Molecular and histological correlations in liver cancer

Citrus limon (L.) Osbeck Fruit Peel Extract Attenuates Carbon Tetrachloride-Induced Hepatocarcinogenesis in Sprague-Dawley Rats

Background

Traditional herbal medicine practitioners in the Ashanti region of Ghana use the fruit peels of Citrus limon (L.) Osbeck (C. limon) in preventive and curative treatment of many cancers including liver cancer. This ethnobotanical claim remains to be verified scientifically. Aim of the Study. This study investigated prophylactic hepatoprotective and anti-HCC effects of C. limon peel extract (LPE) in CCl4/olive oil-induced HCC-like rats.

Materials and Methods

After preparation of LPE, it was subjected to phytochemical screening using standard phytochemical methods. A total of 30 healthy adult male Sprague-Dawley rats (weighing 150-200 g) were randomly assigned into six groups of 5 rats each. Rats in the control group received olive oil (5 mL/kg ip) twice weekly for 16 weeks. Rats in the model group received CCl4/olive oil (2 mL/kg, ip) twice weekly for 16 weeks. Rats in capecitabine (10 mg/kg po) and LPE (50, 100, and 200 mg/kg po) groups received CCl4/olive oil (2 mL/kg, i.p) in the morning and their respective treatments in the afternoon twice a week for 16 weeks. Rats in all groups had free access to food and water ad libitum. Body weight and survival rates were monitored. Rats were sacrificed under deep anesthesia, blood was collected, and liver and other organs were isolated. Aspartate transaminase (AST), alanine transaminase (ALT), alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT), prothrombin time, bilirubin, C-reactive protein (CRP), alpha- (α-) fetoprotein (AFP), and liver histology were assessed.

Results

Alkaloids, tannins, flavonoids, terpenoids, and saponins were detected in LPE. Model rats demonstrated increased serum levels of AFP, CRP, ALP, GGT, ALT, and AST, prothrombin time, total bilirubin, direct bilirubin, blood lymphocyte, and monocyte counts, but decreased serum albumin and total protein compared to control rats. Unlike the control, model rats demonstrated fat accumulation in periportal and centrilobular hepatocytes and neoplastic transformation. Semiquantitation of periodic acid Schiff- (PAS-) stained liver sections showed decreased glycogen storage in hepatocytes of model rats compared to control rats. Compared to the model, LPE treatment protected against CCl4-induced hepatocarcinogenesis, which was evidenced by decreased AFP, CRP, liver enzymes, total and direct bilirubin, prothrombin time, and blood lymphocyte and monocyte counts; attenuation of fat accumulation; and increased glycogen storage, albumin, and total protein.

Conclusion

LPE abates CCl4-induced hepatocarcinogenesis by attenuating liver inflammation and improving metabolic, biosynthetic, and detoxification functions of the liver. The prophylactic hepatoprotective and anti-hepatocarcinogenic effects of LPE are attributable to its phytochemical composition raising hopes of finding potential anticancer bioactive compounds from C. limon fruit peels.

Harmine Hydrochloride Induces G2/M Cell Cycle Arrest and Apoptosis in SK-Hep1 Hepatocellular Carcinoma Cells by Regulating Mitogen-Activated Protein Kinases and the PI3K/AKT Pathway

Liver cancer is a globally common form of cancer. Thus, novel drugs derived from natural products are needed to reduce the side effects of chemotherapy. The present study aimed to analyze the anticancer properties and effects of harmine hydrochloride (HMH), a water-soluble metabolite of harmine that can be easily absorbed into tissues, in treating liver cancer cells. HMH dose-dependently inhibited cell growth, migration, invasion, and colony formation in SK-Hep1 cells. It also induced G2/M arrest by reducing the expression of p-cdc2, cyclin B1, and Rb (G2/M phase regulatory proteins) in a dose-dependent manner. HMH treatment reduced the expression of caspase-9, caspase-3, PARP, and Bcl-2 and increased the expression of Bax (a proapoptotic protein). Moreover, it increased the production of reactive oxygen species and decreased the intracellular uptake of rhodamine 123 due to mitochondrial dysfunction because of oxidative stress. HMH treatment also upregulated the phosphorylation of JNK, p38, and FOXO3a in SK-Hep1 cells and downregulated the PI3K/AKT signaling pathway. Our findings suggest that HMH may activate the compounds responsible for anticancer effects in hepatocellular carcinoma cells.

Induction of Hepatocellular Carcinoma Cell Cycle Arrest and Apoptosis by Dendropanax morbifera Leveille Leaf Extract via the PI3K/AKT/mTOR Pathway

Liver cancer is prevalent worldwide and associated with a high mortality rate. Therefore, developing novel drugs derived from natural products to reduce the side effects of chemotherapy is urgently needed. In this study, the inhibitory effect of Dendropanax morbifera Leveille extract (DME) on growth of hepatocellular carcinoma (HCC) cells and its underlying mechanisms were investigated. DME suppressed the growth, migration, and invasion of SK-Hep1 human HCC cells. It also reduced the expression of the G0/G1 phase regulator proteins cyclin-dependent kinase (CDK) 4, cyclin D, CDK2, and cyclin E, thereby inducing G0/G1 arrest. Moreover, DME treatment reduced the expression of antiapoptotic proteins, including caspase-9, caspase-3, PARP, and Bcl-2 and increased the expression of the proapoptotic protein, Bax. DME also increased reactive oxygen species production and reduced the cellular uptake of rhodamine 123. DME treatment increased the levels of p-p38 and p-FOXO3a in a dose-dependent manner and decreased those of p-PI3K, p-AKT, p-mTOR, and p-p70 in SK-Hep1 cells. In addition, combined treatment with DME and LY294002, an AKT inhibitor, significantly reduced p-AKT levels. In summary, these results show that the PI3K/AKT/mTOR signaling pathway is involved in DME-mediated inhibition of proliferation, migration, and invasiveness, and induction of apoptosis of HCC cells.

Liquid Liver Biopsy for Disease Diagnosis and Prognosis

Liver diseases are a major burden worldwide, the scope of which is expected to further grow in the upcoming years. Clinically relevant liver dysfunction-related blood markers such as alanine aminotransferase and aspartate aminotransferase have limited accuracy. Nowadays, liver biopsy remains the gold standard for several liver-related pathologies, posing a risk of complication due to its invasive nature. Liquid biopsy is a minimally invasive approach, which has shown substantial potential in the diagnosis, prognosis, and monitoring of liver diseases by detecting disease-associated particles such as proteins and RNA molecules in biological fluids. Histones are the core components of the nucleosomes, regulating essential cellular processes, including gene expression and DNA repair. Following cell death or activation of immune cells, histones are released in the extracellular space and can be detected in circulation. Histones are stable in circulation, have a long half-life, and retain their post-translational modifications. Here, we provide an overview of the current research on histone-mediated liquid biopsy methods for liver diseases, with a focus on the most common detection methods.

Integrated omics landscape of hepatocellular carcinoma suggests proteomic subtypes for precision therapy

Patients with hepatocellular carcinoma (HCC) at the same clinical stage can have extremely different prognoses, and molecular subtyping provides an opportunity for individualized precision treatment. In this study, genomic, transcriptomic, proteomic, and phosphoproteomic profiling of primary tumor tissues and paired para-tumor tissues from HCC patients (N = 160) are integrated. Proteomic profiling identifies three HCC subtypes with different clinical prognosis, which are validated in three publicly available external validation sets. A simplified panel of nine proteins associated with metabolic reprogramming is further identified as a potential subtype-specific biomarker for clinical application. Multi-omics analysis further reveals that three proteomic subtypes have significant differences in genetic alterations, microenvironment dysregulation, kinase-substrate regulatory networks, and therapeutic responses. Patient-derived cell-based drug tests (N = 26) show personalized responses for sorafenib in three proteomic subtypes, which can be predicted by a machine-learning response prediction model. Overall, this study provides a valuable resource for better understanding of HCC subtypes for precision clinical therapy.

Deep learning-based phenotyping reclassifies combined hepatocellular-cholangiocarcinoma

Primary liver cancer arises either from hepatocytic or biliary lineage cells, giving rise to hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICCA). Combined hepatocellular- cholangiocarcinomas (cHCC-CCA) exhibit equivocal or mixed features of both, causing diagnostic uncertainty and difficulty in determining proper management. Here, we perform a comprehensive deep learning-based phenotyping of multiple cohorts of patients. We show that deep learning can reproduce the diagnosis of HCC vs. CCA with a high performance. We analyze a series of 405 cHCC-CCA patients and demonstrate that the model can reclassify the tumors as HCC or ICCA, and that the predictions are consistent with clinical outcomes, genetic alterations and in situ spatial gene expression profiling. This type of approach could improve treatment decisions and ultimately clinical outcome for patients with rare and biphenotypic cancers such as cHCC-CCA.

Establishment and Validation of the LI-RADS Morphologic Type II Hepatocellular Carcinoma Early Recurrence Risk Scoring System

BACKGROUND

Tumor morphology links to early recurrence of hepatocellular carcinoma. Controversy exists regarding the recurrence risk of Liver Imaging Reporting and Data System morphologic Type II hepatocellular carcinoma. This study aims to explore risk factors for early recurrence of Type II hepatocellular carcinoma.

METHODS

Retrospective analysis of hepatocellular carcinoma patients who underwent curative resection and preoperative contrast-enhanced MRI from June 2016 to June 2020. Our patients formed the development set, and hepatocellular carcinoma patients from the TCIA database served as validation. Univariable and multivariable Cox regression identified independent risk factors for early recurrence. A risk scoring system was established for risk stratification, and an early recurrence prediction model was developed and validated.

