadly effective immunotherapies, novel strategies, such as adaptive cell therapies and therapeutic vaccination, are being explored. To reduce the recurrence risk of localized high-risk SCCA, strategies combining immunotherapy with chemoradiation are also being investigated. While a small subset of patients with SCCA have prolonged responses to PD1-directed immunotherapy, the majority do not derive clinical benefit, and new immunotherapeutic strategies are needed. Better understanding of the immune microenvironment and predictive biomarkers could accelerate therapeutic advances.

Treatment options for advanced hepatocellular carcinoma: the potential of biologics

INTRODUCTION

Advanced hepatocellular carcinoma (HCC) represents a significant global health burden, whose treatment has been recently revolutionized by the advent of biologic treatments. Despite that, innovative therapeutic regimens and approaches, especially immune-based, remain to be explored aiming at extending the therapeutic benefits to a wider population of patients.

AREAS COVERED

This review comprehensively discusses the evolving landscape of biological treatment modalities for advanced HCC, including immune checkpoint inhibitors, antiangiogenic monoclonal antibodies, tumor-targeting monoclonal antibodies either naked or drug-conjugated, therapeutic vaccines, oncolytic viruses, adoptive cell therapies, and cytokine-based therapies. Key clinical trials and preclinical studies are examined, highlighting the actual or potential impact of these interventions in reshaping treatment paradigms for HCC.

EXPERT OPINION

Tailored and rational combination strategies, leveraging the synergistic effects of different modalities, represent a promising approach to maximize treatment efficacy in advanced HCC, which should aim at conversion endpoints to increase the fraction of patients eligible for curative approaches. The identification of predictive biomarkers holds the key to optimizing patient selection and improving therapeutic outcomes.

CXCL9 Overexpression Predicts Better HCC Response to Anti-PD-1 Therapy and Promotes N1 Polarization of Neutrophils

Background

Anti-programmed death-1 (PD1) antibodies have changed the treatment landscape for hepatocellular carcinoma (HCC) and exhibit promising treatment efficacy. However, the majority of HCCs still do not respond to anti-PD-1 therapy.

Methods

We analyzed the expression of CXCL9 in blood samples from patients who received anti-PD-1 therapy and evaluated its correlation with clinicopathological characteristics and treatment outcomes. Based on the results of Cox regression analysis, a nomogram was established for predicting HCC response to anti-PD-1 therapy. qRT‒PCR and multiple immunofluorescence assays were utilized to analyze the proportions of N1-type neutrophils in vitro and in tumor samples, respectively.

Results

The nomogram showed good predictive efficacy in the training and validation cohorts and may be useful for guiding clinical treatment of HCC patients. We also found that HCC cell-derived CXCL9 promoted N1 polarization of neutrophils in vitro and that AMG487, a specific CXCR3 inhibitor, significantly blocked this process. Moreover, multiple immunofluorescence (mIF) showed that patients with higher serum CXCL9 levels had greater infiltration of the N1 phenotype of tumor-associated neutrophils (TANs).

Conclusion

Our study highlights the critical role of CXCL9 as an effective biomarker of immunotherapy efficacy and in promoting the polarization of N1-type neutrophils; thus, targeting the CXCL9-CXCR3 axis could represent a novel pharmaceutical strategy to enhance immunotherapy for HCC.

Identification of fatty acids synthesis and metabolism-related gene signature and prediction of prognostic model in hepatocellular carcinoma

BACKGROUND

Fatty acids synthesis and metabolism (FASM)-driven lipid mobilization is essential for energy production during nutrient shortages. However, the molecular characteristics, physiological function and clinical prognosis value of FASM-associated gene signatures in hepatocellular carcinoma (HCC) remain elusive.

