An Immune Gene Expression Signature Associated With Development of Human Hepatocellular Carcinoma Identifies Mice That Respond to Chemopreventive Agents

Bulk and single-cell transcriptome reveal the immuno-prognostic subtypes and tumour microenvironment heterogeneity in HCC

BACKGROUND & AIMS

Accumulating evidences suggest tumour microenvironment (TME) profoundly influence clinical outcome in hepatocellular carcinoma (HCC). Existing immune subtypes are susceptible to batch effects, and integrative analysis of bulk and single-cell transcriptome is helpful to recognize immune subtypes and TME in HCC.

METHODS

Based on the relative expression ordering (REO) of 1259 immune-related genes, an immuno-prognostic signature was developed and validated in 907 HCC samples from five bulk transcriptomic cohorts, including 72 in-house samples. The machine learning models based on subtype-specific gene pairs with stable REOs were constructed to jointly predict immuno-prognostic subtypes in single-cell RNA-seq data and validated in another single-cell data. Then, cancer characteristics, immune landscape, underlying mechanism and therapeutic benefits between subtypes were analysed.

RESULTS

An immune-related signature with 29 gene pairs stratified HCC samples individually into two risk subgroups (C1 and C2), which was an independent prognostic factor for overall survival. The machine learning models verified the immune subtypes from five bulk cohorts to two single-cell transcriptomic data. Integrative analysis revealed that C1 had poorer outcomes, higher CNV burden and malignant scores, higher sensitivity to sorafenib, and exhibited an immunosuppressive phenotype with more regulators, e.g., myeloid-derived suppressor cells (MDSCs), Mø_SPP1, while C2 was characterized with better outcomes, higher metabolism, more benefit from immunotherapy, and displayed active immune with more effectors, e.g., tumour infiltrating lymphocyte and dendritic cell. Moreover, both two single-cell data revealed the crosstalk of SPP1-related L-R pairs between cancer and immune cells, especially SPP1-CD44, might lead to immunosuppression in C1.

CONCLUSIONS

The REO-based immuno-prognostic subtypes were conducive to individualized prognosis prediction and treatment options for HCC. This study paved the way for understanding TME heterogeneity between immuno-prognostic subtypes of HCC.

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.

Prognostic Factors for Patients with Proliferative Hepatocellular Carcinoma After Liver Resection

Purpose

There is a scarcity of predictive models currently accessible for prognosticating proliferative hepatocellular carcinoma (HCC), an integrated class of subtype, characterized by a dismal prognosis. Consequently, this study aimed to develop and validate a novel prognostic model capable of accurately predicting the prognosis of proliferative HCC after curative resection.

Patients and Methods

This retrospective multicenter study included patients with solitary HCC who underwent curative liver resection from August 2014 to December 2020 (n = 816). Patients were stratified into either the proliferative HCC cohort (n = 259) or the nonproliferative HCC cohort (n = 557) based on histological criteria. Disease-free survival (DFS) was compared between the two groups before and after one-to-one propensity score matching (PSM). Of all the proliferative HCC patients, 203 patients were assigned to training cohort, and 56 patients were assigned to validation cohort. Univariate and multivariate analyses were performed in training cohort to identify risk factors associated with worse DFS. Thereafter, a predictive model was constructed, subsequently validated in the validation cohort.

Results

The DFS of proliferative HCC was significantly worse than nonproliferative HCC before and after PSM. Meanwhile, multivariate regression analysis revealed that liver cirrhosis (P = 0.032) and larger tumor size (P = 0.000) were independent risk factors of worse DFS. Lastly, the discriminative abilities of the predictive model for 1, 3, 5-year DFS rates, as determined by receiver operating characteristic (ROC) curves, were 0.702, 0.720, and 0.809 in the training cohort and 0.752, 0.776, and 0.851 in the validation cohort, respectively.

Conclusion

This study developed a predictive model with satisfactory accuracy to predict the worse DFS in proliferative HCCs after liver resection. Moreover, this predictive model may serve as a valuable tool for clinicians to predict postoperative HCC recurrence, thereby enabling them to implement early preventative strategies.

Insights into Hepatocellular Carcinoma in Patients with Thalassemia: From Pathophysiology to Novel Therapies

Thalassemia is a heterogeneous congenital hemoglobinopathy common in the Mediterranean region, Middle East, Indian subcontinent, and Southeast Asia with increasing incidence in Northern Europe and North America due to immigration. Iron overloading is one of the major long-term complications in patients with thalassemia and can lead to organ damage and carcinogenesis. Hepatocellular carcinoma (HCC) is one of the most common malignancies in both transfusion-dependent thalassemia (TDT) and non-transfusion-dependent thalassemia (NTDT). The incidence of HCC in patients with thalassemia has increased over time, as better chelation therapy confers a sufficiently long lifespan for the development of HCC. The mechanisms of iron-overloading-associated HCC development include the increased reactive oxygen species (ROS), inflammation cytokines, dysregulated hepcidin, and ferroportin metabolism. The treatment of HCC in patients with thalassemia was basically similar to those in general population. However, due to the younger age of HCC onset in thalassemia, regular surveillance for HCC development is mandatory in TDT and NTDT. Other supplemental therapies and experiences of novel treatments for HCC in the thalassemia population were also reviewed in this article.

Non-Classical HLA Class 1b and Hepatocellular Carcinoma

A number of studies are underway to gain a better understanding of the role of immunity in the pathogenesis of hepatocellular carcinoma and to identify subgroups of individuals who may benefit the most from systemic therapy according to the etiology of their tumor. Human leukocyte antigens play a key role in antigen presentation to T cells. This is fundamental to the host's defense against pathogens and tumor cells. In addition, HLA-specific interactions with innate lymphoid cell receptors, such those present on natural killer cells and innate lymphoid cell type 2, have been shown to be important activators of immune function in the context of several liver diseases. More recent studies have highlighted the key role of members of the non-classical HLA-Ib and the transcript adjacent to the HLA-F locus, FAT10, in hepatocarcinoma. The present review analyzes the major contribution of these molecules to hepatic viral infection and hepatocellular prognosis. Particular attention has been paid to the association of natural killer and Vδ2 T-cell activation, mediated by specific HLA class Ib molecules, with risk assessment and novel treatment strategies to improve immunotherapy in HCC.

Three-dimensional multifrequency magnetic resonance elastography improves preoperative assessment of proliferative hepatocellular carcinoma

BACKGROUND

To investigate the viscoelastic signatures of proliferative hepatocellular carcinoma (HCC) using three-dimensional (3D) magnetic resonance elastography (MRE).

METHODS

This prospective study included 121 patients with 124 HCCs as training cohort, and validation cohort included 33 HCCs. They all underwent preoperative conventional magnetic resonance imaging (MRI) and tomoelastography based on 3D multifrequency MRE. Viscoelastic parameters of the tumor and liver were quantified as shear wave speed (c, m/s) and loss angle (φ, rad), representing stiffness and fluidity, respectively. Five MRI features were evaluated. Multivariate logistic regression analyses were used to determine predictors of proliferative HCC to construct corresponding nomograms.

RESULTS

In training cohort, model 1 (Combining cirrhosis, hepatitis virus, rim APHE, peritumoral enhancement, and tumor margin) yielded an area under the curve (AUC), sensitivity, specificity, accuracy of 0.72, 58.73%,78.69%, 67.74%, respectively. When adding MRE properties (tumor c and tumor φ), established model 2, the AUC increased to 0.81 (95% CI 0.72-0.87), with sensitivity, specificity, accuracy of 71.43%, 81.97%, 75%, respectively. The C-index of nomogram of model 2 was 0.81, showing good performance for proliferative HCC. Therefore, integrating tumor c and tumor φ can significantly improve the performance of preoperative diagnosis of proliferative HCC (AUC increased from 0.72 to 0.81, p = 0.012). The same finding was observed in the validation cohort, with AUC increasing from 0.62 to 0.77 (p = 0.021).

CONCLUSIONS

Proliferative HCC exhibits low stiffness and high fluidity. Adding MRE properties (tumor c and tumor φ) can improve performance of conventional MRI for preoperative diagnosis of proliferative HCC.

CRITICAL RELEVANCE STATEMENT

We investigated the viscoelastic signatures of proliferative hepatocellular carcinoma (HCC) using three-dimensional (3D) magnetic resonance elastography (MRE), and find that adding MRE properties (tumor c and tumor φ) can improve performance of conventional MRI for preoperative diagnosis of proliferative HCC.

Curcumin Alleviates Arsenic Trioxide-Induced Inflammation and Pyroptosis via the NF-κB/NLRP3 Signaling Pathway in the Hypothalamus of Ducks

Arsenic (As) as a neurotoxic environmental pollutant has attracted extensive attention. Curcumin (Cur) is a natural antioxidant that shows an excellent protective effect against arsenic trioxide (ATO)-induced toxicity in many animal organs. However, the mechanism of Cur against ATO-induced hypothalamic toxicity in ducks has not yet been fully elucidated. Here, ducks were treated with ATO and/or Cur during 28 days; the results showed that ATO exposure induced growth retardation, messy feathers, and abnormal posture in ducks. Moreover, ATO caused neuron vacuolar degeneration and disintegration in the hypothalamus of ducks. Simultaneously, ATO induced blood-brain barrier damage, downregulated the expression of ZO-1, Occludin, and mediated NF-κB activation, resulting in an increase in inflammatory factors (TLR-4, NF-κB, TNF-α, IL-2, and IL-6). Furthermore, ATO increased the production of pyroptosis-related factors (Caspase-1, IL-18, IL-1), exacerbating the inflammatory damage through NLRP3-mediated inflammasome activation. Cur, on the other hand, exerted excellent inhibitory effects on inflammation and pyroptosis. In summary, our study revealed that ATO triggered inflammation and pyroptosis by modulating NF-κB/NLRP3 signaling pathways in the hypothalamus of ducks, and Cur can alleviate inflammation and pyroptosis caused by ATO. Therefore, as a plant extract, Cur has the potential to prevent and cure ATO-induced hypothalamus toxicity.

