Progenitor cell markers predict outcome of patients with hepatocellular carcinoma beyond Milan criteria undergoing liver transplantation

MRI-Based Radiomics and Deep Learning in Biological Characteristics and Prognosis of Hepatocellular Carcinoma: Opportunities and Challenges

Hepatocellular carcinoma (HCC) is the fifth most common malignancy and the third leading cause of cancer-related death worldwide. HCC exhibits strong inter-tumor heterogeneity, with different biological characteristics closely associated with prognosis. In addition, patients with HCC often distribute at different stages and require diverse treatment options at each stage. Due to the variability in tumor sensitivity to different therapies, determining the optimal treatment approach can be challenging for clinicians prior to treatment. Artificial intelligence (AI) technology, including radiomics and deep learning approaches, has emerged as a unique opportunity to improve the spectrum of HCC clinical care by predicting biological characteristics and prognosis in the medical imaging field. The radiomics approach utilizes handcrafted features derived from specific mathematical formulas to construct various machine-learning models for medical applications. In terms of the deep learning approach, convolutional neural network models are developed to achieve high classification performance based on automatic feature extraction from images. Magnetic resonance imaging offers the advantage of superior tissue resolution and functional information. This comprehensive evaluation plays a vital role in the accurate assessment and effective treatment planning for HCC patients. Recent studies have applied radiomics and deep learning approaches to develop AI-enabled models to improve accuracy in predicting biological characteristics and prognosis, such as microvascular invasion and tumor recurrence. Although AI-enabled models have demonstrated promising potential in HCC with biological characteristics and prognosis prediction with high performance, one of the biggest challenges, interpretability, has hindered their implementation in clinical practice. In the future, continued research is needed to improve the interpretability of AI-enabled models, including aspects such as domain knowledge, novel algorithms, and multi-dimension data sources. Overcoming these challenges would allow AI-enabled models to significantly impact the care provided to HCC patients, ultimately leading to their deployment for clinical use. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Expanding the Boundaries for Liver Transplantation for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, which was the third most common cause of cancer death worldwide in 2020. Transplantation remains the preferred treatment for cure in otherwise unresectable HCC. There are several areas of active research that have led to expansion of eligibility criteria for transplantation including local-regional therapy for downstaging patients presenting outside of the Milan criteria and identification of tumor biomarkers aiding in the early diagnosis, determining prognosis and likelihood of recurrence after transplantation for HCC. New neoadjuvant therapies and post-transplant immunosuppression regimens may also result in expansion of transplant eligibility criteria for HCC.

Molecular profiling in the management of hepatocellular carcinoma

PURPOSE OF REVIEW

The purpose of this review is to both summarize the current knowledge of hepatocellular carcinoma molecular biology and to suggest a framework in which to prospectively translate this knowledge into patient care. This is timely as recent guidelines recommend increased use of these technologies to advance personalized liver cancer care.

RECENT FINDINGS

The main themes covered here address germline and somatic genetic alterations recently discovered in hepatocellular carcinoma, largely owing to next generation sequencing technologies, and nascent efforts to translate these into contemporary practice.

SUMMARY

Early efforts of translating molecular profiling to hepatocellular carcinoma care demonstrate a growing number of potentially actionable alterations. Still lacking are a consensus on what biomarkers and technologies to adopt, at what scale and cost, and how to integrate them most effectively into care.

Clonorchis sinensis infection amplifies hepatocellular carcinoma stemness, predicting unfavorable prognosis

BACKGROUND

Extensive evidence links Clonorchis sinensis (C. sinensis) to cholangiocarcinoma; however, its association with hepatocellular carcinoma (HCC) is less acknowledged, and the underlying mechanism remains unclear. This study was designed to investigate the association between C. sinensis infection and HCC and reveal the relationship between C. sinensis infection and cancer stemness.

METHODS

A comprehensive analysis of 839 HCC patients categorized into C. sinensis (-) HCC and C. sinensis (+) HCC groups was conducted. Chi-square and Mann-Whitney U tests were used to assess the association between C. sinensis infection and clinical factors. Kaplan-Meier and Cox regression analyses were used to evaluate survival outcomes. Immunohistochemistry was used to determine CK19 and EpCAM expression in HCC specimens.

RESULTS

Compared to C. sinensis (-) HCC patients, C. sinensis (+) HCC patients exhibited advanced Barcelona Clinic Liver Cancer (BCLC) stage, higher male prevalence and more liver cirrhosis as well as elevated alpha-fetoprotein (AFP), carbohydrate antigen 19-9 (CA19-9), eosinophil, complement 3 (C3), and complement 4 (C4) values. C. sinensis infection correlated with shorter overall survival (OS) (p < 0.05) and recurrence-free survival (RFS) (p < 0.05). Furthermore, Cox multivariate analysis revealed that C. sinensis infection was an independent prognostic factor for OS in HCC patients. Importantly, C. sinensis infection upregulated the expression of HCC cancer stem cell markers CK19 and EpCAM.

CONCLUSION

HCC patients with C. sinensis infection exhibit a poor prognosis following hepatectomy. Moreover, C. sinensis infection promotes the acquisition of cancer stem cell-like characteristics, consequently accelerating the malignant progression of HCC.

AUTHOR SUMMARY

Clonorchis sinensis (C. sinensis) is a prominent food-borne parasite prevalent in regions such as China, particularly in Guangxi. C. sinensis has been associated with various hepatobiliary system injuries, encompassing inflammation, periductal fibrosis, cholangiocarcinoma and even hepatocellular carcinoma (HCC). A substantial body of evidence links C. sinensis to cholangiocarcinoma, However, the connection between C. sinensis and HCC and the intricate mechanisms underlying its contribution to HCC development remain incompletely elucidated. Our study demonstrates clear clinicopathological associations between C. sinensis and HCC, such as gender, BCLC stage, liver cirrhosis, MVI, AFP, CA19-9, circulating eosinophils and complements. Furthermore, we found that the co-occurrence of C. sinensis exhibited a significant association with shorter OS and RFS in patients diagnosed with HCC. A major finding was that C. sinensis infection promotes the acquisition of cancer stem cell-like characteristics, consequently accelerating the malignant progression of HCC. Our results provide a more comprehensive comprehension of the interplay between C. sinensis and HCC, shedding fresh light on the carcinogenic potential of C. sinensis.

Machine learning methods for accurately predicting survival and guiding treatment in stage I and II hepatocellular carcinoma

Accurately predicting survival in patients with early hepatocellular carcinoma (HCC) is essential for making informed decisions about treatment and prognosis. Herein, we have developed a machine learning (ML) model that can predict patient survival and guide treatment decisions. We obtained patient demographic information, tumor characteristics, and treatment details from the SEER database. To analyze the data, we employed a Cox proportional hazards (CoxPH) model as well as 3 ML algorithms: neural network multitask logistic regression (N-MLTR), DeepSurv, and random survival forest (RSF). Our evaluation relied on the concordance index (C-index) and Integrated Brier Score (IBS). Additionally, we provided personalized treatment recommendations regarding surgery and chemotherapy choices and validated models' efficacy. A total of 1136 patients with early-stage (I, II) hepatocellular carcinoma (HCC) who underwent liver resection or transplantation were randomly divided into training and validation cohorts at a ratio of 3:7. Feature selection was conducted using Cox regression analyses. The ML models (NMLTR: C-index = 0.6793; DeepSurv: C-index = 0.7028; RSF: C-index = 0.6890) showed better discrimination in predicting survival than the standard CoxPH model (C-index = 0.6696). Patients who received recommended treatments had higher survival rates than those who received unrecommended treatments. ML-based surgery treatment recommendations yielded higher hazard ratios (HRs): NMTLR HR = 0.36 (95% CI: 0.25-0.51, P < .001), DeepSurv HR = 0.34 (95% CI: 0.24-0.49, P < .001), and RSF HR = 0.37 (95% CI: 0.26-0.52, P = <.001). Chemotherapy treatment recommendations were associated with significantly improved survival for DeepSurv (HR: 0.57; 95% CI: 0.4-0.82, P = .002) and RSF (HR: 0.66; 95% CI: 0.46-0.94, P = .020). The ML survival model has the potential to benefit prognostic evaluation and treatment of HCC. This novel analytical approach could provide reliable information on individual survival and treatment recommendations.