METHODS

The Gene Expression Omnibus database (GEO), the Cancer Genome Atlas (TCGA), and International Cancer Genome Consortium (ICGC) database were utilized to acquire transcriptome data and clinical information of HCC patients. The ConsensusClusterPlus was employed for unsupervised clustering. Subsequently, immune cell infiltration, stemness index and therapeutic response among distinct clusters were decoded. The tumor immune dysfunction and exclusion (TIDE) algorithm was utilized to anticipate the response of patients towards immunotherapy, and the genomics of drug sensitivity in cancer (GDSC) tool was employed to predict their response to antineoplastic medications. Least absolute shrinkage and selection operator (LASSO) regression analysis and protein-protein interaction (PPI) network were employed to construct prognostic model and identity hub gene. Single cell RNA sequencing (scRNA-seq) and CellChat were used to analyze cellular interactions. The hub gene of FASM effect on promoting tumor progression was confirmed through a series of functional experiments.

RESULTS

Twenty-six FASM-related genes showed differential expression in HCC. Based on these FASM-related differential genes, two molecular subtypes were established, including Cluster1 and Cluster2 subtype. Compared with cluster2, Cluster1 subtype exhibited a worse prognosis, higher risk, higher immunosuppressive cells infiltrations, higher immune escape, higher cancer stemness and enhanced treatment-resistant. PPI network identified Acetyl-CoA carboxylase1 (ACACA) as central gene of FASM and predicted a poor prognosis. A strong interaction between cancer stem cells (CSCs) with high expression of ACACA and macrophages through CD74 molecule (CD74) and integrin subunit beta 1 (ITGB1) signaling was identified. Finally, increased ACACA expression was observed in HCC cells and patients, whereas depleted ACACA inhibited the stemness straits and drug resistance of HCC cells.

CONCLUSIONS

This study provides a resource for understanding FASM heterogeneity in HCC. Evaluating the FASM patterns can help predict the prognosis and provide new insights into treatment response in HCC patients.

Adjuvant and neoadjuvant immunotherapies in hepatocellular carcinoma

Liver cancer, specifically hepatocellular carcinoma (HCC), is the sixth most common cancer and the third leading cause of cancer mortality worldwide. The development of effective systemic therapies, particularly those involving immune-checkpoint inhibitors (ICIs), has substantially improved the outcomes of patients with advanced-stage HCC. Approximately 30% of patients are diagnosed with early stage disease and currently receive potentially curative therapies, such as resection, liver transplantation or local ablation, which result in median overall survival durations beyond 60 months. Nonetheless, up to 70% of these patients will have disease recurrence within 5 years of resection or local ablation. To date, the results of randomized clinical trials testing adjuvant therapy in patients with HCC have been negative. This major unmet need has been addressed with the IMbrave 050 trial, demonstrating a recurrence-free survival benefit in patients with a high risk of relapse after resection or local ablation who received adjuvant atezolizumab plus bevacizumab. In parallel, studies testing neoadjuvant ICIs alone or in combination in patients with early stage disease have also reported efficacy. In this Review, we provide a comprehensive overview of the current approaches to manage patients with early stage HCC. We also describe the tumour immune microenvironment and the mechanisms of action of ICIs and cancer vaccines in this setting. Finally, we summarize the available evidence from phase II/III trials of neoadjuvant and adjuvant approaches and discuss emerging clinical trials, identification of biomarkers and clinical trial design considerations for future studies.

FASN Inhibition Decreases MHC-I Degradation and Synergizes with PD-L1 Checkpoint Blockade in Hepatocellular Carcinoma

Immune checkpoint inhibitors (ICI) transformed the treatment landscape of hepatocellular carcinoma (HCC). Unfortunately, patients with attenuated MHC-I expression remain refractory to ICIs, and druggable targets for upregulating MHC-I are limited. Here, we found that genetic or pharmacologic inhibition of fatty acid synthase (FASN) increased MHC-I levels in HCC cells, promoting antigen presentation and stimulating antigen-specific CD8+ T-cell cytotoxicity. Mechanistically, FASN inhibition reduced palmitoylation of MHC-I that led to its lysosomal degradation. The palmitoyltransferase DHHC3 directly bound MHC-I and negatively regulated MHC-I protein levels. In an orthotopic HCC mouse model, Fasn deficiency enhanced MHC-I levels and promoted cancer cell killing by tumor-infiltrating CD8+ T cells. Moreover, the combination of two different FASN inhibitors, orlistat and TVB-2640, with anti-PD-L1 antibody robustly suppressed tumor growth in vivo. Multiplex IHC of human HCC samples and bioinformatic analysis of The Cancer Genome Atlas data further illustrated that lower expression of FASN was correlated with a higher percentage of cytotoxic CD8+ T cells. The identification of FASN as a negative regulator of MHC-I provides the rationale for combining FASN inhibitors and immunotherapy for treating HCC.