RESULTS

95 Type II hepatocellular carcinoma patients were in the development set, and 29 cases were in the validation set. Early recurrence rates were 33.7% and 37.9%, respectively. Multivariate analysis revealed age, histological grade, AFP, and intratumoral hemorrhage as independent risk factors for early recurrence. The model's diagnostic performance for early recurrence was AUC = 0.817 in the development set. A scoring system classified patients into low-risk (scores ≤ 3) and high-risk (scores > 3) groups. The high-risk group had significantly lower recurrence-free survival (40.0% vs 73.2%, P = 0.001), consistent with the validation set (25.0% vs 73.3%, P = 0.028).

CONCLUSIONS

The risk scoring system demonstrated excellent discrimination and predictive ability, aiding clinicians in assessing early recurrence risk and identifying high-risk individuals effectively.

Artificial intelligence-based pathology as a biomarker of sensitivity to atezolizumab-bevacizumab in patients with hepatocellular carcinoma: a multicentre retrospective study

BACKGROUND

Clinical benefits of atezolizumab plus bevacizumab (atezolizumab-bevacizumab) are observed only in a subset of patients with hepatocellular carcinoma and the development of biomarkers is needed to improve therapeutic strategies. The atezolizumab-bevacizumab response signature (ABRS), assessed by molecular biology profiling techniques, has been shown to be associated with progression-free survival after treatment initiation. The primary objective of our study was to develop an artificial intelligence (AI) model able to estimate ABRS expression directly from histological slides, and to evaluate if model predictions were associated with progression-free survival.

METHODS

In this multicentre retrospective study, we developed a model (ABRS-prediction; ABRS-P), which was derived from the previously published clustering-constrained attention multiple instance learning (or CLAM) pipeline. We trained the model fit for regression analysis using a multicentre dataset from The Cancer Genome Atlas (patients treated by surgical resection, n=336). The ABRS-P model was externally validated on two independent series of samples from patients with hepatocellular carcinoma (a surgical resection series, n=225; and a biopsy series, n=157). The predictive value of the model was further tested in a series of biopsy samples from a multicentre cohort of patients with hepatocellular carcinoma treated with atezolizumab-bevacizumab (n=122). All samples in the study were from adults (aged ≥18 years). The validation sets were sampled between Jan 1, 2008, to Jan 1, 2023. For the multicentre validation set, the primary objective was to assess the association of high versus low ABRS-P values, defined relative to cross-validation median split thresholds in the first biopsy series, with progression-free survival after treatment initiation. Finally, we performed spatial transcriptomics and matched prediction heatmaps with in situ expression profiles.

FINDINGS

Of the 840 patients sampled, 641 (76%) were male and 199 (24%) were female. Across the development and validation datasets, hepatocellular carcinoma risk factors included alcohol intake, hepatitis B and C virus infections, and non-alcoholic steatohepatitis. Using cross-validation in the development series, the mean Pearson's correlation between ABRS-P values and ABRS score (mean expression of ABRS genes) was r=0·62 (SD 0·09; mean p<0·0001, SD<0·0001). The ABRS-P generalised well on the external validation series (surgical resection series, r=0·60 [95% CI 0·51-0·68], p<0·0001; biopsy series, r=0·53 [0·40-0·63], p<0·0001). In the 122 patients treated with atezolizumab-bevacizumab, those with ABRS-P-high tumours (n=74) showed significantly longer median progression-free survival than those with ABRS-P-low tumours (n=48) after treatment initiation (12 months [95% CI 7-not reached] vs 7 months [4-9]; p=0·014). Spatial transcriptomics showed significantly higher ABRS score, along with upregulation of various other immune effectors, in tumour areas with high ABRS-P values versus areas with low ABRS-P values.

INTERPRETATION

Our study indicates that AI applied on hepatocellular carcinoma digital slides is able to serve as a biomarker for progression-free survival in patients treated with atezolizumab-bevacizumab. This approach could be used in the development of inexpensive and fast biomarkers for targeted therapies. The combination of AI heatmaps with spatial transcriptomics provides insight on the molecular features associated with predictions. This methodology could be applied to other cancers or diseases and improve understanding of the biological mechanisms that drive responses to treatments.

FUNDING

Institut National du Cancer, Fondation ARC, China Scholarship Council, Ligue Contre le Cancer du Val de Marne, Fondation de l'Avenir, Ipsen, and Fondation Bristol Myers Squibb Pour la Recherche en Immuno-Oncologie.

Understanding the role of radiologists in complex treatment decisions for patients with hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary malignant tumor of the liver and represents a significant global health burden. Management of HCC can be challenging due to multiple factors, including variable expectations for treatment outcomes. Several treatment options are available, each with specific eligibility and ineligibility criteria, and are provided by a multidisciplinary team of specialists. Radiologists should be aware of the types of treatment options available, as well as the criteria guiding the development of individualized treatment plans. This awareness enables radiologists to contribute effectively to patient-centered multidisciplinary tumor boards for HCC and play a central role in reassessing care plans when the treatment response is deemed inadequate. This comprehensive review aims to equip radiologists with an overview of HCC staging systems, treatment options, and eligibility criteria. The review also discusses the significance of imaging in HCC diagnosis, treatment planning, and monitoring treatment response. Furthermore, we highlight the crucial branch points in the treatment decision-making process that depend on radiological interpretation.

Integrated bulk and single-cell transcriptomes reveal pyroptotic signature in prognosis and therapeutic options of hepatocellular carcinoma by combining deep learning

Although some pyroptosis-related (PR) prognostic models for cancers have been reported, pyroptosis-based features have not been fully discovered at the single-cell level in hepatocellular carcinoma (HCC). In this study, by deeply integrating single-cell and bulk transcriptome data, we systematically investigated significance of the shared pyroptotic signature at both single-cell and bulk levels in HCC prognosis. Based on the pyroptotic signature, a robust PR risk system was constructed to quantify the prognostic risk of individual patient. To further verify capacity of the pyroptotic signature on predicting patients' prognosis, an attention mechanism-based deep neural network classification model was constructed. The mechanisms of prognostic difference in the patients with distinct PR risk were dissected on tumor stemness, cancer pathways, transcriptional regulation, immune infiltration and cell communications. A nomogram model combining PR risk with clinicopathologic data was constructed to evaluate the prognosis of individual patients in clinic. The PR risk could also evaluate therapeutic response to neoadjuvant therapies in HCC patients. In conclusion, the constructed PR risk system enables a comprehensive assessment of tumor microenvironment characteristics, accurate prognosis prediction and rational therapeutic options in HCC.

Prognostic Factors for Patients with Proliferative Hepatocellular Carcinoma After Liver Resection

Purpose

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

Patients and Methods

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

Results

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

Conclusion

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

Insights on epithelial cells at the single-cell level in hepatocellular carcinoma prognosis and response to chemotherapy

Background: Hepatocellular carcinoma (HCC) originates from Epithelial cells, and epithelial lineage plasticity has become a promising research direction for advancing HCC treatment. This study aims to focus on Epithelial cells to provide target insights for detecting HCC prognosis and response to drug therapy. Methods: Single-cell RNA sequencing (scRNA-seq) data from GSE149614 were clustered using Seurat, and the differentiation and evolution of epithelial cells were analyzed by Monocle 2. Scissor+ and Scissor- Epithelial cells associated with the prognostic phenotypes of bulk RNA-seq of HCC were screened using the Scissor algorithm for differential analysis to screen candidate genes. Candidate genes were overlapped with prognostic related genes screened by univariate Cox regression, and the Least Absolute Shrinkage and Selection Operator (LASSO) sparse penalty was imposed on the intersection genes to construct a risk assessment system. Results: Eight major cell subpopulations of HCC were identified, among which the proportion of epithelial cells in non-tumor liver tissues and HCC tissues was significantly different, and its proportion increased with advanced clinical stage. During the progression of HCC, the whole direction of epithelial cells differentiation trajectory was towards enhanced cell proliferation. Differential analysis between Scissor+ and Scissor- epithelial cells screened 1,265 upregulated and 191 downregulated prognostic candidate genes. Wherein, the upregulated genes were enriched in Cell processes, Genetic information processing, Metabolism and Human disease with Infection. Nevertheless, immune system related pathways took the main proportions in downregulated genes enriched pathways. There were 17 common genes between upregulated candidate genes and prognostic risk genes, of which CDC20, G6PD and PLOD2 were selected as components for constructing the risk assessment system. Risk score showed a significant correlation with tumor stage, epithelial-mesenchymal transition (EMT) related pathways and 22 therapeutic drugs, and was an independent prognostic factor for HCC. Conclusion: This study revealed the cellular composition of HCC, the differentiation evolution and functional landscape of epithelial cells in the further deterioration of HCC, and established a 3-gene risk model, which was closely related to clinical features, EMT, and drug sensitivity prediction. These findings provided insights in patient prognosis and drug therapy detection for HCC.

Benefit and harm of waiting time in liver transplantation for HCC

Liver transplantation is the most successful treatment for limited-stage HCC. The waiting time for liver transplantation (LT) can be a critical factor affecting the oncological prognosis and outcome of patients with HCC. Efficient strategies to optimize waiting time are essential to maximize the benefits of LT and to reduce the harm of delay in transplantation. The ever-increasing demand for donor livers emphasizes the need to improve the organization of the waiting list for transplantation and to optimize organ availability for patients with and without HCC. Current progress in innovations to expand the donor pool includes the implementation of living donor LT and the use of grafts from extended donors. By expanding selection criteria, an increased number of patients are eligible for transplantation, which necessitates criteria to prevent futile transplantations. Thus, the selection criteria for LT have evolved to include not only tumor characteristics but biomarkers as well. Enhancing our understanding of HCC tumor biology through the analysis of subtypes and molecular genetics holds significant promise in advancing the personalized approach for patients. In this review, the effect of waiting time duration on outcome in patients with HCC enlisted for LT is discussed.

