Molecular and histological correlations in liver cancer

Development of a Deep Learning Model to Assist With Diagnosis of Hepatocellular Carcinoma

Background

An accurate pathological diagnosis of hepatocellular carcinoma (HCC), one of the malignant tumors with the highest mortality rate, is time-consuming and heavily reliant on the experience of a pathologist. In this report, we proposed a deep learning model that required minimal noise reduction or manual annotation by an experienced pathologist for HCC diagnosis and classification.

Methods

We collected a whole-slide image of hematoxylin and eosin-stained pathological slides from 592 HCC patients at the First Affiliated Hospital, College of Medicine, Zhejiang University between 2015 and 2020. We propose a noise-specific deep learning model. The model was trained initially with 137 cases cropped into multiple-scaled datasets. Patch screening and dynamic label smoothing strategies are adopted to handle the histopathological liver image with noise annotation from the perspective of input and output. The model was then tested in an independent cohort of 455 cases with comparable tumor types and differentiations.

Results

Exhaustive experiments demonstrated that our two-step method achieved 87.81% pixel-level accuracy and 98.77% slide-level accuracy in the test dataset. Furthermore, the generalization performance of our model was also verified using The Cancer Genome Atlas dataset, which contains 157 HCC pathological slides, and achieved an accuracy of 87.90%.

Conclusions

The noise-specific histopathological classification model of HCC based on deep learning is effective for the dataset with noisy annotation, and it significantly improved the pixel-level accuracy of the regular convolutional neural network (CNN) model. Moreover, the model also has an advantage in detecting well-differentiated HCC and microvascular invasion.

Imaging features of histological subtypes of hepatocellular carcinoma: Implication for LI-RADS

Background & Aims

The histopathological subtypes of hepatocellular carcinoma (HCC) are associated with distinct clinical features and prognoses. This study aims to report Liver Imaging Reporting and Data System (LI-RADS)-defined imaging features of different HCC subtypes in a cohort of resected tumours and to assess the influence of HCC subtypes on computed tomography (CT)/magnetic resonance imaging (MRI) LI-RADS categorisation in the subgroup of high-risk patients.

Methods

This retrospective institutional review board-approved study included patients with resected HCCs and available histopathological classification. Three radiologists independently reviewed preoperative CT and MRI exams. The readers evaluated the presence of imaging features according to LI-RADS v2018 definitions and provided a LI-RADS category in patients at high risk of HCC. Differences in LI-RADS features and categorisations were assessed for not otherwise specified (NOS-HCC), steatohepatitic (SH-HCC), and macrotrabecular-massive (MTM-HCC) types of HCCs.

Results

Two hundred and seventy-seven patients (median age 64.0 years, 215 [77.6%] men) were analysed, which involved 295 HCCs. There were 197 (66.7%) NOS-HCCs, 62 (21.0%) SH-HCCs, 23 (7.8%) MTM-HCCs, and 13 (4.5%) other rare subtypes. The following features were more frequent in MTM-HCC: elevated α-foetoprotein serum levels (p <0.001), tumour-in-vein (p <0.001 on CT, p ≤0.052 on MRI), presence of at least 1 LR-M feature (p ≤0.010 on CT), infiltrative appearance (p ≤0.032 on CT), necrosis or severe ischaemia (p ≤0.038 on CT), and larger size (p ≤0.006 on CT, p ≤0.011 on MRI). SH-HCC was associated with fat in mass (p <0.001 on CT, p ≤0.002 on MRI). The distribution of the LI-RADS major features and categories in high-risk patients did not significantly differ among the 3 main HCC subtypes.

Conclusions

The distribution of LI-RADS major features and categories is not different among the HCC subtypes. Nevertheless, careful analysis of tumour-in-vein, LR-M, and ancillary features as well as clinico-biological data can provide information for the non-invasive diagnosis of HCC subtypes.

Lay summary

In high-risk patients, the overall distribution of LI-RADS major features and categories is not different among the histological subtypes of hepatocellular carcinoma, but tumour-in-vein, presence of LR-M features, and ancillary features can provide information for the non-invasive diagnosis of hepatocellular carcinoma subtypes.

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The distribution of the major features and categories of LI-RADS is not different among the HCC histological subtypes.

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MTM-HCC was associated with TIV, ≥1 LR-M feature, infiltrative appearance, necrosis or severe ischaemia, and larger size.

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Steatohepatitis-related HCC was associated with fat in mass on CT and on MRI.

[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.

Emerging role of long noncoding RNAs in recurrent hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains one of the most frequent types of liver cancer and is characterized by a high recurrence rate. Recent studies have proposed that long non-coding RNAs (lncRNAs) are potential biomarkers in several recurrent tumor types. It is now well understood that invasion, migration, and metastasis are important factors for tumor recurrence. Moreover, some of the known risk factors for HCC may affect the expression levels of several types of lncRNAs and thus affect the recurrence of liver cancer through lncRNA regulation. In this paper, we review the biological functions, molecular mechanisms, and roles of lncRNAs in HCC and summarize current knowledge about lncRNAs as potential biomarkers in recurrent HCC.

Immune profiling of combined hepatocellular-cholangiocarcinoma reveals distinct subtypes and activation of gene signatures predictive of response to immunotherapy

Purpose: Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare malignancy associated with an overall poor prognosis. We aimed to investigate the immune profile of cHCC-CCA and determine its impact on disease outcome. Experimental Design: We performed a multicenter study of 96 patients with cHCC-CCA. Gene expression profile was analyzed using nCounter PanCancer IO 360 Panel. Densities of main immune cells subsets were quantified from digital slides of immunohistochemical stainings. Genetic alterations were investigated using targeted next generation sequencing. Results: Two main immune subtypes of cHCC-CCA were identified by clustering analysis: an "Immune High" (IH) subtype (57% of the cases) and an "Immune Low" (IL) subtype (43% of the cases). Tumors classified as IH showed overexpression of genes related to immune cells recruitment, adaptive and innate immunity, antigen presentation, cytotoxicity, immune suppression, and inflammation (p<0.0001). IH cHCC-CCAs also displayed activation of gene signatures recently shown to be associated with response to immunotherapy in patients with HCC. Immunostainings confirmed that IH tumors were also characterized by higher densities of immune cells. Immune subtypes were not associated with any genetic alterations. Finally, multivariate analysis showed that the IH subtype was an independent predictor of improved overall survival. Conclusions: We have identified a subgroup of cHCC-CCA that displays features of an ongoing intra-tumor immune response, along with an activation of gene signatures predictive of response to immunotherapy in HCC. This tumor subclass is associated with an improved clinical outcome. These findings suggest that a subset of patients with cHCC-CCA may benefit from immunomodulating therapeutic approaches.