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.

Incremental value of radiomics-based heterogeneity to the existing risk criteria in predicting recurrence of hepatocellular carcinoma after liver transplantation

OBJECTIVES

The aim of the study was to evaluate the association between the radiomics-based intratumoral heterogeneity (ITH) and the recurrence risk in hepatocellular carcinoma (HCC) patients after liver transplantation (LT), and to assess its incremental to the Milan, University of California San Francisco (UCSF), Metro-Ticket 2.0, and Hangzhou criteria.

METHODS

A multicenter cohort of 196 HCC patients were investigated. The endpoint was recurrence-free survival (RFS) after LT. A CT-based radiomics signature (RS) was constructed and assessed in the whole cohort and in the subgroups stratified by the Milan, UCSF, Metro-Ticket 2.0, and Hangzhou criteria. The R-Milan, R-UCSF, R-Metro-Ticket 2.0, and R-Hangzhou nomograms which combined RS and the four existing risk criteria were developed respectively. The incremental value of RS to the four existing risk criteria in RFS prediction was evaluated.

RESULTS

RS was significantly associated with RFS in the training and test cohorts as well as in the subgroups stratified by the existing risk criteria. The four combined nomograms showed better predictive capability than the existing risk criteria did with higher C-indices (R-Milan [training/test] vs. Milan, 0.745/0.765 vs. 0.677; R-USCF vs. USCF, 0.748/0.767 vs. 0.675; R-Metro-Ticket 2.0 vs. Metro-Ticket 2.0, 0.756/0.783 vs. 0.670; R-Hangzhou vs. Hangzhou, 0.751/0.760 vs. 0.691) and higher clinical net benefit.

CONCLUSIONS

The radiomics-based ITH can predict outcomes and provide incremental value to the existing risk criteria in HCC patients after LT. Incorporating radiomics-based ITH in HCC risk criteria may facilitate candidate selection, surveillance, and adjuvant trial design.

KEY POINTS

• Milan, USCF, Metro-Ticket 2.0, and Hangzhou criteria may be insufficient for outcome prediction in HCC after LT. • Radiomics allows for the characterization of tumor heterogeneity. • Radiomics adds incremental value to the existing criteria in outcome prediction.

Liver Transplant in Patients with Hepatocarcinoma: Imaging Guidelines and Future Perspectives Using Artificial Intelligence

Hepatocellular carcinoma is the most common primary malignant hepatic tumor and occurs most often in the setting of chronic liver disease. Liver transplantation is a curative treatment option and is an ideal solution because it solves the chronic underlying liver disorder while removing the malignant lesion. However, due to organ shortages, this treatment can only be applied to carefully selected patients according to clinical guidelines. Artificial intelligence is an emerging technology with multiple applications in medicine with a predilection for domains that work with medical imaging, like radiology. With the help of these technologies, laborious tasks can be automated, and new lesion imaging criteria can be developed based on pixel-level analysis. Our objectives are to review the developing AI applications that could be implemented to better stratify liver transplant candidates. The papers analysed applied AI for liver segmentation, evaluation of steatosis, sarcopenia assessment, lesion detection, segmentation, and characterization. A liver transplant is an optimal treatment for patients with hepatocellular carcinoma in the setting of chronic liver disease. Furthermore, AI could provide solutions for improving the management of liver transplant candidates to improve survival.

Cuproptosis-Related Signature Predicts the Prognosis, Tumor Microenvironment, and Drug Sensitivity of Hepatocellular Carcinoma

Background

Copper (Cu) metabolism is strongly associated with liver disease. Cuproptosis is a novel format of cell death, and cuproptosis-related genes (CRGs) were identified. However, the role of CRGs in Hepatocellular Carcinoma (HCC) remains unknown.

Method

The mRNA transcriptome profiling data, somatic mutation data, and copy number gene level data of The Cancer Genome Atlas-Liver Hepatocellular Carcinoma project (TCGA-LIHC) were downloaded for subsequent analysis. Molecular characterization analysis of CRGs, including differential gene expression analysis, mutation analysis, copy number variation (CNV) analysis, Kaplan-Meier analysis, and immune regulator prioritization analysis, was implemented. The nonnegative matrix factorization (NMF) approach was used to identify the CRG-related molecular subtypes. Principal component analysis was adopted to verify the robustness and reliability of the molecular subtype. The least absolute shrinkage and selection operator regression analysis was performed to construct the prognostic signature based on differentially expressed genes between molecular subtypes. The survival characteristics of the molecular subtype and the signature were analyzed. The Gene Set Variation Analysis was performed for functional annotation. The immune landscape analysis, including immune checkpoint gene analysis, single sample gene set enrichment analysis, tumor immune dysfunction and exclusion (TIDE) analysis, immune infiltration cell, and tumor mutation burden analysis (TMB), was conducted. The ability of the signature to predict conventional anti-HCC agent responses was evaluated. The signature was validated in the LIRI-JP cohort and the IMvigor210 cohort.

Result

A total of 13 CRGs are differentially expressed between the tumor and normal samples, while the mutation of CRGs in HCC is infrequent. The expression of CRGs is associated with the CNV level. Fourteen CRGs are associated with the prognosis of HCC. Two clusters were identified and HCC patients were divided into 2 groups with a cutoff risk score value of 1.570. HCC patients in the C1 cluster and high-risk have a worse prognosis. The area under the receiver operating characteristic curve for predicting 1-, 2-, and 3-year overall survival is 0.775, 0.768, and 0.757 in the TCGA-LIHC cohort, and 0.811, 0.741, and 0.775 in the LIRI-JP cohort. Multivariate Cox regression analysis indicates that the signature is an independent prognostic factor. Pathways involved in metabolism and gene stability and immune infiltration cells are significantly enriched. Immune checkpoint genes are highly expressed in the C1 cluster. TMB is positively correlated with the risk score. HCC patients in the high-risk group are more likely to benefit from conventional anti-HCC agents and immune checkpoint inhibitor therapies.

Conclusion

The molecular characterization of CRGs in HCC is presented in this study, and a successful prognostic signature for HCC based on the cuproptosis-related molecular subtype was constructed.

Nanotechnology strategies for hepatocellular carcinoma diagnosis and treatment

Hepatocellular carcinoma (HCC) is a common malignancy threatening human health, and existing diagnostic and therapeutic techniques are facing great challenges. In the last decade or so, nanotechnology has been developed and improved for tumor diagnosis and treatment. For example, nano-intravenous injections have been approved for malignant perivascular epithelioid cell tumors. This article provides a comprehensive review of the applications of nanotechnology in HCC in recent years: (I) in radiological imaging, magnetic resonance imaging (MRI), fluorescence imaging (FMI) and multimodality imaging. (II) For diagnostic applications in HCC serum markers. (III) As embolic agents in transarterial chemoembolization (TACE) or directly as therapeutic drugs. (IV) For application in photothermal therapy and photodynamic therapy. (V) As carriers of chemotherapeutic drugs, targeted drugs, and natural plant drugs. (VI) For application in gene and immunotherapy. Compared with the traditional methods for diagnosis and treatment of HCC, nanoparticles have high sensitivity, reduce drug toxicity and have a long duration of action, and can also be combined with photothermal and photodynamic multimodal combination therapy. These summaries provide insights for the further development of nanotechnology applications in HCC.