SIGNIFICANCE

Inhibition of FASN increases MHC-I protein levels by suppressing its palmitoylation and lysosomal degradation, which stimulates immune activity against hepatocellular carcinoma and enhances the efficacy of immune checkpoint inhibition.

Critical Appraisal of Guideline Recommendations on Systemic Therapies for Advanced Hepatocellular Carcinoma: A Review

Importance

The combination of immune checkpoint inhibitors with antiangiogenic agents has revolutionized the treatment landscape of advanced hepatocellular carcinoma (HCC). However, due to rapid publication of new studies that attained their predefined primary end points, a lack of robust cross-trial comparison of first-line therapies, and diverging clinical guidelines, no clear-cut treatment flowchart and sequence of therapies are available. This critical analysis of the recommendations for the management of advanced HCC from the main scientific societies in the US and Europe adopted an integrated approach to provide information on the clinical benefit (overall survival and progression-free survival) and safety profile of these therapies using the European Society for Medical Oncology (ESMO)-Magnitude of Clinical Benefit Scale (MCBS) score and an ad hoc network meta-analysis.

Observations

There is a major consensus among guidelines that atezolizumab plus bevacizumab has a primacy as the recommended first-line treatment of choice in advanced HCC. On progression after immunotherapy-containing regimens and for patients with contraindications for immunotherapies, most guidelines maintain the established treatment hierarchy, recommending lenvatinib or sorafenib as the preferred options, followed by either regorafenib, cabozantinib, or ramucirumab. Thus far, the first-line immune-based regimen of tremelimumab plus durvalumab has been integrated only in the American Association for the Study of Liver Diseases guidance document and the latest National Comprehensive Cancer Network guidelines and has particular utility for patients with a high risk of gastrointestinal bleeding. Overall, in the first-line setting, both atezolizumab plus bevacizumab and sintilimab plus IBI305 (a bevacizumab biosimilar) and durvalumab plus tremelimumab received the highest ESMO-MCBS score of 5, indicating a substantial magnitude of clinical benefit. In a network meta-analysis, no significant differences in overall survival were found among the various combination regimens. However, the newly reported combination of camrelizumab plus rivoceranib was associated with a significantly higher risk of treatment-related adverse events compared with atezolizumab plus bevacizumab (relative risk, 1.59; 95% CI, 1.25-2.03; P < .001).

Conclusions and Relevance

This narrative review found that atezolizumab plus bevacizumab is regarded as the primary standard of care for advanced HCC in the first-line setting. These findings from integrating the recommendations from scientific societies' guidelines for managing advanced HCC along with new data from cross-trial comparisons may aid clinicians in decision-making and guide them through a rapidly evolving and complex treatment landscape.

Integrating the new systemic treatment landscape and surgical therapy in hepatocellular carcinoma

The treatment landscape of hepatocellular carcinoma has evolved rapidly within the last decade. Minimally-invasive techniques have reached a new level of safety, affording surgeons to pursue more aggressive treatment strategies to ultimately improve oncological outcomes. These procedures have been increasingly applied to treat patients with more progressed tumors and in select case even patients with advanced stage disease confined to the liver. Concomitantly, a dramatic increase in research into immunotherapy has altered the treatment paradigm in advanced disease stages, where the emerging treatment regimens can provide durable responses in a subset of the patient population for whom prognosis is dramatically improved. These treatments are now tested in early-stage disease to address the pressing unmet need of high recurrence rates after resection and in intermediate stage to complement the proven efficacy of intraarterial embolization in delaying progression. This review provides an in-depth discussion of these trends and describes how the treatment landscape has already changed and which impediments remain.