Radiomics in hepatocellular carcinoma: A state-of-the-art review

Hepatocellular carcinoma (HCC) is the most common cancer and the second major contributor to cancer-related mortality. Radiomics, a burgeoning technology that can provide invisible high-dimensional quantitative and mineable data derived from routine-acquired images, has enormous potential for HCC management from diagnosis to prognosis as well as providing contributions to the rapidly developing deep learning methodology. This article aims to review the radiomics approach and its current state-of-the-art clinical application scenario in HCC. The limitations, challenges, and thoughts on future directions are also summarized.

Cyclin E1 in Murine and Human Liver Cancer: A Promising Target for Therapeutic Intervention during Tumour Progression

Simple Summary

The cell cycle regulator Cyclin E1 is a key mediator and biomarker of liver cancer progression in mice and man independent of its canonical interacting partner Cyclin-dependent kinase 2. Over-expression of Cyclin E1 during hepatocarcinogenesis modulates several distinct biological processes such as proliferation, DNA damage response, stemness, invasion and the tumour microenvironment. Interventional depletion of Cyclin E1 in the course of liver cancer progression significantly reduces tumour burden. In contrast, the expression of Cyclin-dependent kinase 2 is dispensable for the progression of liver cancer in mice and lacked diagnostic or prognostic value in patients. Thus, specific inhibition of Cyclin E1 expression represents a promising strategy for the treatment of liver cancer.

Abstract

Cyclin E1 (CCNE1) is a regulatory subunit of Cyclin-dependent kinase 2 (CDK2) and is thought to control the transition of quiescent cells into cell cycle progression. Recently, we identified CCNE1 and CDK2 as key factors for the initiation of hepatocellular carcinoma (HCC). In the present study, we dissected the contributions of CCNE1 and CDK2 for HCC progression in mice and patients. Therefore, we generated genetically modified mice allowing inducible deletion of Ccne1 or Cdk2. After initiation of HCC, using the hepatocarcinogen diethylnitrosamine (DEN), we deleted Ccne1 or Cdk2 and subsequently analysed HCC progression. The relevance of CCNE1 or CDK2 for human HCC progression was investigated by in silico database analysis. Interventional deletion of Ccne1, but not of Cdk2, substantially reduced the HCC burden in mice. Ccne1-deficient HCCs were characterised by attenuated proliferation, impaired DNA damage response and downregulation of markers for stemness and microinvasion. Additionally, the tumour microenvironment of Ccne1-deficient mice showed a reduction in immune mediators, myeloid cells and cancer-associated fibroblasts. In sharp contrast, Cdk2 was dispensable for HCC progression in mice. In agreement with our mouse data, CCNE1 was overexpressed in HCC patients independent of risk factors, and associated with reduced disease-free survival, a common signature for enhanced chromosomal instability, proliferation, dedifferentiation and invasion. However, CDK2 lacked diagnostic or prognostic value in HCC patients. In summary, CCNE1 drives HCC progression in a CDK2-independent manner in mice and man. Therefore, interventional inactivation of CCNE1 represents a promising strategy the treatment of liver cancer.

Evaluation of tumor mutational burden in small early hepatocellular carcinoma and progressed hepatocellular carcinoma

While researchers know that tumor mutational burden (TMB) is low in hepatocellular carcinoma (HCC), prior studies have not investigated TMB in cirrhosis, small early HCC and progressed HCC. HCC (n = 18) and cirrhosis (n = 6) cases were identified. TMB was determined by a 1.7 megabase, 409-gene next-generation sequencing panel. TMB values were defined as the number of nonsynonymous variants per megabase of sequence. There was no significant difference between cirrhosis versus small early HCC or between cohorts when stratified by size, early versus progressed, differentiation or morphology. There was a significant difference between cirrhosis and small early HCC versus progressed HCC (p = 0.045), suggesting TMB may be related to HCC progression. TMB similarities in small early HCC and background cirrhosis suggest TMB is not a useful tool for diagnosing small early HCC. Additional study is needed to address TMB in histological and molecular subsets of HCC.

Identification of SLITRK6 as a Novel Biomarker in hepatocellular carcinoma by comprehensive bioinformatic analysis

Hepatocellular carcinoma (HCC) is the most common primary malignancy of the adult liver and morbidity are increasing in recent years, however, there is still no effective strategy to prevent and diagnose HCC. Therefore, it is urgent to research the effective biomarker to predict clinical outcomes of HCC tumorigenesis. In the current study, differentially expressed genes in HCC and normal tissues were investigated using the Gene Expression Omnibus (GEO) dataset GSE144269 and The Cancer Genome Atlas (TCGA). Gene differential expression analysis and weighted correlation network analysis (WGCNA) methods were used to identify nine and 16 key gene modules from the GEO dataset and TCGA dataset, respectively, in which the green module in the GEO dataset and magenta module in TCGA were significantly correlated with HCC occurrence. Third, the enrichment score of gene function annotation results showed that these two key modules focus on the positive regulation of inflammatory response and cell differentiation, etc. Besides, PPI network analysis, mutation analysis, and survival analysis found that SLITRK6 had high connectivity, and its mutation significantly impacted overall survival. In addition, SLITRK6 was found to be low expressed in tumor cells. To summarize, SLITRK6 mutation was found to significantly affect the occurrence and prognosis of HCC. SLITRK6 was confirmed as a new potential gene target for HCC, which may provide a new theoretical basis for personalized diagnosis and chemotherapy of HCC in the future.