Ultrasomics prediction for cytokeratin 19 expression in hepatocellular carcinoma: A multicenter study

Objective

The purpose of this study was to investigate the preoperative prediction of Cytokeratin (CK) 19 expression in patients with hepatocellular carcinoma (HCC) by machine learning-based ultrasomics.

Methods

We retrospectively analyzed 214 patients with pathologically confirmed HCC who received CK19 immunohistochemical staining. Through random stratified sampling (ratio, 8:2), patients from institutions I and II were divided into training dataset (n = 143) and test dataset (n = 36), and patients from institution III served as external validation dataset (n = 35). All gray-scale ultrasound images were preprocessed, and then the regions of interest were then manually segmented by two sonographers. A total of 1409 ultrasomics features were extracted from the original and derived images. Next, the intraclass correlation coefficient, variance threshold, mutual information, and embedded method were applied to feature dimension reduction. Finally, the clinical model, ultrasonics model, and combined model were constructed by eXtreme Gradient Boosting algorithm. Model performance was assessed by area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy.

Results

A total of 12 ultrasomics signatures were used to construct the ultrasomics models. In addition, 21 clinical features were used to construct the clinical model, including gender, age, Child-Pugh classification, hepatitis B surface antigen/hepatitis C virus antibody (positive/negative), cirrhosis (yes/no), splenomegaly (yes/no), tumor location, tumor maximum diameter, tumor number, alpha-fetoprotein, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, glutamyl-transpeptidase, albumin, total bilirubin, conjugated bilirubin, creatinine, prothrombin time, fibrinogen, and international normalized ratio. The AUC of the ultrasomics model was 0.789 (0.621 – 0.907) and 0.787 (0.616 – 0.907) in the test and validation datasets, respectively. However, the performance of the combined model covering clinical features and ultrasomics signatures improved significantly. Additionally, the AUC (95% CI), sensitivity, specificity, and accuracy were 0.867 (0.712 – 0.957), 0.750, 0.875, 0.861, and 0.862 (0.703 – 0.955), 0.833, 0.862, and 0.857 in the test dataset and external validation dataset, respectively.

Conclusion

Ultrasomics signatures could be used to predict the expression of CK19 in HCC patients. The combination of clinical features and ultrasomics signatures showed excellent effects, which significantly improved prediction accuracy and robustness.

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

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

Cancer stem cells in hepatocellular carcinoma - from origin to clinical implications

Hepatocellular carcinoma (HCC) is an aggressive disease with a poor clinical outcome. The cancer stem cell (CSC) model states that tumour growth is powered by a subset of tumour stem cells within cancers. This model explains several clinical observations in HCC (as well as in other cancers), including the almost inevitable recurrence of tumours after initial successful chemotherapy and/or radiotherapy, as well as the phenomena of tumour dormancy and treatment resistance. The past two decades have seen a marked increase in research on the identification and characterization of liver CSCs, which has encouraged the design of novel diagnostic and treatment strategies for HCC. These studies revealed novel aspects of liver CSCs, including their heterogeneity and unique immunobiology, which are suggestive of opportunities for new research directions and potential therapies. In this Review, we summarize the present knowledge of liver CSC markers and the regulators of stemness in HCC. We also comprehensively describe developments in the liver CSC field with emphasis on experiments utilizing single-cell transcriptomics to understand liver CSC heterogeneity, lineage-tracing and cell-ablation studies of liver CSCs, and the influence of the CSC niche and tumour microenvironment on liver cancer stemness, including interactions between CSCs and the immune system. We also discuss the potential application of liver CSC-based therapies for treatment of HCC.

[Up-to-date Knowledge on the Pathological Diagnosis of Hepatocellular Carcinoma]

Hepatocellular carcinoma (HCC) has heterogeneous molecular and pathological features and biological behavior. Large-scale genetic studies of HCC were accumulated, and a pathological-molecular classification of HCC was proposed. Approximately 35% of HCCs can be classified into distinct histopathological subtypes according to their molecular characteristics. Among recently identified subtypes, macrotrabecular massive HCC, neutrophil-rich HCC, vessels encapsulating tumor clusters HCC, and progenitor phenotype HCC (HCC with CK19 expression) are associated with a poor prognosis, whereas the lymphocyte-rich HCC subtype is related to a better prognosis. This review provides up-to-date knowledge on the pathological diagnosis of HCC according to the updated World Health Organization Classification of Digestive System Tumors 5th ed.

Combined proteomic/transcriptomic signature of recurrence post-liver transplantation for hepatocellular carcinoma beyond Milan

Background and aims

Liver transplantation (LT) can be offered to patients with Hepatocellular carcinoma (HCC) beyond Milan criteria. However, there are currently limited molecular markers on HCC explant histology to predict recurrence, which arises in up to 20% of LT recipients. The goal of our study was to derive a combined proteomic/transcriptomic signature on HCC explant predictive of recurrence post-transplant using unbiased, high-throughput approaches.

Methods

Patients who received a LT for HCC beyond Milan criteria in the context of hepatitis B cirrhosis were identified. Tumor explants from patients with post-transplant HCC recurrence (N = 7) versus those without recurrence (N = 4) were analyzed by mass spectrometry and gene expression array. Univariate analysis was used to generate a combined proteomic/transcriptomic signature linked to recurrence. Significantly predictive genes and proteins were verified and internally validated by immunoblotting and immunohistochemistry.

Results

Seventy-nine proteins and 636 genes were significantly differentially expressed in HCC tumors with subsequent recurrence (p < 0.05). Univariate survival analysis identified Aldehyde Dehydrogenase 1 Family Member A1 (ALDH1A1) gene (HR = 0.084, 95%CI 0.01–0.68, p = 0.0152), ALDH1A1 protein (HR = 0.039, 95%CI 0.16–0.91, p = 0.03), Galectin 3 Binding Protein (LGALS3BP) gene (HR = 7.14, 95%CI 1.20–432.96, p = 0.03), LGALS3BP protein (HR = 2.6, 95%CI 1.1–6.1, p = 0.036), Galectin 3 (LGALS3) gene (HR = 2.89, 95%CI 1.01–8.3, p = 0.049) and LGALS3 protein (HR = 2.6, 95%CI 1.2–5.5, p = 0.015) as key dysregulated analytes in recurrent HCC. In concordance with our proteome findings, HCC recurrence was linked to decreased ALDH1A1 and increased LGALS3 protein expression by Western Blot. LGALS3BP protein expression was validated in 29 independent HCC samples.

Conclusions

Significantly increased LGALS3 and LGALS3BP gene and protein expression on explant were associated with post-transplant recurrence, whereas increased ALDH1A1 was associated with absence of recurrence in patients transplanted for HCC beyond Milan criteria. This combined proteomic/transcriptomic signature could help in predicting HCC recurrence risk and guide post-transplant surveillance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-021-09333-x.

