Molecular predictors of prevention of recurrence in HCC with sorafenib as adjuvant treatment and prognostic factors in the phase 3 STORM trial

Tracing specificity of immune landscape remodeling associated with distinct anticancer treatments

Immune cells within the tumor microenvironment impact cancer progression, resistance, response to treatments. Despite remarkable outcomes for some cancer patients, immunotherapies remain unsatisfactory for others. Here, we designed an experimental setting using the Alb-R26 Met "inside-out" mouse model, faithfully recapitulating molecular features of liver cancer patients, to explore the effects of distinct anticancer targeted therapies on the tumor immune landscape. Using two treatments in clinical trials for different cancer types, Decitabine and MEK+BCL-XL blockage, we show their capability to trigger tumor regression in Alb-R26 Met mice and to superimpose distinct profiles of immune cell types and immune-checkpoints, impacting immunotherapy response. A machine learning approach processing tumor imaging and immune profile data identified a putative signature predicting tumor treatment response in mice and patients. Outcomes exemplify how the tumor immune microenvironment is differentially reshaped by distinct anticancer agents and highlight the importance of measuring its modulation during treatment to optimize oncotherapy and immunotherapy combinations.

CUL1-neddylation contributes to K29-linked ubiquitination on p27 for autophagic degradation in sorafenib-resistant liver cancer

Sorafenib has demonstrated great efficacy in liver cancer, however, its application as first-line treatment has been hampered due to the emerging drug resistance. This study is aimed to investigate the mechanism underlying acquired sorafenib resistance in liver cancer. Based on GSE109211 and TCGA datasets, bioinformatics analysis was conducted to find the potential genes implicated in the sorafenib resistance in liver cancer. mCherry-/eGFP-LC3B dual-fluorescent system was used to assess autophagic state. Wild and mutant types of HA-labeled ubiquitin (K27, K29, K33, K48, K63, K29R and K48R) were used to identify the type of polyubiquitin chains added to p27 by CUL1. Herein, we identified that F-box protein (SCF) ubiquitin ligase complexes (CUL1 and SKP2) and NEDD8 were highly expressed in sorafenib-resistant tissues using both the public data and clinical samples. NEDD8-mediated CUL1 neddylation enhanced SCF ubiquitin ligase complex to target p27 and subsequently linked K29-linked polyubiquitin chains to p27. Furthermore, NBR1 facilitated the degradation of ubiquitinated p27 protein by enhancing autophagy flux. Knocking down of CUL1 could prevent ubiquitination- and autophagy-mediated p27 protein degradation. The resistance to sorafenib was suppressed with CUL1 knockdown both in vitro and in vivo. In conclusion, our findings indicated that blocking neddylation or autophagy can restore drug sensitivity, thus providing a potential strategy for overcoming sorafenib resistance in the future.

Spatial immune scoring system predicts hepatocellular carcinoma recurrence

Given the high recurrence rates of hepatocellular carcinoma (HCC) post-resection1-3, improved early identification of patients at high risk for post-resection recurrence would help to improve patient outcomes and prioritize healthcare resources4-6. Here we observed a spatial and HCC recurrence-associated distribution of natural killer (NK) cells in the invasive front and tumour centre from 61 patients. Using extreme gradient boosting and inverse-variance weighting, we developed the tumour immune microenvironment spatial (TIMES) score based on the spatial expression patterns of five biomarkers (SPON2, ZFP36L2, ZFP36, VIM and HLA-DRB1) to predict HCC recurrence risk. The TIMES score (hazard ratio = 88.2, P < 0.001) outperformed current standard tools for patient risk stratification including the TNM and BCLC systems. We validated the model in 231 patients from five multicentred cohorts, achieving a real-world accuracy of 82.2% and specificity of 85.7%. The predictive power of these biomarkers emerged through the integration of their spatial distributions, rather than individual marker expression levels alone. In vivo models, including NK cell-specific Spon2-knockout mice, revealed that SPON2 enhances IFNγ secretion and NK cell infiltration at the invasive front. Our study introduces TIMES, a publicly accessible tool for predicting HCC recurrence risk, offering insights into its potential to inform treatment decisions for early-stage HCC.

Molecular subtyping combined with multiomics analysis to study correlation between TACE refractoriness and tumor stemness in hepatocellular carcinoma

BACKGROUND

Transarterial chemoembolization (TACE) refractoriness is a significant challenge in treating intermediate to advanced-stage hepatocellular carcinoma (HCC). A few studies suggest that liver cancer stem cells (LCSCs) may be associated with TACE refractoriness. This study aims to explore the potential correlation between TACE refractoriness and HCC stemness, highlighting its clinical significance.

METHODS

This research encompassed the analysis of diverse HCC datasets, including RNA-sequencing, microarray, single-cell RNA-sequencing, and clinical cohorts. We identified common genes between TACE refractoriness and tumor stemness (TSGs). Unsupervised clustering was employed to classify HCC patients into different clusters based on TSGs (TRS clusters). The study explored the differences in clinical prognosis, biological characteristics, genomic variations, immune landscapes, and treatment responses among the TRS clusters.

RESULTS

Patients with TACE-refractoriness demonstrated significantly higher tumor stemness. Our study identified 33 TSGs and established two TRS clusters, including C1 and C2. C1 was associated with TACE refractoriness, elevated tumor stemness, and poorer prognosis. Genomic alterations were found to be significantly different between the TRS clusters. The C1 exhibited signs of immunosuppression and lower activity of immune effector cells, while the C2 had a more robust immune response and higher level of immune cell presence. Single-cell RNA-seq revealed distinct cell type characteristics in each subtypes, with the C1 showing a higher proportion of stem cells and malignant cells.

CONCLUSION

Our findings establish a connection between TACE refractoriness and tumor stemness in HCC, proposing a novel subtype classification to guide personalized treatment. Insights gained may facilitate overcoming TACE refractoriness and the development of innovative therapies.

Liver Transplantation for Hepatocellular Carcinoma: An Expanding Cornerstone of Care in the Era of Immunotherapy

Liver transplantation (LT) has been accepted as a cornerstone of care in hepatocellular carcinoma (HCC) for almost three decades. In recent years, its role has been evolving to include patients with disease burden beyond the widely used Milan criteria. The integration of dynamic biomarkers such as alpha-fetoprotein together with downstaging approaches and tumor evolution after enlistment has allowed the selection of patients most likely to benefit, resulting in 5-year survival rates greater that 70%. With the increasing use of immune checkpoint inhibitors (ICIs) across all stages of disease, alone or in combination with locoregional therapies, there is now the potential to further expand the patient population with HCC who may benefit from LT. This brings challenges, given the global shortage of organs and the need to better understand the optimal use of ICIs before transplantation. Furthermore, the field of transplant oncology awaits additional biomarkers that can predict those likely to benefit from ICIs. More than ever, a multidisciplinary approach for liver cancer management is critical to ensure all patients are considered for LT where appropriate, and do not miss the opportunity for long-term survival.

Graph convolution networks model identifies and quantifies gene and cancer specific transcriptome signatures of cancer driver events

BACKGROUND

The identification and drug targeting of cancer causing (driver) genetic alterations has seen immense improvement in recent years, with many new targeted therapies developed. However, identifying, prioritizing, and treating genetic alterations is insufficient for most cancer patients. Current clinical practices rely mainly on DNA level mutational analyses, which in many cases fail to identify treatable driver events. Arguably, signal strength may determine cell fate more than the mutational status that initiated it. The use of transcriptomics, a complex and highly informative representation of cellular and tumor state, had been suggested to enhance diagnostics and treatment successes. A gene-expression based model trained over known genetic alterations could improve identification and quantification of cancer related biological aberrations' signal strength.

METHODS

We present STAMP (Signatures in Transcriptome Associated with Mutated Protein), a Graph Convolution Networks (GCN) based framework for the identification of gene expression signatures related to cancer driver events. STAMP was trained to identify the p53 dysfunction of cancer samples from gene expression, utilizing comprehensive curated graph structures of gene interactions. Predictions were modified for generating a quantitative score to rank the severity of a driver event in each sample. STAMP was then extended to almost 300 tumor type-specific predictive models for important cancer genes/pathways, by training to identify well-established driver events' annotations from the literature.

RESULTS

STAMP achieved very high AUC on unseen data across several tumor types and on an independent cohort. The framework was validated on p53 related genetic and clinical characteristics, including the effect of Variants of Unknown Significance, and showed strong correlation with protein function. For genes and tumor types where targeted therapy is available, STAMP showed correlation with drugs sensitivity (IC50) in an independent cell line database. It managed to stratify drug effect on samples with similar mutational profiles. STAMP was validated for drug-response prediction in clinical patients' cohorts, improving over a state-of-the-art method and suggesting potential biomarkers for cancer treatments.

CONCLUSIONS

The STAMP models provide a learning framework that successfully identifies and quantifies driver events' signal strength, showing utility in portraying the molecular landscape of tumors based on transcriptomics. Importantly, STAMP manifested the ability to improve targeted therapy selection and hence can contribute to better treatment.

The endoplasmic reticulum degradation-enhancing α-mannosidase-like protein 3 attenuates the unfolded protein response and has pro-survival and pro-viral roles in hepatoma cells and hepatocellular carcinoma patients

BACKGROUND

Chronic hepatitis B virus (HBV) infection is a major risk for development of hepatocellular carcinoma (HCC), a frequent malignancy with a poor survival rate. HBV infection results in significant endoplasmic reticulum (ER) stress and activation of the unfolded protein response (UPR) signaling, a contributing factor to carcinogenesis. As part of the UPR, the ER-associated degradation (ERAD) pathway is responsible for removing the burden of misfolded secretory proteins, to re-establish cellular homeostasis. Emerging evidence indicates consistent upregulation of ERAD factors, including members of the ER degradation-enhancing alpha-mannosidase-like protein (EDEM) family in infection and various tumor types. However, the significance of this gene expression pattern in HBV-driven pathology is just beginning to be deciphered.

METHODS

In this study we quantified the expression of the ERAD factor EDEM3, in a cohort of HCC patients with and without HBV infection, and validated our results by analysis of publically available transcriptomic and microarray data sets. We performed mechanistic studies in HepaRG cells with modulated EDEM3 expression to address UPR, ERAD, autophagy and apoptosis signaling, and their consequences on HBV infection.