Integrative analysis identified two subtypes and a taurine-related signature to predict the prognosis and efficacy of immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most prevalent subtypes of primary liver cancer, with high mortality and poor prognosis. Immunotherapy has revolutionized treatment strategies for many cancers. However, only a subset of patients with HCC achieve satisfactory benefits from immunotherapy. Therefore, a reliable biomarker that could predict the prognosis and immunotherapy response in patients with HCC is urgently needed. Taurine plays an important role in many physiological processes. However, its participation in the occurrence and progression of liver cancer and regulation of the composition and function of various components of the immune microenvironment remains elusive. In this study, we identified and validated two heterogeneous subtypes of HCC with different taurine metabolic profiles, presenting distinct genomic features, clinicopathological characteristics, and immune landscapes, using multiple bulk transcriptome datasets. Subsequently, we constructed a risk model based on genes related to taurine metabolism to assess the prognosis, immune cell infiltration, immunotherapy response, and drug sensitivity of patients with HCC. The risk model was validated using several independent external cohorts and showed a robust predictive performance. In addition, we evaluated the expression patterns of taurine metabolism-related genes in the tumor microenvironment and the heterogeneity of taurine metabolism among cancer cells using a single-cell transcriptome. In conclusion, our study provides insights into the important role played by taurine metabolism in tumor progression and immune regulation. Furthermore, the risk model can serve as a biomarker to assess patient prognosis and immunotherapy response, potentially helping clinicians make more precise and personalized clinical decisions.

Development of a Model including MRI Features for Predicting Advanced-stage Recurrence of Hepatocellular Carcinoma after Liver Resection

Background Identifying patients at high risk for advanced-stage hepatocellular carcinoma (HCC) recurrence after liver resection may improve patient survival. Purpose To develop a model including MRI features for predicting postoperative advanced-stage HCC recurrence. Materials and Methods This single-center, retrospective study includes consecutive adult patients who underwent preoperative contrast-enhanced MRI and curative-intent resection for early- to intermediate-stage HCC (from December 2011 to April 2021). Three radiologists evaluated 52 qualitative features on MRI scans. In the training set, Fine-Gray proportional subdistribution hazard analysis was performed to identify clinical, laboratory, imaging, pathologic, and surgical variables to include in the predictive model. In the test set, the concordance index (C-index) was computed to compare the developed model with current staging systems. The Kaplan-Meier survival curves were compared using the log-rank test. Results The study included 532 patients (median age, 54 years; IQR, 46-62 years; 465 male patients), 302 patients from the training set (median age, 54 years; IQR, 46-63 years; 265 male patients), and 128 patients from the test set (median age, 53 years; IQR, 46-63 years; 108 male patients). Advanced-stage recurrence was observed in 38 of 302 (12.6%) and 15 of 128 (11.7%) of patients from the training and test sets, respectively. Serum neutrophil count (109/L), tumor size (in centimeters), and arterial phase hyperenhancement proportion on MRI scans were associated with advanced-stage recurrence (subdistribution hazard ratio range, 1.16-3.83; 95% CI: 1.02, 7.52; P value range, <.001 to .02) and included in the predictive model. The model showed better test set prediction for advanced-stage recurrence than four staging systems (2-year C-indexes, 0.82 [95% CI: 0.74, 0.91] vs 0.63-0.68 [95% CI: 0.52, 0.82]; P value range, .001-.03). Patients at high risk for HCC recurrence (model score, ≥15 points) showed increased advanced-stage recurrence and worse all-stage recurrence-free survival (RFS), advanced-stage RFS, and overall survival than patients at low risk for HCC recurrence (P value range, <.001 to .02). Conclusion A model combining serum neutrophil count, tumor size, and arterial phase hyperenhancement proportion predicted advanced-stage HCC recurrence better than current staging systems and may identify patients at high risk. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Tsai and Mellnick in this issue.

Current Status of Cancer Genomics and Imaging Phenotypes: What Radiologists Need to Know

Ongoing discoveries in cancer genomics and epigenomics have revolutionized clinical oncology and precision health care. This knowledge provides unprecedented insights into tumor biology and heterogeneity within a single tumor, among primary and metastatic lesions, and among patients with the same histologic type of cancer. Large-scale genomic sequencing studies also sparked the development of new tumor classifications, biomarkers, and targeted therapies. Because of the central role of imaging in cancer diagnosis and therapy, radiologists need to be familiar with the basic concepts of genomics, which are now becoming the new norm in oncologic clinical practice. By incorporating these concepts into clinical practice, radiologists can make their imaging interpretations more meaningful and specific, facilitate multidisciplinary clinical dialogue and interventions, and provide better patient-centric care. This review article highlights basic concepts of genomics and epigenomics, reviews the most common genetic alterations in cancer, and discusses the implications of these concepts on imaging by organ system in a case-based manner. This information will help stimulate new innovations in imaging research, accelerate the development and validation of new imaging biomarkers, and motivate efforts to bring new molecular and functional imaging methods to clinical radiology. Keywords: Oncology, Cancer Genomics, Epignomics, Radiogenomics, Imaging Markers Supplemental material is available for this article. © RSNA, 2023.

Frequent expression of PD-L1 in lymphocyte-rich hepatocellular carcinoma: A report of 4 cases

BACKGROUND

Programmed death ligand 1 (PD-L1) is an immune checkpoint inhibitor. PD-L1 binds to its receptor programmed death receptor (PD-1) expressed by immune cells and plays a key role in regulating immune responses. Engagement of PD-L1 on cancer cells and PD-1 on immune cells avoid destruction of tumour cells by immune cells. Immunostaining with PD-L1 has been suggested as a biomarker predictive of antiPD-L1 immunotherapy. Lymphocyte-rich hepatocellular carcinoma (LrHCC) is a rare histological HCC subtype which is characterised by neoplastic epithelial cells intermixed with numerous immune cells.

METHODS

Here in we investigated immunohistochemical PD-L1 expression in 4 cases of LrHCC. Tumour proportion score (TPS) and immune cell score was recorded. Immunophenotypic characterization of the tumour and inflammatory cells was also done. Epstein-Barr encoding region (EBER) in situ hybridization (ISH) assay as performed in all four tumours.

RESULTS

Expression of PD-L1 was demonstrated in tumour epithelial cells and immune cells in all four cases. Incomplete to membranous staining was demonstrated in the tumour cells. Tumour proportion score (TPS) was 1.2-20 %. Immune cells demonstrated membranous and cytoplasmic immunostaining. Immune cell score was ≥1 % to >10 %.

CONCLUSION

PD-L1 expression in both tumour and immune cells suggests distinct immunogenic feature and potential role of antiPD-L1 therapies in cases with inoperable disease.

β-HB treatment reverses sorafenib resistance by shifting glycolysis-lactate metabolism in HCC

Hepatocellular carcinoma (HCC) is the most common primary malignant tumor. Although sorafenib and regorafenib have been approved for first-line and second-line treatment, respectively, of patients with advanced HCC, long-term treatment often results in acquired resistance. Given that glycolysis-mediated lactate production can contribute to drug resistance and impair HCC treatment efficacy, we investigated the effects of ketone body treatment on the metabolic shift in sorafenib-resistant HCC cells. We discovered differential expression of 3-hydroxymethyl glutaryl-CoA synthase 2 (HMGCS2) and the ketone body D-β-hydroxybutyrate (β-HB) in four sorafenib-resistant HCC cell lines. In sorafenib-resistant HCC cells, lower HMGCS2 and β-HB levels were correlated with more glycolytic alterations and higher lactate production. β-HB treatment enhanced pyruvate dehydrogenase (PDH) expression and decreased lactate dehydrogenase (LDHA) expression and lactate production in sorafenib-resistant HCC cells. Additionally, β-HB combined with sorafenib or regorafenib promoted the antiproliferative and antimigratory abilities of sorafenib-resistant HCC cells by inhibiting the B-raf/mitogen-activated protein kinase pathway and mesenchymal N-cadherin-vimentin axis. Although the in vivo β-HB administration did not affect tumor growth, the expression of proliferative and glycolytic proteins was inhibited in subcutaneous sorafenib-resistant tumors. In conclusion, exogenous β-HB treatment can reduce lactate production and reverse sorafenib resistance by inducing a glycolytic shift; it can also synergize with regorafenib for treating sorafenib-resistant HCC.

Dynamic contrast-enhanced CT and clinical features of sarcomatoid hepatocellular carcinoma

PURPOSE

To investigate the dynamic contrast-enhanced computed tomography (CECT) features and clinical characteristics of sarcomatoid hepatocellular carcinoma (S-HCC).

METHODS

We retrospectively reviewed the CECT data and clinical findings of 13 patients (11 male and 2 female, with an average age of 58.6 ± 11.2 years) with pathologically proven S-HCC, including 9 patients with surgical resection and 4 patients with biopsy examination. All patients underwent CECT scans. Two radiologists reviewed and evaluated general features, CECT features and extratumoral features of each lesions based on a consensus.

RESULTS

Among the thirteen tumors, a mean size of 66.7 mm was observed, ranging in diameter from 30 to 146 mm. Seven of thirteen patients had hepatitis B virus (HBV) infection and an elevation of alpha-fetoprotein (AFP) level. Most of cases located in the right lobe of liver (84.6%, 11/13). Nine of thirteen tumors showed lobulated or wavy contours and infiltrative morphology, while eight tumors presented with unclear margin. The tumor textures were mainly heterogeneous for ischemia or necrosis, with solid components dominantly in all cases. Eight of thirteen tumors exhibited "slow-in and and slow-out" dynamic enhancement pattern in CECT, with a enhancement peak in the portal venous phase. Portal vein or hepatic thrombus, adjacent organs invasion and lymph node metastasis were observed in two patients, respectively. Four of thirteen lesions occurred intrahepatic metastasis and hepatic surface retraction respectively.

CONCLUSION

S-HCC gengerally seen in elderly male with HBV infection and elevated AFP level. The CT manifestations including: large diameter, frequently hepatic right lobe involvement, lobular or wavy contours, ill-defined margins, infiltrative morphology, obvious heterogeneity and dynamic enhancement pattern of "slow-in and and slow-out" , contributed to the diagnosis of S-HCC. These tumors usually occurred hepatic surface retraction and intrahepatic metastasis.