The distinct responsiveness of cytokeratin 19-positive hepatocellular carcinoma to regorafenib

Cytokeratin 19-positive (CK19+) hepatocellular carcinoma (HCC) is an aggressive subtype characterized by early recurrence and chemotherapy tolerance. However, there is no specific therapeutic option for CK19+ HCC. The correlation between tumor recurrence and expression status of CK19 were studied in 206 patients undergoing liver transplantation for HCC. CK19-/+ HCC cells were isolated to screen effective antitumor drugs. The therapeutic effects of regorafenib were evaluated in patient-derived xenograft (PDX) models from 10 HCC patients. The mechanism of regorafenib on CK19+ HCC was investigated. CK19 positiveness indicated aggressiveness of tumor and higher recurrence risk of HCC after liver transplantation. The isolated CK19+ HCC cells had more aggressive behaviors than CK19- cells. Regorafenib preferentially increased the growth inhibition and apoptosis of CK19+ cells in vitro, whereas sorafenib, apatinib, and 5-fluorouracil did not. In PDX models from CK19-/+ HCC patients, the tumor control rate of regorafenib achieved 80% for CK19+ HCCs, whereas 0% for CK19- HCCs. RNA-sequencing revealed that CK19+ cells had elevated expression of mitochondrial ribosomal proteins, which are essential for mitochondrial function. Further experiments confirmed that regorafenib attenuated the mitochondrial respiratory capacity in CK19+ cells. However, the mitochondrial respiration in CK19- cells were faint and hardly repressed by regorafenib. The mitochondrial respiration was regulated by the phosphorylation of signal transducer and activator of transcription 3 (STAT3), which was inhibited by regorafenib in CK19+ cells. Hence, CK19 could be a potential marker of the therapeutic benefit of regorafenib, which facilitates the individualized therapy for HCC. STAT3/mitochondria axis determines the distinct response of CK19+ cells to regorafenib treatment.

Molecular classification of hepatocellular carcinoma: prognostic importance and clinical applications

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

MRI-Radiomics Prediction for Cytokeratin 19-Positive Hepatocellular Carcinoma: A Multicenter Study

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and has poor prognosis. Cytokeratin (CK)19-positive (CK19+) HCC is especially aggressive; early identification of this subtype and timely intervention can potentially improve clinical outcomes. In the present study, we developed a preoperative gadoxetic acid-enhanced magnetic resonance imaging (MRI)-based radiomics model for noninvasive and accurate classification of CK19+ HCC. A multicenter and time-independent cohort of 257 patients were retrospectively enrolled (training cohort, n = 143; validation cohort A, n = 75; validation cohort B, n = 39). A total of 968 radiomics features were extracted from preoperative multisequence MR images. The maximum relevance minimum redundancy algorithm was applied for feature selection. Multiple logistic regression, support vector machine, random forest, and artificial neural network (ANN) algorithms were used to construct the radiomics model, and the area under the receiver operating characteristic (AUROC) curve was used to evaluate the diagnostic performance of corresponding classifiers. The incidence of CK19+ HCC was significantly higher in male patients. The ANN-derived combined classifier comprising 12 optimal radiomics features showed the best diagnostic performance, with AUROCs of 0.857, 0.726, and 0.790 in the training cohort and validation cohorts A and B, respectively. The combined model based on multisequence MRI radiomics features can be used for preoperative noninvasive and accurate classification of CK19+ HCC, so that personalized management strategies can be developed.

Peritumoral Dilation Radiomics of Gadoxetate Disodium-Enhanced MRI Excellently Predicts Early Recurrence of Hepatocellular Carcinoma without Macrovascular Invasion After Hepatectomy

Background

Whether peritumoral dilation radiomics can excellently predict early recrudescence (≤2 years) in hepatocellular carcinoma (HCC) remains unclear.

Methods

Between March 2012 and June 2018, 323 pathologically confirmed HCC patients without macrovascular invasion, who underwent liver resection and preoperative gadoxetate disodium (Gd-EOB-DTPA) MRI, were consecutively recruited into this study. Multivariate logistic regression identified independent clinicoradiologic predictors of 2-year recrudescence. Peritumoral dilation (tumor and peritumoral zones within 1cm) radiomics extracted features from 7-sequence images for modeling and achieved average but robust predictive performance through 5-fold cross validation. Independent clinicoradiologic predictors were then incorporated with the radiomics model for constructing a comprehensive nomogram. The predictive discrimination was quantified with the area under the receiver operating characteristic curve (AUC) and net reclassification improvement (NRI).

Results

With the median recurrence-free survival (RFS) reaching 60.43 months, 28.2% (91/323) and 16.4% (53/323) patients suffered from early and delay relapse, respectively. Microvascular invasion, tumor size >5 cm, alanine aminotransferase >50 U/L, γ-glutamyltransferase >60 U/L, prealbumin ≤250 mg/L, and peritumoral enhancement independently impaired 2-year RFS in the clinicoradiologic model with AUC of 0.694 (95% CI 0.628–0.760). Nevertheless, these indexes were paucity of robustness (P >0.05) when integrating with 38 most recurrence-related radiomics signatures for developing the comprehensive nomogram. The peritumoral dilation radiomics—the ultimate prediction model yielded satisfactory mean AUCs (training cohort: 0.939, 95% CI 0.908–0.973; validation cohort: 0.842, 95% CI 0.736–0.951) after 5-fold cross validation and fitted well with the actual relapse status in the calibration curve. Besides, our radiomics model obtained the best clinical net benefits, with significant improvements of NRI (35.9%-66.1%, P <0.001) versus five clinical algorithms: the clinicoradiologic model, the tumor-node-metastasis classification, the Barcelona Clinic Liver Cancer stage, the preoperative and postoperative risks of Early Recurrence After Surgery for Liver tumor.

Conclusion

Gd-EOB-DTPA MRI-based peritumoral dilation radiomics is a potential preoperative biomarker for early recurrence of HCC patients without macrovascular invasion.

HNF-1β is a More Sensitive and Specific Marker Than C-Reactive Protein for Identifying Biliary Differentiation in Primary Hepatic Carcinomas

CONTEXT.—

Intrahepatic cholangiocarcinoma (iCCA) needs to be distinguished from hepatocellular carcinoma (HCC) and metastasis, and in the absence of any specific biliary markers, is often a diagnosis of exclusion. Hepatocyte nuclear factor (HNF)-1β is a transcription factor that plays a critical role in bile duct system morphogenesis.

OBJECTIVE.—

To investigate the diagnostic value of HNF-1β to differentiate iCCA from HCC by immunohistochemistry and compare HNF-1β with C-reactive protein (CRP), a previously identified marker for iCCA.

DESIGN.—

Cases of iCCA (n = 75), combined hepatocellular-cholangiocarcinoma (cHCC-CCA) (n = 13) and HCC (n = 65) were included in the study.

RESULTS.—

All cases of iCCA (74 of 74, 100%) expressed HNF-1β compared with CRP expressed in 72.60% (53 of 73). The sensitivity and specificity of HNF-1β to differentiate iCCA from HCC was 100% and 92.31%, whereas the sensitivity and specificity for CRP was 75.58% and 7.79%. The expression of HNF-1β was greater in iCCA and the CCA component of cHCC-CCA compared with CRP (87 of 87, 100% versus 65 of 86, 75.58%, P < .001). On the contrary, CRP was more frequently expressed compared with HNF-1β in HCC and HCC component of cHCC-CCA (71 of 77, 92.21% versus 6 of 78, 7.69%; P < .001).

CONCLUSIONS.—

Our data indicate that HNF-1β is a more sensitive and specific marker than CRP for the diagnosis of iCCA and to identify the CCA component in cHCC-CCA. Lack of HNF-1β expression may be used to exclude iCCA from consideration in cases of adenocarcinomas of unknown primary.

Combined identification of ARID1A, CSMD1, and SENP3 as effective prognostic biomarkers for hepatocellular carcinoma

Background: The current study aimed to understand the genetic landscape and investigate the diagnostic and prognostic biomarkers of primary hepatocellular carcinoma (HCC).