Classification and survival prediction in early-stage cirrhosis by gene expression profiling

Liver cirrhosis has been increasingly diagnosed at an early stage owing to the non-invasive diagnostic techniques. However, it is difficult to identify patients at high risk of disease progression. Screening cirrhotic patients with poor prognosis who are most in need of surveillance is still challenging. Gene expression data GSE15654 and GSE14520 were downloaded for performing unsupervised clustering analysis. The prognostic differences between the different clusters were explored by Cox regression. Integrative analysis of gene expression signature, immune cell enrichments and clinical characterization was performed for different clusters. Two distinctive subclasses were identified in HCV-related GSE15654, and Kaplan-Meier analysis indicated that subtype 2 had lower survival rates than subtype 1 (p = 0.0399). Further analysis revealed subtype 2 had a higher density of follicular T helper cells, resting natural killer cells and M0, M2 macrophages while subtype 1 with a higher fraction of naive B cells, memory B cells, resting memory CD 4 T cells, activated natural killer cells and monocytes. 226 differentially expressed genes were identified between the two subtypes, and Reactome analysis showed the mainly enriched pathways were biological oxidations and fatty acid metabolism. Five hub genes (AKT1, RPS16, CDC42, CCND1 and PCBP2) and three significant modules were extracted from the PPI network. The results were validated in HBV-related GSE14520 cohort. We identified two subtypes of patients with different prognosis for hepatitis C-related early-stage liver cirrhosis. Bioinformatics analysis of the gene expression and immune cell profile may provide fresh insight into understanding the prognosis difference.

Crosstalk between 5-methylcytosine and N6-methyladenosine machinery defines disease progression, therapeutic response and pharmacogenomic landscape in hepatocellular carcinoma

BACKGROUND

Accumulated evidence highlights the significance of the crosstalk between epigenetic and epitranscriptomic mechanisms, notably 5-methylcytosine (5mC) and N⁶-methyladenosine (m⁶A). Herein, we conducted a widespread analysis regarding the crosstalk between 5mC and m⁶A regulators in hepatocellular carcinoma (HCC).

METHODS

Pan-cancer genomic analysis of the crosstalk between 5mC and m⁶A regulators was presented at transcriptomic, genomic, epigenetic, and other multi-omics levels. Hub 5mC and m⁶A regulators were summarized to define an epigenetic and epitranscriptomic module eigengene (EME), which reflected both the pre- and post-transcriptional modifications.

RESULTS

5mC and m⁶A regulators interacted with one another at the multi-omic levels across pan-cancer, including HCC. The EME scoring system enabled to greatly optimize risk stratification and accurately predict HCC patients' clinical outcomes and progression. Additionally, the EME accurately predicted the responses to mainstream therapies (TACE and sorafenib) and immunotherapy as well as hyper-progression. In vitro, 5mC and m⁶A regulators cooperatively weakened apoptosis and facilitated proliferation, DNA damage repair, G2/M arrest, migration, invasion and epithelial-to-mesenchymal transition (EMT) in HCC cells. The EME scoring system was remarkably linked to potential extrinsic and intrinsic immune escape mechanisms, and the high EME might contribute to a reduced copy number gain/loss frequency. Finally, we determined potential therapeutic compounds and druggable targets (TUBB1 and P2RY4) for HCC patients with high EME.

CONCLUSIONS

Our findings suggest that HCC may result from a unique synergistic combination of 5mC-epigenetic mechanism mixed with m⁶A-epitranscriptomic mechanism, and their crosstalk defines therapeutic response and pharmacogenomic landscape.

Significance of Identifying Key Genes Involved in HBV-Related Hepatocellular Carcinoma for Primary Care Surveillance of Patients with Cirrhosis

Cirrhosis is frequently the final stage of disease preceding the development of hepatocellular carcinoma (HCC) and is one of the risk factors for HCC. Preventive surveillance for early HCC in patients with cirrhosis is advantageous for achieving early HCC prevention and diagnosis, thereby enhancing patient prognosis and reducing mortality. However, there is no highly sensitive diagnostic marker for the clinical surveillance of HCC in patients with cirrhosis, which significantly restricts its use in primary care for HCC. To increase the accuracy of illness diagnosis, the study of the effective and sensitive genetic biomarkers involved in HCC incidence is crucial. In this study, a set of 120 significantly differentially expressed genes (DEGs) was identified in the GSE121248 dataset. A protein-protein interaction (PPI) network was constructed among the DEGs, and Cytoscape was used to extract hub genes from the network. In TCGA database, the expression levels, correlation analysis, and predictive performance of hub genes were validated. In total, 15 hub genes showed increased expression, and their positive correlation ranged from 0.80 to 0.90, suggesting they may be involved in the same signaling pathway governing HBV-related HCC. The GSE10143, GSE25097, GSE54236, and GSE17548 datasets were used to investigate the expression pattern of these hub genes in the progression from cirrhosis to HCC. Using Cox regression analysis, a prediction model was then developed. The ROC curves, DCA, and calibration analysis demonstrated the superior disease prediction accuracy of this model. In addition, using proteomic analysis, we investigated whether these key hub genes interact with the HBV-encoded oncogene X protein (HBx), the oncogenic protein in HCC. We constructed stable HBx-expressing LO2-HBx and Huh-7-HBx cell lines. Co-immunoprecipitation coupled with mass spectrometry (Co-IP/MS) results demonstrated that CDK1, RRM2, ANLN, and HMMR interacted specifically with HBx in both cell models. Importantly, we investigated 15 potential key genes (CCNB1, CDK1, BUB1B, ECT2, RACGAP1, ANLN, PBK, TOP2A, ASPM, RRM2, NEK2, PRC1, SPP1, HMMR, and DTL) participating in the transformation process of HBV infection to HCC, of which 4 hub genes (CDK1, RRM2, ANLN, and HMMR) probably serve as potential oncogenic HBx downstream target molecules. All these findings of our study provided valuable research direction for the diagnostic gene detection of HBV-related HCC in primary care surveillance for HCC in patients with cirrhosis.

Hepatitis B virus pathogenesis relevant immunosignals uncovering amino acids utilization related risk factors guide artificial intelligence-based precision medicine

Background: Although immune microenvironment-related chemokines, extracellular matrix (ECM), and intrahepatic immune cells are reported to be highly involved in hepatitis B virus (HBV)-related diseases, their roles in diagnosis, prognosis, and drug sensitivity evaluation remain unclear. Here, we aimed to study their clinical use to provide a basis for precision medicine in hepatocellular carcinoma (HCC) via the amalgamation of artificial intelligence. Methods: High-throughput liver transcriptomes from Gene Expression Omnibus (GEO), NODE (https://www.bio.sino.org/node), the Cancer Genome Atlas (TCGA), and our in-house hepatocellular carcinoma patients were collected in this study. Core immunosignals that participated in the entire diseases course of hepatitis B were explored using the "Gene set variation analysis" R package. Using ROC curve analysis, the impact of core immunosignals and amino acid utilization related gene on hepatocellular carcinoma patient's clinical outcome were calculated. The utility of core immunosignals as a classifier for hepatocellular carcinoma tumor tissue was evaluated using explainable machine-learning methods. A novel deep residual neural network model based on immunosignals was constructed for the long-term overall survival (LS) analysis. In vivo drug sensitivity was calculated by the "oncoPredict" R package. Results: We identified nine genes comprising chemokines and ECM related to hepatitis B virus-induced inflammation and fibrosis as CLST signals. Moreover, CLST was co-enriched with activated CD4+ T cells bearing harmful factors (aCD4) during all stages of hepatitis B virus pathogenesis, which was also verified by our hepatocellular carcinoma data. Unexpectedly, we found that hepatitis B virus-hepatocellular carcinoma patients in the CLST^highaCD4^high subgroup had the shortest overall survival (OS) and were characterized by a risk gene signature associated with amino acids utilization. Importantly, characteristic genes specific to CLST/aCD4 showed promising clinical relevance in identifying patients with early-stage hepatocellular carcinoma via explainable machine learning. In addition, the 5-year long-term overall survival of hepatocellular carcinoma patients can be effectively classified by CLST/aCD4 based GeneSet-ResNet model. Subgroups defined by CLST and aCD4 were significantly involved in the sensitivity of hepatitis B virus-hepatocellular carcinoma patients to chemotherapy treatments. Conclusion: CLST and aCD4 are hepatitis B virus pathogenesis-relevant immunosignals that are highly involved in hepatitis B virus-induced inflammation, fibrosis, and hepatocellular carcinoma. Gene set variation analysis derived immunogenomic signatures enabled efficient diagnostic and prognostic model construction. The clinical application of CLST and aCD4 as indicators would be beneficial for the precision management of hepatocellular carcinoma.

A novel risk score based on immune-related genes for hepatocellular carcinoma as a reliable prognostic biomarker and correlated with immune infiltration

BACKGROUND

Immunological-related genes (IRGs) play a critical role in the immune microenvironment of tumors. Our study aimed to develop an IRG-based survival prediction model for hepatocellular carcinoma (HCC) patients and to investigate the impact of IRGs on the immune microenvironment.