RESULTS

Our work revealed significantly elevated EDEM3 expression in HCC tissues irrespective of HBV infection, while the highest levels were observed in tissues from HBV-infected patients. Investigation of published transcriptomic data sets confirmed EDEM3 upregulation in independent HCC patient cohorts, associated with tumor progression, poor survival prognosis and resistance to therapy. EDEM3-overexpressing hepatic cells exhibited attenuated UPR and activated secretory autophagy, which promoted HBV production. Conversely, cell depletion of EDEM3 resulted in significant ER stress inducing pro-apoptotic mechanisms and cell death.

CONCLUSIONS

We provide evidence of major implications of the ERAD pathway in HBV infection and HCC development and progression. Our results suggest that ERAD activation in HBV-infected cells is a protective mechanism against prolonged ER stress, potentially contributing to establishment of chronic HBV infection and promoting tumorigenesis. Developing specific inhibitors for ERAD factors may be an attractive approach to improve efficiency of current antiviral and anticancer therapies.

Efficacy and safety of nivolumab plus ipilimumab in gastrointestinal cancers: a systematic review and meta-analysis

Introduction

Gastrointestinal (GI) cancers represent a significant global health burden, and the need for more effective treatment options is exceptionally pressing. The present meta-analysis aimed to explore the efficacy and safety of the combination of nivolumab and ipilimumab in treating GI cancers.

Methods

A systematic search of four databases (PubMed, Embase, Web of Science, and Cochrane Library) was conducted for articles on the treatment of GI cancers with nivolumab combined with ipilimumab, published from 2014 up to 30 August 2024. The inclusion criteria were designed according to the principles of Participants, Intervention, Control, Outcomes, and Study (PICOS). The control group was chemotherapy or nivolumab monotherapy or nivolumab in combination with other drugs. We extracted data from 10 randomized controlled trials and utilized a random effects model to assess the objective response rate (ORR), median progression-free survival (mPFS), median overall survival (mOS), median duration of response (mDOR), and treatment-related adverse events (TRAEs). The data analysis was conducted using Review Manager version 5.4 and Stata version 12.0.

Results

Overall, the combination of nivolumab and ipilimumab demonstrated superior outcomes, including a higher ORR (OR = 1.69, P = 0.01), prolonged mOS (MD = 1.74, P = 0.04) and extended mDOR (MD = 5.64, P < 0.00001) compared to the control group. Subgroup analysis demonstrated that the ORR (OR = 1.75, P = 0.02) and mOS (MD = 5.02, P = 0.003) were significantly improved in patients with esophageal cancer. Notably, the ORR in patients with biliary cancer was significantly lower (OR = 0.11, P = 0.04). Additionally, the ORR was significantly higher in the NIVO1 + IPI3group (OR = 2.82, P = 0.01) and NIVO3 + IPI1 group (OR = 1.62, P = 0.01). Regarding safety, there was no statistically significant difference between the combination regimen and the control group in terms of any grade (OR = 0.72, P = 0.26) or grade 3-4 TRAEs (OR = 1.36, P = 0.14).

Conclusions

Nivolumab in combination with ipilimumab demonstrated significant efficacy in GI cancers (especially esophageal cancer) without causing more adverse reactions. However, its efficacy in biliary cancer still needs to be further proven.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42024590994.

Hepatocellular carcinoma hosts cholinergic neural cells and tumoral hepatocytes harboring targetable muscarinic receptors

Background & Aims

Owing to unexplained interpatient variation and treatment failure in hepatocellular carcinoma (HCC), novel therapeutic approaches remain an urgent clinical need. Hepatic neurons, belonging to the autonomic nervous system (ANS), mediate liver/whole body crosstalk. Pathological innervation of the ANS has been identified in cancer, nurturing tumor stroma and conferring stronger carcinogenic properties.

Methods

We characterized the innervation of liver tumors from the French Liver Biobank, then applied bioinformatics to TCGA (The Cancer Genome Atlas), several other datasets and a European validation cohort, to re-evaluate patient stratification. Cell biology and pharmacology studies were also performed.

Results

Densely packed nucleated DCX+, synaptophysin+, NeuN+, VAChT+, TH-, CD31-, CD45- clusters, to date undetected, were identified in human HCCs, and independently confirmed by single-cell RNA sequencing data. Using the new concept of a neuronal score, human and rat HCCs displayed tightly netrin-1-associated neural reconfiguration towards cholinergic polarity, which was associated with chronic liver disease progression, cancer onset and many features of aggressive (proliferative class) HCC, including shortened survival. This score was conditioned by tumoral hepatocytes, and predicted sorafenib efficacy in the STORM HCC phase III trial. Conversely, intratumoral adrenergic lymphocytes were enriched in TEMRA and cytotoxic phenotypes. Amongst all cholinergic transcripts, the medically targeted CHRM3 receptor was enriched and associated with pathogenic traits in HCC, as well as poor prognosis in HCC stages 1-2, while its level dropped upon experimental re-differentiation. Its pharmacological inhibition with low concentrations of anticholinergic drugs, but not cholinomimetics, decreased anchorage-independent growth and anoikis, synergized with sorafenib and lenvatinib in HCC class 1 to 3 lines, yet not in primary human hepatocytes, and preserved mature hepatocyte functions.

Conclusion

These data identify cholinergic processes as instrumental in liver carcinogenesis and support the use of EMA/FDA-approved cholinergic drugs in HCC research.

Impact and implications

Hepatocellular carcinoma (HCC) care has long been hampered by the enigmatic nature of disease evolution, as well as of response or resistance to treatment. Hepatic neurons are likely the least studied liver cell type and mediate patients singularities from the ANS to the organ in real-time. Cholinergic inputs identified in this study as pathogenic may be targeted with the well charted pharmacopoeia of neurotropic drugs already available, for basic or clinical research purposes, with an expected high level of safety.

Lasso-Cox interpretable model of AFP-negative hepatocellular carcinoma

BACKGROUND

In AFP-negative hepatocellular carcinoma patients, markers for predicting tumor progression or prognosis are limited. Therefore, our objective is to establish an optimal predicet model for this subset of patients, utilizing interpretable methods to enhance the accuracy of HCC prognosis prediction.

METHODS

We recruited a total of 508 AFP-negative HCC patients in this study, modeling with randomly divided training set and validated with validation set. At the same time, 86 patients treated in different time periods were used as internal validation. After comparing the cox model with the random forest model based on Lasso regression, we have chosen the former to build our model. This model has been interpreted with SHAP values and validated using ROC, DCA. Additionally, we have reconfirmed the model's effectiveness by employing an internal validation set of independent periods. Subsequently, we have established a risk stratification system.

RESULTS

The AUC values of the Lasso-Cox model at 1, 2, and 3 years were 0.807, 0.846, and 0.803, and the AUC values of the Lasso-RSF model at 1, 2, and 3 years were 0.783, 0.829, and 0.776. Lasso-Cox model was finally used to predict the prognosis of AFP-negative HCC patients in this study. And BCLC stage, gamma-glutamyl transferase (GGT), diameter of tumor, lung metastases (LM), albumin (ALB), alkaline phosphatase (ALP), and the number of tumors were included in the model. The validation set and the separate internal validation set both indicate that the model is stable and accurate. Using risk factors to establish risk stratification, we observed that the survival time of the low-risk group, the middle-risk group, and the high-risk group decreased gradually, with significant differences among the three groups.

CONCLUSION

The Lasso-Cox model based on AFP-negative HCC showed good predictive performance for liver cancer. SHAP explained the model for further clinical application.

Characterizing the pan-cancer role of exosomal miRNAs in metastasis across cancers

Exosomal microRNAs (exomiRs) play a critical role in intercellular communication, especially in cancer, where they regulate key cellular processes like proliferation, angiogenesis, and metastasis, highlighting their significance as potential diagnostic and therapeutic targets. Here, we aimed to characterize the role of exomiRs, derived from seven cancer types (four cell lines and three tumors), in influencing the pre-metastatic niche (PMN). In each cancer type we extracted high confidence exomiRs (LogFC >= 2 in exosomes relative to control), their experimentally validated targets, and the enriched pathways among those targets. We then selected the top100 high-confidence targets based on their frequency of appearance in the enriched pathways. We observed significantly higher GC content in exomiRs relative to genomic background. Gene Ontology analysis revealed both general cancer processes, such as wound healing and epithelial cell proliferation, as well as cancer-specific processes, such as "angiogenesis" in the kidney and "ossification" in the lung. ExomiR targets were enriched for cancer-specific tumor suppressor genes and downregulated in PMN formed in lungs compared to normal. Motif analysis showed high inter-cancer similarity among motifs enriched in exomiRs. Our analysis recapitulated exomiRs associated with M2 macrophage differentiation and chemoresistance, such as miR-21 and miR-222-3p, regulating signaling pathways like PTEN/PI3/Akt, NF-kB, etc. Additionally, Cox regression analysis in TCGA indicated that exomiR targets are significantly associated with better overall survival of patients. Lastly, support vector machine model using exomiR targets gene expression classified responders and non-responders to therapy with an AUROC ranging from 0.72 to 0.96, higher than previously reported gene signatures.

Bibliometric study on the utilization of sorafenib in hepatocellular carcinoma

Background

Although the number of studies on sorafenib for hepatocellular carcinoma (HCC) is increasing during the past two decades, no detailed scientometric examination of its knowledge framework has been undertaken. Therefore, we performed a bibliometric analysis on this topic.

Methods

VOSviewer and CiteSpace were utilized to analyze the articles regarding sorafenib for HCC from 2005 to 2024, which were retrieved from the Web of Science Core Collection (WoSCC) database.

Results

There were 7,667 articles related to sorafenib in HCC were retrieved from the WoSCC database, and they covered 99 countries/regions, 5,640 institutions, and 30,450 authors. The most published literature of countries and institutions were China and Sun Yat-sen University, respectively. Cancers is the journal with the most papers published in this field, and the journal with the most co-citations is N Engl J Med. Among authors, Masatoshi Kudo has published the most research papers, and the most co-citations go to JM Llovet. The keywords "survival", "apoptosis", "efficacy", "transarterial chemoembolization", "lenvatinib", etc. represent the current hotspots in this field.