Translational research on drug development and biomarker discovery for hepatocellular carcinoma

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

Precision treatment in advanced hepatocellular carcinoma

The past decade has witnessed significant advances in the systemic treatment of advanced hepatocellular carcinoma (HCC). Nevertheless, the newly developed treatment strategies have not achieved universal success and HCC patients frequently exhibit therapeutic resistance to these therapies. Precision treatment represents a paradigm shift in cancer treatment in recent years. This approach utilizes the unique molecular characteristics of individual patient to personalize treatment modalities, aiming to maximize therapeutic efficacy while minimizing side effects. Although precision treatment has shown significant success in multiple cancer types, its application in HCC remains in its infancy. In this review, we discuss key aspects of precision treatment in HCC, including therapeutic biomarkers, molecular classifications, and the heterogeneity of the tumor microenvironment. We also propose future directions, ranging from revolutionizing current treatment methodologies to personalizing therapy through functional assays, which will accelerate the next phase of advancements in this area.

Multimodal Integrative Genomics and Pathology Analyses in Neoadjuvant Nivolumab Treatment for Intermediate and Locally Advanced Hepatocellular Carcinoma

Introduction

Immunotherapy has resulted in pathologic responses in hepatocellular carcinoma (HCC), but the benefits and molecular mechanisms of neoadjuvant immune checkpoint blockade are largely unknown.

Methods

In this study, we evaluated the efficacy and safety of preoperative nivolumab (anti-PD-1) in patients with intermediate and locally advanced HCC and determined the molecular markers for predicting treatment response.

Results

Between July 2020 and November 2021, 20 treatment-naive HCC patients with intermediate and locally advanced tumors received preoperative nivolumab at 3 mg/kg for 3 cycles prior to surgical resection. Nineteen patients underwent surgical resection on trial. Seven (36.8%) of the 19 patients had major pathologic tumor necrosis (≥60%) in the post-nivolumab resection specimens, with 3 having almost complete (>90%) tumor necrosis. The tumor necrosis was hemorrhagic and often accompanied by increased or dense immune cell infiltrate at the border of the tumors. None of the patients developed major adverse reactions contradicting hepatectomy. RNA-sequencing analysis on both pre-nivolumab tumor biopsies and post-nivolumab resected specimens showed that, in cases with major pathologic necrosis, the proportion of CD8 T cells in the HCC tissues predominantly increased after treatment. Moreover, to investigate noninvasive biomarker for nivolumab response, we evaluated the copy number variation (CNV) using target-panel sequencing on plasma cell-free DNA of the patients and derived a CNV-based anti-PD-1 score. The score correlated with the extent of tumor necrosis and was validated in a Korean patient cohort with anti-PD-1 treatment.

Conclusion

Neoadjuvant nivolumab demonstrated promising clinical activity in intermediate and locally advanced HCC patients. We also identified useful noninvasive biomarker predicting responsiveness.

γδ T Cells: A Game Changer in the Future of Hepatocellular Carcinoma Immunotherapy

Hepatocellular carcinoma (HCC) remains a global health challenge with limited treatment options and a poor prognosis for advanced-stage patients. Recent advancements in cancer immunotherapy have generated significant interest in exploring novel approaches to combat HCC. One such approach involves the unique and versatile subset of T cells known as γδ T cells. γδ T cells represent a distinct subset of T lymphocytes that differ from conventional αβ T cells in terms of antigen recognition and effector functions. They play a crucial role in immunosurveillance against various malignancies, including HCC. Recent studies have demonstrated that γδ T cells can directly recognize and target HCC cells, making them an attractive candidate for immunotherapy. In this article, we aimed to explore the role exerted by γδ T cells in the context of HCC. We investigate strategies designed to maximize the therapeutic effectiveness of these cells and examine the challenges and opportunities inherent in applying these research findings to clinical practice. The potential to bring about a revolutionary shift in HCC immunotherapy by capitalizing on the unique attributes of γδ T cells offers considerable promise for enhancing patient outcomes, warranting further investigation.