METHODS

Differentially expressed IRGs were obtained from The Genomic Data Commons Data Portal (TCGA) and the immunology database and analysis portal (ImmPort). The univariate Cox regression was used to identify the IRGs linked to overall survival (OS), and a Lasso-regularized Cox proportional hazard model was constructed. The International Cancer Genome Consortium (ICGC) database was used to verify the prediction model. ESTIMATE and CIBERSORT were used to estimate immune cell infiltration in the tumor immune microenvironment (TIME). RNA sequencing was performed on HCC tissue specimens to confirm mRNA expression.

RESULTS

A total of 401 differentially expressed IRGs were identified, and 63 IRGs were found related to OS on the 237 up-regulated IRGs by univariate Cox regression analyses. Finally, five IRGs were selected by the LASSO Cox model, including SPP1, BIRC5, STC2, GLP1R, and RAET1E. This prognostic model demonstrated satisfactory predictive value in the ICGC dataset. The risk score was an independent predictive predictor for OS in HCC patients. Immune-related analysis showed that the immune infiltration level in the high-risk group was higher, suggesting that the 5-IRG signature may play an important role in mediating immune escape and immune resistance in the TIME of HCC. Finally, we confirmed the 5-IRG signature is highly expressed in 65 HCC patients with good predictive power.

CONCLUSION

We established and verified a new prognosis model for HCC patients based on survival-related IRGs, and the signature could provide new insights into the prognosis of HCC.

Expression, Prognostic Value, and Functional Mechanism of Polarity-Related Genes in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and poor prognoses around the world. Within-cell polarity is crucial to cell development and function maintenance, and some studies have found that it is closely related to cancer initiation, metastasis, and prognosis. The aim of our research was to find polarity-related biomarkers which improve the treatment and prognosis of HCC. For the knowledge-driven analysis, 189 polarity-related genes (PRGs) were retrieved and curated manually from the molecular signatures database and reviews. Meanwhile, in the data-driven part, genomic datasets and clinical records of HCC was obtained from the cancer genome atlas database. The potential candidates were considered in the respect to differential expression, mutation rate, and prognostic value. Sixty-one PRGs that passed the knowledge and data-driven screening were applied for function analysis and mechanism deduction. Elastic net model combing least absolute shrinkage and selection operator and ridge regression analysis refined the input into a 12-PRG risk model, and its pharmaceutical potency was evaluated. These findings demonstrated that the integration of multi-omics of PRGs can help us in untangling the liver cancer pathogenesis as well as illustrate the underlying mechanisms and therapeutic targets.

Signature construction and molecular subtype identification based on cuproptosis-related genes to predict the prognosis and immune activity of patients with hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignancies in the world, with high incidence, high malignancy, and low survival rate. Cuproptosis is a novel form of cell death mediated by lipoylated TCA cycle proteins-mediated novel cell death pathway and is highly associated with mitochondrial metabolism. However, the relationship between the expression level of cuproptosis-related genes (CRGs) and the prognosis of HCC is still unclear.

Methods

Combining the HCC transcriptomic data from The Cancer Genome Atlas(TCGA) and Gene Expression Omnibus (GEO) databases, we identified the differentially expressed cuproptosis-related genes (DECRGs) and obtained the prognosis-related DECRGs through univariate regression analysis.LASSO and multivariate COX regression analyses of these DECRGs yielded four genes that were used to construct the signature. Next, we use ROC curves to evaluate the performance of signatures. The tumor microenvironment, immune infiltration, tumor mutation load, half-maximum suppression concentration, and immunotherapy effects were also compared between the low-risk and high-risk groups. Finally, we analyzed the expression level, prognosis, and immune infiltration correlation on the four genes that constructed the model.

Results

Four DECRGs s were used to construct the signature. The ROC curves indicated that signature can better assess the prognosis of HCC patients. Patients were grouped according to the signature risk score. Patients in the low-risk group had a significantly longer survival time than those in the high-risk group. Furthermore, the tumor mutation burden (TMB) values were associated with the risk score and the higher-risk group had a higher proportion of TP53 mutations than the low-risk group.ESTIMATE analysis showed significant differences in stromal scores between the two groups.N6-methyladenosine (m6A) and multiple immune checkpoints were expressed at higher levels in the high-risk group. Then, we found that signature score correlated with chemotherapeutic drug sensitivity and immunotherapy efficacy in HCC patients. Finally, we further confirmed that the four DECRGs genes were associated with the prognosis of HCC through external validation.

Conclusions

We studied from the cuproptosis perspective and developed a new prognostic feature to predict the prognosis of HCC patients. This signature with good performance will help physicians to evaluate the overall prognosis of patients and may provide new ideas for clinical decision-making and treatment strategies.

Molecular Classification of Hepatocellular Carcinoma Using Wnt-Hippo Signaling Pathway-Related Genes

Simple Summary

The characters of Taiwanese hepatocellular carcinoma (HCC) are different from other parts of the world. We characterized the molecular features of HCC using a newly developed classification system based on the expression of the Wnt–Hippo signaling pathway-related genes. We analyzed the data in terms of prognostic value, transcriptome features, immune infiltration, and clinical characteristics, and compared the resulting subclasses with previously published classifications. A new molecular classification method based on a 272 gene panel of Wnt–Hippo pathways that may provide a new target for the treatment.

Abstract

In Taiwan, a combination of hepatitis B and C infection, economic boom-related food and alcohol overconsumption, and Chinese medicine prescriptions has led to a high rate of hepatocellular carcinoma (HCC). However, the causative factors and underlying tumor biology for this unique HCC environment have not been identified. Wnt and Hippo signaling pathways play an important regulatory role in HCC development, and their functions are generally considered as positive and negative regulators of cell proliferation, respectively. In this study, we characterized the molecular features of HCC using a newly developed classification system based on the expression of the Wnt–Hippo signaling pathway-related genes. RNA sequencing (RNA-Seq) was performed on liver tumor tissues from 100 patients with liver cancer. RNA-Seq data for 272 previously characterized Wnt–Hippo signaling pathway-related genes were used for hierarchical clustering. We analyzed the data in terms of prognostic value, transcriptome features, immune infiltration, and clinical characteristics, and compared the resulting subclasses with previously published classifications. Four subclasses of HCC (HCCW1–4) were identified. Subclass HCCW1 displayed the highest PCDHB4 expression. Subclass HCCW2 displayed lower Edmondson–Steiner grades (I and II) and CTNNB1 mutation frequencies. Subclass HCCW3 was associated with a good prognosis, the highest PCDHGB7 expression, high CD8+ naïve T cells abundance, and relatively low TP53 mutation rates. Subclass HCCW4 was associated with a poor prognosis, the highest PCDHB2 and PCDHB6 expression, a relatively high abundance of Th1 cells, NKT and class-switched memory B cells, relatively low enrichment of cDC, iDC, and CD4+ memory T cells, and high Edmondson–Steiner grades (III and IV). We also identified Wnt–Hippo signaling pathway-related genes that may influence immune cell infiltration. We developed a panel of 272 Wnt–Hippo signaling pathway-related genes to classify HCC into four groups based on Taiwanese HCC and The Cancer Genome Atlas Liver Hepatocellular Carcinoma datasets. This novel molecular classification system may aid the treatment of HCC.

Aspirin use and risk of hepatocellular carcinoma in patients with chronic hepatitis B with or without cirrhosis

BACKGROUND AND AIMS

Studies on differential effect of aspirin therapy on HCC risk across the spectrum of liver diseases are lacking. We investigated the association between aspirin use and risks of HCC, liver-associated death, and major bleeding in chronic hepatitis B (CHB) patients with or without cirrhosis.

APPROACH AND RESULTS

We identified 329,635 eligible adults with CHB from 2007 through 2017, using the Korean National Health Insurance Service database, including patients who received aspirin for ≥90 consecutive days (n = 20,200) and patients who never received antiplatelet therapy (n = 309,435). Risks of HCC, liver-associated mortality, and major bleeding were estimated in a propensity-score-matched cohort (19,003 pairs), accounting for competing risks. With a median follow-up of 6.7 years, 10-year cumulative incidence of HCC was 9.5% in the aspirin-treated group and 11.3% in the untreated group (adjusted subdistribution hazard ratio [aSHR], 0.85; 95% CI, 0.78-0.92). However, among patients with cirrhosis (2479 pairs), an association of aspirin use with HCC risk was not evident (aSHR, 1.00; 95% CI, 0.85-1.18). Cirrhosis status had a significant effect on the association between aspirin use and HCC risk (p_interaction , n = 0.04). Aspirin use was also associated with lower liver-associated mortality (aSHR, 0.80; 95% CI, 0.71-0.90). Moreover, aspirin use was not associated with major bleeding risk (aSHR, 1.09; 95% CI, 0.99-1.21).

CONCLUSIONS

Aspirin use was associated with reduced risks of HCC and liver-associated mortality in adults with CHB. Cirrhosis status had a substantial effect on the association between aspirin use and HCC risk.

Genomic analysis quantifies pyroptosis in the immune microenvironment of HBV-related hepatocellular carcinoma

Pyroptosis, a way of pro-inflammatory death, plays a significant part in the tumor microenvironment (TME). A recent study has shown that the hepatitis C virus changes the TME by inducing pyroptosis against hepatocellular carcinoma (HCC). However, compared to TME in hepatitis C virus-infected HCC, the exploration of immune characteristics and response to immunotherapy associated with the pyroptosis phenotype is still insufficient in hepatitis B virus-related HCC (HBV-HCC). Our study constructed pyroptosis-score (PYS) via principal-component analysis (PCA) to unveil the link between pyroptosis and tumor immunity in 369 HBV-HCC patients. Compared with the low-PYS group, subjects with higher PYS were associated with poor prognosis but were more susceptible to anti-PD-L1 treatment. In addition, we found that PYS can serve independently as a prognostic factor for HBV-HCC, making it possible for us to identify specific small molecule drugs with a potential value in inhibiting tumors via targeting pyroptosis. Also, the target genes predicted by the Weighted gene co-expression network analysis (WGCNA) and pharmacophore model were enriched in the HIF-1 signaling pathway and NF-kB transcription factor activity, which were related to the mechanism of inflammation-driven cancer. The PYS is extremely important in predicting prognosis and responses to immunotherapy. New treatment strategies for inflammation-driven cancers may be found by targeting pyroptosis.