Histological diagnosis of polyploidy discriminates an aggressive subset of hepatocellular carcinomas with poor prognosis

BACKGROUND

Although genome duplication, or polyploidization, is believed to drive cancer evolution and affect tumor features, its significance in hepatocellular carcinoma (HCC) is unclear. We aimed to determine the characteristics of polyploid HCCs by evaluating chromosome duplication and to discover surrogate markers to discriminate polyploid HCCs.

METHODS

The ploidy in human HCC was assessed by fluorescence in situ hybridization for multiple chromosomes. Clinicopathological and expression features were compared between polyploid and near-diploid HCCs. Markers indicating polyploid HCC were explored by transcriptome analysis of cultured HCC cells.

RESULTS

Polyploidy was detected in 36% (20/56) of HCCs and discriminated an aggressive subset of HCC that typically showed high serum alpha-fetoprotein, poor differentiation, and poor prognosis compared to near-diploid HCCs. Molecular subtyping revealed that polyploid HCCs highly expressed alpha-fetoprotein but did not necessarily show progenitor features. Histological examination revealed abundant polyploid giant cancer cells (PGCCs) with a distinct appearance and frequent macrotrabecular-massive architecture in polyploid HCCs. Notably, the abundance of PGCCs and overexpression of ubiquitin-conjugating enzymes 2C indicated polyploidy in HCC and efficiently predicted poor prognosis in combination.

CONCLUSIONS

Histological diagnosis of polyploidy using surrogate markers discriminates an aggressive subset of HCC, apart from known HCC subgroups, and predict poor prognosis in HCC.

Residual Deformable Split Channel and Spatial U-Net for Automated Liver and Liver Tumour Segmentation

Accurate segmentation of the liver and liver tumour (LT) is challenging due to its hazy boundaries and large shape variability. Although using U-Net for liver and LT segmentation achieves better results than manual segmentation, it loses spatial and channel features during segmentation, leading to inaccurate liver and LT segmentation. A residual deformable split depth-wise separable U-Net (RDSDSU-Net) is proposed to increase the accuracy of liver and LT segmentation. The residual deformable convolution layer (DCL) with deformable pooling (DP) is used in the encoder as an attention mechanism to adaptively extract liver and LT shape and position characteristics. Afterward, a convolutional spatial and channel features split graph network (CSCFSG-Net) is introduced in the middle processing layer to improve the expression capability of the liver and LT features by capturing spatial and channel features separately and to extract global contextual liver and LT information from spatial and channel features. Sub-pixel convolutions (SPC) are used in the decoder section to prevent the segmentation results from having a chequerboard artefact effect. Also, the residual deformable encoder features are combined with the decoder through summation to avoid increasing the number of feature maps (FM). Finally, the efficiency of the RDSDSU-Net is evaluated on the 3DIRCADb and LiTS datasets. The DICE score of the proposed RDSDSU-Net achieved 98.21% for liver segmentation and 93.25% for LT segmentation on 3DIRCADb. The experimental outcomes illustrate that the proposed RDSDSU-Net model achieved better segmentation results than the existing techniques.

Pathological overview of steatohepatitic hepatocellular carcinoma in a surgical series

AIMS

According to the last WHO classification, steatohepatitic hepatocellular carcinoma (SH-HCC) is recognized as a distinct HCC subtype, even though a consensual definition is still lacking. The objectives of the study were to carefully describe the morphological features of SH-HCC and evaluate its impact on prognosis.

METHODS AND RESULTS

We conducted a single-centre retrospective study including 297 surgically resected HCC. Pathological features including SH criteria (steatosis, ballooning, Mallory-Denk bodies, fibrosis, and inflammation) were assessed. SH-HCC was defined by the presence of at least four of the five SH criteria and the SH component represented >50% of the tumour area. According to this definition, 39 (13%) HCC cases corresponded to SH-HCC and 30 cases (10%) corresponded to HCC with an SH component (<50%). SH criteria in SH-HCC and non-SH-HCC were distributed as follows: ballooning (100% versus 11%), fibrosis (100% versus 81%), inflammation (100% versus 67%), steatosis (92% versus 8%), and Mallory-Denk bodies (74% versus 3%). Inflammation markers (c-reactive protein [CRP] and serum amyloid A [SAA]) were significantly more expressed in SH-HCC compared to non-SH-HCC (82% versus 14%, P = <0.001). Five-year recurrence-free survival (RFS) and 5-year overall survival (OS) were similar for SH-HCC and non-SH-HCC (P = 0.413 and P = 0.866, respectively). The percentage of SH component does not impact OS and RFS.

CONCLUSION

We confirm in a large cohort the relatively high prevalence (13%) of SH-HCC. Ballooning is the most specific criteria for this subtype. The percentage of the SH component does not impact prognosis.

Milk thistle nano-micelle formulation promotes cell cycle arrest and apoptosis in hepatocellular carcinoma cells through modulating miR-155-3p /SOCS2 /PHLDA1 signaling axis

BACKGROUND

Hepatocellular Carcinoma (HCC) is a prevalent form of liver cancer that causes significant mortality in numerous individuals worldwide. This study compared the effects of milk thistle (MT) and nano-milk thistle (N-MT) on the expression of the genes that participate in apoptosis and cell cycle pathways in Huh-7 and HepG2 cells.

METHODS

IC50 values of MT and N-MT were determined using the MTT assay. Huh-7 and HepG2 cell lines (containing mutant and wild-type TP53 gene, respectively) were incubated with MT and N-MT for 24h and 48h and the impact of MT and N-MT on the proliferation of these cell lines was evaluated through a comparative analysis. Cell cycle and apoptosis were assessed by flow cytometry after 24h and 48h treatment in the cell lines mentioned. Real-time PCR was used to analyze miR-155-3p, PHLDA1, SOCS2, TP53, P21, BAX, and BCL-2 expression in the cell lines that were being treated.

RESULTS

N-MT reduces cancer cell growth in a time and concentration-dependent manner, which is more toxic compared to MT. Huh-7 was observed to have IC50 values of 2.35 and 1.7 μg/ml at 24h and 48h, and HepG2 was observed to have IC50 values of 3.4 and 2.6 μg/ml at 24 and 48h, respectively. N-MT arrested Huh-7 and HepG2 cells in the Sub-G1 phase and induced apoptosis. N-MT led to a marked reduction in the expression of miR-155-3p and BCL-2 after 24h and 48h treatments. Conversely, PHLDA1, SOCS2, BAX, and P21 were upregulated in the treated cells compared to untreated cells, which suggests that milk thistle has the potential to regulate these genes. N-MT reduced the expression of TP53 in Huh-7 cells after mentioned time points, while there was a significant increase in the expression of the TP53 gene in HepG2 cells. No gene expression changes were observed in MT-treated cells after 24h and 48h.

CONCLUSION

N-MT can regulate cancer cell death by arresting cell cycle and inducing apoptosis. This occurs through the alteration of apoptotic genes expression. A reduction in the expression of miR-155-3p and increase in the expression of SOCS2 and PHLDA1 after N-MT treatment showed the correlation between miR-155-3p and PHLDA1/SOCS2 found in bioinformatics analysis. While N-MT increased TP53 expression in HepG2, reduced it in Huh-7. The findings indicate that N-MT can function intelligently in cancer cells and can be a helpful complement to cancer treatment.

Advances in Histological and Molecular Classification of Hepatocellular Carcinoma

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

Identifying Network Biomarkers in Early Diagnosis of Hepatocellular Carcinoma via miRNA-Gene Interaction Network Analysis

BACKGROUND

Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer at the histological level. Despite the emergence of new biological technology, advanced-stage HCC remains largely incurable. The prediction of a cancer biomarker is a key problem for targeted therapy in the disease.

METHODS

We performed a miRNA-gene integrated analysis to identify differentially expressed miRNAs (DEMs) and genes (DEGs) of HCC. The DEM-DEG interaction network was constructed and analyzed. Gene ontology enrichment and survival analyses were also performed in this study.

RESULTS

By the analysis of healthy and tumor samples, we found that 94 DEGs and 25 DEMs were significantly differentially expressed in different datasets. Gene ontology enrichment analysis showed that these 94 DEGs were significantly enriched in the term "Liver" with a statistical p-value of 1.71 × 10-26. Function enrichment analysis indicated that these genes were significantly overrepresented in the term "monocarboxylic acid metabolic process" with a p-value = 2.94 × 10-18. Two sets (fourteen genes and five miRNAs) were screened by a miRNA-gene integrated analysis of their interaction network. The statistical analysis of these molecules showed that five genes (CLEC4G, GLS2, H2AFZ, STMN1, TUBA1B) and two miRNAs (hsa-miR-326 and has-miR-331-5p) have significant effects on the survival prognosis of patients.

CONCLUSION

We believe that our study could provide critical clinical biomarkers for the targeted therapy of HCC.

Imaging prognostication and tumor biology in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, and represents a significant global health burden with rising incidence rates, despite a more thorough understanding of the etiology and biology of HCC, as well as advancements in diagnosis and treatment modalities. According to emerging evidence, imaging features related to tumor aggressiveness can offer relevant prognostic information, hence validation of imaging prognostic features may allow for better noninvasive outcomes prediction and inform the selection of tailored therapies, ultimately improving survival outcomes for patients with HCC.

SART3, regulated by p53, is a biomarker for diagnosis, prognosis and immune infiltration in hepatocellular carcinoma

OBJECTIVE

This study aimed to investigate the role of squamous cell carcinoma antigen recognized by T cells 3 (SART3) in hepatocellular carcinoma (HCC).

METHODS

SART3 expression and prognostic value were analyzed in TCGA and GEO datasets. The diagnostic value and prognostic significance of SART3 were determined using immunohistochemistry in the Guangxi cohort. The whole-exome mutation spectrum of SART3 was analyzed in high and low expression groups in both TCGA and Guangxi cohorts. The biological functions of the SART3 gene were validated through in vitro experiments using small interfering RNA technology to downregulate SART3 expression in HCC cell lines.