Methods: A cohort of 36 Chinese HCC samples with hepatitis B virus (HBV) infection was examined by whole-exome sequencing (WES). Prognosis-related alterations were identified and further verified in the TCGA database and GSE65372 profiles in the GEO database. A Chinese replication cohort of 180 HCC samples with HBV infection was collected to evaluate the candidate genes by immunohistochemical analysis. A receiver operating characteristic (ROC) curve analysis evaluated the prognostic power of candidate genes. Finally, EdU and transwell invasion assay were performed to detect the function of candidate genes.

Results: A total of 11 novel genes showed a significant association with HCC in the discovery cohort. The data were verified using the GEO and TCGA databases, and the expression of ARID1A, CSMD1, and SENP was evaluated in the replication cohort. Furthermore, ARID1A, CSMD1, and SENP3 are effective prognostic biomarkers for HCC patients in the replication population.

Conclusions: Molecular heterogeneity was detected in HCC patients, and ARID1A, CSMD1, and SENP3 were identified as effective HCC prognosis biomarkers. CSMD1 prevents HCC by suppressing cell invasion.

Hepatocellular carcinoma

Liver cancer remains a global health challenge, with an estimated incidence of >1 million cases by 2025. Hepatocellular carcinoma (HCC) is the most common form of liver cancer and accounts for ~90% of cases. Infection by hepatitis B virus and hepatitis C virus are the main risk factors for HCC development, although non-alcoholic steatohepatitis associated with metabolic syndrome or diabetes mellitus is becoming a more frequent risk factor in the West. Moreover, non-alcoholic steatohepatitis-associated HCC has a unique molecular pathogenesis. Approximately 25% of all HCCs present with potentially actionable mutations, which are yet to be translated into the clinical practice. Diagnosis based upon non-invasive criteria is currently challenged by the need for molecular information that requires tissue or liquid biopsies. The current major advancements have impacted the management of patients with advanced HCC. Six systemic therapies have been approved based on phase III trials (atezolizumab plus bevacizumab, sorafenib, lenvatinib, regorafenib, cabozantinib and ramucirumab) and three additional therapies have obtained accelerated FDA approval owing to evidence of efficacy. New trials are exploring combination therapies, including checkpoint inhibitors and tyrosine kinase inhibitors or anti-VEGF therapies, or even combinations of two immunotherapy regimens. The outcomes of these trials are expected to change the landscape of HCC management at all evolutionary stages.

Multi-scale and multi-parametric radiomics of gadoxetate disodium-enhanced MRI predicts microvascular invasion and outcome in patients with solitary hepatocellular carcinoma ≤ 5 cm

Objectives

To develop radiomics-based nomograms for preoperative microvascular invasion (MVI) and recurrence-free survival (RFS) prediction in patients with solitary hepatocellular carcinoma (HCC) ≤ 5 cm.

Methods

Between March 2012 and September 2019, 356 patients with pathologically confirmed solitary HCC ≤ 5 cm who underwent preoperative gadoxetate disodium–enhanced MRI were retrospectively enrolled. MVI was graded as M0, M1, or M2 according to the number and distribution of invaded vessels. Radiomics features were extracted from DWI, arterial, portal venous, and hepatobiliary phase images in regions of the entire tumor, peritumoral area ≤ 10 mm, and randomly selected liver tissue. Multivariate analysis identified the independent predictors for MVI and RFS, with nomogram visualized the ultimately predictive models.

Results

Elevated alpha-fetoprotein, total bilirubin and radiomics values, peritumoral enhancement, and incomplete or absent capsule enhancement were independent risk factors for MVI. The AUCs of MVI nomogram reached 0.920 (95% CI: 0.861–0.979) using random forest and 0.879 (95% CI: 0.820–0.938) using logistic regression analysis in validation cohort (n = 106). With the 5-year RFS rate of 68.4%, the median RFS of MVI-positive (M2 and M1) and MVI-negative (M0) patients were 30.5 (11.9 and 40.9) and > 96.9 months (p < 0.001), respectively. Age, histologic MVI, alkaline phosphatase, and alanine aminotransferase independently predicted recurrence, yielding AUC of 0.654 (95% CI: 0.538–0.769, n = 99) in RFS validation cohort. Instead of histologic MVI, the preoperatively predicted MVI by MVI nomogram using random forest achieved comparable accuracy in MVI stratification and RFS prediction.

Conclusions

Preoperative radiomics-based nomogram using random forest is a potential biomarker of MVI and RFS prediction for solitary HCC ≤ 5 cm.

Key Points

• The radiomics score was the predominant independent predictor of MVI which was the primary independent risk factor for postoperative recurrence.

• The radiomics-based nomogram using either random forest or logistic regression analysis has obtained the best preoperative prediction of MVI in HCC patients so far.

• As an excellent substitute for the invasive histologic MVI, the preoperatively predicted MVI by MVI nomogram using random forest (MVI-RF) achieved comparable accuracy in MVI stratification and outcome, reinforcing the radiologic understanding of HCC angioinvasion and progression.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-020-07601-2.

Recurrence of hepatocellular carcinoma following liver transplantation

INTRODUCTION

Hepatocellular carcinoma (HCC) is an increasingly common disease with liver transplant (LT) the best long-term therapy for early stage disease. We will review the data for assessing risk and managing recurrence for patients undergoing LT for HCC.

AREAS COVERED

In this review, we will provide an overview of methods of patient risk stratification in the post-transplant period, the data around surveillance for HCC recurrence, and the evidence for and against post-LT adjuvant treatment strategies. Finally, we will provide data regarding treatment options for patients with HCC recurrence after LT. Using an extensive search of original papers and society guidelines, this paper provides a comprehensive review of the data for assessing risk and managing recurrence for patients undergoing LT for HCC.

EXPERT OPINION

The development of multiple post-transplant prognostic scoring systems have allowed for improved assessment of recurrence risk and stratification of patients. However, the ability to translate this information into surveillance and therapeutic strategies that improve patient outcomes still have to be fully demonstrated. Post-LT immunosuppression strategies have been implemented in order to attempt to reduce this risk. Evidence-based strategies for managing recurrent HCC are evolving. We expect that with further understanding of individual patient characteristics will allow for optimal therapeutic selection.

Clinico-Radio-Pathological and Molecular Features of Hepatocellular Carcinomas with Keratin 19 Expression

Hepatocellular carcinoma (HCC) is a heterogeneous neoplasm, both from the molecular and histomorphological aspects. One example of heterogeneity is the expression of keratin 19 (K19) in a subset (4-28%) of HCCs. The presence of K19 expression in HCCs has important clinical implications, as K19-positive HCCs have been associated with aggressive tumor biology and poor prognosis. Histomorphologically, K19-positive HCCs demonstrate a more infiltrative appearance, poor histological differentiation, more frequent vascular invasion, and more intratumoral fibrous stroma than K19-negative conventional HCCs. From the molecular aspect, K19-positive HCCs have been matched with various gene signatures that have been associated with stemness and poor prognosis, including the G1-3 groups, S2 class, cluster A, proliferation signature, and vascular invasion signature. K19-positive HCCs also show upregulated signatures related to transforming growth factor-β pathway and epithelial-to-mesenchymal transition. The main regulators of K19 expression include hepatocyte growth factor-MET paracrine signaling by cancer-associated fibroblast, epidermal growth factor-epidermal growth factor receptor signaling, laminin, and DNA methylation. Clinically, higher serum alpha-fetoprotein levels, frequent association with chronic hepatitis B, more invasive growth, and lymph node metastasis have been shown to be characteristics of K19-positive HCCs. Radiologic features including atypical enhancement patterns, absence of tumor capsules, and irregular tumor margins can be a clue for K19-positive HCCs. From a therapeutic standpoint, K19-positive HCCs have been associated with poor outcomes after curative resection or liver transplantation, and resistance to systemic chemotherapy and locoregional treatment, including transarterial chemoembolization and radiofrequency ablation. In this review, we summarize the currently available knowledge on the clinico-radio-pathological and molecular features of K19-expressing HCCs, including a detailed discussion on the regulation mechanism of these tumors.