Conclusions

We identified current hotspots and trends by bibliometric analysis in sorafenib-HCC field, which might provide valuable guidance for future researches. Further explorations are supposed to conduct the continued study of HCC apoptosis, large-scaled clinical trials with international cooperations, and comprehensive treatments including multiple systemic or locoregional approaches in patients with HCC.

Identification of potential biomarkers for hepatocellular carcinoma based on machine learning and bioinformatics analysis

Metastasis is the major cause of hepatocellular carcinoma (HCC) mortality. But the effective biomarkers for HCC metastasis remain underexplored. Here we integrated GEO (Gene Expression Omnibus) and TCGA (The Cancer Genome Atlas) datasets to screen candidate genes for hepatocellular carcinoma metastasis, a consensus metastasis-derived prognostic signature (MDPS) was constructed by machine learning. Based on the risk scores, HCC patients were stratified into high-risk and low-risk groups. Comprehensive analyses were conducted to investigate various aspects including survival outcomes, clinical characteristics, immune cell infiltration, as well as in vitro experiments. Together, we develop a comprehensive machine learning-based program for constructing a consensus MDPS including four genes (SPP1, TYMS, HMMR and MYCN). Our findings revealed that four genes could serve as efficient prognostic biomarkers and therapeutic targets in HCC. In addition, in vitro experiments showed that HMMR overregulation exacerbated tumor progression, including proliferation, migration and invasion.

Clinical diagnostic value of PIMREG on liver cancer cell phenotype and tumorigenic ability in nude mice

OBJECTIVES

In vitro experiments were manipulated to investigate the effect of the PIMREG (PICALM-interacting mitotic regulator gene) expression level on the malignant phenotype of liver cancer cells and their tumorigenesis ability in nude mice, and bioinformatics were used to analyze the clinical diagnostic and prognostic value in liver cancer.

METHODS

After liver cancer-related data were obtained from the TCGA database and GTEx database, the differences in PIMREG expression in liver cancer and normal liver tissue were compared using bioinformatics, and their correlation with the clinical pathological characteristics of liver cancer and the prognosis value were analyzed. A knockdown and overexpression model of PIMREG was constructed using Huh7 cells. The effect of the PIMREG expression level on the malignant phenotype of Huh7 cells was tested through CCK-8 and Transwell experiments. At the same time, animal knockdown and overexpression models were constructed to study the effect of the PIMREG expression level on the tumorigenesis ability in nude mice.

RESULTS

Bioinformatics analysis showed that PIMREG mRNA was significantly overexpressed in liver cancer tissue (P<0.001). There were differences in T-staging (P<0.001), pathological staging (P=0.002), vascular infiltration (P<0.001), histological grading (P<0.001), and AFP levels (P<0.001) between the high- and low-expression groups. A high expression of PIMREG is associated with a poor prognosis, manifested as a significant decrease in the overall survival, disease-specific survival, and progression-free survival rates of patients (P values of 0.006, 0.014, and 0.002, respectively). In the PIMREG overexpression model, the proliferation rate and invasion ability of Huh7 cells were significantly increased, and the tumorigenesis ability of nude mice was significantly enhanced. In the knockdown model, the opposite results were observed.

CONCLUSIONS

The PIMREG gene is highly expressed in hepatocellular carcinoma, and increasing its expression level can significantly promote the malignant phenotype of liver cancer cells and their tumorigenesis ability in nude mice. Knocking down its expression level has the opposite effect. The expression level of PIMREG is related to the pathological stages of liver cancer patients, and its elevated expression is a risk factor for poor prognosis. PIMREG may become a new target for the clinical diagnosis, treatment, and prognosis evaluation of liver cancer.

Targeting the immune privilege of tumor-initiating cells to enhance cancer immunotherapy

Tumor-initiating cells (TICs) possess the ability to evade anti-tumor immunity, potentially explaining many failures of cancer immunotherapy. Here, we identify CD49f as a prominent marker for discerning TICs in hepatocellular carcinoma (HCC), outperforming other commonly used TIC markers. CD49f-high TICs specifically recruit tumor-promoting neutrophils via the CXCL2-CXCR2 axis and create an immunosuppressive milieu in the tumor microenvironment (TME). Reciprocally, the neutrophils reprogram nearby tumor cells toward a TIC phenotype via secreting CCL4. These cells can evade CD8+ T cell-mediated killing through CCL4/STAT3-induced and CD49f-stabilized CD155 expression. Notably, while aberrant CD155 expression contributes to immune suppression, it also represents a TIC-specific vulnerability. We demonstrate that either CD155 deletion or antibody blockade significantly enhances sensitivity to anti-PD-1 therapy in preclinical HCC models. Our findings reveal a new mechanism of tumor immune evasion and provide a rationale for combining CD155 blockade with anti-PD-1/PD-L1 therapy in HCC.

Oncofetal MCB1 Is a Functional Biomarker for HCC Personalized Therapy

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide and lacks biomarkers for personalized therapy. Herein, it is reported that MCB1 could be a novel oncofetal protein that is upregulated in the preneoplastic lesions and serum of early HCC patients. Functional studies reveal that MCB1 modulated p53 protein degradation to promote T-IC generation and drive HCC initiation. Furthermore, the MCB1/p53 axis is shown to determine the responses of hepatoma cells to conventional chemotherapeutics and predict transcatheter arterial chemoembolization (TACE) benefits in patients. Importantly, MCB1 can mediate sorafenib/lenvatinib resistance by downregulating two essential drug targets fibroblast growth factor receptor 1 (FGFR1) and vascular endothelial growth factor receptor 3 (VEGFR3) expression in a proteasome-dependent manner. Patient-derived tumor organoids (PDOs), patient-derived xenografts (PDXs), and patient cohorts analysis suggested that MCB1 levels in HCCs may determine the distinct responses to conventional therapeutics and targeted drugs. Furthermore, treatment of targeted drugs-resistant HCC with adeno-associated virus (AAV) targeting MCB1 or a proteasome inhibitor restores targeted drug response, suggesting their clinical significance in HCC combinational therapy. In conclusion, these findings demonstrate that MCB1 could act as a driver for HCC initiation, a contributor to drug resistance, and a biomarker for individualized HCC therapy.

NK cell-based immunotherapy in hepatocellular carcinoma: An attractive therapeutic option for the next decade

Hepatocellular carcinoma (HCC), a major subtype of liver cancer, poses significant therapeutic challenges due to its late diagnosis and rapid progression. The evolving landscape of immunotherapy offers a beacon of hope, with natural killer (NK) cells emerging as pivotal players in combating HCC. NK cells are unique cytotoxic lymphocytes that are essential in the fight against infections and malignancies. Phenotypic and functional NK cell abnormalities have been shown in HCC patients, indicating their significance as a component of the innate immune system against cancer. This review elucidates the critical role of NK cells in combating HCC, focusing on their interaction with the tumor microenvironment, the development of NK cell-based therapies, and the innovative strategies to enhance their efficacy in the immunosuppressive milieu of HCC. The review delves into the various therapeutic strategies, including autologous and allogeneic NK cell therapies, genetic engineering to improve NK cell resilience and targeting, and the integration of NK cells with other immunotherapeutic approaches like checkpoint inhibitors and oncolytic virotherapy. By highlighting recent advancements and the ongoing challenges in the field, this review sets the stage for future research directions that could unlock the full potential of NK cell-based immunotherapy for HCC, offering a beacon of hope for patients battling this formidable cancer.

Histological predictors of aggressive recurrence of hepatocellular carcinoma after liver resection

BACKGROUND & AIMS

Assessment of recurrence risk after liver resection (LR) is critical in hepatocellular carcinoma (HCC), particularly with the advent of effective adjuvant therapy. The aim of this study was to analyze the clinical and pathological factors associated with recurrence, aggressive recurrence, and survival after LR.

METHOD

We performed a retrospective study in which all single HCC (BCLC-0/A) patients treated with LR between February 2000 and November 2020 were included. The main clinical variables were recorded. Histological features were blindly evaluated by two independent pathologists. Aggressive recurrence was defined as those that exceeded the Milan criteria at 1st recurrence.

RESULTS

A total of 218 patients were included (30% BCLC 0 and 70% BCLC A), median (IQR) tumor size of 28 (19-42 mm). The prevalence of microvascular invasion and/or satellitosis (mVI/S) was 39%, with a kappa-index between both pathologists of 0.8. After a median follow-up of 49 (23-85) months, 61/218 (28%) patients died, 32/218 (15%) underwent liver transplantation, 127 (58%) developed HCC recurrence. The prevalence of aggressive recurrence was 35% (44/127 Milan-out, with 20 cases at advanced stage), and the 5-year survival rate was 81%. The presence of mVI/S was the only independent predictor of recurrence (hazard ratio [HR] 1.83, 95% CI 1.28-2.61, p <0.001), aggressive recurrence (HR 3.31, 95% CI 1.74-6.29, p <0.001) and mortality (HR 2.23, 95% CI 1.27-3.91, p = 0.005). The macrotrabecular-massive subtype was significantly associated with a higher prevalence of mVI/S, Edmonson Steiner grade III-IV, AFP values and vessels that encapsulate tumor clusters, but not with recurrence, aggressive recurrence, or overall survival.

CONCLUSION

The presence of mVI/S was the only independent risk factor for aggressive recurrence and mortality. This has important implications for early-stage patient management, especially in the setting of adjuvant immunotherapy or ab initio LT.

IMPACT AND IMPLICATIONS

Assessment of recurrence risk after liver resection is crucial in patients with hepatocellular carcinoma. Patients with a high risk of recurrence are candidates for liver transplantation as an ab initio indication or for the potential use of adjuvant therapy. Aggressive recurrences, defined as those exceeding the Milan criteria at first recurrence, have a significant impact on overall survival (OS). Fifty-eight percent of patients experienced hepatocellular carcinoma recurrence, with a prevalence of aggressive recurrence at the first occurrence standing at 35%. After a median follow-up of 49 (23-85) months, 61 (28%) patients died, and 32 (15%) underwent liver transplantation, resulting in a 5-year OS rate of 81%. Microvascular invasion and/or satellitosis was present in 39% of our cohort and was the only independent predictor of recurrence, aggressive recurrence, and OS on multivariate analysis. This is important as it could be used to guide therapeutic management.