Lineage-specific regulation of PD-1 expression in early-stage hepatocellular carcinoma following 90yttrium transarterial radioembolization - Implications in treatment outcomes

BACKGROUND

Hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related deaths in the world. Liver-directed therapies, including 90Yttrium (90Y) radioembolization, play an integral role in the management of HCC with excellent response rates. This has led to clinical trials of immunotherapy in combination with 90Y. Elevated PD-1 expression and lymphopenia were recently shown as risk factors for disease progression in early-stage HCC treated with liver-directed therapies. The aim of this study was to investigate PD-1 expression dynamics in bridge/downstage to transplant in HCC patients receiving first-cycle 90Y and evaluate the impact of these changes on response rates and time-to-progression (TTP).

METHODS

Patients with HCC receiving first-cycle 90Y as a bridge to liver transplantation (n = 99) were prospectively enrolled. Blood specimens were collected before 90Y and again during routine imagining follow-up to analyze PD-1 expression via flow cytometry. Complete and objective response rates (CR and ORR) were determined using mRECIST.

RESULTS

In 84/88 patients with available follow-up imaging, 83% had a localized ORR with 63% having localized CR. For overall response, 71% and 54% experienced ORR and CR, respectively. Post-90Y PD-1 upregulation in CD8 + associated with HCC progression and decreased TTP. Treatment with 90Y was associated with an anticipated significant post-treatment drop in lymphocytes (P < 0.001) that was independent of PD-1 expression for either CD4+ or CD8+ T cells (P = 0.751 and P = 0.375) and not associated with TTP risk. The change in lymphocytes was not correlated with PD-1 expression following treatment nor TTP.

CONCLUSIONS

Elevated PD-1 expression on peripheral T cells is associated with increased risk of HCC progression and shorter time to progression in bridging/downstaging to transplant HCC patients undergoing first-cycle 90Y. Treatment-induced lymphopenia was not associated with treatment response, or increased progression risk, suggesting this anticipated adverse event does not impact short-term HCC outcomes.

Predicting T Cell-Inflamed Gene Expression Profile in Hepatocellular Carcinoma Based on Dynamic Contrast-Enhanced Ultrasound Radiomics

Purpose

The T cell-inflamed gene expression profile (GEP) quantifies 18 genes' expression indicative of a T-cell immune tumor microenvironment, playing a crucial role in the immunotherapy of hepatocellular carcinoma (HCC). Our study aims to develop a radiomics-based machine learning model using contrast-enhanced ultrasound (CEUS) for predicting T cell-inflamed GEP in HCC.

Methods

The primary cohort of HCC patients with preoperative CEUS and RNA sequencing data of tumor tissues at the single center was used to construct the model. A total of 5936 radiomics features were extracted from the regions of interest in representative images of each phase, and the least absolute shrinkage and selection operator and logistic regression were used to construct four models including three phase-specific models and an integrated model. The area under the curve (AUC) was calculated to evaluate the performance of the model. The independent cohort of HCC patients with preoperative CEUS and Immunoscore based on immunohistochemistry and digital pathology was used to validate the correlation between model prediction value and T-cell infiltration.

Results

There were 268 patients enrolled in the primary cohort and 46 patients enrolled in the independent cohort. Compared with the other three models, the AP model constructed by 36 arterial phase (AP) features showed good performance with a mean AUC of 0.905 in the 5-fold cross-validation and was easier to apply in the clinical setting. The decision curve and calibration curve confirmed the clinical utility of the model. In the independent cohort, patients with high Immunoscores showed significantly higher GEP prediction values than those with low Immunoscores (t=-2.359, p=0.029).

Conclusion

The CEUS-based model is a reliable predictive tool for T cell-inflamed GEP in HCC, and might facilitate individualized immunotherapy decision-making.

A Noninvasive Approach to Evaluate Tumor Immune Microenvironment and Predict Outcomes in Hepatocellular Carcinoma