Molecular subtyping of hepatocellular carcinoma: A step toward precision medicine

Hepatocellular carcinoma (HCC) is one of the most prevalent and fatal digestive tumors. Treatment for this disease has been constraint by heterogeneity of this group of tumors, which has greatly limited the progress in personalized therapy. Although existing studies have revealed the genetic and epigenetic blueprints that drive HCCs, many of the molecular mechanisms that lead to HCCs remain elusive. Recent advances in techniques for studying functional genomics, such as genome sequencing and transcriptomic analyses, have led to the discovery of molecular mechanisms that participate in the initiation and evolution of HCC. Integrative multi-omics analyses have identified several molecular subtypes of HCC associated with specific molecular characteristics and clinical outcomes. Deciphering similar molecular features among highly heterogeneous HCC patients is a prerequisite to implementation of personalized therapeutics. This review summarizes the current research progresses in precision therapy on the backbone of molecular subtypes of HCC.

Hepatocellular Carcinoma: Role of Pathology in the Era of Precision Medicine

Hepatocellular carcinoma (HCC) is a morphologically heterogeneous tumor with variable architectural growth patterns and several distinct histologic subtypes. Large-scale attempts have been made over the past decade to identify targetable genomic alterations in HCC; however, its translation into clinical personalized care remains a challenge to precision oncology. The role of pathology is no longer limited to confirmation of diagnosis when radiologic features are atypical. Pathology is now in a position to predict the underlying molecular alteration, prognosis, and behavior of HCC. This review outlines various aspects of histopathologic diagnosis and role of pathology in cutting-edge diagnostics of HCC.

Association between Genetic and Immunological Background of Hepatocellular Carcinoma and Expression of Programmed Cell Death-1

Background and Aim

Immune checkpoint inhibitors are promising agents for the treatment of hepatocellular carcinomas (HCC) refractory to conventional therapies. To enhance the efficacy of this treatment, immunological and molecular characteristics of HCC with programmed cell death ligand 1 (PD-L1) should be explored.

Methods

Clinical backgrounds, PD-L1 expression, and the amount of CD8+ tumor-infiltrating mononuclear cells (TIMCs) were analyzed in 154 HCCs. The expression of 3 stem cell markers and co-inhibitory receptors on tumor cells and TIMCs, respectively, were examined by immunohistochemical analysis. Somatic mutations in the 409 cancer-associated genes and TERT promoter were determined; HCCs were classified based on the presence of gene alterations affecting the 8 oncogenic pathways. The results were validated using the dataset from the Cancer Genome Atlas.

Results

The expression of PD-L1 in the HCCs was positively correlated with progressive tumor features, the presence of cytokeratin 19 (CK19), Sal-like protein 4 (SALL4), and the mutations of genes involving the phosphatidyl inositol 3-kinase (PI3K)-Akt pathway. Although CD8+ cells were densely infiltrated in PD-L1-positive tumors, these TIMCs frequently expressed multiple co-inhibitory receptors. However, a subset of PD-L1-positive tumors characterized by activating mutations of the PI3K-Akt pathway showed a low degree of TIMCs. Conversely, PD-L1-negative HCCs were associated with mutations in the β-catenin pathway and a small number of TIMCs, although the expression of co-inhibitory receptors was rare.

Conclusions

PD-L1-positive HCCs frequently showed an inflamed phenotype with stem cell features; a subset of PD-L1-positive HCCs with mutations in the PI3K-Akt pathway showed a non-inflamed phenotype. In HCCs with dense infiltration of TIMCs, CD8+ cells expressed multiple co-inhibitory receptors, suggesting T cell exhaustion. On the other hand, PD-L1-negative HCCs showed mutations leading to β-catenin activation and exhibited a non-inflamed background. These characteristics should be taken into consideration for developing novel combination therapies using immune checkpoint inhibitors.

Association between Genetic and Immunological Background of Hepatocellular Carcinoma and Expression of Programmed Cell Death-1

BACKGROUND AND AIM

Immune checkpoint inhibitors are promising agents for the treatment of hepatocellular carcinomas (HCC) refractory to conventional therapies. To enhance the efficacy of this treatment, immunological and molecular characteristics of HCC with programmed cell death ligand 1 (PD-L1) should be explored.

METHODS

Clinical backgrounds, PD-L1 expression, and the amount of CD8+ tumor-infiltrating mononuclear cells (TIMCs) were analyzed in 154 HCCs. The expression of 3 stem cell markers and co-inhibitory receptors on tumor cells and TIMCs, respectively, were examined by immunohistochemical analysis. Somatic mutations in the 409 cancer-associated genes and TERT promoter were determined; HCCs were classified based on the presence of gene alterations affecting the 8 oncogenic pathways. The results were validated using the dataset from the Cancer Genome Atlas.

RESULTS

The expression of PD-L1 in the HCCs was positively correlated with progressive tumor features, the presence of cytokeratin 19 (CK19), Sal-like protein 4 (SALL4), and the mutations of genes involving the phosphatidyl inositol 3-kinase (PI3K)-Akt pathway. Although CD8+ cells were densely infiltrated in PD-L1-positive tumors, these TIMCs frequently expressed multiple co-inhibitory receptors. However, a subset of PD-L1-positive tumors characterized by activating mutations of the PI3K-Akt pathway showed a low degree of TIMCs. Conversely, PD-L1-negative HCCs were associated with mutations in the β-catenin pathway and a small number of TIMCs, although the expression of co-inhibitory receptors was rare.

CONCLUSIONS

PD-L1-positive HCCs frequently showed an inflamed phenotype with stem cell features; a subset of PD-L1-positive HCCs with mutations in the PI3K-Akt pathway showed a non-inflamed phenotype. In HCCs with dense infiltration of TIMCs, CD8+ cells expressed multiple co-inhibitory receptors, suggesting T cell exhaustion. On the other hand, PD-L1-negative HCCs showed mutations leading to β-catenin activation and exhibited a non-inflamed background. These characteristics should be taken into consideration for developing novel combination therapies using immune checkpoint inhibitors.

CK19-positive Hepatocellular Carcinoma is a Characteristic Subtype

The heterogeneity of hepatocellular carcinoma (HCC) commonly leads to therapeutic failure of HCC. Cytokeratin 19 (CK19) is well acknowledged as a biliary/progenitor cell marker and a marker of tumor stem cell. CK19-positive HCCs demonstrate aggressive behaviors and poor outcomes which including worse overall survival and early tumor recurrence after hepatectomy and liver transplantation. CK19-positive HCCs are resistant to chemotherapies as well as local treatment. This subset of HCC is thought to derive from liver progenitor cells and can be induced by extracellular stimulation such as hypoxia. Besides being a stemness marker, CK19 plays an important role in promoting malignant property of HCC. The regulatory network associated with CK19 expression has been summarized that extracellular stimulations which transmit into cytoplasm through signal transduction pathways (TGF-β, MAKP/JNK and MEK-ERK1/2), further induce important nuclear transcriptional factors (SALL4, AP1, SP1) to activate CK19 promoter. Novel noncoding RNAs are also involved in the regulation of CK19 expression. TGFβR1 becomes a therapeutic target for CK19-positive HCC. In conclusion, CK19 can be a potential biomarker for predicting poor prognosis after surgical and adjuvant therapies. CK19-pisitive HCCs exhibit distinctive molecular profiling, should be diagnosed and treated as a separate subtype of HCCs.