Development and Validation of a Gene Mutation-Associated Nomogram for Hepatocellular Carcinoma Patients From Four Countries

Background: Genomic alteration is the basis of occurrence and development of carcinoma. Specific gene mutation may be associated with the prognosis of hepatocellular carcinoma (HCC) patients without distant or lymphatic metastases. Hence, we developed a nomogram based on prognostic gene mutations that could predict the overall survival of HCC patients at early stage and provide reference for immunotherapy.

Methods: HCC cohorts were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The total patient was randomly assigned to training and validation sets. Univariate and multivariate cox analysis were used to select significant variables for construction of nomogram. The support vector machine (SVM) and principal component analysis (PCA) were used to assess the distinguished effect of significant genes. Besides, the nomogram model was evaluated by concordance index, time-dependent receiver operating characteristics (ROC) curve, calibration curve and decision curve analysis (DCA). Gene Set Enrichment Analysis (GSEA), CIBERSORT, Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenoscore (IPS) were utilized to explore the potential mechanism of immune-related process and immunotherapy.

Results: A total of 695 HCC patients were selected in the process including 495 training patients and 200 validation patients. Nomogram was constructed based on T stage, age, country, mutation status of DOCK2, EYS, MACF1 and TP53. The assessment showed the nomogram has good discrimination and high consistence between predicted and actual data. Furthermore, we found T cell exclusion was the potential mechanism of malignant progression in high-risk group. Meanwhile, low-risk group might be sensitive to immunotherapy and benefit from CTLA-4 blocker treatment.

Conclusion: Our research established a nomogram based on mutant genes and clinical parameters, and revealed the underlying association between these risk factors and immune-related process.

Identification of Potential Biomarkers for Liver Cancer Through Gene Mutation and Clinical Characteristics

Liver cancer is a common malignant tumor worldwide, which is a serious threat to the health of people. We try to investigate some mutations and clinical indicators as candidate markers for the development of liver cancer through targeted region capture technology combined with next-generation sequencing. We collected peripheral blood and liver cancer tissue samples from 32 liver patients concurrently. The SeqCap EZ Prime Choice Probe was used to perform the targeted enrichment; this probe captures 1,000 known cancer-associated genes. We calculated the tumor mutation burden (TMB) for each patient. The high-frequency mutations and these relative genes were identified. Eventually, survival analysis was performed based on the mutations and clinical indicators. In 32 liver patients, a total of 29 high-frequency mutations were investigated. They were located in 25 genes, which were enriched in 9 cellular components (CCs), 6 molecular functions (MFs), and 21 biological processes (BPs). Among them, EZH2 c.1544A>G and CCND1 c.839A>T had the highest mutation frequency (5/32). In the protein-protein interaction (PPI) network, EZH2-DNMT3A, NOTCH1-CCND1, and ABL1-CCND1 were the top three pairs. The survival analysis showed that there were significant differences in progression-free survival (PFS) and overall survival (OS) between the Karnofsky performance score (KPS) groups. The PFS and OS in the TMB high group were higher than those in the TMB low group. OS and tumor stage had a remarkable relationship. In conclusion, EZH2 c.1544A>G and CCND1 c.839A>T might be potential biomarkers of liver cancer. TMB might be used as a prognosis and survival indicator of liver cancer.

Terahertz circular dichroism sensing of living cancer cells based on microstructure sensor

Terahertz (THz) waves have the advantages of being noninvasive and nonionizing because of their low radiation energy, so they have potential applications in the biomedical field, but thus far, those have been limited by the strong absorption in water and low detection sensitivity. Herein, we propose a reflective THz time-domain circular dichroism (CD) sensing system and a silicon subwavelength grating as the microstructure sensor to generate and detect the THz chiral polarization states, to realize quantitative detection of living cell numbers and qualitative identification of cell kinds in a liquid environment. Three kinds of hepatoma cell proliferation and inhibition with different concentrations of aspirin were measured by this sensing method, and the experimental results show that the sensitivities for CD resonance intensity and frequency shift can reach 3.44 dB mL/10⁶ cells and 5.88 GHz mL/10⁶ cells, respectively, and the minimum detection concentration is in the order of 10⁴ cells/mL for THz detection in a liquid environment for the first time. This new THz sensing system and sensing method are expected to become a broadband, label-free, noncontact, real-time detection technology that can be used for quantitative detection and qualitative identification of cells or other active biochemical materials.

HCC and Molecular Targeting Therapies: Back to the Future

Hepatocellular carcinoma (HCC) is one of the leading causes of death from cancer in the world. Recently, the effectiveness of new antiviral therapies and the HBV vaccine have reduced HCC’s incidence, while non-alcoholic steato-hepatitis is an emerging risk factor. This review focuses on antiangiogenic molecules and immune checkpoint inhibitors approved for HCC treatment and possible future approaches. Sorafenib was the first drug approved for the treatment of advanced HCC (aHCC) and it has been shown to increase survival by a few months. Lenvatinib, a multikinase inhibitor, has shown non-inferiority in survival compared with sorafenib and an improvement in progression-free survival (PFS). The combination of atezolizumab (an anti-PDL1 antibody) and bevacizumab (an anti-VEGF antibody) was the first drug combination approved for HCC, demonstrating improved survival compared with sorafenib (19.2 vs. 13.4 months). As a second line of therapy, three regimens (regorafenib, cabozantinib, and ramucirumab) have been approved for the treatment of aHCC after progression on sorafenib according to guidelines. Furthermore, nivolumab, pembrolizumab, and nivolumab plus ipilimumab have been approved by the FDA (2017, 2018, and 2020, respectively). Finally, immune target therapy, cancer vaccines, and epigenetic drugs represent three new possible weapons for the treatment of HCC.