BAIAP2L2 promotes the malignancy of hepatocellular carcinoma via GABPB1-mediated reactive oxygen species imbalance

Hepatocellular carcinoma (HCC) is a common type of cancer worldwide and ranks as the fourth leading cause of cancer-related deaths. This research investigation identified an upregulation of BAI1-associated protein 2-like 2 (BAIAP2L2) in HCC tissues, which was found to be an independent prognostic factor for overall survival in HCC patients. BAIAP2L2 was observed to enhance cell proliferation, metastasis, stemness, cell cycle progression, and inhibit apoptosis in HCC. Mechanistically, NFκB1 was found to stimulate BAIAP2L2 transcription by directly binding to its promoter region. BAIAP2L2 interacts with GABPB1 to inhibit its ubiquitin-mediated degradation and promote its nuclear translocation. BAIAP2L2 inhibits the levels of reactive oxygen species (ROS) by regulating GABPB1, thereby promoting cancer properties in HCC and reducing the sensitivity of HCC to lenvatinib. In summary, this study elucidates the role and underlying mechanism of BAIAP2L2 in HCC, providing a potential biomarker and therapeutic target for this disease.

Resistance to Tyrosine Kinase Inhibitors in Hepatocellular Carcinoma (HCC): Clinical Implications and Potential Strategies to Overcome the Resistance

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, and the development of effective treatment strategies remains a significant challenge in the management of advanced HCC patients. The emergence of tyrosine kinase inhibitors (TKIs) has been a significant advancement in the treatment of HCC, as these targeted therapies have shown promise in prolonging the survival of patients with advanced disease. Although immunotherapy is currently considered as the first line of treatment for advanced HCC patients, many such patients do not meet the clinical criteria to be eligible for immunotherapy, and in many parts of the world there is still lack of accessibility to immunotherapy. As such, TKIs still serve as the first line of treatment and play a major role in the treatment repertoire for advanced HCC patients. However, the development of resistance to these agents is a major obstacle that must be overcome. In this review, we explore the underlying mechanisms of resistance to TKIs in HCC, the clinical implications of this resistance, and the potential strategies to overcome or prevent the emergence of resistance.

A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma

Recent studies suggest cGAS-STING pathway may play a crucial role in the genesis and development of hepatocellular carcinoma (HCC), closely associated with classical pathways and tumor immunity. We aimed to develop models predicting survival and anti-PD-1/PD-L1 outcomes centered on the cGAS-STING pathway in HCC. We identified classical pathways highly correlated with cGAS-STING pathway and constructed transformer survival model preserving raw structure of pathways. We also developed explainable XGBoost model for predicting anti-PD-1/PD-L1 outcomes using SHAP algorithm. We trained and validated transformer survival model on pan-cancer cohort and tested it on three independent HCC cohorts. Using 0.5 as threshold across cohorts, we divided each HCC cohort into two groups and calculated P values with log-rank test. TCGA-LIHC: C-index = 0.750, P = 1.52e-11; ICGC-LIRI-JP: C-index = 0.741, P = .00138; GSE144269: C-index = 0.647, P = .0233. We trained and validated [area under the receiver operating characteristic curve (AUC) = 0.777] XGBoost model on immunotherapy datasets and tested it on GSE78220 (AUC = 0.789); we also tested XGBoost model on HCC anti-PD-L1 cohort (AUC = 0.719). Our deep learning model and XGBoost model demonstrate potential in predicting survival risks and anti-PD-1/PD-L1 outcomes in HCC. We deployed these two prediction models to the GitHub repository and provided detailed instructions for their usage: deep learning survival model, https://github.com/mlwalker123/CSP_survival_model; XGBoost immunotherapy model, https://github.com/mlwalker123/CSP_immunotherapy_model.

Natural Killer Cell-Associated Radiogenomics Model for Hepatocellular Carcinoma: Integrating CD2 and Enhanced CT-Derived Radiomics Signatures

RATIONALE AND OBJECTIVES

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality. Natural Killer (NK) cells play a crucial role in immune defense against HCC, but their activity is often impaired by the tumor microenvironment (TME). This study aims to integrate radiomics and transcriptomics to develop a prognostic model linking NK cell characteristics to clinical outcomes in HCC.

METHODS

Transcriptomic data from five cohorts (734 HCC patients) from the Gene Expression Omnibus and The Cancer Genome Atlas databases were analyzed using the Microenvironment Cell Populations-counter algorithm. NK cell-related prognostic biomarkers were identified via weighted gene co-expression network analysis and LASSO-Cox regression. Radiomics models were established using CT imaging features from 239 patients in three datasets from The Cancer Imaging Archive and Shanghai East Hospital. HCC radiogenomic subtypes were proposed by integrating genetic biomarkers and radiomics models.

RESULTS

CD2 expression was identified as an independent NK cell-related prognostic biomarker, with a positive impact on prognosis and a strong correlation with NK cell-associated biological processes in HCC. A robust radiomics model was constructed, and the integration of CD2 expression with radioscore identified potential radiogenomic subtypes of HCC.

CONCLUSION

Radiomics has potential to link TME immune phenotypes with HCC prognosis. CD2 is a key biomarker connecting NK cells with radiomic features, offering a new classification of HCC into radiogenomic subtypes. This approach supports the use of radiogenomics in personalized HCC treatment.

Tumor-Targeted CO Nanodelivery System Design and Therapy for Hepatocellular Carcinoma

In recent years, carbon monoxide (CO) has garnered increased attention as a novel green therapy for hepatocellular carcinoma (HCC) treatment. However, the CO donor is still limited in clinical application due to its lack of targeted ability and unstable release rate. Here, self-assembled amphiphilic nanomicelles glucose-polyethylene glycol (PEG)-lipoic acid (LA)-Fe2(CO)6 (Glu-Fe2(CO)6) are first designed as a CO donor and synthesized via a chemical method, combining glucose with Fe2(CO)6 through PEG-LA. Some advantages of this tumor-targeted Glu-Fe2(CO)6 delivery system include (I) good water-solubility, (II) the glutathione responsive CO slow release, (III) the active tumor-targeted ability of glucose as targeted ligands, and (IV) outstanding efficacy of antitumor and safety of CO therapy of HCC both in vitro and in vivo. These findings suggest that Glu-Fe2(CO)6 nanomicelles hold promise for enhancing antitumor therapeutic capabilities, presenting a novel tumor-targeted delivery strategy in gas therapy for HCC treatment.

Serum apolipoprotein H determines ferroptosis resistance by modulating cellular lipid composition

Ferroptosis is a regulated cell death process dependent on iron, triggered by the accumulation of lipid peroxidation. The environmental context significantly impacts cellular sensitivities to ferroptosis. Serum, constituting the extracellular fluid composition in vivo, provides crucial environmental biomolecules. In this study, we investigated the influence of sera on ferroptosis induction, pinpointing the serum protein apolipoprotein H (APOH) as a pivotal inhibitor of ferroptosis. Moreover, we elucidated that APOH suppresses ferroptosis by activating the phosphoinositide 3-kinase (PI3K)-AKT-sterol regulatory element-binding proteins (SREBPs) pathway, thereby elevating stearoyl-CoA desaturase (SCD) levels and augmenting cellular monounsaturated fatty acid-containing phospholipids (MUFA-PLs). Furthermore, ApoHinfer, the peptide derivative of the active region of APOH, mimics its ferroptosis inhibitory activity. Our findings underscore the critical role of serum protein APOH in the inhibition of ferroptosis and indicates potential therapeutic applications in treating cancer and diseases associated with ferroptosis.

Global research trends in the tumor microenvironment of hepatocellular carcinoma: insights based on bibliometric analysis

Objective

This study aimed to use visual mapping and bibliometric analysis to summarize valuable information on the tumor microenvironment (TME)-related research on hepatocellular carcinoma (HCC) in the past 20 years and to identify the research hotspots and trends in this field.

Methods

We screened all of the relevant literature on the TME of HCC in the Web of Science database from 2003 to 2023 and analysed the research hotspots and trends in this field via VOSviewer and CiteSpace.

Results

A total of 2,157 English studies were collected. According to the prediction, the number of papers that were published in the past three years will be approximately 1,394, accounting for 64.63%. China published the most papers (n=1,525) and had the highest total number of citations (n=32,253). Frontiers In Immunology published the most articles on the TME of HCC (n=75), whereas, Hepatology was the journal with the highest total number of citations (n=4,104) and average number of citations (n=91). The four clusters containing keywords such as "cancer-associated fibroblasts", "hepatic stellate cells", "immune cells", "immunotherapy", "combination therapy", "landscape", "immune infiltration", and "heterogeneity" are currently hot research topics in this field. The keywords "cell death", "ferroptosis", "biomarkers", and "prognostic features" have emerged relatively recently, and these research directions are becoming increasingly popular.

Conclusions

We identified four key areas of focus in the study of the TME in HCC: the main components and roles in the TME, immunotherapy, combination therapy, and the microenvironmental landscape. Moreover, the result of our study indicate that effect of ferroptosis on the TME in HCC may become a future research trend.

Delivering adjuvant and neoadjuvant treatments in the early stages of hepatocellular carcinoma

INTRODUCTION

Hepatocellular carcinoma (HCC) presents a formidable challenge in oncology, demanding innovative treatment approaches. Both adjuvant and neoadjuvant therapies, thanks to the introduction of immunotherapy, have emerged as promising strategies in the management of HCC, aiming to reduce the risk of relapse and ultimately to improve survival.

AREAS COVERED

This review considers current evidence, ongoing clinical trials, and future strategies to elucidate the evolving landscape of neoadjuvant and adjuvant treatments in HCC.

EXPERT OPINION

Both adjuvant and neoadjuvant regimens, notably those incorporating immune checkpoint inhibitors, demonstrated encouraging safety profiles and efficacy outcomes in HCC.While significant challenges persist, including optimizing patient selection and endpoint definition, the evolving landscape of neoadjuvant and adjuvant therapy holds promise for maximizing the therapeutic potential of immunotherapy across all stages of HCC. Further insights into tumor biology and host immunity will shape the role of these approaches which are close to becoming reality in clinical practice.

LOCC: a novel visualization and scoring of cutoffs for continuous variables with hepatocellular carcinoma prognosis as an example

BACKGROUND

The interpretation of large datasets, such as The Cancer Genome Atlas (TCGA), for scientific and research purposes, remains challenging despite their public availability. In this study, we focused on identifying gene expression profiles most relevant to patient prognosis and aimed to develop a method and database to address this issue. To achieve this, we introduced Luo's Optimization Categorization Curve (LOCC), an innovative tool for visualizing and scoring continuous variables against dichotomous outcomes. To demonstrate the efficacy of LOCC using real-world data, we analyzed gene expression profiles and patient data from TCGA hepatocellular carcinoma samples.