It is widely recognized that tumor immune microenvironment (TIME) plays a crucial role in tumor progression, metastasis, and therapeutic response. Despite several noninvasive strategies have emerged for cancer diagnosis and prognosis, there are still lack of effective radiomic-based model to evaluate TIME status, let alone predict clinical outcome and immune checkpoint inhibitor (ICIs) response for hepatocellular carcinoma (HCC). In this study, we developed a radiomic model to evaluate TIME status within the tumor and predict prognosis and immunotherapy response. A total of 301 patients who underwent magnetic resonance imaging (MRI) examinations were enrolled in our study. The intra-tumoral expression of 17 immune-related molecules were evaluated using co-detection by indexing (CODEX) technology, and we construct Immunoscore (IS) with the least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression method to evaluate TIME. Of 6115 features extracted from MRI, five core features were filtered out, and the Radiomic Immunoscore (RIS) showed high accuracy in predicting TIME status in testing cohort (area under the curve = 0.753). More importantly, RIS model showed the capability of predicting therapeutic response to anti-programmed cell death 1 (PD-1) immunotherapy in an independent cohort with advanced HCC patients (area under the curve = 0.731). In comparison with previously radiomic-based models, our integrated RIS model exhibits not only higher accuracy in predicting prognosis but also the potential guiding significance to HCC immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-023-00136-8.

Biomarkers for immunotherapy of hepatocellular carcinoma

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

Targeting USP8 Inhibits O-GlcNAcylation of SLC7A11 to Promote Ferroptosis of Hepatocellular Carcinoma via Stabilization of OGT

Hepatocellular carcinoma (HCC) is a lethal and aggressive human malignancy. The present study examins the anti-tumor effects of deubiquitylating enzymes (DUB) inhibitors in HCC. It is found that the inhibitor of ubiquitin specific peptidase 8 (USP8) and DUB-IN-3 shows the most effective anti-cancer responses. Targeting USP8 inhibits the proliferation of HCC and induces cell ferroptosis. In vivo xenograft and metastasis experiments indicate that inhibition of USP8 suppresses tumor growth and lung metastasis. DUB-IN-3 treatment or USP8 depletion decrease intracellular cystine levels and glutathione biosynthesis while increasing the accumulation of reactive oxygen species (ROS). Mechanistical studies reveal that USP8 stabilizes O-GlcNAc transferase (OGT) via inhibiting K48-specific poly-ubiquitination process on OGT protein at K117 site, and STE20-like kinase (SLK)-mediated S716 phosphorylation of USP8 is required for the interaction with OGT. Most importantly, OGT O-GlcNAcylates solute carrier family 7, member 11 (SLC7A11) at Ser26 in HCC cells, which is essential for SLC7A11 to import the cystine from the extracellular environment. Collectively, this study demonstrates that pharmacological inhibition or knockout of USP8 can inhibit the progression of HCC and induce ferroptosis via decreasing the stability of OGT, which imposes a great challenge that targeting of USP8 is a potential approach for HCC treatment.

The Extended Surgical Concepts for Hepatocellular Carcinoma in the Era of Immune Checkpoint Inhibitors

Surgical resection remains one of the most effective curative therapies for HCC. However, the majority of patients have advanced unresectable diseases upon presentation. It is of paramount importance to raise the resectability of patients with HCC. The remarkable objective response rate reported by Phase III IMbrave150 trial has led to the concept of "Atezo/Bev followed by curative conversion (ABC conversion)" for initially unresectable HCC. With this revolutionary treatment strategy, the concept of surgical resection for HCC should be amended. The current opinion illustrated three extended surgical concepts, which could be integrated into clinical practice in the era of immune checkpoint inhibitors (ICI).

Identifying endoplasmic reticulum stress-related molecular subtypes and prognostic model for predicting the immune landscape and therapy response in pancreatic cancer

Endoplasmic reticulum stress (ERS) is caused by the accumulation of intracellular misfolded or unfolded proteins and is associated with cancer development. In this study, pan-cancer analysis revealed complex genetic variations, including copy number variation, methylation, and somatic mutations for ERS-related genes (ERGs) in 33 kinds of cancer. Consensus clustering divided pancreatic cancer (PC) patients from TCGA and GEO databases into two ERS-related subtypes: ERGcluster A and B. Compared with ERGcluster A, ERGcluster B had a more active ERS state and worse prognosis. Subsequently, the ERS-related prognostic model was established to quantify the ERS score for a single sample. The patient with a low ERS score had remarkably longer survival times. ssGSEA and CIBERSORT algorithms revealed that activated B cells and CD8+ T cells had higher infiltration in the low ERS score group, but higher infiltration of activated CD4+ T cells, activated dendritic cells, macrophages, and neutrophils in the high ERS score group. Drug sensitivity analysis indicated the low ERS score group had a better response to gemcitabine, paclitaxel, 5-fluorouracil, oxaliplatin, and irinotecan. RT-qPCR validated that MET, MUC16, and KRT7 in the model had higher expression levels in pancreatic tumour tissues. Single-cell analysis further revealed that MET, MUC16, and KRT7 were mainly expressed in cancer cells in PC tumour microenvironment. In all, we first constructed the ERS-related molecular subtypes and prognostic model in PC. Our research highlighted the vital role of ERS in PC and contributed to further research on molecular mechanisms and novel therapeutic strategies for PC in the future.