RESULTS

SART3 expression was significantly higher in HCC tissues than in adjacent noncancerous liver tissues in TCGA, GEO and Guangxi cohorts. High expression of SART3 was significantly associated with poor prognosis in HCC patients. In TCGA and Guangxi cohorts, the expression of SART3 in the TP53 mutation group was significantly higher than that in the non-mutation group. Downregulation of SART3 expression significantly inhibited the migration and proliferation of HCC cells. SART3 may be involved mainly in immune infiltration of Th2 cells and macrophages in HCC. Additionally, SART3 can upregulate the expression of immune checkpoints (PD-L1 and TIM-3) and predict potential therapeutic agents for HCC.

CONCLUSION

The findings of this study demonstrate the diagnostic and prognostic value of SART3 in HCC. SART3 may be associated with immune infiltration of Th2 cells and macrophages in HCC, highlighting its potential role in the development and progression of HCC.

Association of Hepatobiliary Phase of Gadoxetic-Acid-Enhanced MRI Imaging with Immune Microenvironment and Response to Atezolizumab Plus Bevacizumab Treatment

It has been reported that high intensity in the hepatobiliary (HB) phase of Gd-EOB-DTPA-enhanced MRI (EOB-MRI) is associated with an immune-cold microenvironment in HCC. The aim of this study is to reveal whether non-high-intensity HCCs are homogeneous with respect to the immune microenvironment and to investigate the predictive ability of EOB-MRI for the response to atezolizumab + bevacizumab therapy (Atezo/Bev). The association between differences in stepwise signal intensity of HB phase and molecular subtypes and somatic mutations associated with the immune microenvironment was investigated in 65 HCC patients (cohort 1). The association between EOB-MRI and the therapeutic effect of Atezo/Bev was evaluated in the Atezo/Bev cohort (60 patients in cohort 2). The proportion of HCCs having CTNNB1 mutations and classified as Chiang CTNNB1 and Hoshida S3 was high in the high-intensity HB-phase group. Infiltration of tumor-associated macrophages (TAM) and regulatory T-lymphocytes (Treg) was characteristic of the high-intensity and low-intensity groups, respectively. Although EOB-MRI could not predict the response to Atezo/Bev treatment, our results demonstrate that EOB-MRI could serve as a surrogate marker predicting the immune microenvironment. This suggests that Atezo/Bev treatment can be selected regardless of signal intensity in the EOB-MRI HB phase.

Pathology of Hepatocellular Carcinoma and Tumor-Bearing Liver Tissue in Association with hTERT Promoter Mutation

Background

The hTERT promoter mutation represents a common and early event in hepatocarcinogenesis, but its linkage to the morphological status of the underlying liver tissue is poorly understood. We analyzed the connection between the histopathological changes in tumor-bearing liver tissue and the occurrence of the hTERT promoter mutation in hepatocellular carcinoma (HCC), correlated with clinical data.

Methods

The study cohort comprised 160 histologically confirmed HCC in patients with or without cirrhosis that were investigated for the hTERT promoter mutation. We evaluated the frequency of the hTERT promoter mutation in patients with HCC with or without cirrhosis and correlated it with potential clinical and histopathological drivers. In particular, we examined tumor-bearing noncirrhotic liver tissue regarding inflammation; the modified histological activity index (mHAI), fibrosis, and steatosis; and its correlation with the frequency of the hTERT promoter mutation in HCC. We evaluated overall survival with multivariate Cox regression. Furthermore, we compared hTERT antibody immunohistochemistry and molecular hTERT promoter mutation analysis of both HCC and background liver tissue.

Results

The hTERT promoter mutation was especially related to HCC in cirrhotic compared with noncirrhotic liver (p < 0.001) and independently of cirrhosis in patients ≥ 60 years (p = 0.005). Furthermore, the hTERT promoter mutation was associated with cirrhosis caused by alcohol toxicity and hepatitis C virus infection. In noncirrhotic liver tissue, the frequency of hTERT-promoter-mutated HCC increased with the degree of inflammation and fibrosis. Nevertheless, 25% of the hTERT-promoter-mutated HCC developed in normal liver tissue without HCC risk factors. Multivariate Cox regression analysis did not reveal an influence of the hTERT promoter mutation in HCC on overall survival at 3, 5, and 16 years. Immunohistochemical analysis with the hTERT antibodies LS-B95 and 2D8 in hTERT-promoter-mutated HCC and hTERT-wildtype HCC showed a mildly stronger immunoreaction compared with the tumor-bearing liver tissue (LS-B95: p < 0.01, 2D8: p < 0.01).

Conclusions

Our study reveals a connection between pathological changes in tumor-bearing liver tissue and the hTERT promoter mutation in most HCC, even in noncirrhotic liver tissue. Immunohistochemical hTERT antibodies do not discriminate between hTERT-promoter-mutated and wildtype HCC.

Five Critical Gene-Based Biomarkers With Optimal Performance for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most fatal cancers in the world. There is an urgent need to understand the molecular background of HCC to facilitate the identification of biomarkers and discover effective therapeutic targets. Published transcriptomic studies have reported a large number of genes that are individually significant for HCC. However, reliable biomarkers remain to be determined. In this study, built on max-linear competing risk factor models, we developed a machine learning analytical framework to analyze transcriptomic data to identify the most miniature set of differentially expressed genes (DEGs). By analyzing 9 public whole-transcriptome datasets (containing 1184 HCC samples and 672 nontumor controls), we identified 5 critical differentially expressed genes (DEGs) (ie, CCDC107, CXCL12, GIGYF1, GMNN, and IFFO1) between HCC and control samples. The classifiers built on these 5 DEGs reached nearly perfect performance in identification of HCC. The performance of the 5 DEGs was further validated in a US Caucasian cohort that we collected (containing 17 HCC with paired nontumor tissue). The conceptual advance of our work lies in modeling gene-gene interactions and correcting batch effect in the analytic framework. The classifiers built on the 5 DEGs demonstrated clear signature patterns for HCC. The results are interpretable, robust, and reproducible across diverse cohorts/populations with various disease etiologies, indicating the 5 DEGs are intrinsic variables that can describe the overall features of HCC at the genomic level. The analytical framework applied in this study may pave a new way for improving transcriptome profiling analysis of human cancers.

Identifying Proliferative Hepatocellular Carcinoma at Pretreatment CT: Implications for Therapeutic Outcomes after Transarterial Chemoembolization

Background Hepatocellular carcinomas (HCCs) can be divided into proliferative and nonproliferative types, which may have implications for outcomes after conventional transarterial chemoembolization (cTACE). Biopsy to identify proliferative HCC is not routinely performed before cTACE. Purpose To develop and validate a predictive model for identifying proliferative HCCs using CT imaging features and to compare therapeutic outcomes between predicted proliferative and nonproliferative HCCs after cTACE according to this model. Materials and Methods This retrospective multicenter study included adults with HCC who underwent liver resection or cTACE between August 2013 and December 2020. A CT-based predictive model for identifying proliferative HCCs was developed and externally validated in a cohort that underwent resection. Diagnostic performance was calculated for the model. Thereafter, patients in the cTACE cohort were stratified into groups with predicted proliferative or nonproliferative HCCs according to the model. The primary outcome was overall survival (OS), and the secondary outcomes were tumor response rate and progression-free survival (PFS). These were compared between the two groups with use of the χ2 test and the log-rank test. Results A total of 1194 patients (1021 men; mean age, 54 years ± 12 [SD]; median follow-up time, 29.1 months) were included. The predictive model, named the SMARS score, incorporated lobulated shape, mosaic architecture, α-fetoprotein levels, rim arterial phase hyperenhancement, and satellite lesions. The area under the receiver operating characteristic curve for the SMARS score was 0.83 for the training cohort and 0.80 for the validation cohort. According to the SMARS score, patients with predicted proliferative HCCs (n = 114) had lower tumor response rate (48% vs 71%; P < .001) and worse PFS (6.6 months vs 12.4 months; P < .001) and OS (14.4 months vs 38.7 months; P < .001) than those with nonproliferative HCCs (n = 263). Conclusion The predictive model demonstrated good performance for identifying proliferative HCCs. According to the SMARS score, patients with predicted proliferative HCCs have worse prognosis than those with predicted nonproliferative HCCs after cTACE. © RSNA, 2023 Supplemental material is available for this article.

Non-invasive preoperative prediction of Edmondson-Steiner grade of hepatocellular carcinoma based on contrast-enhanced ultrasound using ensemble learning

Purpose

This study aimed to explore the clinical value of non-invasive preoperative Edmondson-Steiner grade of hepatocellular carcinoma (HCC) using contrast-enhanced ultrasound (CEUS).

Methods

212 cases of HCCs were retrospectively included, including 83 cases of high-grade HCCs and 129 cases of low-grade HCCs. Three representative CEUS images were selected from the arterial phase, portal vein phase, and delayed phase and stored in a 3-dimensional array. ITK-SNAP was used to segment the tumor lesions manually. The Radiomics method was conducted to extract high-dimensional features on these contrast-enhanced ultrasound images. Then the independent sample T-test and the Least Absolute Shrinkage and Selection Operator (LASSO) were employed to reduce the feature dimensions. The optimized features were modeled by a classifier based on ensemble learning, and the Edmondson Steiner grading was predicted in an independent testing set using this model.

Results

A total of 1338 features were extracted from the 3D images. After the dimension reduction, 10 features were finally selected to establish the model. In the independent testing set, the integrated model performed best, with an AUC of 0.931.

Conclusion

This study proposed an Edmondson-Steiner grading method for HCC with CEUS. The method has good classification performance on independent testing sets, which can provide quantitative analysis support for clinical decision-making.