Liver-specific over-expression of Cripto-1 in transgenic mice promotes hepatocyte proliferation and deregulated expression of hepatocarcinogenesis-related genes and signaling pathways

In this study, we investigated the role of embryonic gene Cripto-1 (CR-1) in hepatocellular carcinoma (HCC) using hepatocyte-specific CR-1-overexpressing transgenic mice. The expression of truncated 1.7-kb CR-1 transcript (SF-CR-1) was significantly higher than the full-length 2.0-kb CR-1 transcript (FL-CR-1) in a majority of HCC tissues and cell lines. Moreover, CR-1 mRNA and protein levels were significantly higher in HCC tissues than adjacent normal liver tissues. Hepatocyte-specific over-expression of CR-1 in transgenic mice enhanced hepatocyte proliferation after 2/3 partial hepatectomy (2/3 PHx). CR-1 over-expression significantly increased in vivo xenograft tumor growth of HCC cells in nude mice and in vitro HCC cell proliferation, migration, and invasion. CR-1 over-expression in the transgenic mouse livers deregulated HCC-related signaling pathways such as AKT, Wnt/β-catenin, Stat3, MAPK/ERK, JNK, TGF-β and Notch, as well as expression of HCC-related genes such as CD5L, S100A8, S100A9, Timd4, Orm2, Orm3, PDK4, DMBT1, G0S2, Plk2, Plk3, Gsta1 and Gsta2. However, histological signs of precancerous lesions, hepatocyte dysplasia or HCC formation were not observed in the livers of 3-, 6- or 8-month-old hepatocyte-specific CR-1-overexpressing transgenic mice. These findings demonstrate that liver-specific CR-1 overexpression in transgenic mice deregulates signaling pathways and genes associated with HCC.

Low expression of KIF20A suppresses cell proliferation, promotes chemosensitivity and is associated with better prognosis in HCC

This study analysed the microarray datasets from Gene Expression Omnibus (GEO) database, and aimed to identify novel potential hub genes associated with the progression of HCC via bioinformatics analysis and experimental validation. The common differentially expressed genes (DEGs) from five GEO datasets were screened using GEO2R tool. The expression and survival analysis of hub genes in HCC were performed using Gene Expression Profiling Interactive Analysis, UALCAN and Kaplan-Meier plotter tools. In vitro functional assays were used to determine the caspase-3, -9, cell proliferation and chemo-sensitivity of HCC cells. A total of 177 common DEGs were identified between normal liver and HCC tissues among these datasets. Functional enrichment and PPI network analysis identified 22 hub genes from the common DEGs. The mRNA expression of 22 hub genes was all significantly up-regulated in HCC tissues compared to that in normal liver tissues. Further survival analysis showed that 10 hub genes predicted poor prognosis of patients with HCC. More importantly, the in vitro functional studies demonstrated that KIF20A knockdown suppressed the HCC cell proliferation and promoted the chemosensitivity of HCC cells to cisplatin and sorafenib. In conclusion, the present study identified a total of 177 common DEGs among 5 GEO microarray datasets and found that 10 hub genes could predict the poor prognosis of patients with HCC using the comprehensive bioinformatics analysis. Furthermore, KIF20A silence suppressed cell proliferation and enhanced chemosensitivity in HCC cells. Further studies may be required to determine the mechanistic role of these hub genes in HCC progression.

Programmed cell death-ligand 1 expression in hepatocellular carcinoma and its correlation with clinicopathological characteristics

BACKGROUND AND AIM

Programmed cell death-ligand 1 (PD-L1) immunohistochemistry score has been approved as the predictive biomarker for anti-PD1/PD-L1 therapy in several advanced malignancies. Although its predictive role remained inconclusive in hepatocellular carcinoma, ongoing study of anti-PD1/PD-L1 therapy showed promising results. However, less is known about the PD-L1 immunohistochemistry score and factors correlated with it in hepatocellular carcinoma. We investigated PD-L1 immunohistochemistry scores in a large cohort of hepatocellular carcinoma, as well as its correlation with various clinical and genomic factors.

METHODS

Immunohistochemistry was performed to detect the expression of PD-L1 protein in 315 hepatocellular carcinoma tissues. All slides were independently reviewed by three senior pathologists. Next-generation YS panel (450 genes) sequencing was performed on 309 patients.

RESULTS

Higher PD-L1 expression as measured by combined positive score (CPS) was associated with increased Edmondson-Steiner grade (grade III vs II, P = 0.041) and TP53 mutations (P = 0.021). PD-L1 CPS had no correlation with tumor mutational burden (Spearman's correlation coefficient 0.067). PD-L1 CPS was not significantly associated with hepatitis B virus infection.

CONCLUSIONS

Our data indicated that patients with higher Edmondson-Steiner grade (grade III) had significantly higher PD-L1 CPS than patients with lower Edmondson-Steiner grade (grade II). Patients with TP53 mutations had significantly higher PD-L1 expression.

PARP inhibitors and radiation potentiate liver cell death in vitro. Do hepatocellular carcinomas have an achilles' heel?

BACKGROUND

A promising avenue for cancer treatment is exacerbating the deregulation of the DNA repair machinery that would normally protect the genome. To address the applicability of poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) combined with radiotherapy for the treatment of hepatocellular carcinoma (HCC) two approaches were used: firstly, the in vitro sensitivity to the PARPi Veliparib and Talazoparib +/- radiation exposure was determined in liver cell lines and the impact of the HBV X protein (HBx) that deregulates cellular DNA damage repair via SMC5/6 degradation was investigated. Secondly, PARP expression profiles and DNA damage levels using the surrogate marker gammaH2AX were assessed in a panel of control liver vs HCC tissues.

METHODS

Cell cytotoxicity was measured by clonogenic survival or relative cell growth and the DNA damage response using immunological-based techniques in Hep3B, PLC/PRF/5, HepG2- and HepaRG-derived models. Transcriptome changes due to HBx expression vs SMC6 loss were assessed by RNA sequencing in HepaRG-derived models. PARP and PARG transcripts (qPCR) and PARP1, H2AX and gammaH2AX protein levels (RPPA) were compared in control liver vs HBV-, HCV-, alcohol- and non-alcoholic steatohepatitis-associated HCC (tumor/peritumor) tissues.