Immunotherapy for Advanced Hepatocellular Carcinoma-a Large Tertiary Center Experience

INTRODUCTION

Combination of immune-checkpoint inhibitor (ICI) and vascular endothelial growth factor (VEGF) antagonist has become the first line systemic treatment for advanced hepatocellular carcinoma (HCC). However, two-thirds of patients do not respond to ICI-based treatments and biomarkers for response remain elusive.

METHODS

Patients with advanced HCC who received Atezolizumab/Bevacizumab combination or Nivolumab during 2016-2022 were identified in our Liver Cancer Database. Retrospective review of their clinical data was performed to investigate parameters that could be predictive of immunotherapy response.

RESULTS

96 patients received Atezolizumab/Bevacizumab (n=60) or Nivolumab (n=36). Median age at diagnosis was 67.1 years. 70 patients had received treatment and 26 patients were treatment naïve before starting immunotherapy. Mean pre-treatment AFP was 9780.7 (±32035) ng/mL. Confirmed objective response (complete or partial) was seen in 29% of the population (n=27). Disease remained stable in 12% (n=11) and progressed in 60% (n=56). On univariate analysis, pre-treatment AFP>400 ng/mL was associated with objective response (OR=4.5, 95% CI:1.7-11.9, p=0.0015), while white race (OR=0.35, 95% CI:0.13-0.92, p=0.030) and prior radiotherapy (OR=0.14, 95% CI:0.01-1.1, p=0.033) or systemic therapy with TKIs (OR=0.25, 95% CI:0.08-0.81, p=0.017) were associated with poor response. On multivariate analysis only AFP>400 ng/mL remained associated with response (OR=3.7, 95% CI:1.3-10.5, p=0.014). Overall survival (OS) at one and three years was 86% and 43% in responders, and 45% and 29% in non-responders, respectively.

CONCLUSION

In our institutional experience, treatment naivety and pre-treatment AFP>400 ng/mL were associated with objective response. Prospective studies aimed at identifying factors associated with response to immunotherapy will aide patient selection.

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.

Current Evidence for Immune Checkpoint Inhibition in Advanced Hepatocellular Carcinoma

The treatment of advanced unresectable HCC (aHCC) remains a clinical challenge, with limited therapeutic options and poor prognosis. The results of IMbrave150 and HIMALAYA have changed the treatment paradigm for HCC and established immune checkpoint inhibition (ICI), either combined with anti-angiogenic therapy or dual ICI, as preferred first-line therapy for eligible patients with aHCC. Numerous other combination regimens involving ICI are under investigation with the aim of improving the tumour response and survival of patients with all stages of HCC. This review will explore the current evidence for ICI in patients with advanced HCC and discuss future directions, including the unmet clinical need for predictive biomarkers to facilitate patient selection, the effects of cirrhosis aetiology on response to ICI, and the safety of its use in patients with impaired liver function.

Advances in Histological and Molecular Classification of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a primary liver cancer characterized by hepatocellular differentiation. HCC is molecularly heterogeneous with a wide spectrum of histopathology. The prognosis of patients with HCC is generally poor, especially in those with advanced stages. HCC remains a diagnostic challenge for pathologists because of its morphological and phenotypic diversity. However, recent advances have enhanced our understanding of the molecular genetics and histological subtypes of HCC. Accurate diagnosis of HCC is important for patient management and prognosis. This review provides an update on HCC pathology, focusing on molecular genetics, histological subtypes, and diagnostic approaches.