FGF19/FGFR4-mediated elevation of ETV4 facilitates hepatocellular carcinoma metastasis by upregulating PD-L1 and CCL2

BACKGROUND & AIMS

Metastasis remains the major reason for the high mortality of patients with hepatocellular carcinoma (HCC). This study was designed to investigate the role of E-twenty-six-specific sequence variant 4 (ETV4) in promoting HCC metastasis and to explore a new combination therapy strategy for ETV4-mediated HCC metastasis.

METHODS

PLC/PRF/5, MHCC97H, Hepa1-6, and H22 cells were used to establish orthotopic HCC models. Clodronate liposomes were used to clear macrophages in C57BL/6 mice. Gr-1 monoclonal antibody was used to clear myeloid-derived suppressor cells (MDSCs) in C57BL/6 mice. Flow cytometry and immunofluorescence were used to detect the changes of key immune cells in the tumour microenvironment.

RESULTS

ETV4 expression was positively related to higher tumour-node-metastasis (TNM) stage, poor tumour differentiation, microvascular invasion, and poor prognosis in human HCC. Overexpression of ETV4 in HCC cells transactivated PD-L1 and CCL2 expression, which increased tumour-associated macrophage (TAM) and MDSC infiltration and inhibited CD8+ T-cell accumulation. Knockdown of CCL2 by lentivirus or CCR2 inhibitor CCX872 treatment impaired ETV4-induced TAM and MDSC infiltration and HCC metastasis. Furthermore, FGF19/FGFR4 and HGF/c-MET jointly upregulated ETV4 expression through the ERK1/2 pathway. Additionally, ETV4 upregulated FGFR4 expression, and downregulation of FGFR4 decreased ETV4-enhanced HCC metastasis, which created a FGF19-ETV4-FGFR4 positive feedback loop. Finally, anti-PD-L1 combined with FGFR4 inhibitor BLU-554 or MAPK inhibitor trametinib prominently inhibited FGF19-ETV4 signalling-induced HCC metastasis.

CONCLUSIONS

ETV4 is a prognostic biomarker, and anti-PD-L1 combined with FGFR4 inhibitor BLU-554 or MAPK inhibitor trametinib may be effective strategies to inhibit HCC metastasis.

IMPACT AND IMPLICATIONS

Here, we reported that ETV4 increased PD-L1 and chemokine CCL2 expression in HCC cells, which resulted in TAM and MDSC accumulation and CD8+ T-cell inhibition to facilitate HCC metastasis. More importantly, we found that anti-PD-L1 combined with FGFR4 inhibitor BLU-554 or MAPK inhibitor trametinib markedly inhibited FGF19-ETV4 signalling-mediated HCC metastasis. This preclinical study will provide a theoretical basis for the development of new combination immunotherapy strategies for patients with HCC.

Gadoxetic acid-enhanced MRI combined with T1 mapping and clinical factors to predict Ki-67 expression of hepatocellular carcinoma

Objectives

To explore the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) combined with T1 mapping and clinical factors for Ki-67 expression in hepatocellular carcinoma (HCC).

Methods

A retrospective study was conducted on 185 patients with pathologically confirmed solitary HCC from two institutions. All patients underwent preoperative T1 mapping on gadoxetic acid-enhanced MRI. Patients from institution I (n = 124) and institution II (n = 61) were respectively assigned to the training and validation sets. Univariable and multivariable analyses were performed to assess the correlation of clinico-radiological factors with Ki-67 labeling index (LI). Based on the significant factors, a predictive nomogram was developed and validated for Ki-67 LI. The performance of the nomogram was evaluated on the basis of its calibration, discrimination, and clinical utility.

Results

Multivariable analysis showed that alpha-fetoprotein (AFP) levels > 20ng/mL, neutrophils to lymphocyte ratio > 2.25, non-smooth margin, tumor-to-liver signal intensity ratio in the hepatobiliary phase ≤ 0.6, and post-contrast T1 relaxation time > 705 msec were the independent predictors of Ki-67 LI. The nomogram based on these variables showed the best predictive performance with area under the receiver operator characteristic curve (AUROC) 0.899, area under the precision-recall curve (AUPRC) 0.946 and F1 score of 0.912; the respective values were 0.823, 0.879 and 0.857 in the validation set. The Kaplan-Meier curves illustrated that the cumulative recurrence probability at 2 years was significantly higher in patients with high Ki-67 LI than in those with low Ki-67 LI (39.6% [53/134] vs. 19.6% [10/51], p = 0.011).

Conclusions

Gadoxetic acid-enhanced MRI combined with T1 mapping and several clinical factors can preoperatively predict Ki-67 LI with high accuracy, and thus enable risk stratification and personalized treatment of HCC patients.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CRITICAL RELEVANCE STATEMENT

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

Preoperative prediction of macrotrabecular-massive hepatocellular carcinoma through dynamic contrast-enhanced magnetic resonance imaging-based radiomics

BACKGROUND

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) is closely related to aggressive phenotype, gene mutation, carcinogenic pathway, and immunohistochemical markers and is a strong independent predictor of early recurrence and poor prognosis. With the development of imaging technology, successful applications of contrast-enhanced magnetic resonance imaging (MRI) have been reported in identifying the MTM-HCC subtype. Radiomics, as an objective and beneficial method for tumour evaluation, is used to convert medical images into high-throughput quantification features that greatly push the development of precision medicine.

AIM

To establish and verify a nomogram for preoperatively identifying MTM-HCC by comparing different machine learning algorithms.

METHODS

This retrospective study enrolled 232 (training set, 162; test set, 70) hepatocellular carcinoma patients from April 2018 to September 2021. A total of 3111 radiomics features were extracted from dynamic contrast-enhanced MRI, followed by dimension reduction of these features. Logistic regression (LR), K-nearest neighbour (KNN), Bayes, Tree, and support vector machine (SVM) algorithms were used to select the best radiomics signature. We used the relative standard deviation (RSD) and bootstrap methods to quantify the stability of these five algorithms. The algorithm with the lowest RSD represented the best stability, and it was used to construct the best radiomics model. Multivariable logistic analysis was used to select the useful clinical and radiological features, and different predictive models were established. Finally, the predictive performances of the different models were assessed by evaluating the area under the curve (AUC).

RESULTS

The RSD values based on LR, KNN, Bayes, Tree, and SVM were 3.8%, 8.6%, 4.3%, 17.7%, and 17.4%, respectively. Therefore, the LR machine learning algorithm was selected to construct the best radiomics signature, which performed well with AUCs of 0.766 and 0.739 in the training and test sets, respectively. In the multivariable analysis, age [odds ratio (OR) = 0.956, P = 0.034], alpha-fetoprotein (OR = 10.066, P < 0.001), tumour size (OR = 3.316, P = 0.002), tumour-to-liver apparent diffusion coefficient (ADC) ratio (OR = 0.156, P = 0.037), and radiomics score (OR = 2.923, P < 0.001) were independent predictors of MTM-HCC. Among the different models, the predictive performances of the clinical-radiomics model and radiological-radiomics model were significantly improved compared to those of the clinical model (AUCs: 0.888 vs 0.836, P = 0.046) and radiological model (AUCs: 0.796 vs 0.688, P = 0.012), respectively, in the training set, highlighting the improved predictive performance of radiomics. The nomogram performed best, with AUCs of 0.896 and 0.805 in the training and test sets, respectively.

CONCLUSION

The nomogram containing radiomics, age, alpha-fetoprotein, tumour size, and tumour-to-liver ADC ratio revealed excellent predictive ability in preoperatively identifying the MTM-HCC subtype.

Osteoclast-like giant cells in hepatocellular carcinoma case description and review of the literature

BACKGROUND

The presence of osteoclast-like giant cells (OGC) in hepatocellular carcinoma (HCC) is rare and literature on this topic is scarce. In this article, we report on a case of a 77-year-old male patient with HCC with OGC and provide an overview of the current literature.

METHODS

We conducted a systematic search to find all available literature on OGC in HCC. The electronic databases PubMed, Web of Science, Embase and CENTRAL were searched from inception until October 2020.

RESULTS

Thirteen articles on this topic were identified and were included in this review. Data on 14 patients were available, described in twelve case reports, one patient in a patient series and the present case. Median age of included patients was 68 years. Two patients underwent neoadjuvant therapy prior to surgery. Of the 14 cases, eight tumours with OGC arose in a cirrhotic liver. Oncological outcome in this series was unfavourable, even after surgical resection, with a median disease-free survival of 75 d.

CONCLUSIONS

The presence of OGC in HCC is rare. Current literature is scarce, and suggests an unfavourable outcome in regard to overall survival of HCC.

Combining γ-GT, PIVKA-II, and AFP to predict long-term prognosis in patients with hepatocellular carcinoma after hepatectomy

Hepatocellular carcinoma (HCC) is one of the top five contributors to the cancer burden in China, with a poor prognosis and heavy disability-adjusted life year burden. The criteria used for HCC prognosis are complicated and therefore restricted in routine clinical practice. Multiple factors influence HCC malignancy and progression. In this study, we retrospectively evaluated 173 patients with HCC who underwent curative resection for 9 years to evaluate the correlation of a combination of γ-glutamyl transferase (γ-GT), protein induced by vitamin K absence or antagonist-II (PIVKA-II), and α-fetoprotein (AFP) with the long-term survival of patients with HCC. Multivariate analysis revealed that the γ-GT level was an independent prognostic factor for recurrence. The prediction rate of early recurrence with γ-GT, PIVKA-II, and AFP levels individually was 63.5%, 79.4%, and 39.7%, respectively, whereas the prediction rate of early recurrence was 95.2% with the combination of γ-GT, PIVKA-II, and AFP levels as a composite indicator. Our long-term retrospective study revealed that γ-GT, PIVKA-II, and AFP can aid in predicting long-term prognosis of HCC recurrence. The combination of γ-GT, PIVKA-II, and AFP can further aid in identifying patients with early recurrence. Together, γ-GT, PIVKA-II, and AFP may a be used to develop a new prediction method to improve the prognosis of patients with HCC, and our results indicate the requirement of more active HCC treatment strategies.