RESULTS

PARPi cytotoxicity was significantly enhanced when combined with X-rays (2Gy) with Talazoparib having a greater impact than Veliparib in most in vitro models. HBx expression significantly lowered survival, probably driven by SMC5/6 loss based on the transcriptome analysis and higher DNA damage levels. PARP1 and PARP2 transcript levels were significantly higher in tumor than peritumor and control tissues. The HBV/HCV/alcohol-associated tumor tissues studied had reduced H2AX but higher gammaH2AX protein levels compared to peritumor and control tissues providing evidence of increased DNA damage during liver disease progression.

CONCLUSIONS

These proof-of-concept experiments support PARPi alone or combined with radiotherapy for HCC treatment, particularly for HBV-associated tumors, that warrant further investigation.

Molecular phenotypes reveal heterogeneous engraftments of patient-derived hepatocellular carcinoma xenografts

Objective

Patient-derived xenograft (PDX) models provide a promising preclinical platform for hepatocellular carcinoma (HCC). However, the molecular features associated with successful engraftment of PDX models have not been revealed.

Methods

HCC tumor samples from 76 patients were implanted in immunodeficient mice. The molecular expression was evaluated by immunohistochemistry. Patient and tumor characteristics as well as tumor molecular expressions were compared for PDX engraftment using the Chi-square test. The independent prediction parameters were identified by logistic regression analyses.

Results

The engraftment rate for PDX models from patients with HCC was 39.47% (30/76). Tumors from younger patients and patients with elevated preoperative alpha-fetoprotein level had higher engraftment rates. Tumors with poor differentiation and vascular invasion were related to engraftment success. The positive expression of CK19, CD133, glypican-3 (GPC3), and Ki67 in tumor samples was associated with engraftment success. Logistic regression analyses indicated that GPC3 and Ki67 were two of the strongest predictors of PDX engraftment. Tumors with GPC3/Ki67 phenotypes showed heterogeneous engraftment rates, with 71.9% in GPC3⁺/Ki67⁺ tumors, 30.8% in GPC3⁻/Ki67⁺ tumors, 15.0% in GPC3⁺/Ki67⁻ tumors, and 0 in GPC3⁻/Ki67⁻ tumors.

Conclusions

Successful engraftment of HCC PDXs was significantly related to molecular features. Tumors with the GPC3⁺/Ki67⁺ phenotype were the most likely to successfully establish HCC PDXs.

Identification and integrative analysis of ACLY and related gene panels associated with immune microenvironment reveal prognostic significance in hepatocellular carcinoma

BACKGROUND

Cumulating evidence reveals the key role of aberrant lipogenesis and immunogenomic features in hepatocellular carcinoma (HCC). However, there are still obstacles in our understanding of the complicated interaction between metabolic reprogramming and tumor immune microenvironment.

METHODS

We compared metabolomic, transcriptomic and immunogenomic characteristics of portal vein tumor thrombosis (PVTT) and primary tumor to seek valuable markers. Human HCC samples with PVTT (n  =  28) was analyzed through ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). Transcript levels of mRNA in two cohorts from published database GEO (n  =  60) and TCGA (n  =  411) were downloaded to explore differentially expressed genes and functional enriched gene set. Evaluation of immune infiltration was estimated and validated from transcriptomic data in both cohorts through six immune deconvolution algorithms and in a high-resolution mode (CIBERSORTx). Survival analysis (Kaplan-Meier and multivariable Cox regression model) was performed to examine prognostic value of ACLY, related immune checkpoints and immune infiltration levels from TCGA cohort. LASSO regression was further conducted to determine a gene panel to further predict survival outcomes associated with ACLY.

RESULTS

We identified a novel signature, ATP citrate lyase, through transcriptomic and metabolomic approaches. We demonstrated that the metabolism adaptations in both fatty acid and cholesterol biosynthesis triggered by ACLY oncogenic activation. We illustrated the crucial function of ACLY in lipogenesis and its potential interaction with immune microenvironment. CD276, a promising target in immune checkpoint blockade, showed correlation to ACLY and differential expression in ACLY risk classification. Combination of ACLY, CD276 and immune infiltration level and a novel ACLY-associated panel from a predictive model retrieved from published database validated the prognostic value to risk stratification in patients with HCC.ACLY blockade to counteract metabolic activation and immunosuppressive status of the tumor microenvironment highlighted attractive prospect for translational application.

CONCLUSIONS

We investigated ACLY and its indispensable role in metabolism, immune function and a prognostic gene panel in HCC. We anticipate that the multifaced role of ACLY may reveal the potential value for mechanistic research and combinational therapy, suggesting that the combination blockade of ACLY and immune checkpoints may work as a promising strategy.

BH3-only protein expression determines hepatocellular carcinoma response to sorafenib-based treatment

Hepatocellular carcinoma (HCC) represents a global health challenge with limited therapeutic options. Anti-angiogenic immune checkpoint inhibitor-based combination therapy has been introduced for progressed HCC, but improves survival only in a subset of HCC patients. Tyrosine-kinase inhibitors (TKI) such as sorafenib represent an alternative treatment option but have only modest efficacy. Using different HCC cell lines and HCC tissues from various patients reflecting HCC heterogeneity, we investigated whether the sorafenib response could be enhanced by combination with pro-apoptotic agents, such as TNF-related apoptosis-inducing ligand (TRAIL) or the BH3-mimetic ABT-737, which target the death receptor and mitochondrial pathway of apoptosis, respectively. We found that both agents could enhance sorafenib-induced cell death which was, however, dependent on specific BH3-only proteins. TRAIL augmented sorafenib-induced cell death only in NOXA-expressing HCC cells, whereas ABT-737 enhanced the sorafenib response also in NOXA-deficient cells. ABT-737, however, failed to augment sorafenib cytotoxicity in the absence of BIM, even when NOXA was strongly expressed. In the presence of NOXA, BIM-deficient HCC cells could be in turn strongly sensitized for cell death induction by the combination of sorafenib with TRAIL. Accordingly, HCC tissues sensitive to apoptosis induction by sorafenib and TRAIL revealed enhanced NOXA expression compared to HCC tissues resistant to this treatment combination. Thus, our results suggest that BH3-only protein expression determines the treatment response of HCC to different sorafenib-based drug combinations. Individual profiling of BH3-only protein expression might therefore assist patient stratification to certain TKI-based HCC therapies.