Delivery of sPD1 gene by anti-CD133 antibody conjugated microbubbles combined with ultrasound for the treatment of cervical cancer in mice

To explore new therapeutic options for cervical cancer, the inhibitory effect on cervical cancer of targeted CD133-loaded sPD1 gene microbubbles (MBs) combined with low-frequency ultrasound was studied and its mechanism was explored. We prepared microbubbles conjugated with anti-CD133 antibody to deliver the sPD1 gene and determined concentration, particle size, and potentials of MBs. In addition, we verified that CD133 targeted-MBs could specifically bind to U14 cervical cancer cells in vitro. A mouse model of subcutaneous xenograft cervical cancer was established and mice were divided into a control group, an non-targeted microbubble group, a CD133-MBs group, an sPD1-MBs group and a CD133/sPD1-MBs group. Compared with the control group, tumor growth was inhibited in each group, with the CD133/sPD1 group showing the strongest inhibitory effect after treatment. The tumor volume and weight inhibition rates in the CD133/sPD1-MBs group were 78.01% and 72.25% respectively, which were statistically different from the other groups (P < 0.05), and HE staining and TUNEL immunofluorescence showed necrosis and apoptosis in tumor tissue. Flow cytometry, lactate dehydrogenase, and indirect immunofluorescence experiments showed that T lymphocytes were activated and a large number of CD8-positive T cells infiltrated the tumor tissue after treatment, with the CD133/sPD1-MBs group showing the most prominent effects (P < 0.05). The combination of ultrasound with anti- CD133 antibody-conjugated microbubbles loaded with the sPD1 gene can inhibit the growth of cervical cancer, suggesting that the immunosuppressive microenvironment of the tumor is improved after treatment.

Unleashing the efficacy of immune checkpoint inhibitors for advanced hepatocellular carcinoma: factors, strategies, and ongoing trials

Hepatocellular carcinoma (HCC) is a prevalent primary liver cancer, representing approximately 85% of cases. The diagnosis is often made in the middle and late stages, necessitating systemic treatment as the primary therapeutic option. Despite sorafenib being the established standard of care for advanced HCC in the past decade, the efficacy of systemic therapy remains unsatisfactory, highlighting the need for novel treatment modalities. Recent breakthroughs in immunotherapy have shown promise in HCC treatment, particularly with immune checkpoint inhibitors (ICIs). However, the response rate to ICIs is currently limited to approximately 15%-20% of HCC patients. Recently, ICIs demonstrated greater efficacy in "hot" tumors, highlighting the urgency to devise more effective approaches to transform "cold" tumors into "hot" tumors, thereby enhancing the therapeutic potential of ICIs. This review presented an updated summary of the factors influencing the effectiveness of immunotherapy in HCC treatment, identified potential combination therapies that may improve patient response rates to ICIs, and offered an overview of ongoing clinical trials focusing on ICI-based combination therapy.

Potential Predictive Biomarkers of Systemic Drug Therapy for Hepatocellular Carcinoma: Anticipated Usefulness in Clinical Practice

In the systemic drug treatment of hepatocellular carcinoma, only the tyrosine kinase inhibitor (TKI) sorafenib was available for a period. This was followed by the development of regorafenib as a second-line treatment after sorafenib, and then lenvatinib, a new TKI, proved non-inferiority to sorafenib and became available as a first-line treatment. Subsequently, cabozantinib, another TKI, was introduced as a second-line treatment, along with ramucirumab, the only drug proven to be predictive of therapeutic efficacy when AFP levels are >400 ng/mL. It is an anti-VEGF receptor antibody. More recently, immune checkpoint inhibitors have become the mainstay of systemic therapy and can now be used as a first-line standard treatment for HCC. However, the objective response rate for these drugs is currently only 30% to 40%, and there is a high incidence of side effects. Additionally, there are no practical biomarkers to predict their therapeutic effects. Therefore, this review provides an overview of extensive research conducted on potential HCC biomarkers from blood, tissue, or imaging information that can be used in practice to predict the therapeutic efficacy of systemic therapy before its initiation.