Can MRI features predict clinically relevant hepatocellular carcinoma genetic subtypes?

PURPOSE

Recent studies in cancer genomics have revealed core drivers for hepatocellular carcinoma (HCC) pathogenesis. We aim to study whether MRI features can serve as non-invasive markers for the prediction of common genetic subtypes of HCC.

METHODS

Sequencing of 447 cancer-implicated genes was performed on 43 pathology proven HCC from 42 patients, who underwent contrast-enhanced MRI followed by biopsy or resection. MRI features were retrospectively evaluated including tumor size, infiltrative tumor margin, diffusion restriction, arterial phase hyperenhancement, non-peripheral washout, enhancing capsule, peritumoral enhancement, tumor in vein, fat in mass, blood products in mass, cirrhosis and tumor heterogeneity. Fisher's exact test was used to correlate genetic subtypes with imaging features. Prediction performance using correlated MRI features for genetic subtype and inter-reader agreement were assessed.

RESULTS

The two most prevalent genetic mutations were TP53 (13/43, 30%) and CTNNB1 (17/43, 40%). Tumors with TP53 mutation more often demonstrated an infiltrative tumor margin on MRI (p = 0.01); inter-reader agreement was almost perfect (kappa = 0.95). The CTNNB1 mutation was associated with peritumoral enhancement on MRI (p = 0.04), inter-reader agreement was substantial (kappa = 0.74). The MRI feature of an infiltrative tumor margin correlated with the TP53 mutation with accuracy, sensitivity, and specificity of 74.4%, 61.5% and 80.0%, respectively. Peritumoral enhancement correlated with the CTNNB1 mutation with accuracy, sensitivity, and specificity of 69.8%, 47.0% and 84.6%, respectively.

CONCLUSION

An infiltrative tumor margin on MRI correlated with TP53 mutation and peritumoral enhancement correlated with CTNNB1 mutation in HCC. Absence of these MRI features are potential negative predictors of the respective HCC genetic subtypes that have implications for prognosis and treatment response.

Evaluation and Application of Drug Resistance by Biomarkers in the Clinical Treatment of Liver Cancer

Liver cancer is one of the most lethal cancers in the world, mainly owing to the lack of effective means for early monitoring and treatment. Accordingly, there is considerable research interest in various clinically applicable methods for addressing these unmet needs. At present, the most commonly used biomarker for the early diagnosis of liver cancer is alpha-fetoprotein (AFP), but AFP is sensitive to interference from other factors and cannot really be used as the basis for determining liver cancer. Treatment options in addition to liver surgery (resection, transplantation) include radiation therapy, chemotherapy, and targeted therapy. However, even more expensive targeted drug therapies have a limited impact on the clinical outcome of liver cancer. One of the big reasons is the rapid emergence of drug resistance. Therefore, in addition to finding effective biomarkers for early diagnosis, an important focus of current discussions is on how to effectively adjust and select drug strategies and guidelines for the treatment of liver cancer patients. In this review, we bring this thought process to the drug resistance problem faced by different treatment strategies, approaching it from the perspective of gene expression and molecular biology and the possibility of finding effective solutions.

Effect of HBsAg expression in liver tissue on prognosis of hepatocellular carcinoma after minimally invasive interventional therapy

Background

The aim of this study was to investigate the association between pathologic markers and prognosis in patients with hepatocellular carcinoma who received transcatheter chemoembolization combined with locoregional ablation therapy.

Methods

This retrospective study included 111 hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC). All patients underwent transcatheter arterial chemoembolization (TACE) combined with locoregional ablation therapy, and received core needle biopsy before therapy in Beijing You ‘an Hospital affiliated to Capital Medical University from January 1, 2013 to December 31, 2016. Demographic, pathological indicators and clinical laboratory data were collected. The cumulative recurrence-free survival (RFS) and overall survival (OS) were calculated and compared by Kaplan-Meier method and Log-rank test, and Cox proportional risk model was used to screen for independent predictors of recurrence and long-term prognosis in HCC patients.

Results

There was a correlation between HBsAg expression in liver tissue and prognosis of HCC patients. Patients with negative HBsAg expression had longer 1-,3- and 5-year RFS rates than positive HBsAg expression (78.3%, 43.5%, 30.4% and 58.5%, 24.5%, 17.0%, P=0.018). Meanwhile,the postoperative 1-,3-and 5-year OS rates of HCC patients in the negative HBsAg expression group were significantly higher than those of HCC patients in the positive HBsAg expression group (100%, 89.1%, 80.4% and 100%, 75.5%, 58.5%, P=0.008).

Conclusions

The prognosis of patients with hepatocellular carcinoma with negative HBsAg expression was better than that with positive HBsAg expression. Accordingly, the expression of the liver HBsAg before combined therapy was a prognostic indicator for OS and RFS. For patients with liver HBsAg positive, follow-up should be strengthened and corresponding intervention measures should be taken to improve prognosis.

Curcumin in the treatment of liver cancer: From mechanisms of action to nanoformulations

Liver cancer is the sixth most prevalent cancer and ranks third in cancer-related death, after lung and colorectal cancer. Various natural products have been discovered as alternatives to conventional cancer therapy strategies, including radiotherapy, chemotherapy, and surgery. Curcumin (CUR) with antiinflammatory, antioxidant, and antitumor activities has been associated with therapeutic benefits against various cancers. It can regulate multiple signaling pathways, such as PI3K/Akt, Wnt/β-catenin, JAK/STAT, p53, MAPKs, and NF-ĸB, which are involved in cancer cell proliferation, metastasis, apoptosis, angiogenesis, and autophagy. Due to its rapid metabolism, poor oral bioavailability, and low solubility in water, CUR application in clinical practices is restricted. To overcome these limitations, nanotechnology-based delivery systems have been applied to use CUR nanoformulations with added benefits, such as reducing toxicity, improving cellular uptake, and targeting tumor sites. Besides the anticancer activities of CUR in combating various cancers, especially liver cancer, here we focused on the CUR nanoformulations, such as micelles, liposomes, polymeric, metal, and solid lipid nanoparticles, and others, in the treatment of liver cancer.

2022 KLCA-NCC Korea practice guidelines for the management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the fourth most common cancer among men in South Korea, where the prevalence of chronic hepatitis B infection is high in middle and old age. The current practice guidelines will provide useful and sensible advice for the clinical management of patients with HCC. A total of 49 experts in the fields of hepatology, oncology, surgery, radiology, and radiation oncology from the Korean Liver Cancer Association-National Cancer Center Korea Practice Guideline Revision Committee revised the 2018 Korean guidelines and developed new recommendations that integrate the most up-to-date research findings and expert opinions. These guidelines provide useful information and direction for all clinicians, trainees, and researchers in the diagnosis and treatment of HCC.

CBX2-mediated suppression of SIAH2 triggers WNK1 accumulations to promote glycolysis in hepatocellular carcinoma

Previous studies have highlighted the poor prognosis of liver cancer, and treatment effects are overall limited. We aimed to confirm the biological roles of SIAH2 in liver cancer and provide potential therapeutic targets. Differential analysis was conducted based on public datasets and found that SIAH2 expressed lowly in HCC samples relative to normal tissues, which was demonstrated in tumor samples via immunohistochemistry (IHC). Besides, SIAH2 overexpression could significantly suppress HCC proliferation. SIAH2 deficiency induced cell proliferation, migration and self-renewal abilities in vitro and in vivo. Mechanistically, SIAH2 could interact with WNK1, and trigger the ubiquitination and degradation of WNK1 proteins. In addition, low SIAH2 depended on elevated WNK1 proteins to drive HCC malignant features, including proliferation, migration and stemness. Meanwhile, we further found that CBX2 could regulate SIAH2 expressions. CBX2 cooperated with EZH2 to mediate the H3K27me3 enrichment on the promoter region of SIAH2 to suppress its transcriptional levels. High CBX2/EZH2 levels in HCC correlated with poor prognosis of patients. Gene set enrichment analysis (GSEA) further implicated that WNK1 correlates tightly with glycolytic process in HCC samples. WNK1 overexpression was found to notably enhance glycolytic activity, whereas WNK1 deficiency could significantly suppress the HCC glycolysis activity. Lastly, the subcutaneous tumor model further demonstrated that targeting WNK1 was effective to inhibit the in vivo tumor growth of SIAH2^low HCC. Collectively, down-regulated SIAH2 expressions induced by CBX2/EZH2 could drive progression and glycolysis via accumulating WNK1 proteins, indicating that CBX2/SIAH2/WNK1 axis is a potential prognostic biomarker and therapeutic vulnerability for human HCC.

Indocyanine green fluorescence patterns of hepatocellular carcinoma correlate with pathological and molecular features

BACKGROUND

Intraoperative Indocyanine Green Dye (ICG) routinely used in hepatobiliary surgery identifies different fluorescent patterns of hepatocellular carcinoma (HCC), a highly heterogeneous cancer. We aimed to correlate these patterns with gene mutations and extensive pathological features beyond the well-known tumor differentiation.

METHODS

Between February 2017 and December 2019, 21 HCC in 16 consecutive patients who underwent intraoperative ICG fluorescence imaging were included. Pathological review was performed by one pathologist blinded to fluorescence features. Random forest machine learning algorithm correlated pathological features of the tumor, peritumoral and non-tumoral liver, and gene mutations from a 28 gene-panel with rim and intra-lesion fluorescence.

RESULTS

Three HCC had negative intra-lesion and rim-like emission, 7 HCC had homogeneous pattern and 11 heterogeneous patterns in whom 3 with rim-like emission. Rim emission was associated with peritumoral vascular changes, lower differentiation and lower serum AFP level. Homogeneous intra-lesion fluorescence was associated with lower necrosis rate, thinner capsule, absence of peritumoral liver changes, and higher serum AFP level. Heterogeneous HCC without rim harbored lesser TP53 and ARID1A mutations.