Role of Molecular Biomarkers in Liver Transplantation for Hepatocellular Carcinoma

Patient selection and organ allocation for liver transplantation (LT) in patients with hepatocellular carcinoma (HCC) relies predominantly on clinical parameters, such as tumor burden (ie, radiological imaging). Patients transplanted within Milan criteria have outstanding outcomes with a 5- and 10-year survival of 70% and 55%, respectively. Tumor recurrence after transplantion is rare in these patients (10%); however, treatment options upon recurrence are generally limited, and outcomes are poor. There are also several studies showing how a subgroup of patients with tumors outside the Milan criteria might achieve comparable outcomes to patients within Milan criteria. In other words, the size and number of tumor nodules does not always reflect tumor biology, which could be better captured using molecular proxies for cancer aggressiveness. Over the last decade, we have significantly improved our understanding of the molecular landscape of early stage HCC. This includes the development of molecular classification, identification of prognostic and mutational signatures, and potential mechanisms of hepatocarcinogenesis. Some molecular markers have already proven useful to predict tumor-related outcomes in HCC patients after LT. Most of these analyses are limited to tissue-derived biomarkers, which limits their implementation in clinical practice because tissue biopsy is not required for HCC diagnosis. Minimally invasive alternative tools, such as liquid biopsy, are being increasingly explored and could help to individualize risk stratification for patients with HCC who will benefit from LT despite being outside the accepted clinical criteria.

Liver transplantation for hepatocellular carcinoma: Management after the transplant

Hepatocellular carcinoma (HCC) is an increasingly common indication for liver transplantation (LT) in the United States and in many parts of the world. In the last decade, significant work has been done to better understand how to risk stratify LT candidates for recurrence of HCC following transplant using a combination of biomarker and imaging findings. However, despite the high frequency of HCC in the LT population, guidance regarding posttransplant management is lacking. In particular, there is no current evidence to support specific post-LT surveillance strategies, leading to significant heterogeneity in practices. In addition, there are no current recommendations regarding recurrence prevention, including immunosuppression regimen or secondary prevention with adjuvant chemotherapy. Finally, guidance on treatment of disease recurrence is also lacking and there is significant controversy about the use of immunotherapy in transplant recipients due to the risk of rejection. Thus, outcomes for patients with recurrence are poor. This paper therefore provides a comprehensive review of the current literature on post-LT management of patients with HCC and identifies gaps in our current knowledge that are in urgent need of further investigation.

A Point-based Histologic Scoring System for Hepatocellular Carcinoma Can Stratify Risk of Posttransplant Tumor Recurrence

Eligibility for liver transplant is most commonly decided by measuring tumor size and number on radiographic imaging. However, this method often underestimates the extent of disease. Evaluation of tumor histology has been shown to improve risk stratification when compared with imaging-based transplant criteria, but the World Health Organization (WHO) guidelines for grading hepatocellular carcinoma (HCC) are imprecise and require subjective interpretation by the pathologist. We performed a retrospective analysis of 190 explanted livers containing HCC and correlated histologic features with posttransplant recurrence to formulate a three-tiered, point-based scoring system that categorizes tumors as having a low, intermediate, or high risk of recurrence. Our Recurrence Risk Assessment Score (RRAS) evaluates tumor architecture and specific cytologic features-nuclear pleomorphism, cytoplasmic amphophilia, and nuclear-to-cytoplasmic ratio-showing superior stratification of HCC recurrence risk compared with imaging criteria and grade assigned by WHO methodology. Stratifying tumors using RRAS criteria, the rate of recurrence after transplant was 0% among low-risk tumors (compared with 3% of well-differentiated tumors), 12% among intermediate-risk tumors (compared with 15% of moderately differentiated tumors), and 54% among high-risk tumors (compared with 29% of poorly differentiated tumors). Receiver operating characteristic analysis shows significantly improved performance of RRAS criteria in predicting HCC recurrence compared with WHO grade (area under curve of 0.841 and 0.671, respectively; P=0.0061). Our results indicate that evaluation of tumor histology offers superior prediction of recurrence risk following liver transplantation compared with radiographic criteria, and that the RRAS system better stratifies recurrence risk compared with HCC grading by WHO methodology.

Dimensions of hepatocellular carcinoma phenotypic diversity

Hepatocellular carcinoma (HCC) is the 3^rd leading cause of cancer-related death worldwide. More than 80% of HCCs arise within chronic liver disease resulting from viral hepatitis, alcohol, hemochromatosis, obesity and metabolic syndrome or genotoxins. Projections based on Western lifestyle and its metabolic consequences anticipate a further increase in incidence, despite recent breakthroughs in the management of viral hepatitis. HCCs display high heterogeneity of molecular phenotypes, which challenges clinical management. However, emerging molecular classifications of HCCs have not yet formed a unified corpus translatable to the clinical practice. Thus, patient management is currently based upon tumor number, size, vascular invasion, performance status and functional liver reserve. Nonetheless, an impressive body of molecular evidence emerged within the last 20 years and is becoming increasingly available to medical practitioners and researchers in the form of repositories. Therefore, the aim this work is to review molecular data underlying HCC classifications and to organize this corpus into the major dimensions explaining HCC phenotypic diversity. Major efforts have been recently made worldwide toward a unifying “clinically-friendly” molecular landscape. As a result, a consensus emerges on three major dimensions explaining the HCC heterogeneity. In the first dimension, tumor cell proliferation and differentiation enabled allocation of HCCs to two major classes presenting profoundly different clinical aggressiveness. In the second dimension, HCC microenvironment and tumor immunity underlie recent therapeutic breakthroughs prolonging patients’ survival. In the third dimension, metabolic reprogramming, with the recent emergence of subclass-specific metabolic profiles, may lead to adaptive and combined therapeutic approaches. Therefore, here we review recent molecular evidence, their impact on tumor histopathological features and clinical behavior and highlight the remaining challenges to translate our cognitive corpus into patient diagnosis and allocation to therapeutic options.

Novel tumor suppressor SPRYD4 inhibits tumor progression in hepatocellular carcinoma by inducing apoptotic cell death

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-associated deaths worldwide. Although recent studies have proposed different biomarkers for HCC progression and therapy resistance, a better understanding of the molecular mechanisms underlying HCC progression and recurrence, as well as the identification of molecular markers with a higher diagnostic accuracy, are necessary for the development of more effective clinical management strategies. Here, we aimed to identify novel players in HCC progression.

METHODS

SPRYD4 mRNA and protein expression analyses were carried out on a normal liver-derived cell line (HL-7702) and four HCC-derived cell lines (HepG2, SMMC7721, Huh-7, BEL-7402) using qRT-PCR and Western blotting, respectively. Cell proliferation Cell Counting Kit-8 (CCK-8) assays, protein expression analyses for apoptosis markers using Western blotting, and Caspase-Glo 3/7 apoptosis assays were carried out on the four HCC-derived cell lines. Expression comparison, functional annotation, gene set enrichment, correlation and survival analyses were carried out on patient data retrieved from the NCBI Gene module, the NCBI GEO database and the TCGA database.

RESULTS

Through a meta-analysis we found that the expression of SPRYD4 was downregulated in primary HCC tissues compared to non-tumor tissues. We also found that the expression of SPRYD4 was downregulated in HCC-derived cells compared to normal liver-derived cells. Subsequently, we found that the expression of SPRYD4 was inversely correlated with a gene signature associated with HCC cell proliferation. Exogenous SPRYD4 expression was found to inhibit HCC cell proliferation by inducing apoptotic cell death. We also found that SPRYD4 expression was associated with a good prognosis and that its expression became downregulated when HCCs progressed towards more aggressive stages and higher grades. Finally, we found that SPRYD4 expression may serve as a biomarker for a good overall and relapse-free survival in HCC patients.