The Role of Chronic Liver Diseases in the Emergence and Recurrence of Hepatocellular Carcinoma: An Omics Perspective

Hepatocellular carcinoma (HCC) typically develops from a background of cirrhosis resulting from chronic inflammation. This inflammation is frequently associated with chronic liver diseases (CLD). The advent of next generation sequencing has enabled extensive analyses of molecular aberrations in HCC. However, less attention has been directed to the chronically inflamed background of the liver, prior to HCC emergence and during recurrence following surgery. Hepatocytes within chronically inflamed liver tissues present highly activated inflammatory signaling pathways and accumulation of a complex mutational landscape. In this altered environment, cells may transform in a stepwise manner toward tumorigenesis. Similarly, the chronically inflamed environment which persists after resection may impact the timing of HCC recurrence. Advances in research are allowing an extensive epigenomic, transcriptomic and proteomic characterization of CLD which define the emergence of HCC or its recurrence. The amount of data generated will enable the understanding of oncogenic mechanisms in HCC from the CLD perspective and provide the possibility to identify robust biomarkers or novel therapeutic targets for the treatment of primary and recurrent HCC. Importantly, biomarkers defined by the analysis of CLD tissue may permit the early detection or prevention of HCC emergence and recurrence. In this review, we compile the current omics based evidence of the contribution of CLD tissues to the emergence and recurrence of HCC.

T cells: Friends and foes in NASH pathogenesis and hepatocarcinogenesis

In association with the pandemic spreading of obesity and metabolic syndrome, the prevalence of NAFLD-related HCC is increasing almost exponentially. In recent years, many of the underlining multifactorial causes of NAFLD have been identified, and the cellular mechanisms sustaining disease development have been dissected up to the single-cell level. However, there is still an urgent need to provide clinicians with more therapeutic targets, with particular attention on NAFLD-induced HCC, where immune checkpoint inhibitors do not work as efficiently. Whereas much effort has been invested in elucidating the role of innate immune response in the hepatic NAFLD microenvironment, only in the past decade have novel critical roles been unraveled for T cells in driving chronic inflammation toward HCC. The metabolic and immune microenvironment interact to recreate a tumor-promoting and immune-suppressive terrain, responsible for resistance to anticancer therapy. In this article, we will review the specific functions of several T-cell populations involved in NAFLD and NAFLD-driven HCC. We will illustrate the cellular crosstalk with other immune cells, regulatory networks or stimulatory effects of these interactions, and role of the metabolic microenvironment in influencing immune cell functionality. Finally, we will present the pros and cons of the current therapeutic strategies against NAFLD-related HCC and delineate possible novel approaches for the future.

Immunotherapies for hepatocellular carcinoma

Liver cancer, more specifically hepatocellular carcinoma (HCC), is the second leading cause of cancer-related death and its incidence is increasing globally. Around 50% of patients with HCC receive systemic therapies, traditionally sorafenib or lenvatinib in the first line and regorafenib, cabozantinib or ramucirumab in the second line. In the past 5 years, immune-checkpoint inhibitors have revolutionized the management of HCC. The combination of atezolizumab and bevacizumab has been shown to improve overall survival relative to sorafenib, resulting in FDA approval of this regimen. More recently, durvalumab plus tremelimumab yielded superior overall survival versus sorafenib and atezolizumab plus cabozantinib yielded superior progression-free survival. In addition, pembrolizumab monotherapy and the combination of nivolumab plus ipilimumab have received FDA Accelerated Approval in the second-line setting based on early efficacy data. Despite these major advances, the molecular underpinnings governing immune responses and evasion remain unclear. The immune microenvironment has crucial roles in the development and progression of HCC and distinct aetiology-dependent immune features have been defined. Inflamed and non-inflamed classes of HCC and genomic signatures have been associated with response to immune-checkpoint inhibitors, yet no validated biomarker is available to guide clinical decision-making. This Review provides information on the immune microenvironments underlying the response or resistance of HCC to immunotherapies. In addition, current evidence from phase III trials on the efficacy, immune-related adverse events and aetiology-dependent mechanisms of response are described. Finally, we discuss emerging trials assessing immunotherapies across all stages of HCC that might change the management of this disease in the near future.

Innate and Adaptive Immunopathogeneses in Viral Hepatitis; Crucial Determinants of Hepatocellular Carcinoma

Viral hepatitis B (HBV) and hepatitis C (HCV) infections remain the most common risk factors for the development of hepatocellular carcinoma (HCC), and their heterogeneous distribution influences the global prevalence of this common type of liver cancer. Typical hepatitis infection elicits various immune responses within the liver microenvironment, and viral persistence induces chronic liver inflammation and carcinogenesis. HBV is directly mutagenic but can also cause low-grade liver inflammation characterized by episodes of intermittent high-grade liver inflammation, liver fibrosis, and cirrhosis, which can progress to decompensated liver disease and HCC. Equally, the absence of key innate and adaptive immune responses in chronic HCV infection dampens viral eradication and induces an exhausted and immunosuppressive liver niche that favors HCC development and progression. The objectives of this review are to (i) discuss the epidemiological pattern of HBV and HCV infections, (ii) understand the host immune response to acute and chronic viral hepatitis, and (iii) explore the link between this diseased immune environment and the development and progression of HCC in preclinical models and HCC patients.

Liver cancer risk-predictive molecular biomarkers specific to clinico-epidemiological contexts

Hepatocellular carcinoma (HCC) risk prediction is increasingly important because of the low annual HCC incidence in patients with the rapidly emerging non-alcoholic fatty liver disease or cured HCV infection. To date, numerous clinical HCC risk biomarkers and scores have been reported in literature. However, heterogeneity in clinico-epidemiological context, e.g., liver disease etiology, patient race/ethnicity, regional environmental exposure, and lifestyle-related factors, obscure their real clinical utility and applicability. Proper characterization of these factors will help refine HCC risk prediction according to certain clinical context/scenarios and contribute to improved early HCC detection. Molecular factors underlying the clinical heterogeneity encompass various features in host genetics, hepatic and systemic molecular dysregulations, and cross-organ interactions, which may serve as clinical-context-specific biomarkers and/or therapeutic targets. Toward the goal to enable individual-risk-based HCC screening by incorporating the HCC risk biomarkers/scores, their assessment in patient with well-defined clinical context/scenario is critical to gauge their real value and to maximize benefit of the tailored patient management for substantial improvement of the poor HCC prognosis.

Prognosis of Tumor Microenvironment in Luminal B-Type Breast Cancer

Objective

Tumor microenvironment as an important element of malignancy could help predict cancer prognosis and therapeutic response; thus, a prognostic landscape map of the tumor microenvironment in luminal B breast cancers should be developed.

Methods

The GEO and TCGA databases were employed to retrieve clinical follow-up data and expression profiles of luminal B breast cancer. CIBERSORT was applied to assess the infiltration of the tumor microenvironment of 209 patients and to construct tumor microenvironment-based subtypes of luminal B breast cancer. We also conducted Cox multivariate regression analysis to select features that could be used to develop a microenvironment signature for cancer. Samples were categorized as having low and high TME scores according to the median TME score. The correlations of prognosis and TME score, expression levels of immune factors and genomic variation, and clinical features were further investigated.

Results

We found that high TME scores were correlated with poor prognosis. The current findings showed that the expressions of multiple immune-related genes, including CXCL9, CXCL10, GZMB, and PDCD1LG2, were upregulated in cancer with high TME scores. The high-risk group showed lower TP53 gene mutation frequency as opposed to that of the low-risk group. For the purpose of developing a TME scoring system, the TME infiltration levels of 209 patients with luminal B breast cancer from TCGA were comprehensively analyzed.

Conclusions

Our analysis revealed that the TME score was an indicator of patients' response to immune checkpoint modulators and an effective prognostic biomarker. TME scoring improves current immunotherapy on luminal B breast cancer.

Identification and Validation of an Immune-related Prognostic Signature for Hepatocellular Carcinoma

BACKGROUND AND AIMS

The immune system plays vital roles in hepatocellular carcinoma (HCC) initiation and progression. The present study aimed to construct an immune-gene related prognostic signature (IRPS) for predicting the prognosis of HCC patients.

METHODS

Gene expression data were retrieved from The Cancer Genome Atlas database. The IRPS was established via least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis. The prognostic values of the IRPS were further validated using the International Cancer Genome Consortium (ICGC) dataset.

RESULTS

A total of 62 genes were identified as candidate immune-related prognostic genes. According to the results of Lasso and multivariate Cox regression analysis, we established an IRPS and confirmed its stability and reliability in the ICGC dataset. The IRPS was significantly associated with advanced clinicopathological characteristics. Both Cox regression analyses revealed that the IRPS could be independent risk factors influencing prognosis of HCC patients. The relationships between the IRPS and infiltration of immune cells demonstrated that the IRPS was associated with immune cell infiltration. Furthermore, a nomogram was constructed to estimate the survival probability of HCC patients.

CONCLUSIONS

The IRPS was effective for predicting prognosis of HCC patients, which might serve as novel prognostic and therapeutic biomarkers for HCC.