RESULTS

To showcase LOCC, we demonstrate an optimal cutoff for E2F1 expression in hepatocellular carcinoma, which was subsequently validated in an independent cohort. Compared to ROC curves and their AUC, LOCC offered a superior description of the predictive value of E2F1 expression across various cancer types. The LOCC score, comprised of factors representing significance, range, and impact of the biomarker, facilitated the ranking of all gene expression profiles in hepatocellular carcinoma, aiding in the evaluation and understanding of previously published prognostic gene signatures. We also demonstrate that LOCC does not have the same assumptions required of Cox proportional hazards modeling for accurate analysis. Repeated sampling demonstrated that LOCC scores outperformed ROC's AUC in discriminating predictors from non-predictors. Additionally, gene set enrichment analysis revealed significant associations between certain genes and prognosis, such as E2F target genes and G2M checkpoint with poor prognosis, and bile acid metabolism and oxidative phosphorylation with good prognosis.

CONCLUSION

In summary, we present LOCC as a novel visualization tool for the analysis of gene expression in cancer, particularly for understanding and selecting cutoffs. Our findings suggest that LOCC scores, which effectively rank genes based on their prognostic potential, represent a more suitable approach than ROC curves and Cox proportional hazard for prognostic modeling and understanding in cancer gene expression analysis. LOCC holds promise as an invaluable tool for advancing precision medicine and furthering biomarker research. Further research regarding multivariable integration and validation will help LOCC reach its full potential and establish its utility across diverse cancer types and clinical settings.

The role of NCAPH in cancer treatment

Many solid tumors frequently overexpress Non-SMC Condensin I Complex Subunit H (NCAPH), and new studies suggest that NCAPH may be a target gene for clinical cancer therapy. Numerous investigations have shown that a variety of transcription factors, including as MYBL2, FOXP3, GATA3, and OTC1, can stimulate the transcription of NCAPH. Additionally, NCAPH stimulates many oncogenic signaling pathways, such as β-Catenin/PD-L1, PI3K/AKT/SGK3, MEK/ERK, AURKB/AKT/mTOR, PI3K/PDK1/AKT, and Chk1/Chk2. Tumor immune microenvironment modification and tumor growth, apoptosis, metastasis, stemness, and treatment resistance all depend on these signals. NCAPH has the ability to form complexes with other proteins that are involved in glycolysis, DNA damage repair, and chromatin remodeling. This review indicates that NCAPH expression in most malignant tumors is associated with poor prognosis and low recurrence-free survival.

Heterogeneity of hepatocellular carcinoma that responds differently to combination therapy with TACE and Sorafenib as determined by digital spatial gene expression profiling

BACKGROUND

The combination of Sorafenib and transcatheter arterial chemoembolization (TACE) exhibits limited efficacy in the treatment of certain advanced hepatocellular carcinomas (HCC), and the molecular mechanisms underlying resistance to this combination remain unclear.

OBJECTIVE

This study aims to underscore the distinctive contribution of GeoMx DSP technology in elucidating the molecular intricacies of HCC resistance to the Sorafenib and TACE combination.

METHODS

Patients with advanced HCC during the waiting period before liver transplantation were classified into sensitive and resistant groups based on their response to Sorafenib and TACE combination therapy. Employing GeoMx DSP technology for comprehensive gene expression profiling, we identified pivotal molecular targets linked to resistance against combination therapy.

RESULTS

The investigation scrutinized intra-tumoral and inter-individual variances, unveiling a spectrum of crucial molecular targets, such as PLG, PLVAP, immunoglobulin genes, ORM1, and NR4A1, among others. Additionally, we explored signaling pathways associated with treatment responsiveness, including the PPAR signaling pathway. Notably, we emphasized the significance of the immune microenvironment characterized by heightened SPP1 expression in HCC resistance to combination therapy. In the resistant group, SPP1+ tumor-associated macrophage (TAM) infiltration was notably pronounced (p = 0.037), while T-cell depletion showed a mitigated presence (p = 0.013).

CONCLUSION

The study reveals intra- and inter-individual heterogeneity in HCC that is differentially responsive to the combination of Sorafenib and TACE, highlighting multiple key molecular targets associated with treatment resistance. The immune microenvironment is important, and in particular, SPP1+ TAM infiltration may play a key role. Meanwhile, the introduction of immunotherapy in patients resistant to combination therapy may lead to positive results.

AC099850.3 promotes HBV-HCC cell proliferation and invasion through regulating CD276: a novel strategy for sorafenib and immune checkpoint combination therapy

BACKGROUND

This study investigates the molecular mechanisms of CC@AC&SF@PP NPs loaded with AC099850.3 siRNA and sorafenib (SF) for improving hepatitis B virus-related hepatocellular carcinoma (HBV-HCC).

METHODS

A dataset of 44 HBV-HCC patients and their survival information was selected from the TCGA database. Immune genes related to survival status were identified using the ImmPort database and WGCNA analysis. A prognostic risk model was constructed and analyzed using Lasso regression. Differential analysis was performed to screen key genes, and their significance and predictive accuracy for HBV-HCC were validated using Kaplan-Meier survival curves, ROC analysis, CIBERSORT analysis, and correlation analysis. The correlation between AC099850.3 and the gene expression matrix was calculated, followed by GO and KEGG enrichment analysis using AC099850.3 and its co-expressed genes. HepG2.2.15 cells were selected for in vitro validation, and lentivirus interference, cell cycle determination, CCK-8 experiments, colony formation assays, Transwell experiments, scratch experiments, and flow cytometry were performed to investigate the effects of key genes on HepG2.2.15 cells. A subcutaneous transplanted tumor model in mice was constructed to verify the inhibitory effect of key genes on HBV-HCC tumors. Subsequently, pH-triggered drug release NPs (CC@AC&SF@PP) were prepared, and their therapeutic effects on HBV-HCC in situ tumor mice were studied.

RESULTS

A prognostic risk model (AC012313.9, MIR210HG, AC099850.3, AL645933.2, C6orf223, GDF10) was constructed through bioinformatics analysis, showing good sensitivity and specificity in diagnostic prediction. AC099850.3 was identified as a key gene, and enrichment analysis revealed its impact on cell cycle pathways. In vitro cell experiments demonstrated that AC099850.3 promotes HepG2.2.15 cell proliferation and invasion by regulating immune checkpoint CD276 expression and cell cycle progression. In vivo, subcutaneously transplanted tumor experiments showed that AC099850.3 promotes the growth of HBV-HCC tumors in nude mice. Furthermore, pH-triggered drug release NPs (CC@AC&SF@PP) loaded with AC099850.3 siRNA and SF were successfully prepared and delivered to the in situ HBV-HCC, enhancing the effectiveness of combined therapy for HBV-HCC.

CONCLUSIONS

AC099850.3 accelerates the cell cycle progression and promotes the occurrence and development of HBV-HCC by upregulating immune checkpoint CD276 expression. CC@AC&SF@PP NPs loaded with AC099850.3 siRNA and SF improve the effectiveness of combined therapy for HBV-HCC.

Phytochemical profiling and anticancer potential of gardenia latifolia extracts against arsenic trioxide induced liver fibrosis in rat model

Introduction

Arsenic trioxide (As2O3) is an environmental contaminant that may cause hepatic injuries. As2O3-induced liver injuries are detected as an underlying cause of hepatocellular carcinoma (HCC) around the globe. The present study aimed to investigate the potential of Gardenia latifolia (GL) extracts against oxidative stress and apoptotic activity in HCC-induced rats and to explore in silico molecular docking analysis of phytocompounds of G. latifolia.

Methods

The present study was designed to investigate the hepato-protective effect of ethanol and n-hexane extract of G. latifolia. Phytochemical analysis was performed using gas-chromatography-mass spectrometry (GC-MS), and the identified metabolites were used for computational docking analysis. The binding potential and inhibitory effect of the identified metabolites against inflammatory markers were assessed. Fifty male albino rats were selected for the in vivo study and were randomly divided into five groups, with 10 rats in each group. Group I is the control group. Hepatotoxicity was induced in groups II, III, IV, and V with 350 mg/kg/day of As2O3. Group II was taken as positive control, Group III and IV were treated with ethanol and n-hexane extract of G. latifolia, respectively, and Group V was treated with cisplatin 3.0 mg/kg/day. At the end of treatment, different stress and liver biomarkers were also analyzed.

Results and Discussion

The quantitative phytochemical profiling revealed a high content of total flavonoid and tannins found at 5.731 ± 0.1856 mg quercetin equivalent (QE)/g and 86.31 ± 14.20 mg tannic acid equivalent (TAE)/g in G. latifolia n-hexane extract, while a significant concentration of TFC was 276.821 ± 2.19 mg gallic acid equivalent (GAE)/g, in ethanolic extract. GC-MS analysis resulted in the identification of 26 metabolites in ethanol extract while 32 metabolites in n-hexane extract, respectively. Both the extracts restored the abnormal levels of stress markers (p < 0.05) in Groups III and IV, and were comparable to the comparative control group V, which was given cisplatin as the standard drug. The histopathological examination revealed the regeneration of hepatocytes, dilated sinusoidal cells, necrosis, and distorted hepatic architecture observed in arsenic trioxide hepatotoxic liver. Among the top most identified metabolites from GC-MS analysis, stigmasterol exhibited -8.3 and -7.1 kcal/mol in silico binding affinities against cyclooxygenase-2 (COX-2), and interleukin (IL-6), respectively, while Dasycarpidan-1-methanol exhibited the best binding affinities of -6.8 and -7.2 kcal/mole against matrixmetalloprotinease (MMP)-3 and heat shock protein-90 (HSP-90), respectively. 6-AH-cAMP showed the best docking score of -7.5 kcal/mol for the vascular endothelial growth factor (VEGF) macromolecule. Metabolite Dasycarpidan-1-methanol, acetate represented drug like properties so it was further analyzed by MD simulation and stable dynamic nature of protein ligand complex was evaluated.