Artificial Intelligence for solid tumor diagnosis in digital pathology

Tumor diagnosis relies on the visual examination of histological slides by pathologists through a microscope eyepiece. Digital pathology, the digitalization of histological slides at high magnification with slides scanners, has raised the opportunity to extract quantitative information thanks to image analysis. In the last decade, medical image analysis has made exceptional progress due to the development of artificial intelligence (AI) algorithms. AI has been successfully used in the field of medical imaging and more recently in digital pathology. The feasibility and usefulness of AI assisted pathology tasks have been demonstrated in the very last years and we can expect those developments to be applied on routine histopathology in the future. In this review, we will describe and illustrate this technique and present the most recent applications in the field of tumor histopathology.

Decoding Genes: Current Update on Radiogenomics of Select Abdominal Malignancies

Technologic advances in chromosomal analysis and DNA sequencing have enabled genome-wide analysis of cancer cells, yielding considerable data on the genetic basis of malignancies. Evolving knowledge of tumor genetics and oncologic pathways has led to a better understanding of histopathologic features, tumor classification, tumor biologic characteristics, and imaging findings and discovery of targeted therapeutic agents. Radiogenomics is a rapidly evolving field of imaging research aimed at correlating imaging features with gene mutations and gene expression patterns, and it may provide surrogate imaging biomarkers that may supplant genetic tests and be used to predict treatment response and prognosis and guide personalized treatment options. Multidetector CT, multiparametric MRI, and PET with use of multiple radiotracers are some of the imaging techniques commonly used to assess radiogenomic associations. Select abdominal malignancies demonstrate characteristic imaging features that correspond to gene mutations. Recent advances have enabled us to understand the genetics of steatotic and nonsteatotic hepatocellular adenomas, a plethora of morphologic-molecular subtypes of hepatic malignancies, a variety of clear cell and non-clear cell renal cell carcinomas, a myriad of hereditary and sporadic exocrine and neuroendocrine tumors of the pancreas, and the development of targeted therapeutic agents for gastrointestinal stromal tumors based on characteristic KIT gene mutations. Mutations associated with aggressive phenotypes of these malignancies can sometimes be predicted on the basis of their imaging characteristics. Radiologists should be familiar with the genetics and pathogenesis of common cancers that have associated imaging biomarkers, which can help them be integral members of the cancer management team and guide clinicians and pathologists. Online supplemental material is available for this article. ^©RSNA, 2020 See discussion on this article by Luna (pp 1627-1630).

Gadoxetate-enhanced MRI Features of Proliferative Hepatocellular Carcinoma Are Prognostic after Surgery

Background Hepatocellular carcinomas (HCCs) are heterogeneous neoplasms, and the prognosis varies based on the subtype. Two broad molecular classes of HCC have been proposed: a proliferative and a nonproliferative class. Purpose To evaluate the gadoxetate-enhanced MRI findings of the proliferative class HCC and its prognostic significance after surgery. Materials and Methods This retrospective cohort study evaluated patients with surgically resected treatment-naive single HCC (≤5 cm) who underwent hepatic resection from January 2010 through February 2013 and preoperative gadoxetate-enhanced MRI. A Cox proportional hazards model was used to determine the predictive factors for overall survival (OS), intrahepatic distant recurrence, and extrahepatic metastasis (EM). The mean follow-up period was 75.5 months ± 30.2 (standard deviation). Multivariable logistic regression was performed to determine factors associated with proliferative class HCC. Results A total of 158 patients (mean age, 57 years ± 11; 128 men and 30 women) were evaluated. Forty-two of the 158 HCCs (26.6%) were proliferative class HCCs (17 macrotrabecular-massive HCCs, 14 keratin 19-positive HCCs, 10 scirrhous HCCs, and one sarcomatoid HCC). The proliferative class was associated with worse OS (hazard ratio [HR], 3.1; 95% CI: 1.5, 6.0; P = .01) and higher rates of intrahepatic distant recurrence (HR, 1.83; 95% CI: 1.1, 2.9; P = .01) and EM (HR, 9.97; 95% CI: 3.2, 31.4; P < .001). Rim arterial phase hyperenhancement (APHE) at gadoxetate-enhanced MRI (odds ratio [OR], 6.35; 95% CI: 1.9, 21.7; P = .01) and high serum α-fetoprotein (>100 ng/mL) (OR, 4.18; 95% CI: 1.64, 10.7; P = .01) were independent predictors for proliferative HCC. The presence of rim APHE was associated with poor OS (HR, 2.4; 95% CI: 1.2, 4.9; P = .02) and higher rates of EM (HR, 7.4; 95% CI: 2.5, 21.7; P < .01). Conclusion The proliferative class of hepatocellular carcinoma (HCC) is an independent factor for poor overall survival with increased rates of intrahepatic and extrahepatic metastasis. Rim arterial phase hyperenhancement at gadoxetate-enhanced MRI may help to identify proliferative class HCC and predict poor overall survival and an increased incidence of extrahepatic metastasis. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Krinsky and Shanbhogue in this issue.

A radiomics nomogram based on contrast-enhanced MRI for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma

BACKGROUND

Macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) represents an aggressive form of hepatocellular carcinoma and is associated with poor survival outcomes.

AIMS

This study aimed to develop a radiomics nomogram based on contrast-enhanced MRI for preoperative prediction of MTM-HCC.

METHODS

This study enrolled 88 patients with histologically confirmed HCC, including 32 MTM-HCCs and 56 Non-MTM-HCCs. The clinical and gadobenate dimeglumine (Gd)-enhanced MRI features were retrospectively reviewed by two abdominal radiologists. The regions of interest (ROIs) on the largest cross-sectional image and two adjacent images of the tumor, from which radiomics features were extracted via MaZda software and a radiomics score (Rad-score) was calculated via Python software. Combined with the Rad-score and independent imaging factors, a radiomics nomogram was constructed using R software. Nomogram performance was estimated with calibration curve.