Epigenetic priming in chronic liver disease impacts the transcriptional and genetic landscapes of hepatocellular carcinoma

Hepatocellular carcinomas (HCCs) usually arise from chronic liver disease (CLD). Precancerous cells in chronically inflamed environments may be 'epigenetically primed', sensitising them to oncogenic transformation. We investigated whether epigenetic priming in CLD may affect HCC outcomes by influencing the genomic and transcriptomic landscapes of HCC. Analysis of DNA methylation arrays from 10 paired CLD-HCC identified 339 shared dysregulated CpG sites and 18 shared differentially methylated regions compared with healthy livers. These regions were associated with dysregulated expression of genes with relevance in HCC, including ubiquitin D (UBD), cytochrome P450 family 2 subfamily C member 19 (CYP2C19) and O-6-methylguanine-DNA methyltransferase (MGMT). Methylation changes were recapitulated in an independent cohort of nine paired CLD-HCC. High CLD methylation score, defined using the 124 dysregulated CpGs in CLD and HCC in both cohorts, was associated with poor survival, increased somatic genetic alterations and TP53 mutations in two independent HCC cohorts. Oncogenic transcriptional and methylation dysregulation is evident in CLD and compounded in HCC. Epigenetic priming in CLD sculpts the transcriptional landscape of HCC and creates an environment favouring the acquisition of genetic alterations, suggesting that the extent of epigenetic priming in CLD could influence disease outcome.

Molecular alterations that precede the establishment of the hallmarks of cancer: An approach on the prevention of hepatocarcinogenesis

Chronic liver injury promotes the molecular alterations that precede the establishment of cancer. Usually, several decades of chronic insults are needed to develop the most common primary liver tumor known as hepatocellular carcinoma. As other cancer types, liver cancer cells are governed by a common set of rules collectively called the hallmarks of cancer. Although those rules have provided a conceptual framework for understanding the complex pathophysiology of established tumors, therapeutic options are still ineffective in advanced stages. Thus, the molecular alterations that precede the establishment of cancer remain an attractive target for therapeutic interventions. Here, we first summarize the chemopreventive interventions targeting the early liver carcinogenesis stages. After an integrative analysis on the plethora of molecular alterations regulated by anticancer agents, we then underline and discuss that two critical processes namely oxidative stress and genetic alterations, play the role of 'dirty work laborer' in the initial cell damage and drive the transformation of preneoplastic into neoplastic cells, respectively; besides, the activation of cellular senescence works as a key mechanism in attempting to prevent the onset and establishment of liver cancer. Whereas the detrimental effects of the binomial made up of oxidative stress and genetic alterations are either eliminated or reduced, senescence activation is promoted by anticancer agents. We argue that collectively, oxidative stress, genetic alterations, and senescence are key events that influence the fate of initiated cells and the establishment of the hallmarks of cancer.

Molecular classification of hepatocellular carcinoma: prognostic importance and clinical applications

Hepatocellular carcinoma (HCC) is a lethal human malignancy with a very low overall and long-term survival rate. Poor prognostic outcomes are predominantly associated with HCC due to a huge landscape of heterogeneity found in the deadliest disease. However, molecular subtyping of HCC has significantly improved the knowledge of the underlying mechanisms that contribute towards the heterogeneity and progression of the disease. In this review, we have extensively summarized the current information available about molecular classification of HCC. This review can be of great significance for providing the insight information needed for development of novel, efficient and personalized therapeutic options for the treatment of HCC patients globally.

DEN-Induced Rat Model Reproduces Key Features of Human Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma is the most frequent form of primary liver cancer, characterized by increasing incidence and high mortality. Animal models of hepatocellular carcinoma are widely used to study the biology of cancer and to test potential therapies. Herein, we describe how the rat model of DEN-induced hepatocellular carcinoma mimics the pathogenesis of hepatocellular carcinoma seen in humans, including liver damage, chronic inflammation, hepatocytes proliferation, liver fibrosis and cirrhosis, disorganized vasculature, and modulations of the liver’s immune microenvironment. Our results should help the hepatocellular carcinoma field to better tailor the use of the DEN-induced rat liver cancer model for testing specific experimental hypotheses or to perform preclinical testing.

Abstract

Hepatocellular carcinoma (HCC) is the most common type of liver cancer. The majority of HCC cases are associated with liver fibrosis or cirrhosis developing from chronic liver injuries. The immune system of the liver contributes to the severity of tissue damage, the establishment of fibrosis and the disease’s progression towards HCC. Herein, we provide a detailed characterization of the DEN-induced HCC rat model during fibrosis progression and HCC development with a special focus on the liver’s inflammatory microenvironment. Fischer 344 male rats were treated weekly for 14 weeks with intra-peritoneal injections of 50 mg/kg DEN. The rats were sacrificed before starting DEN-injections at 0 weeks, after 8 weeks, 14 weeks and 20 weeks after the start of DEN-injections. We performed histopathological, immunohistochemical, RT-qPCR, RNA-seq and flow cytometry analysis. Data were compared between tumor and non-tumor samples from the DEN-treated versus untreated rats, as well as versus human HCCs. Chronic DEN injections lead to liver damage, hepatocytes proliferation, liver fibrosis and cirrhosis, disorganized vasculature, and a modulated immune microenvironment that mimics the usual events observed during human HCC development. The RNA-seq results showed that DEN-induced liver tumors in the rat model shared remarkable molecular characteristics with human HCC, especially with HCC associated with high proliferation. In conclusion, our study provides detailed insight into hepatocarcinogenesis in a commonly used model of HCC, facilitating the future use of this model for preclinical testing.

Molecular characterisation of hepatocellular carcinoma in patients with non-alcoholic steatohepatitis

BACKGROUND AND AIMS

Non-alcoholic steatohepatitis (NASH)-related hepatocellular carcinoma (HCC) is increasing globally, but its molecular features are not well defined. We aimed to identify unique molecular traits characterising NASH-HCC compared to other HCC aetiologies.

METHODS

We collected 80 NASH-HCC and 125 NASH samples from 5 institutions. Expression array (n = 53 NASH-HCC; n = 74 NASH) and whole exome sequencing (n = 52 NASH-HCC) data were compared to HCCs of other aetiologies (n = 184). Three NASH-HCC mouse models were analysed by RNA-seq/expression-array (n = 20). Activin A receptor type 2A (ACVR2A) was silenced in HCC cells and proliferation assessed by colorimetric and colony formation assays.

RESULTS

Mutational profiling of NASH-HCC tumours revealed TERT promoter (56%), CTNNB1 (28%), TP53 (18%) and ACVR2A (10%) as the most frequently mutated genes. ACVR2A mutation rates were higher in NASH-HCC than in other HCC aetiologies (10% vs. 3%, p <0.05). In vitro, ACVR2A silencing prompted a significant increase in cell proliferation in HCC cells. We identified a novel mutational signature (MutSig-NASH-HCC) significantly associated with NASH-HCC (16% vs. 2% in viral/alcohol-HCC, p = 0.03). Tumour mutational burden was higher in non-cirrhotic than in cirrhotic NASH-HCCs (1.45 vs. 0.94 mutations/megabase; p <0.0017). Compared to other aetiologies of HCC, NASH-HCCs were enriched in bile and fatty acid signalling, oxidative stress and inflammation, and presented a higher fraction of Wnt/TGF-β proliferation subclass tumours (42% vs. 26%, p = 0.01) and a lower prevalence of the CTNNB1 subclass. Compared to other aetiologies, NASH-HCC showed a significantly higher prevalence of an immunosuppressive cancer field. In 3 murine models of NASH-HCC, key features of human NASH-HCC were preserved.

CONCLUSIONS

NASH-HCCs display unique molecular features including higher rates of ACVR2A mutations and the presence of a newly identified mutational signature.

LAY SUMMARY

The prevalence of hepatocellular carcinoma (HCC) associated with non-alcoholic steatohepatitis (NASH) is increasing globally, but its molecular traits are not well characterised. In this study, we uncovered higher rates of ACVR2A mutations (10%) - a potential tumour suppressor - and the presence of a novel mutational signature that characterises NASH-related HCC.

Transcription factors linked to the molecular signatures in the development of hepatocellular carcinoma on a cirrhotic background

Mechanisms underlying the regulation of gene expression in cancer have been surveyed for decades to find novel prognostic factors and new targets for molecular targeted therapies in cancer. Because most cases of liver cancer are associated with liver cirrhosis, we aimed to analyze the gene expression signatures and the gene regulatory mechanism in hepatocellular carcinoma (HCC) on a cirrhotic background using high-throughput data analysis. In the present study, three valid array-based datasets containing HCC and liver cirrhosis samples were obtained to identify common differentially expressed genes (DEGs). Moreover, a comprehensive data analysis was conducted based on RNA-Seq data and using Kaplan-Meier curve analysis to find molecular signatures that reduce patients' survival rate. Furthermore, we proposed a gene regulatory network (GRN) to explore the possible regulatory mechanism of these molecular signatures by transcription factors in HCC progression from cirrhosis. Besides, we analyzed protein-protein interactions, gene ontology (GO), and pathway enrichment to elucidate the cellular and molecular function of the GRN elements in HCC. In this way, we found a list of 231 molecular signatures in HCC derived from cirrhosis. We also found the importance of TCF4, RUNX1, HINFP, KDM2B, MAF, JUN, NR5A2, NFYA, and AR as key differentially expressed transcription factors (DETFs) in the progression of HCC from cirrhosis. In conclusion, the identified molecular signatures and their transcription factors propose candidate prognostic markers and possible molecular targets in the progression of HCC.