Conclusion

In conclusion, the effective therapeutic potential of G. latifolia extracts targeted oxidative stress, increasing antioxidant activities and inhibiting inflammation and liver complications at early stages. Further research on the molecular level may further explore the anticancer potential of this plant against various types of cancers.

CCT3/ACTN4/TFRC axis protects hepatocellular carcinoma cells from ferroptosis by inhibiting iron endocytosis

Sorafenib is widely used in treating advanced hepatocellular carcinoma (HCC). However, its effectiveness in prolonging patient survival is limited by the development of drug resistance. To systematically investigate the resistance mechanisms of Sorafenib, an integrative analysis combining posttranslational modification (PTM) omics and CRISPR/Cas9 knockout library screening was conducted. This analysis identified ubiquitination at lysine 21 (K21) on chaperonin-containing TCP1 subunit 3 (CCT3) as being associated with Sorafenib resistance. Transcriptomic data from HCC patients treated with Sorafenib revealed that CCT3 expression was lower in responders compared to non-responders. Experimentally, inhibiting the expression of CCT3 sensitized HCC cells to Sorafenib and enhanced Sorafenib-induced ferroptosis. Additionally, CCT3 was found to interact with ACTN4, hindering the recycling of transferrin receptor protein 1 (TFRC) to the cell membrane, thus obstructing iron endocytosis. Mechanistically, the inhibition of ferroptosis by CCT3 depends on the deubiquitination of K6-linked non-degradative ubiquitination at its K21, which occurs upon Sorafenib treatment. Moreover, CCT3 knockdown enhanced the anti-tumor effects of Sorafenib in nude mice. In summary, we have identified a novel function of the chaperone protein. Targeting the CCT3/ACTN4/TFRC axis offers a promising strategy to enhance ferroptosis and overcome Sorafenib resistance in HCC.

HMGB2 drives tumor progression and shapes the immunosuppressive microenvironment in hepatocellular carcinoma: insights from multi-omics analysis

Background

Hepatocellular carcinoma (HCC) poses a significant health burden globally, with high mortality rates despite various treatment options. Immunotherapy, particularly immune-checkpoint inhibitors (ICIs), has shown promise, but resistance and metastasis remain major challenges. Understanding the intricacies of the tumor microenvironment (TME) is imperative for optimizing HCC management strategies and enhancing patient prognosis.

Methods

This study employed a comprehensive approach integrating multi-omics approaches, including single-cell RNA sequencing (scRNA-seq), bulk RNA sequencing (Bulk RNA-seq), and validation in clinical samples using spatial transcriptomics (ST) and multiplex immunohistochemistry (mIHC). The analysis aimed to identify key factors influencing the immunosuppressive microenvironment associated with HCC metastasis and immunotherapy resistance.

Results

HMGB2 is significantly upregulated in HCCTrans, a transitional subgroup associated with aggressive metastasis. Furthermore, HMGB2 expression positively correlates with an immunosuppressive microenvironment, particularly evident in exhausted T cells. Notably, HMGB2 expression correlated positively with immunosuppressive markers and poor prognosis in HCC patients across multiple cohorts. ST combined with mIHC validated the spatial expression patterns of HMGB2 within the TME, providing additional evidence of its role in HCC progression and immune evasion.

Conclusion

HMGB2 emerges as a critical player of HCC progression, metastasis, and immunosuppression. Its elevated expression correlates with aggressive tumor behavior and poor patient outcomes, suggesting its potential as both a therapeutic target and a prognostic indicator in HCC management.

Characterizing the role of exosomal miRNAs in metastasis

Background

Exosomal microRNAs (exomiRs), transported via exosomes, play a pivotal role in intercellular communication. In cancer, exomiRs influence tumor progression by regulating key cellular processes such as proliferation, angiogenesis, and metastasis. Their role in mediating communication between cancer cells and the tumor microenvironment highlights their significance as potential diagnostic and therapeutic targets.

Methodology

In this study, we aimed to characterize the role of exomiRs in influencing the pre-metastatic niche (PMN). Across 7 tumor types, including 4 cell lines and three tumors, we extracted high confidence exomiRs (Log FC >= 2 in exosomes relative to control) and their targets (experimentally identified and targeted by at least 2 exomiRs). Subsequently, we identified enriched pathways and selected the top 100 high-confidence exomiR targets based on the frequency of their appearance in the enriched pathways. These top 100 targets were consistently used throughout the analysis.

Results

Cancer cell line and tumor derived ExomiRs have significantly higher GC content relative to genomic background. Pathway enriched among the top exomiR targets included general cancer-associated processes such as "wound healing" and "regulation of epithelial cell proliferation", as well as cancer-specific processes, such as "regulation of angiogenesis in kidney" (KIRC), "ossification" in lung (LUAD), and "positive regulation of cytokine production" in pancreatic cancer (PAAD). Similarly, 'Pathways in cancer' and 'MicroRNAs in cancer' ranked among the top 10 enriched KEGG pathways in all cancer types. ExomiR targets were not only enriched for cancer-specific tumor suppressor genes (TSG) but are also downregulated in pre-metastatic niche formed in lungs compared to normal lung. Motif analysis shows high similarity among motifs identified from exomiRs across cancer types. Our analysis recapitulates exomiRs associated with M2 macrophage differentiation and chemoresistance such as miR-21 and miR-222-3p, regulating signaling pathways such as PTEN/PI3/Akt, NF-κB, etc. Cox regression indicated that exomiR targets are significantly associated with overall survival of patients in TCGA. Lastly, a Support Vector Machine (SVM) model using exomiR target gene expression classified responders and non-responders to neoadjuvant chemotherapy with an AUROC of 0.96 (in LUAD), higher than other previously reported gene signatures.

Conclusion

Our study characterizes the pivotal role of exomiRs in shaping the PMN in diverse cancers, underscoring their diagnostic and therapeutic potential.

Matrix stiffness-dependent PD-L2 deficiency improves SMYD3/xCT-mediated ferroptosis and the efficacy of anti-PD-1 in HCC

INTRODUCTION

Heterogeneous tissue stiffening promotes tumor progression and resistance, and predicts a poor clinical outcome in patients with hepatocellular carcinoma (HCC). Ferroptosis, a congenital tumor suppressive mechanism, mediates the anticancer activity of various tumor suppressors, including immune checkpoint inhibitors, and its induction is currently considered a promising treatment strategy. However, the role of extracellular matrix (ECM) stiffness in regulating ferroptosis and ferroptosis-targeted resistance in HCC remains unclear.

OBJECTIVES

This research aimed to explore how extracellular matrix stiffness affects ferroptosis and its treatment efficacy in HCC.

METHODS

Ferroptosis analysis was confirmed via cell activity, intracellular ferrous irons, and mitochondrial pathology assays. Baseline PD-L2, SMYD3, and SLC7A11 (xCT) were evaluated in 67 sorafenib-treated patients with HCC (46 for non-responder and 21 for responder) from public data. The combined efficacy of shPD-L2, sorafenib, and anti-PD-1 antibody in HCC was investigated in vivo.

RESULTS

Here, we revealed that matrix stiffness-induced PD-L2 functions as a suppressor of xCT-mediated ferroptosis to promote cancer growth and sorafenib resistance in patients with HCC. Mechanically, matrix stiffening induced the expression of PD-L2 by activating SMYD3/H3K4me3, which acts as an RNA binding protein to enhance the mRNA stability of FTL and elevate its protein level. Knockdown of PD-L2 significantly promoted xCT-mediated ferroptosis induced by RSL3 or sorafenib on stiff substrate via FTL, whereas its overexpression abolished these upward trends. Notably, PD-L2 deletion in combination with sorafenib and anti-PD-1 antibody significantly sensitized HCC cells and blunted cancer growth in vivo. Additionally, we found the ferroptosis- and immune checkpoint-related prognostic genes that combined PD-L2, SLC7A11 and SYMD3 well predict the clinical efficacy of sorafenib in patients with HCC.

CONCLUSION

These findings expand our understanding of the mechanics-dependent PD-L2 role in ferroptosis, cancer progression and resistance, providing a basis for the clinical translation of PD-L2 as a therapeutic target or diagnostic biomarker.

Circulating microRNAs as biomarkers for stratifying different phases of liver cancer progression and response to therapy

Hepatocellular carcinoma (HCC) is the most common liver cancer and is among the leading causes of cancer-related death worldwide. There is no reliable biomarker for the early diagnosis of HCC. Circulating microRNAs (miRNAs) have attracted attention as potential biomarkers of disease. By small-RNA next-generation sequencing, the analysis of serum miRNAs led to the identification of molecular signatures able to discriminate advanced HCC from early HCC (n = 246); advanced HCC from CIRRHOSIS (n = 299); advanced HCC from HEALTHY (n = 320); HEALTHY from early HCC (n = 343); and HEALTHY from CIRRHOSIS (n = 414). Cirrhotic patients and early HCC patients exhibited similar serum miRNA profiles, yet a small number of miRNAs (n = 57) were able to distinguish these two classes of patients. A second objective of the study was to identify serum miRNAs capable of predicting the response to therapy in patients with advanced HCC. All patients were treated with sorafenib as first-line therapy: 24 were nonresponsive and 24 responsive. Analysis of circulating miRNAs revealed a 54 miRNAs signature able to separate the two subgroups. This study suggested that circulating miRNAs could be useful biomarkers for monitoring patients with liver diseases ranging from cirrhosis to advanced HCC and possibly predicting susceptibility to first-line treatment based on sorafenib.

Noncanonical regulation of HOIL-1 on cancer stemness and sorafenib resistance identifies pixantrone as a novel therapeutic agent for HCC

BACKGROUND AND AIMS

Cancer stem cells (CSCs) contribute to therapy resistance in HCC. Linear ubiquitin chain assembly complex (LUBAC) has been reported to accelerate the progression of cancers, yet its role in the sorafenib response of HCC is poorly defined. Herein, we investigated the impact of LUBAC on sorafenib resistance and the CSC properties of HCC, and explored the potential targeted drugs.