RESULTS

A total of eleven top weighted radiomics features were selected among five sequences of MR images. There was a significant difference in Rad-score between MTM-HCC and non-MTM-HCC patients (P < 0.001), where patients with MTM-HCC generally had higher Rad-scores (absolute value). After multivariate analysis, radiomics score (OR = 7.794, P < 0.001) and intratumor fat (OR = 9.963, P = 0.014) were determined as independent predictors associated with MTM-HCC. The area under the receiver operating characteristic (ROC) curve of the selected model was 0.813 (95% CI 0.714-0.912) and the optimal cutoff value was 0.60. The nomogram showed overall satisfactory prediction performance (AUC = 0.785 [95% CI 0.684-0.886]).

CONCLUSIONS

A contrast-enhanced MRI-based radiomics nomogram may be useful for preoperative prediction of MTM-HCC in primary HCC patients, allowing opportunity to improve the treatment course and patient outcomes.

The Anti-Tumor Effect and Underlying Apoptotic Mechanism of Ginsenoside Rk1 and Rg5 in Human Liver Cancer Cells

Ginsenoside Rk1 and Rg5 are minor ginseng saponins that have received more attention recently because of their high oral bioavailability. Each of them can effectively inhibit the survival and proliferation of human liver cancer cells, but the underlying mechanism remains largely unknown. Network pharmacology and bioinformatics analysis demonstrated that G-Rk1 and G-Rg5 yielded 142 potential targets, and shared 44 putative targets associated with hepatocellular carcinoma. Enrichment analysis of the overlapped genes showed that G-Rk1 and G-Rg5 may induce apoptosis of liver cancer cells through inhibition of mitogen-activated protein kinase (MAPK) and nuclear factor-kappa B (NF-κB) signal pathways. Methyl thiazolyl tetrazolium (MTT) assay was used to confirm the inhibition of cell viability with G-Rk1 or G-Rg5 in highly metastatic human cancer MHCC-97H cells. We evaluated the apoptosis of MHCC-97H cells by using flow cytometry and 4′,6-diamidino-2-phenylindole (DAPI) staining. The translocation of Bax/Bak led to the depolarization of mitochondrial membrane potential and release of cytochrome c and Smac. A sequential activation of caspase-9 and caspase-3 and the cleavage of poly(ADP-ribose) polymerase (PARP) were observed after that. The levels of anti-apoptotic proteins were decreased after treatment of G-Rk1 or G-Rg5 in MHCC-97H cells. Taken together, G-Rk1 and G-Rg5 promoted the endogenous apoptotic pathway in MHCC-97H cells by targeting and regulating some critical liver cancer related genes that are involved in the signal pathways associated with cell survival and proliferation.

Identification of NAA40 as a Potential Prognostic Marker for Aggressive Liver Cancer Subtypes

Liver hepatocellular carcinoma (LIHC) is a leading cause of cancer-related mortality. In this study we initially interrogated the Cancer Genome Atlas (TCGA) dataset to determine the implication of N-terminal acetyltransferases (NATs), a family of enzymes that modify the N-terminus of the majority of eukaryotic proteins, in LIHC. This examination unveiled NAA40 as the NAT family member with the most prominent upregulation and significant disease prognosis for this cancer. Focusing on this enzyme, which selectively targets histone proteins, we show that its upregulation occurs from early stages of LIHC and is not specifically correlated with any established risk factors such as viral infection, obesity or alcoholic disease. Notably, in silico analysis of TCGA and other LIHC datasets found that expression of this epigenetic enzyme is associated with high proliferating, poorly differentiating and more aggressive LIHC subtypes. In particular, NAA40 upregulation was preferentially linked to mutational or non-mutational P53 functional inactivation. Accordingly, we observed that high NAA40 expression was associated with worse survival specifically in liver cancer patients with inactivated P53. These findings define NAA40 as a NAT with potentially oncogenic functions in LIHC and uncover its prognostic value for aggressive LIHC subtypes.

Effect of Lenvatinib on a Hepatocellular Carcinoma with Fibroblast Growth Factor Receptor 4 Expression: A Case Report and Review of the Literature

Basic and clinical research have shown that the expression of molecules involved in the hepatocellular carcinoma (HCC) cell signaling pathway is related to the sensitivity to molecular-targeted agents. We herein report a case of HCC that was effectively treated with lenvatinib after a poor response to sorafenib. The tumor showed a high expression of fibroblast growth factor receptor 4, which is reportedly related to the sensitivity to lenvatinib in vitro. The information obtained from this case and from our literature review highlights the importance of assessing the expression of the molecules involved in tumors for effective precision medicine.

Hepatocellular carcinoma: a clinical and pathological overview

HCC incidence rates have been rising in the past 3 decades and by 2025 > 1 million individuals will be affected annually. High-throughput sequencing technologies led to the identification of several molecular HCC subclasses that can be broadly grouped into 2 major subgroups, each characterized by specific morphological and phenotypical features. It is likely that this increasing knowledge and a more appropriate characterization of HCC at the pathological level will impact HCC patient management.

Artificial intelligence-based pathology for gastrointestinal and hepatobiliary cancers

Artificial intelligence (AI) can extract complex information from visual data. Histopathology images of gastrointestinal (GI) and liver cancer contain a very high amount of information which human observers can only partially make sense of. Complementing human observers, AI allows an in-depth analysis of digitised histological slides of GI and liver cancer and offers a wide range of clinically relevant applications. First, AI can automatically detect tumour tissue, easing the exponentially increasing workload on pathologists. In addition, and possibly exceeding pathologist's capacities, AI can capture prognostically relevant tissue features and thus predict clinical outcome across GI and liver cancer types. Finally, AI has demonstrated its capacity to infer molecular and genetic alterations of cancer tissues from histological digital slides. These are likely only the first of many AI applications that will have important clinical implications. Thus, pathologists and clinicians alike should be aware of the principles of AI-based pathology and its ability to solve clinically relevant problems, along with its limitations and biases.

Biomarkers in Hepatobiliary Cancers: What is Useful in Clinical Practice?