Key features of the environment promoting liver cancer in the absence of cirrhosis

The prevalence of obesity and non-alcoholic fatty liver disease (NAFLD) associated hepatocellular carcinoma (HCC) is rising, even in the absence of cirrhosis. We aimed to develop a murine model that would facilitate further understanding of NAFLD-HCC pathogenesis. A total of 144 C3H/He mice were fed either control or American lifestyle (ALIOS) diet, with or without interventions, for up to 48 weeks of age. Gross, liver histology, immunohistochemistry (IHC) and RNA-sequencing data were interpreted alongside human datasets. The ALIOS diet promoted obesity, elevated liver weight, impaired glucose tolerance, non-alcoholic fatty liver disease (NAFLD) and spontaneous HCC. Liver weight, fasting blood glucose, steatosis, lobular inflammation and lipogranulomas were associated with development of HCC, as were markers of hepatocyte proliferation and DNA damage. An antioxidant diminished cellular injury, fibrosis and DNA damage, but not lobular inflammation, lipogranulomas, proliferation and HCC development. An acquired CD44 phenotype in macrophages was associated with type 2 diabetes and NAFLD-HCC. In this diet induced NASH and HCC (DINAH) model, key features of obesity associated NAFLD-HCC have been reproduced, highlighting roles for hepatic steatosis and proliferation, with the acquisition of lobular inflammation and CD44 positive macrophages in the development of HCC-even in the absence of progressive injury and fibrosis.

DNA Methylation Signatures Reveal the Diversity of Processes Remodeling Hepatocellular Carcinoma Methylomes

BACKGROUND AND AIMS

DNA methylation patterns are highly rearranged in HCCs. However, diverse sources of variation are intermingled in cancer methylomes, precluding the precise characterization of underlying molecular mechanisms. We developed a computational framework (methylation signature analysis with independent component analysis [MethICA]) leveraging independent component analysis to disentangle the diverse processes contributing to DNA methylation changes in tumors.

APPROACH AND RESULTS

Applied to a collection of 738 HCCs, MethICA unraveled 13 stable methylation components preferentially active in specific chromatin states, sequence contexts, and replication timings. These included signatures of general processes associated with sex and age but also signatures related to specific driver events and molecular subgroups. Catenin beta 1 mutations were major modulators of methylation patterns in HCC, characterized by a targeted hypomethylation of transcription factor 7-bound enhancers in the vicinity of Wnt target genes as well as a widespread hypomethylation of late-replicated partially methylated domains. By contrast, demethylation of early replicated highly methylated domains was a signature of replication stress, leading to an extensive hypomethylator phenotype in cyclin-activated HCC. Inactivating mutations of the chromatin remodeler AT-rich interactive domain-containing protein 1A were associated with epigenetic silencing of differentiation-promoting transcriptional networks, also detectable in cirrhotic liver. Finally, a hypermethylation signature targeting polycomb-repressed chromatin domains was identified in the G1 molecular subgroup with progenitor features.

CONCLUSIONS

This study elucidates the diversity of processes remodeling HCC methylomes and reveals the epigenetic and transcriptional impact of driver alterations.

Identification of New Biomarker for Prediction of Hepatocellular Carcinoma Development in Early-Stage Cirrhosis Patients

Background

Liver cirrhosis is one of the major drivers of hepatocellular carcinoma (HCC). In the present study, we aimed to identify and validate new biomarker for early prediction of HCC development in early-stage cirrhosis patients.

Methods

mRNA expression and clinical parameters of GSE63898, GSE89377, GSE15654, GSE14520, and TCGA-HCC cohort and ICGC-HCC cohort were downloaded for analysis. Wilcoxon test was performed to identify DEGs. Univariate and multivariate Cox regression analysis were used to develop the risk signature, and ROC analysis was performed to analyze the predictive accuracy and sensitivity of the risk signature.

Results

There were 42 DEGs (including 28 upregulated genes and 14 downregulated genes) found in early-stage liver cirrhosis patients before developing HCC from GSE1565442. Then, a risk signature consisting of 8 DEGs could effectively classify early-stage cirrhosis patients into high-risk group with shorter HCC development time and low-risk group with longer HCC development time from GSE15654. Multivariate Cox analysis indicated that the risk signature was an independent prognostic factor for the prediction of HCC development and ROC analysis showed that the signature exhibited good predictive efficiency in predicting 2-, 5-, and 10-year HCC development. Mechanistically, significantly higher proportions of CD8 T cells were found to be enriched in cirrhosis patients with low risk score, and higher CD8 T cells were associated with longer HCC development time. Besides, the signature was an independent prognostic factor for poorer prognosis of early-stage liver cirrhosis patients of GSE15654. Moreover, the signature could also separate HCC patients from healthy controls and was also associated with the poorer prognosis of HCC patients from three HCC cohorts. Finally, we also identified HDAC inhibitors, such as trichostatin A, to be a potential chemopreventive treatment for the prevention of HCC development by targeting risk signature based on CMap analysis.

Conclusion

A risk signature was developed and validated for early prediction of HCC development, which may be a useful tool to set up individualized follow-up interval schedules.

Identification of immune-infiltrating cell-related biomarkers in hepatocellular carcinoma based on gene co-expression network analysis

Background

Hepatocellular carcinoma (HCC) is often caused by chronic liver infection or inflammation. Searching for potential immunotherapy targets will aid the early diagnosis and treatment of HCC.

Methods

Firstly, detailed HCC data were downloaded from The Cancer Genome Atlas database. GDCRNATools was used for the comprehensive analysis of RNA sequencing data. Subsequently, the CIBERSORT package was used to estimate infiltration scores of 22 types of immune cells in complex samples. Furthermore, hub genes were identified via weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network analysis. In addition, multiple databases were used to validate the expression of hub gene in the tumor tissue. Finally, prognostic, diagnostic and immunohistochemical analysis of key hub genes was performed.

Results

In the present study, 9 hub genes were identified using WGCNA and PPI network analysis. Furthermore, the expression levels of 9 genes were positively correlated with the infiltration levels of CD8-positive T (CD8⁺ T) cells. In multiple dataset validations, the expression levels of CCL5, CXCR6, CD3E, and LCK were decreased in cancer tissues. In addition, survival analysis revealed that patients with LCK low expression had a poor survival prognosis (P < 0.05). Immunohistochemistry results demonstrated that CCL5, CD3E and LCK were expressed at low levels in HCC cancer tissues.

Conclusion

The identification of CCL5, CXCR6, CD3E and LCK may be helpful in the development of early diagnosis and therapy of HCC. LCK may be a potential prognostic biomarker for immunotherapy for HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13000-021-01118-y.

DNA Methylation Profiling of Human Hepatocarcinogenesis

BACKGROUND AND AIMS

Mutations in TERT (telomerase reverse transcriptase) promoter are established gatekeepers in early hepatocarcinogenesis, but little is known about other molecular alterations driving this process. Epigenetic deregulation is a critical event in early malignancies. Thus, we aimed to (1) analyze DNA methylation changes during the transition from preneoplastic lesions to early HCC (eHCC) and identify candidate epigenetic gatekeepers, and to (2) assess the prognostic potential of methylation changes in cirrhotic tissue.

APPROACH AND RESULTS

Methylome profiling was performed using Illumina HumanMethylation450 (485,000 cytosine-phosphateguanine, 96% of known cytosine-phosphateguanine islands), with data available for a total of 390 samples: 16 healthy liver, 139 cirrhotic tissue, 8 dysplastic nodules, and 227 HCC samples, including 40 eHCC below 2cm. A phylo-epigenetic tree derived from the Euclidean distances between differentially DNA-methylated sites (n = 421,997) revealed a gradient of methylation changes spanning healthy liver, cirrhotic tissue, dysplastic nodules, and HCC with closest proximity of dysplasia to HCC. Focusing on promoter regions, we identified epigenetic gatekeeper candidates with an increasing proportion of hypermethylated samples (beta value > 0.5) from cirrhotic tissue (<1%), to dysplastic nodules (≥25%), to eHCC (≥50%), and confirmed inverse correlation between DNA methylation and gene expression for TSPYL5 (testis-specific Y-encoded-like protein 5), KCNA3 (potassium voltage-gated channel, shaker-related subfamily, member 3), LDHB (lactate dehydrogenase B), and SPINT2 (serine peptidase inhibitor, Kunitz type 2) (all P < 0.001). Unsupervised clustering of genome-wide methylation profiles of cirrhotic tissue identified two clusters, M1 and M2, with 42% and 58% of patients, respectively, which correlates with survival (P < 0.05), independent of etiology.

CONCLUSIONS

Genome-wide DNA-methylation profiles accurately discriminate the different histological stages of human hepatocarcinogenesis. We report on epigenetic gatekeepers in the transition between dysplastic nodules and eHCC. DNA-methylation changes in cirrhotic tissue correlate with clinical outcomes.

Wnt/β-catenin inhibitor ICG-001 enhances the antitumor efficacy of radiotherapy by increasing radiation-induced DNA damage and improving tumor immune microenvironment in hepatocellular carcinoma

BACKGROUND AND PURPOSE

Radiotherapy (RT) has a promising anti-tumor effect depending on its effects on both cancer cells and tumor immune microenvironment (TIME). As one of the most common alterations in hepatocellular carcinoma (HCC), wnt/β-catenin pathway activation, has been reported to induce radioresistance and suppressive TIME. In this study, we aim to explore the effect of wnt/β-catenin inhibitor ICG-001 on radiosensitivity and RT-related TIME of HCC and the underlying mechanism.

MATERIALS AND METHODS

C57BL/6 and nude mouse tumor models were used to evaluate the efficacy of different treatments on tumor growth, recurrence and mice survival. Flow cytometry was performed to assess tumor infiltrating lymphocytes (TILs). DNA damage response (DDR) and radioresistance was investigated by colony formation assays, γ-H2AX and micronuclei measurements.