APPROACH AND RESULTS

We found that HOIL-1, but not the other components of LUBAC, played a contributing role in LUBAC-mediated HCC sorafenib resistance, independent of its ubiquitin ligase activity. Both in vitro and in vivo assays revealed that the upregulated HOIL-1 expression enhanced the CSC properties of HCC. Mechanistically, HOIL-1 promoted sorafenib resistance and the CSC properties of HCC through Notch1 signaling. Mass spectrometry, co-immunoprecipitation, western blot, and immunofluorescence were used to determine that the A64/Q65 residues of HOIL-1 bound with the K78 residue of Numb, resulting in impaired Numb-mediated Notch1 lysosomal degradation. Notably, pixantrone was screened out by Autodock Vina, which was validated to disrupt HOIL-1/Numb interaction to inhibit Notch1 signaling and CSC properties by targeting the Q65 residue of HOIL-1. Moreover, pixantrone exerted synergistic effects with sorafenib for the treatment of HCC in different HCC mouse models.

CONCLUSIONS

HOIL-1 is critical in promoting sorafenib resistance and CSC properties of HCC through Notch1 signaling. Pixantrone targeting HOIL-1 restrains the sorafenib resistance and provides a potential therapeutic intervention for HCC.

POSTN+ cancer-associated fibroblasts determine the efficacy of immunotherapy in hepatocellular carcinoma

OBJECTIVE

Hepatocellular carcinoma (HCC) poses a significant clinical challenge because the long-term benefits of immune checkpoint blockade therapy are limited. A comprehensive understanding of the mechanisms underlying immunotherapy resistance in HCC is imperative for improving patient prognosis.

DESIGN

In this study, to systematically investigate the characteristics of cancer-associated fibroblast (CAF) subsets and the dynamic communication among the tumor microenvironment (TME) components regulated by CAF subsets, we generated an HCC atlas by compiling single-cell RNA sequencing (scRNA-seq) datasets on 220 samples from six datasets. We combined spatial transcriptomics with scRNA-seq and multiplexed immunofluorescence to identify the specific CAF subsets in the TME that determine the efficacy of immunotherapy in HCC patients.

RESULTS

Our findings highlight the pivotal role of POSTN+ CAFs as potent immune response barriers at specific tumor locations, as they hinder effective T-cell infiltration and decrease the efficacy of immunotherapy. Additionally, we elucidated the interplay between POSTN+ CAFs and SPP1+ macrophages, whereby the former recruits the latter and triggers increased SPP1 expression via the IL-6/STAT3 signaling pathway. Moreover, we demonstrated a spatial correlation between POSTN+ CAFs and SPP1+ macrophages, revealing an immunosuppressive microenvironment that limits the immunotherapy response. Notably, we found that patients with elevated expression levels of both POSTN+ CAFs and SPP1+ macrophages achieved less therapeutic benefit in an immunotherapy cohort.

CONCLUSION

Our research elucidates light on the role of a particular subset of CAFs in immunotherapy resistance, emphasizing the potential benefits of targeting specific CAF subpopulations to improve clinical responses to immunotherapy.

Extracellular Vesicles, Circadian Rhythms, and Cancer: A Comprehensive Review with Emphasis on Hepatocellular Carcinoma

This review comprehensively explores the complex interplay between extracellular vesicles (ECVs)/exosomes and circadian rhythms, with a focus on the role of this interaction in hepatocellular carcinoma (HCC). Exosomes are nanovesicles derived from cells that facilitate intercellular communication by transporting bioactive molecules such as proteins, lipids, and RNA/DNA species. ECVs are implicated in a range of diseases, where they play crucial roles in signaling between cells and their surrounding environment. In the setting of cancer, ECVs are known to influence cancer initiation and progression. The scope of this review extends to all cancer types, synthesizing existing knowledge on the various roles of ECVs. A unique aspect of this review is the emphasis on the circadian-controlled release and composition of exosomes, highlighting their potential as biomarkers for early cancer detection and monitoring metastasis. We also discuss how circadian rhythms affect multiple cancer-related pathways, proposing that disruptions in the circadian clock can alter tumor development and treatment response. Additionally, this review delves into the influence of circadian clock components on ECV biogenesis and their impact on reshaping the tumor microenvironment, a key component driving HCC progression. Finally, we address the potential clinical applications of ECVs, particularly their use as diagnostic tools and drug delivery vehicles, while considering the challenges associated with clinical implementation.

Prognostic insights, immune infiltration, and therapeutic response: Cytoplasmic poly(A) tail regulators in hepatocellular carcinoma

The presence of a poly(A) tail is indispensable for the post-transcriptional regulation of gene expression in cancer. This dynamic and modifiable feature of transcripts is under the control of various nuclear and cytoplasmic proteins. This study aimed to develop a novel cytoplasmic poly(A)-related signature for predicting prognosis, clinical attributes, tumor immune microenvironment (TIME), and treatment response in hepatocellular carcinoma (HCC). Utilizing RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA), non-negative matrix factorization (NMF), and principal-component analysis (PCA) were employed to categorize HCC patients into three clusters, thus demonstrating the pivotal prognostic role of cytoplasmic poly(A) tail regulators. Furthermore, machine learning algorithms such as least absolute shrinkage and selection operator (LASSO), survival analysis, and Cox proportional hazards modeling were able to distinguish distinct cytoplasmic poly(A) subtypes. As a result, a 5-gene signature derived from TCGA was developed and validated using International Cancer Genome Consortium (ICGC) HCC datasets. This novel classification based on cytoplasmic poly(A) regulators has the potential to improve prognostic predictions and provide guidance for chemotherapy, immunotherapy, and transarterial chemoembolization (TACE) in HCC.

Novel genetic alterations in liver cancer distinguish distinct clinical outcomes and combination immunotherapy responses

Introduction: Genomic profiling has revolutionized therapeutic interventions and the clinical management of liver cancer. However, pathogenetic mechanisms, molecular determinants of recurrence, and predictive biomarkers for first-line treatment (anti-PD-(L)1 plus bevacizumab) in liver cancer remain incompletely understood. Materials and methods: Targeted next-generation sequencing (tNGS) (a 603-cancer-gene panel) was applied for the genomic profiling of 232 hepatocellular carcinoma (HCC) and 22 intrahepatic cholangiocarcinoma (ICC) patients, among which 47 unresectable/metastatic HCC patients underwent anti-PD-1 plus bevacizumab therapy. Genomic alterations were estimated for their association with vascular invasion (VI), location of onset, recurrence, overall survival (OS), recurrence-free survival (RFS), and anti-PD-1 plus bevacizumab therapy response. Results: The genomic landscape exhibited that the most commonly altered genes in HCC were TP53, FAT3, PDE4DIP, KMT2C, FAT1, and MYO18A, while TP53, FAT1, FAT3, PDE4DIP, ROS1, and GALNT11 were frequently altered in ICC; notably, KRAS (18.18% vs. 1.29%) and BAP1 (13.64% vs. 1.29%) alterations were significantly more prevalent in ICC. Comparison analysis demonstrated the distinct clinicopathological/genomic characterizations between Chinese and Western HCC cohorts. Genomic profiling of HCC underlying VI showed that LDLR, MSH2, KDM5D, PDE3A, and FOXO1 were frequently altered in the VI group compared to patients without VIs. Compared to the right hepatic lobes of HCC patients, the left hepatic lobe of HCC patients had superior OS (median OS: 36.77 months vs. unreached, p < 0.05). By further comparison, Notch signaling pathway-related alterations were significantly prevalent among the right hepatic lobes of HCC patients. Of note, multivariate Cox regression analysis showed that altered RB1, NOTCH3, MGA, SYNE1, and ZFHX3, as independent prognostic factors, were significantly correlated with the OS of HCC patients. Furthermore, altered LATS1 was abundantly enriched in the HCC-recurrent group, and impressively, it was independent of clinicopathological features in predicting RFS (median RFS of altered type vs. wild-type: 5.57 months vs. 22.47 months, p < 0.01). Regarding those treated HCC patients, TMB value, altered PTPRZ1, and cell cycle-related alterations were identified to be positively associated with the objective response rate (ORR), but KMT2D alterations were negatively correlated with ORR. In addition, altered KMT2D and cell cycle signaling were significantly associated with reduced and increased time to progression-free survival (PFS), respectively. Conclusion: Comprehensive genomic profiling deciphered distinct molecular characterizations underlying VI, location of onset, recurrence, and survival time in liver cancer. The identification of novel genetic predictors of response to anti-PD-1 plus bevacizumab in HCC facilitated the development of an evidence-based approach to therapy.

Alternative splicing-related long noncoding RNA ANRIL facilitates hepatocellular carcinoma by targeting the miR-199a-5p/SRSF1 axis and impacting Anillin

Hepatocellular carcinoma (HCC) is characterized by aberrant alternative splicing (AS), which plays an important part in the pathological process of this disease. However, available reports about genes and mechanisms involved in AS process are limited. Our previous research has identified ANRIL as a long noncoding RNA related to the AS process of HCC. Here, we investigated the exact effect and the mechanism of ANRIL on HCC progress. The ANRIL expression profile was validated using the real-time quantitative polymerase chain reaction assay. The western blot analysis and IHC assay were conducted on candidate targets, including SRSF1 and Anillin. The clinicopathological features of 97 patients were collected and analyzed. Loss-of and gain-of-function experiments were conducted. The dual-luciferase reporter assay was applied to verify the interaction between ANRIL, miR-199a-5p, and SRSF1. Anomalous upregulation of ANRIL in HCC was observed, correlating with worse clinicopathological features of HCC. HCC cell proliferation, mobility, tumorigenesis, and metastasis were impaired by depleting ANRIL. We found that ANRIL acts as a sponger of miRNA-199a-5p, resulting in an elevated level of its target protein SRSF1. The phenotypes induced by ANRIL/miR-199a-5p/SRSF1 alteration are associated with Anillin, a validated HCC promoter. ANRIL is an AS-related lncRNA promoting HCC progress by modulating the miR-199a-5p/SRSF1 axis. The downstream effector of this axis in the development of HCC is Anillin.