CONCLUSIONS

Our data indicate that a decreased SPRYD4 expression may serve as an independent predictor for a poor prognosis in patients with HCC and that increased SPRYD4 expression may reduce HCC growth and progression through the induction of apoptotic cell death, thereby providing a potential therapeutic target.

Expansion of the hepatocellular carcinoma Milan criteria in liver transplantation: Future directions

Milan criteria are currently the benchmark related to liver transplantation (LT) for hepatocellular carcinoma. However, several groups have proposed different expanded criteria with acceptable results. In this article, we review the current status of LT beyond the Milan criteria in three different scenarios-expanded criteria with cadaveric LT, downstaging to Milan criteria before LT, and expansion in the context of adult living donor LT. The review focuses on three main questions: what would the impact of the expansion beyond Milan criteria be on the patients on the waiting list; whether the dichotomous criteria (yes/no) currently used are appropriate for LT or continuous survival estimations, such as the one of “Metroticket” and whether it should enter into the clinical practice; and, whether the use of living donor LT in the context of expansion beyond Milan criteria is justified.

Keratin 19 Expression in Hepatocellular Carcinoma Is Regulated by Fibroblast-Derived HGF via a MET-ERK1/2-AP1 and SP1 Axis

Keratin (KRT) 19 is a poor prognostic marker for hepatocellular carcinoma (HCC); however, regulatory mechanisms underlying its expression remain unclear. We have previously reported the presence of fibrous tumor stroma in KRT19-positive HCC, suggesting that cross-talk between cancer-associated fibroblasts (CAF) and tumor epithelial cells could regulate KRT19 expression. This was investigated in this study using an in vitro model of paracrine interaction between HCC cell lines (HepG2, SNU423) and hepatic stellate cells (HSC), a major source of hepatic myofibroblasts. HSCs upregulated transcription and translation of KRT19 in HCC cells via paracrine interactions. Mechanistically, hepatocyte growth factor (HGF) from HSCs activated c-MET and the MEK-ERK1/2 pathway, which upregulated KRT19 expression in HCC cells. Furthermore, AP1 (JUN/FOSL1) and SP1, downstream transcriptional activators of ERK1/2, activated KRT19 expression in HCC cells. In clinical specimens of human HCC (n = 339), HGF and KRT19 protein expression correlated with CAF levels. In addition, HGF or MET protein expression was associated with FOSL1 and KRT19 expression and was found to be a poor prognostic factor. Analysis of data from The Cancer Genome Atlas also revealed KRT19 expression was closely associated with CAF and MET-mediated signaling activities. These results provide insights into the molecular background of KRT19-positive HCC that display an aggressive phenotype.Significance: These findings reveal KRT19 expression in hepatocellular carcinoma is regulated by cross-talk between cancer-associated fibroblasts and HCC cells, illuminating new therapeutic targets for this aggressive disease. Cancer Res; 78(7); 1619-31. ©2018 AACR.

Pilot study of living donor liver transplantation for patients with hepatocellular carcinoma exceeding Milan Criteria (Barcelona Clinic Liver Cancer extended criteria)

A subset of patients with hepatocellular carcinoma (HCC) beyond Milan criteria might obtain acceptable survival outcomes after liver transplantation. Living donor liver transplantation (LDLT) has emerged as a feasible alternative to overcome the paucity of donors. In 2001, we started a protocol for LDLT in Child A-B patients with HCC fulfilling a set of criteria-the Barcelona Clinic Liver Cancer (BCLC) expanded criteria-that expanded the conventional indications of transplantation: 1 tumor ≤ 7 cm, 5 tumors ≤ 3 cm, and 3 tumors ≤ 5 cm without macrovascular invasion or downstaging to Milan after locoregional therapies. We present a prospective cohort of 22 patients with BCLC extended indications based on size/number (n = 17) or downstaging (n = 5) treated with LDLT between 2001 and 2014. Characteristics of the patients were as follows: median age, 57 years old; males/female, n = 20/2; Child-Pugh A/B, n = 16/6; and alpha fetoprotein < 100 ng/mL, n = 21. Twelve patients received neoadjuvant locoregional therapies. At the time of transplantation, 12 patients had HCC staging beyond Milan criteria and 10 within. Pathological reports showed that 50% exceeded BCLC expanded criteria. Perioperative mortality was 0%. After a median follow-up of 81 months, the 1-, 3-, 5-, and 10-year survival was 95.5%, 86.4%, 80.2%, and 66.8%, respectively. Overall, 7 patients recurred (range, 9-108 months), and the 5-year and 10-year actuarial recurrence rates were 23.8% and 44.4%, respectively. In conclusion, a proper selection of candidates for extended indications of LDLT for HCC patients provide survival outcomes comparable to those obtained within the Milan criteria, but these results need confirmation. Liver Transplantation 24 369-379 2018 AASLD.

FAM83D associates with high tumor recurrence after liver transplantation involving expansion of CD44+ carcinoma stem cells

To investigate the potential oncogene promoting recurrence of hepatocellular carcinoma (HCC) following liver transplantation (LT), throughput RNA sequencing was performed in a subgroup of HCC patients. The up-regulated FAM83D in HCC tissues was found and further verified in 150 patients by real-time PCR and immunohistochemistry. FAM83D overexpression significantly correlated with high HCC recurrence rate following LT and poor HCC characteristics such as high AFP, poor differentiation. Of cancer stem cells (CSCs) markers, CD44 expression was effectively suppressed when FAM83D was knocked down by siRNA. Meanwhile, the siRNA transfected cells suppressed formation of sphere and ability of self-renew. In a xenograft tumorigenesis model, FAM83D knockdown apparently inhibited tumor growth and metastasis. Microarray assays revealed that FAM83D promotes CD44 expression via activating the MAPK, TGF-β and Hippo signaling pathways. Furthermore, CD44 knockdown presented reverse effect on above signaling pathways, which suggested that FAM83D was a key activator of loop between CD44 and above signaling pathways. In conclusion, FAM83D promotes HCC recurrence by promoting CD44 expression and CD44⁺ CSCs malignancy. FAM83D provides a novel therapeutic approach against HCC recurrence after LT.

Liver Cancer: Molecular Characterization, Clonal Evolution and Cancer Stem Cells

Liver cancer is the second most common cause of cancer-related death. The major forms of primary liver cancer are hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). Both these tumors develop against a background of cirrhotic liver, non-alcoholic fatty liver disease, chronic liver damage and fibrosis. HCC is a heterogeneous disease which usually develops within liver cirrhosis related to various etiologies: hepatitis B virus (HBV) infection (frequent in Asia and Africa), hepatitis C virus (HCV), chronic alcohol abuse, or metabolic syndrome (frequent in Western countries). In cirrhosis, hepatocarcinogenesis is a multi-step process where pre-cancerous dysplastic macronodules transform progressively into HCC. The patterns of genomic alterations observed in these tumors were recently identified and were instrumental for the identification of potential targeted therapies that could improve patient care. Liver cancer stem cells are a small subset of undifferentiated liver tumor cells, responsible for cancer initiation, metastasis, relapse and chemoresistance, enriched and isolated according to immunophenotypic and functional properties: cell surface proteins (CD133, CD90, CD44, EpCAM, OV-6, CD13, CD24, DLK1, α2δ1, ICAM-1 and CD47); the functional markers corresponding to side population, high aldehyde dehydrogenase (ALDH) activity and autofluorescence. The identification and definition of liver cancer stem cells requires both immunophenotypic and functional properties.