RESULTS

The addition of ICG-001 to RT exhibited better anti-tumor and survival-prolong efficacy in C57BL/6 than nude mice. TILs analysis revealed that ICG-001 plus RT boosted the infiltration and IFN-γ production of TIL CD8⁺ T cells, meanwhile reduced the number of Tregs. Moreover, mechanistic study demonstrated that ICG-001 increased the radiation-induced DDR of HCC cells by suppressing p53, thus leading to stronger activation of cGAS/STING pathway. Utilization of cGAS/STING pathway inhibitors impaired the therapeutic effect of combination therapy. Furthermore, combination therapy led to stronger immunologic memory and tumor relapse prevention.

CONCLUSIONS

Our findings showed that ICG-001 displayed both local and systematic effects by increasing radiosensitivity and improving immunity in HCC, which indicated that ICG-001 might be a potential synergetic treatment for radiotherapy and radioimmunotherapy in HCC patients.

Upregulating KTN1 promotes Hepatocellular Carcinoma progression

Background: Hepatocellular carcinoma (HCC) presents a common malignant tumor worldwide. Although kinectin 1 (KTN1) is the most frequently identified antigen in HCC tissues, the detailed roles of KTN1 in HCC remain unknown. This study seeks to clarify the expression status and clinical value of KTN1 in HCC and to explore the complicated biological functions of KTN1 and its underlying mechanisms.

Methods: In-house reverse transcription quantitative polymerase chain reaction (RT-qPCR) was used to detect the expression of KTN1 in HCC tissues. External gene microarrays and RNA-sequencing datasets were downloaded to confirm the expression patterns of KTN1. The prognostic ability of KTN1 in HCC was assessed by a Kaplan-Meier curve and a hazard ratio forest plot. The CRISPR/Cas9 gene-editing system was used to knock out KTN1 in Huh7 cells, which was verified by PCR-Sanger sequencing and western blotting. Assays of cell migration, invasion, viability, cell cycle, and apoptosis were conducted to explore the biological functions. RNA sequencing was performed to quantitatively analyze the functional deregulation in KTN1-knockout cells compared to Huh7-wild-type cells. Upregulated genes that co-expressed with KTN1 were identified from HCC tissues and were functionally annotated.

Results: KTN1 expression was increased in HCC tissues (standardized mean difference [SMD] = 0.20 [0.04, 0.37]). High KTN1 expression was significantly correlated with poorer prognosis of HCC patients, and KTN1 may be an independent risk factor for HCC (pooled HRs = 1.31 [1.05, 1.64]). After KTN1-knockout, the viability, migration, and invasion ability of HCC cells were inhibited. The proportion of HCC cells in the G0-G1 phases increased after KTN1 knockout, which also elevated the apoptosis rates in HCC cells. Several cascades, including innate immune response, chemical carcinogenesis, and positive regulation of transcription by RNA polymerase II, were dramatically changed after KTN1 knockout. KTN1 primarily participated in the cell cycle, DNA replication, and microRNAs in cancer pathways in HCC tissues.

Conclusion: Upregulation of KTN1 served as a promising prognosticator in HCC patients. KTN1 promotes the occurrence and deterioration of HCC by mediating cell survival, migration, invasion, cell cycle activation, and apoptotic inhibition. KTN1 may be a therapeutic target in HCC patients.

Hepatocellular Carcinoma: An Overview of the Changing Landscape of Treatment Options

The last three years have seen remarkable progress in comprehending predisposing factors and upgrading our treatment arsenal concerning hepatocellular carcinoma (HCC). Until recently, there were no means to withstand the progression of viral hepatitis-associated liver cirrhosis to HCC. A deeper understanding of the molecular mechanism of the disease, the use of biomarkers, and the follow-up, allowed us to realize that conventional chemotherapy failing to increase survival in patients with advanced HCC tends to be exiled from clinical practice. Multi-kinase inhibitors (TKIs) such as sorafenib, lenvatinib targeting mainly the vascular endothelial growth factor receptors 1–3 VEGFRs 1–3 provided until recently the standard of care for these patients, as first- or second-line treatment. Since May 2020, the atezolizumab plus bevacizumab combination (immunotherapy plus anti-VEGF) has become the new reference standard in first-line HCC treatment. Additionally, anti-programmed cell death protein 1 (anti-PD-1) immunotherapy can be used as a second-line treatment following first-line treatment’s failure. Phase III clinical trials have recently suggested the efficacy of novel anti-angiogenic factors such as cabozantinib and ramucirumab as a second-line treatment option. With considerations about toxicity arising, clinical trials are investigating combinations of the aforementioned targeted therapies with immunotherapy as first-line treatment. This paper aims to perform a systematic review describing the evolving treatment options for HCC over the last decades, ranging from neoadjuvant treatment to systemic therapy of advanced-stage HCC. With the landscape of HCC treatment shifting towards novel agents the forming of a new therapeutic algorithm for HCC seems to be imperative.

A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC such as progression, recurrence, and metastasis, and some have discussed using it as a weapon against a variety of cancers. However, the impact of immune-related genes (IRGs) on the prognosis of HCC remains unclear.

METHODS

Based on The Cancer Gene Atlas (TCGA) and Immunology Database and Analysis Portal (ImmPort) datasets, we integrated the ribonucleic acid (RNA) sequencing profiles of 424 HCC patients with IRGs to calculate immune-related differentially expressed genes (DEGs). Survival analysis was used to establish a prognostic model of survival- and immune-related DEGs. Based on genomic and clinicopathological data, we constructed a nomogram to predict the prognosis of HCC patients. Gene set enrichment analysis further clarified the signalling pathways of the high-risk and low-risk groups constructed based on the IRGs in HCC. Next, we evaluated the correlation between the risk score and the infiltration of immune cells, and finally, we validated the prognostic performance of this model in the GSE14520 dataset.

RESULTS

A total of 100 immune-related DEGs were significantly associated with the clinical outcomes of patients with HCC. We performed univariate and multivariate least absolute shrinkage and selection operator (Lasso) regression analyses on these genes to construct a prognostic model of seven IRGs (Fatty Acid Binding Protein 6 (FABP6), Microtubule-Associated Protein Tau (MAPT), Baculoviral IAP Repeat Containing 5 (BIRC5), Plexin-A1 (PLXNA1), Secreted Phosphoprotein 1 (SPP1), Stanniocalcin 2 (STC2) and Chondroitin Sulfate Proteoglycan 5 (CSPG5)), which showed better prognostic performance than the tumour/node/metastasis (TNM) staging system. Moreover, we constructed a regulatory network related to transcription factors (TFs) that further unravelled the regulatory mechanisms of these genes. According to the median value of the risk score, the entire TCGA cohort was divided into high-risk and low-risk groups, and the low-risk group had a better overall survival (OS) rate. To predict the OS rate of HCC, we established a gene- and clinical factor-related nomogram. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve showed that this model had moderate accuracy. The correlation analysis between the risk score and the infiltration of six common types of immune cells showed that the model could reflect the state of the immune microenvironment in HCC tumours.

CONCLUSION

Our IRG prognostic model was shown to have value in the monitoring, treatment, and prognostic assessment of HCC patients and could be used as a survival prediction tool in the near future.

Exploration of prognostic index based on immune-related genes in patients with liver hepatocellular carcinoma

The present study aimed to screen the immune-related genes (IRGs) in patients with liver hepatocellular carcinoma (LIHC) and construct a synthetic index for indicating the prognostic outcomes. The bioinformatic analysis was performed on the data of 374 cancer tissues and 50 normal tissues, which were downloaded from TCGA database. We observed that 17 differentially expressed IRGs were significantly associated with survival in LIHC patients. These LIHC-specific IRGs were validated with function analysis and molecular characteristics. Cox analysis was applied for constructing a RiskScore for predicting the survival. The RiskScore involved six IRGs and corresponding coefficients, which was calculated with the following formula: RiskScore = [Expression level of FABP5 *(0.064)] + [Expression level of TRAF3 * (0.198)] + [Expression level of CSPG5 * (0.416)] + [Expression level of IL17D * (0.197)] + [Expression level of STC2 * (0.036)] + [Expression level of BRD8 * (0.140)]. The RiskScore was positively associated with the poor survival, which was verified with the dataset from ICGC database. Further analysis revealed that the RiskScore was independent of any other clinical feature, while it was linked with the infiltration levels of six types of immune cells. Our study reported the survival-associated IRGs in LIHC and then constructed IRGs-based RiskScore as prognostic indicator for screening patients with high risk of short survival. Both the screened IRGs and IRGs-based RiskScore were clinically significant, which may be informative for promoting the individualized immunotherapy against LIHC.

Exploration and validation of a novel prognostic signature based on comprehensive bioinformatics analysis in hepatocellular carcinoma

The present study aimed to construct a novel signature for indicating the prognostic outcomes of hepatocellular carcinoma (HCC). Gene expression profiles were downloaded from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. The prognosis-related genes with differential expression were identified with weighted gene co-expression network analysis (WGCNA), univariate analysis, the least absolute shrinkage and selection operator (LASSO). With the stepwise regression analysis, a risk score was constructed based on the expression levels of five genes: Risk score = (−0.7736* CCNB2) + (1.0083* DYNC1LI1) + (−0.6755* KIF11) + (0.9588* SPC25) + (1.5237* KIF18A), which can be applied as a signature for predicting the prognosis of HCC patients. The prediction capacity of the risk score for overall survival was validated with both TCGA and ICGC cohorts. The 1-, 3- and 5-year ROC curves were plotted, in which the AUC was 0.842, 0.726 and 0.699 in TCGA cohort and 0.734, 0.691 and 0.700 in ICGC cohort, respectively. Moreover, the expression levels of the five genes were determined in clinical tumor and normal specimens with immunohistochemistry. The novel signature has exhibited good prediction efficacy for the overall survival of HCC patients.