Indolent cancer and pattern of progression: Two missing parameters in trial design for hepatology

The indolent and aggressive behaviors of HCC might have a role in clinical trial (CT) results; however, the indolent HCC is less analyzed compared to others cancer. Indolent profile could be characterized as follows: (1) patients with low risk of progression itself due to the HCC molecular profile and/or due to the interaction between cancer cell their microenvironment; (2) patients who achieve objective response or present spontaneous regression; and (3) patients who develop radiological progression with no consequence on either the liver function or general status, and without trigger a change in the tumor stage. Patients with "indolent HCC" generally never develop cancer-related symptoms neither die for HCC-related causes. Thus, we hypothesize that the imbalance in the proportion of "indolent" versus "aggressive HCC" between arms or the underestimation/overestimation of HCC behavior at baseline in single-arm CT could be associated with CT failure or under-overestimation of trial results. The "indolent progression" may also explain the discrepancy between radiological progression-based end points and survival. Moreover, we discuss the related causes that explain the indolent profile of HCC and propose (1) refining the progression-related end point by the pattern of progression to minimize the limitations of the current end points; (2) considering alternative statistical tools for survival analysis such as milestone survival, or restricted mean survival time to capture the value of indolent HCC. According to these considerations, we propose incorporating novel end points into the single arm of phase I/II CT as exploratory analysis or as a secondary end point in phase III CT.

Integrated Exploration of Epigenetic Dysregulation Reveals a Stemness/EMT Subtype and MMP12 Linked to the Progression and Prognosis in Hepatocellular Carcinoma

Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes. Specially, a stemness/epithelial-mesenchymal transition (EMT) subtype was featured by immune exhaustion and the worst prognosis. Besides, MMP12, a characteristic gene, was highly expressed in the stemness/EMT subtype, which was verified as a pivotal regulator linked to the unfavorable prognosis and further proven to promote tumor proliferation, invasion, and metastasis in vitro experiments. Proteomic analysis by mass spectrometry sequencing also indicated that the overexpression of MMP12 was significantly associated with cell proliferation and adhesion. Taken together, this study unveils innovative insights into epigenetic dysregulation and identifies a stemness/EMT subtype-specific gene, MMP12, correlated with the progression and prognosis of HCC.

The Current and Prospective Adjuvant Therapies for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) stands as the most prevalent form of primary liver cancer and is highly invasive and easily recurs. For HCC, chemotherapy shows limited effect. The gold standard for HCC treatment includes curative surgical resection or liver transplantation. However, the recurrence rate at 5 years after liver resection is estimated at approximately 70% and even at 5 years after liver transplantation, it is 20%. Therefore, improving survival outcomes after curative surgical resection of liver cancer is crucial. This review highlights the importance of identifying risk factors for HCC recurrence following radical surgical resection and adjuvant therapy options that may reduce the recurrence risk and improve overall survival, including local adjuvant therapy (e.g., transcatheter arterial chemoembolization and radiotherapy), adjuvant systemic therapy (e.g., small molecule targeted therapy and immunotherapy), and other adjuvant therapies (e.g., chemotherapy). However, further research is needed to refine the use of these therapies and optimize their effectiveness in preventing HCC recurrence.

Macroscopic Characterization of Hepatocellular Carcinoma: An Underexploited Source of Prognostic Factors

The macroscopic appearance of a tumor such as hepatocellular carcinoma (HCC) may be defined as its phenotype which is de facto dictated by its genotype. Therefore, macroscopic characteristics of HCC are unlikely random but rather reflect genomic traits of cancer, presumably acting as a valuable source of information that can be retrieved and exploited to infer prognosis. This review aims to provide a comprehensive overview of the available data on the prognostic value of macroscopic characterization in HCC. A total of 57 studies meeting eligible criteria were identified, including patients undergoing liver resection (LR; 47 studies, 83%) or liver transplant (LT; 9 studies, 16%). The following macroscopic variables were investigated: tumor size (n = 42 studies), number of nodules (n = 28), vascular invasion (n = 24), bile duct invasion (n = 6), growth pattern (n = 15), resection margin (n = 11), tumor location (n = 6), capsule (n = 2) and satellite (n = 1). Although the selected studies provided insightful data with notable prognostic performances, a lack of standardization and substantial gaps were noted in the report and the analysis of gross findings. This topic remains incompletely covered. While the available studies underscored the value of macroscopic variables in HCC prognostication, important lacks were also observed. Macroscopic characterization of HCC is likely an underexploited source of prognostic factors that must be actively explored by future multidisciplinary research.

Radiomic Analysis Based on Gd-EOB-DTPA Enhanced MRI for the Preoperative Prediction of Ki-67 Expression in Hepatocellular Carcinoma

RATIONALE AND OBJECTIVES

To develop and validate a random forest model based on radiomic features in Gd-EOB-DTPA enhanced MRI for predicting the Ki-67 expression in solitary HCC.

MATERIALS AND METHODS

This retrospective study analyzed 258 patients with solitary HCC. Significant clinicoradiological factors were identified through univariate and multivariate analyses for distinguishing HCC with high (>20%) and low (≤20%) Ki-67 expression. Radiomic features were extracted at Gd-EOB-DTPA enhanced MRI. The recursive feature elimination (RFE) strategy was employed to screen robust radiomic features, and the Random Forest (RF) algorithm was utilized to rank radiomic features and construct prediction models. The AUC, accuracy, precision, recall, and f1-score were used to evaluate the performance of RF models.

RESULTS

Multivariate analysis identified serum AFP level, tumor size, growth type, and peritumoral enhancement as independent predictors for HCC with high Ki-67 expression. The clinicoradiological-radiomic model that incorporated the clinicoradiological predictors and the top ten radiomic features outperformed the clinicoradiological model in the training set (AUCs 0.876 vs. 0.780; p < 0.001), though the test set did not have a statistical significance (AUCs 0.809 vs. 0.723; p = 0.123). The addition of clinicoradiological predictors did not yield a significant improvement in the performance of radiomic features in both sets (training, p = 0.692; test, p = 0.229). Decision curve analysis further confirmed the clinical utility of the RF models.

CONCLUSION

The RF models based on radiomic features of Gd-EOB-DTPA enhanced MRI achieved satisfactory performance in preoperatively predicting Ki-67 expression in HCC.

Adjuvant sintilimab in resected high-risk hepatocellular carcinoma: a randomized, controlled, phase 2 trial

Hepatocellular carcinoma (HCC), particularly when accompanied by microvascular invasion (MVI), has a markedly high risk of recurrence after liver resection. Adjuvant immunotherapy is considered a promising avenue. This multicenter, open-label, randomized, controlled, phase 2 trial was conducted at six hospitals in China to assess the efficacy and safety of adjuvant sintilimab, a programmed cell death protein 1 inhibitor, in these patients. Eligible patients with HCC with MVI were randomized (1:1) into the sintilimab or active surveillance group. The sintilimab group received intravenous injections every 3 weeks for a total of eight cycles. The primary endpoint was recurrence-free survival (RFS) in the intention-to-treat population. Key secondary endpoints included overall survival (OS) and safety. From September 1, 2020, to April 23, 2022, a total of 198 eligible patients were randomly allocated to receive adjuvant sintilimab (n = 99) or undergo active surveillance (n = 99). After a median follow-up of 23.3 months, the trial met the prespecified endpoints. Sintilimab significantly prolonged RFS compared to active surveillance (median RFS, 27.7 versus 15.5 months; hazard ratio 0.534, 95% confidence interval 0.360-0.792; P = 0.002). Further follow-up is needed to confirm the difference in OS. In the sintilimab group, 12.4% of patients experienced grade 3 or 4 treatment-related adverse events, the most common of which were elevated alanine aminotransferase levels (5.2%) and anemia (4.1%). These findings support the potential of immune checkpoint inhibitors as effective adjuvant therapy for these high-risk patients. Chinese Clinical Trial Registry identifier: ChiCTR2000037655 .

The transcription factor ChREBP Orchestrates liver carcinogenesis by coordinating the PI3K/AKT signaling and cancer metabolism

Cancer cells integrate multiple biosynthetic demands to drive unrestricted proliferation. How these cellular processes crosstalk to fuel cancer cell growth is still not fully understood. Here, we uncover the mechanisms by which the transcription factor Carbohydrate responsive element binding protein (ChREBP) functions as an oncogene during hepatocellular carcinoma (HCC) development. Mechanistically, ChREBP triggers the expression of the PI3K regulatory subunit p85α, to sustain the activity of the pro-oncogenic PI3K/AKT signaling pathway in HCC. In parallel, increased ChREBP activity reroutes glucose and glutamine metabolic fluxes into fatty acid and nucleic acid synthesis to support PI3K/AKT-mediated HCC growth. Thus, HCC cells have a ChREBP-driven circuitry that ensures balanced coordination between PI3K/AKT signaling and appropriate cell anabolism to support HCC development. Finally, pharmacological inhibition of ChREBP by SBI-993 significantly suppresses in vivo HCC tumor growth. Overall, we show that targeting ChREBP with specific inhibitors provides an attractive therapeutic window for HCC treatment.

Comparative effectiveness of several adjuvant therapies after hepatectomy for hepatocellular carcinoma patients with microvascular invasion

BACKGROUND

For resectable hepatocellular carcinoma (HCC), radical hepatectomy is commonly used as a curative treatment. However, postoperative recurrence significantly diminishes the overall survival (OS) of HCC patients, especially with microvascular invasion (MVI) as an independent high-risk factor for recurrence. While some studies suggest that postoperative adjuvant therapy may decrease the risk of recurrence following liver resection in HCC patients, the specific role of adjuvant therapies in those with MVI remains unclear.

AIM

To conduct a network meta-analysis (NMA) to evaluate the efficacy of various adjuvant therapies and determine the optimal adjuvant regimen.

METHODS

A systematic literature search was conducted on PubMed, EMBASE, and Web of Science until April 6, 2023. Studies comparing different adjuvant therapies or comparing adjuvant therapy with hepatectomy alone were included. Hazard ratios (HRs) with 95% confidence intervals were used to combine data on recurrence free survival and OS in both pairwise meta-analyses and NMA.

RESULTS

Fourteen eligible trials (2268 patients) reporting five different therapies were included. In terms of reducing the risk of recurrence, radiotherapy (RT) [HR = 0.34 (0.23, 0.5); surface under the cumulative ranking curve (SUCRA) = 97.7%] was found to be the most effective adjuvant therapy, followed by hepatic artery infusion chemotherapy [HR = 0.52 (0.35, 0.76); SUCRA = 65.1%]. Regarding OS improvement, RT [HR: 0.35 (0.2, 0.61); SUCRA = 93.1%] demonstrated the highest effectiveness, followed by sorafenib [HR = 0.48 (0.32, 0.69); SUCRA = 70.9%].

CONCLUSION

Adjuvant therapy following hepatectomy may reduce the risk of recurrence and provide a survival benefit for HCC patients with MVI. RT appears to be the most effective adjuvant regimen.