CONCLUSION

Tumoral and peri-tumoral fluorescence classification of HCC yielded a possible intraoperative pathological and molecular characterization. These preliminary observations could lead to intraoperative refinement in surgical strategy.

Genetic variation in TERT modifies the risk of hepatocellular carcinoma in alcohol-related cirrhosis: results from a genome-wide case-control study

OBJECTIVE

Hepatocellular carcinoma (HCC) often develops in patients with alcohol-related cirrhosis at an annual risk of up to 2.5%. Some host genetic risk factors have been identified but do not account for the majority of the variance in occurrence. This study aimed to identify novel susceptibility loci for the development of HCC in people with alcohol related cirrhosis.

DESIGN

Patients with alcohol-related cirrhosis and HCC (cases: n=1214) and controls without HCC (n=1866), recruited from Germany, Austria, Switzerland, Italy and the UK, were included in a two-stage genome-wide association study using a case-control design. A validation cohort of 1520 people misusing alcohol but with no evidence of liver disease was included to control for possible association effects with alcohol misuse. Genotyping was performed using the InfiniumGlobal Screening Array (V.24v2, Illumina) and the OmniExpress Array (V.24v1-0a, Illumina).

RESULTS

Associations with variants rs738409 in PNPLA3 and rs58542926 in TM6SF2 previously associated with an increased risk of HCC in patients with alcohol-related cirrhosis were confirmed at genome-wide significance. A novel locus rs2242652(A) in TERT (telomerase reverse transcriptase) was also associated with a decreased risk of HCC, in the combined meta-analysis, at genome-wide significance (p=6.41×10-9, OR=0.61 (95% CI 0.52 to 0.70). This protective association remained significant after correction for sex, age, body mass index and type 2 diabetes (p=7.94×10-5, OR=0.63 (95% CI 0.50 to 0.79). Carriage of rs2242652(A) in TERT was associated with an increased leucocyte telomere length (p=2.12×10-44).

CONCLUSION

This study identifies rs2242652 in TERT as a novel protective factor for HCC in patients with alcohol-related cirrhosis.

Treatment of HCC with claudin-1-specific antibodies suppresses carcinogenic signaling and reprograms the tumor microenvironment

BACKGROUND & AIMS

Despite recent approvals, the response to treatment and prognosis of patients with advanced hepatocellular carcinoma (HCC) remain poor. Claudin-1 (CLDN1) is a membrane protein that is expressed at tight junctions, but it can also be exposed non-junctionally, such as on the basolateral membrane of the human hepatocyte. While CLDN1 within tight junctions is well characterized, the role of non-junctional CLDN1 and its role as a therapeutic target in HCC remains unexplored.

METHODS

Using humanized monoclonal antibodies (mAbs) specifically targeting the extracellular loop of human non-junctional CLDN1 and a large series of patient-derived cell-based and animal model systems we aimed to investigate the role of CLDN1 as a therapeutic target for HCC.

RESULTS

Targeting non-junctional CLDN1 markedly suppressed tumor growth and invasion in cell line-based models of HCC and patient-derived 3D ex vivo models. Moreover, the robust effect on tumor growth was confirmed in vivo in a large series of cell line-derived xenograft and patient-derived xenograft mouse models. Mechanistic studies, including single-cell RNA sequencing of multicellular patient HCC tumorspheres, suggested that CLDN1 regulates tumor stemness, metabolism, oncogenic signaling and perturbs the tumor immune microenvironment.

CONCLUSIONS

Our results provide the rationale for targeting CLDN1 in HCC and pave the way for the clinical development of CLDN1-specific mAbs for the treatment of advanced HCC.

IMPACT AND IMPLICATIONS

Hepatocellular carcinoma (HCC) is associated with high mortality and unsatisfactory treatment options. Herein, we identified the cell surface protein Claudin-1 as a treatment target for advanced HCC. Monoclonal antibodies targeting Claudin-1 inhibit tumor growth in patient-derived ex vivo and in vivo models by modulating signaling, cell stemness and the tumor immune microenvironment. Given the differentiated mechanism of action, the identification of Claudin-1 as a novel therapeutic target for HCC provides an opportunity to break the plateau of limited treatment response. The results of this preclinical study pave the way for the clinical development of Claudin-1-specific antibodies for the treatment of advanced HCC. It is therefore of key impact for physicians, scientists and drug developers in the field of liver cancer and gastrointestinal oncology.

18F-FDG PET/CT-based radiomics nomogram for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma: a two-center study

PURPOSE

To explore the potential of β-2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) in the evaluation of macrotrabecular-massive (MTM) hepatocellular carcinoma (HCC) and to apply radiomics approach to build a radiomics nomogram for predicting MTM-HCC.

METHODS

This study included 140 (training cohort:101; validation cohort:39) HCC patients who underwent preoperative ¹⁸F-FDG PET/CT at two institutions. The clinical features and tumor FDG metabolism measured by the tumor-to-liver ratio (TLR) via ¹⁸F-FDG PET/CT were retrospectively collected. Radiomics features were extracted from ¹⁸F-FDG PET/CT images and a radiomics score (Rad-score) was calculated. A radiomics nomogram was then constructed by combining Rad-score and independent clinical features and was assessed with a calibration curve. The performance of the radiomics nomogram, Rad-score and TLR was evaluated by receiver operating characteristic (ROC) curves and decision curve analysis (DCA).

RESULTS

A total of six top weighted radiomics features were selected from PET/CT images by the least absolute shrinkage and selection operator (LASSO) regression algorithm and were used to construct a Rad-score. Multivariate analysis identified Rad-score (OR = 2.183, P = 0.004), age ≤ 50 years (OR = 3.136, P = 0.036), AST > 40U/L (OR = 0.270, P = 0.017) and TLR (OR = 1.641, P = 0.049) as independent predictors of MTM-HCC. The radiomics nomogram had a higher area under the curves (AUCs) than the Rad-score and TLR for predicting MTM-HCC in both training (0.849 [95% CI 0.774-0.924] vs. 0.764 [95% CI 0.669-0.843], 0.763 [95% CI 0.668-0.842]) and validation (0.749 [95% CI 0.584-0.873] vs. 0.690 [95% CI 0.522-0.828], 0.541 [95% CI 0.374-0.701]) cohorts. DCA showed the radiomics nomogram to be more clinically useful than Rad-score and TLR.

CONCLUSIONS

Tumor FDG metabolism is significantly associated with MTM-HCC. A ¹⁸F-FDG PET/CT-based radiomics nomogram may be useful for preoperatively predicting the MTM subtype in primary HCC patients, contributing to pretreatment decision-making.

Analysis of angiogenesis-related subtypes of hepatocellular carcinoma and tumor microenvironment infiltration feature in hepatocellular carcinoma

PURPOSE

Hepatocellular carcinoma (HCC) is a highly vascularized tumor, and angiogenesis plays an important role in its progression. However, the role of angiogenesis in cell infiltration in the tumor microenvironment (TME) remains unclear.

METHODS

We evaluated the associations of 35 angiogenesis-related genes (ARGs) with the clinicopathological features of 816 HCC patients. In addition, we assessed the associations between the ARGs and TME cell infiltration. A nomogram was constructed to determine the prognostic value of ARGs for HCC. The ARG score was used to distinguish angiogenic subtypes of HCC, and its usefulness for predicting the prognosis and treatment response of HCC patients was evaluated.

RESULTS

We distinguished three ARG clusters differing in terms of TME cell infiltration, immune cell activation status, clinicopathological features, and clinical outcomes. There were significant associations of ARG expression with tumor immunity, the epithelial-mesenchymal transition (EMT), and transforming growth factor-β expression. An ARG score model was constructed to generate a risk score for each patient based on differentially expressed genes between clusters. Furthermore, a high ARG score was associated with high expression of CTLA-4 and PD-L1/PD-1, and a low Tumor Immune Dysfunction and Exclusion score, indicating the usefulness of the ARG score for selecting patients for immunotherapy. Considering the relationship between ARGs and tumor immunity, immunotherapy combined with vascular-targeted therapy may be the best treatment for HCC.

CONCLUSIONS

ARGs play an important role in TME diversity and complexity in HCC patients. The ARG score of HCC predicts TME invasion and can guide immunotherapy.

Revamping the innate or innate-like immune cell-based therapy for hepatocellular carcinoma: new mechanistic insights and advanced opportunities

A cancerous tumour termed hepatocellular carcinoma (HCC) is characterized by inflammation and subsequently followed by end-stage liver disease and necrosis of the liver. The liver's continuous exposure to microorganisms and toxic molecules affects the immune response because normal tissue requires some immune tolerance to be safeguarded from damage. Several innate immune cells are involved in this process of immune system activation which includes dendritic cells, macrophages, and natural killer cells. The liver is an immunologic organ with vast quantities of innate and innate-like immune cells subjected to several antigens (bacteria, fungal or viral) through the gut-liver axis. Tumour-induced immune system engagement may be encouraged or suppressed through innate immunological systems, which are recognized promoters of liver disease development in pre-HCC conditions such as fibrosis or cirrhosis, ultimately resulting in HCC. Immune-based treatments containing several classes of drugs have transformed the treatment of several types of cancers in recent times. The effectiveness of such immunotherapies relies on intricate interactions between lymphocytes, tumour cells, and neighbouring cells. Even though immunotherapy therapy has already reported to possess potential effect to treat HCC, a clear understanding of the crosstalk between innate and adaptive immune cell pathways still need to be clearly understood for better exploitation of the same. The identification of predictive biomarkers, understanding the progression of the disease, and the invention of more efficient combinational treatments are the major challenges in HCC immunotherapy. The functions and therapeutic significance of innate immune cells, which have been widely implicated in HCC, in addition to the interplay between innate and adaptive immune responses during the pathogenesis, have been explored in the current review.