Identification of hepatocellular carcinoma prognostic markers based on 10-immune gene signature

Background: Due to the heterogeneity of hepatocellular carcinoma (HCC), hepatocelluarin-associated differentially expressed genes were analyzed by bioinformatics methods to screen the molecular markers for HCC prognosis and potential molecular targets for immunotherapy.

Methods: RNA-seq data and clinical follow-up data of HCC were downloaded from The Cancer Genome Atlas (TCGA) database. Multivariate Cox analysis and Lasso regression were used to identify robust immunity-related genes. Finally, a risk prognosis model of immune gene pairs was established and verified by clinical features, test set and Gene Expression Omnibus (GEO) external validation set.

Results: A total of 536 immune-related gene (IRGs) were significantly associated with the prognosis of patients with HCC. Ten robust IRGs were finally obtained and a prognostic risk prediction model was constructed by feature selection of Lasso. The risk score of each sample is calculated based on the risk model and is divided into high risk group (Risk-H) and low risk group (Risk-L). Risk models enable risk stratification of samples in training sets, test sets, external validation sets, staging and subtypes. The area under the curve (AUC) in the training set and the test set were all >0.67, and there were significant overall suvival (OS) differences between the Risk-H and Risk-L samples. Compared with the published four models, the traditional clinical features of Grade, Stage and Gender, the model performed better on the risk prediction of HCC prognosis.

Conclusion: The present study constructed 10-gene signature as a novel prognostic marker for predicting survival in patients with HCC.

NASH limits anti-tumour surveillance in immunotherapy-treated HCC

Hepatocellular carcinoma (HCC) can have viral or non-viral causes^1-5. Non-alcoholic steatohepatitis (NASH) is an important driver of HCC. Immunotherapy has been approved for treating HCC, but biomarker-based stratification of patients for optimal response to therapy is an unmet need^6,7. Here we report the progressive accumulation of exhausted, unconventionally activated CD8⁺PD1⁺ T cells in NASH-affected livers. In preclinical models of NASH-induced HCC, therapeutic immunotherapy targeted at programmed death-1 (PD1) expanded activated CD8⁺PD1⁺ T cells within tumours but did not lead to tumour regression, which indicates that tumour immune surveillance was impaired. When given prophylactically, anti-PD1 treatment led to an increase in the incidence of NASH-HCC and in the number and size of tumour nodules, which correlated with increased hepatic CD8⁺PD1⁺CXCR6⁺, TOX⁺, and TNF⁺ T cells. The increase in HCC triggered by anti-PD1 treatment was prevented by depletion of CD8⁺ T cells or TNF neutralization, suggesting that CD8⁺ T cells help to induce NASH-HCC, rather than invigorating or executing immune surveillance. We found similar phenotypic and functional profiles in hepatic CD8⁺PD1⁺ T cells from humans with NAFLD or NASH. A meta-analysis of three randomized phase III clinical trials that tested inhibitors of PDL1 (programmed death-ligand 1) or PD1 in more than 1,600 patients with advanced HCC revealed that immune therapy did not improve survival in patients with non-viral HCC. In two additional cohorts, patients with NASH-driven HCC who received anti-PD1 or anti-PDL1 treatment showed reduced overall survival compared to patients with other aetiologies. Collectively, these data show that non-viral HCC, and particularly NASH-HCC, might be less responsive to immunotherapy, probably owing to NASH-related aberrant T cell activation causing tissue damage that leads to impaired immune surveillance. Our data provide a rationale for stratification of patients with HCC according to underlying aetiology in studies of immunotherapy as a primary or adjuvant treatment.

NASH limits anti-tumour surveillance in immunotherapy-treated HCC

Hepatocellular carcinoma (HCC) can have viral or non-viral causes^1–5. Non-alcoholic steatohepatitis (NASH) is an important driver of HCC. Immunotherapy has been approved for treating HCC, but biomarker-based stratification of patients for optimal response to therapy is an unmet need^6,7. Here we report the progressive accumulation of exhausted, unconventionally activated CD8⁺PD1⁺ T cells in NASH-affected livers. In preclinical models of NASH-induced HCC, therapeutic immunotherapy targeted at programmed death-1 (PD1) expanded activated CD8⁺PD1⁺ T cells within tumours but did not lead to tumour regression, which indicates that tumour immune surveillance was impaired. When given prophylactically, anti-PD1 treatment led to an increase in the incidence of NASH–HCC and in the number and size of tumour nodules, which correlated with increased hepatic CD8⁺PD1⁺CXCR6⁺, TOX⁺, and TNF⁺ T cells. The increase in HCC triggered by anti-PD1 treatment was prevented by depletion of CD8⁺ T cells or TNF neutralization, suggesting that CD8⁺ T cells help to induce NASH–HCC, rather than invigorating or executing immune surveillance. We found similar phenotypic and functional profiles in hepatic CD8⁺PD1⁺ T cells from humans with NAFLD or NASH. A meta-analysis of three randomized phase III clinical trials that tested inhibitors of PDL1 (programmed death-ligand 1) or PD1 in more than 1,600 patients with advanced HCC revealed that immune therapy did not improve survival in patients with non-viral HCC. In two additional cohorts, patients with NASH-driven HCC who received anti-PD1 or anti-PDL1 treatment showed reduced overall survival compared to patients with other aetiologies. Collectively, these data show that non-viral HCC, and particularly NASH–HCC, might be less responsive to immunotherapy, probably owing to NASH-related aberrant T cell activation causing tissue damage that leads to impaired immune surveillance. Our data provide a rationale for stratification of patients with HCC according to underlying aetiology in studies of immunotherapy as a primary or adjuvant treatment.

In hepatocellular carcinoma driven by non-alcoholic steatohepatitis, aberrant T cell activation and impaired immune surveillance seem to make hepatocellular carcinoma less responsive to anti-PD1 or anti-PDL1 immunotherapy.

Activation of FXR modulates SOCS3/Jak2/STAT3 signaling axis in a NASH-dependent hepatocellular carcinoma animal model

Despite the recent substantial progress in the treatment of hepatocellular carcinoma (HCC) from viral etiology, non-alcoholic steatohepatitis (NASH) is on a trajectory to become the fastest growing indication for HCC-related liver transplantation. The Farnesoid X receptor (FXR) is a member of the nuclear receptor superfamily with multifaceted roles in several metabolic disorders, particularly NASH. Its role as a tumor suppressor was also highlighted. Herein, we investigated the effect of obeticholic acid (OCA), as an FXR agonist, on NASH-associated HCC (NASH-HCC) animal model induced by diethylnitrosamine and high fat choline-deficient diet, exploring the potential impact on the suppressor of cytokine signaling 3 (SOCS3)/Janus kinase 2 (Jak2)/signal transducer and activator of transcription 3 (STAT3) pathway. Results indicated that OCA treatment upregulated FXR and its key mediator, small heterodimer partner (SHP), with remarkable amelioration in the dysplastic foci observed in the NASH-HCC group. This was paralleled with noticeable downregulation of alpha fetoprotein along with reduction in interferon gamma and transforming growth factor beta-1 hepatic levels besides caspase-3 and p53 upregulation. Moreover, sirtuin-1 (SIRT-1), a key regulator of FXR that controls the regenerative response of the liver, was elevated following OCA treatment. Modulation in the SOCS3/Jak2/STAT3 signaling axis was also reported. In conclusion, OCA attenuated the development and progression of NASH-dependent HCC possibly by interfering with SOCS3/Jak2/STAT3 pathway suggesting the potential use of FXR activators in NASH-related disorders, even at later stages of the disease, to impede its progression to the more deteriorating condition of HCC.

Liver Inflammation and Hepatobiliary Cancers

Immune regulation has an important role in cancer development, particularly in organs with continuous exposure to environmental pathogens, such as the liver and gastrointestinal tract. Chronic liver inflammation can lead to the development of hepatobiliary cancers, namely hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (iCCA), or combined HCC (cHCC)-CCA. In this review, we discuss the link between oxidative stress and the hepatic immune compartments, as well as how these factors trigger hepatocyte damage, proliferation, and eventually cancer initiation and its sustainment. We further give an overview of new anticancer therapies based on immunomodulation.

Liver Injury Increases the Incidence of HCC following AAV Gene Therapy in Mice

Adeno-associated virus (AAV) integrates into host genomes at low frequency, but when integration occurs in oncogenic hotspots it can cause hepatocellular carcinoma (HCC). Given the possibility of recombinant AAV (rAAV) integration leading to HCC, common causes of liver inflammation like non-alcoholic fatty liver disease (NAFLD) may increase the risk of rAAV-induced HCC. A rAAV targeting the oncogenic mouse Rian locus was used, and as expected led to HCC in all mice infected as neonates, likely due to growth-related hepatocyte proliferation in young mice. Mice infected with rAAV as adults did not develop HCC unless they were fed a diet leading to NAFLD, with increased inflammation and hepatocyte proliferation. Female mice were less susceptible to rAAV-induced HCC, and male mice with NAFLD treated with estrogen exhibited less inflammation and immune exhaustion associated with oncogenesis compared to those without estrogen. Adult NAFLD mice infected with a non-targeted control rAAV also developed HCC, though only half as frequently as those exposed to the Rian targeted rAAV. This study shows that adult mice exposed to rAAV gene therapy in the context of chronic liver disease developed HCC at high frequency, and thus warrants further study in humans given the high prevalence of NAFLD in the population.