Hepatocellular carcinoma (HCC) and biliary tract cancers (BTC) exhibit a poor prognosis with 5-year overall survival rates around 15%, all stages combined. Most of these primary liver malignancies are metastatic at diagnostic, with only limited therapeutic options, relying mainly on systemic therapies. Treatment modalities are different yet partially overlapping between HCC and BTC. The complex molecular profile of BTC yields to several actionable therapeutic targets, contrary to HCC that remains the field of antiangiogenic drugs in non-molecularly selected patients. Immunotherapy is now validated in the first line in HCC in combination with bevacizumab, while clinical activity of single agent immunotherapy appears limited to a subset of patients in BTC, still poorly characterized, and combinations are currently under investigation. In this review, we provide a critical evaluation and grading of clinical relevance on (i) the main prognostic biomarkers in HCC and BTC, (ii) the main theragnostic biomarkers in both tumors, and lastly (iii) what is recommended in clinical practice.

Preoperative CT for Characterization of Aggressive Macrotrabecular-Massive Subtype and Vessels That Encapsulate Tumor Clusters Pattern in Hepatocellular Carcinoma

Background Macrotrabecular-massive (MTM) subtype and vessels encapsulating tumor clusters (VETC) pattern of hepatocellular carcinoma (HCC) are associated with unfavorable prognosis. Purpose To estimate the potential of preoperative CT in the prediction of MTM subtype and VETC pattern. Materials and Methods Patients who underwent surgical resection or liver transplant and preoperative CT for HCC between January 2015 and June 2018 were retrospectively included in the primary cohort. CT imaging features were evaluated by two radiologists. Predictors associated with the MTM subtype or VETC pattern were determined by using logistic regression analyses and the performance was tested in a validation cohort. Prognostic factors associated with early recurrence after surgical resection were identified by using Cox regression analyses. Results The primary cohort included 170 patients (median age, 55 years; interquartile range, 48-63 years; 152 men). Serum α-fetoprotein level higher than 100 ng/mL (odds ratio [OR], 4.3; 95% CI: 2.1, 9.2; P < .001), intratumor necrosis (OR, 5.2; 95% CI: 2.5, 11.0; P < .001), and intratumor hemorrhage (OR, 5.4; 95% CI: 1.3, 23.3; P = .02) were independent predictors for MTM subtype, whereas tumor size greater than 5 cm (OR, 3.8; 95% CI: 1.7, 8.1; P = .001) and intratumor necrosis (OR, 2.1; 95% CI: 1.0, 4.4; P = .045) were independent predictors for VETC pattern. These features were used for the construction of ANH and SN scores (where A is α-fetoprotein level, N is necrosis, H is hemorrhage, and S is size), respectively, which showed comparable prediction performance in the primary and validation cohorts. Preoperative high ANH and high SN phenotype (hazard ratio, 1.9; 95% CI: 1.2, 3.0; P = .01) was independently associated with early recurrence after surgical resection. Conclusion Preoperative CT features could be used for the characterization of macrotrabecular-massive subtype and vessels that encapsulate tumor clusters pattern and were of prognostic significance for early recurrence in patients with hepatocellular carcinoma. Online supplemental material is available for this article. See also the editorial by Yoon and Kim in this issue. Published under a CC BY 4.0 license.

Clinicopathological Features of Two Extremely Rare Hepatocellular Carcinoma Variants: a Brief Review of Fibrolamellar and Scirrhous Hepatocellular Carcinoma

PURPOSE

We aimed to distinguish between fibrolamellar hepatocellular carcinoma and scirrhous hepatocellular carcinoma histopathologically.

METHODS AND RESULTS

In this review, fibrolamellar hepatocellular carcinoma and scirrhous hepatocellular carcinoma two specific and rare variants of hepatocellular carcinoma, which are difficult to diagnose histopathologically are discussed.

CONCLUSION

The clinical, radiological, gross, histopathological, immunohistochemical, and molecular features of these two tumors, which are defined by the World Health Organization (WHO), are mentioned.

Update on Hepatocellular Carcinoma: a Brief Review from Pathologist Standpoint

Hepatocellular carcinoma is one of the most common cancers and an important health problem all over the world. Its prognosis is poor. For better patient care, early diagnosis is essential. Although new imaging techniques have a big impact on hepatocellular carcinoma diagnosis, histopathological examination is still the gold standard for precise diagnosis. Histopathological evaluation gives exact diagnosis in the meaning of tumor size, histological subtypes, grading, and differential diagnosis from metastasis and other tumors. Immunohistochemistry as a part of diagnostic histopathological technique plays an important role in routine practice. Immunohistochemistry is useful for confirming of hepatocytic origin, supporting hepatocellular malignancy, and differential diagnosis. It also gives prognostic information. There are growing attempts to classify tumors by their molecular genetic signatures. This is also actual for hepatocellular carcinoma. This mini review focuses on the histopathology of hepatocellular carcinoma including subtypes; differential diagnosis and immunohistochemistry as an ancillary diagnostic tool, updated or added entities, i.e., combined hepatocellular-cholangiocarcinoma; small hepatocellular carcinoma; correlation with molecular studies; and future perspectives.

Centromere protein N may be a novel malignant prognostic biomarker for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the deadliest tumors. The majority of HCC is detected in the late stage, and the clinical results for HCC patients are poor. There is an urgent need to discover early diagnostic biomarkers and potential therapeutic targets for HCC.

Methods

The GSE87630 and GSE112790 datasets from the Gene Expression Omnibus (GEO) database were downloaded to analyze the differentially expressed genes (DEGs) between HCC and normal tissues. R packages were used for Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses of the DEGs. A Search Tool for Retrieval of Interacting Genes (STRING) database was used to develop a protein-protein interaction (PPI) network, and also cytoHubba, Molecular Complex Detection (MCODE), EMBL-EBI, CCLE, Gene Expression Profiling Interactive Analysis (GEPIA), and Oncomine analyses were performed to identify hub genes. Gene expression was verified with a third GEO dataset, GSE25097. The Cancer Genome Atlas (TCGA) database was used to explore the correlations between the hub genes and clinical indexes of HCC patients. The functions of the hub genes were enriched by gene set enrichment analysis (GSEA), and the biological significance of the hub genes was explored by real-time polymerase chain reaction (qRT-PCR), western blot, immunofluorescence, CCK-8, colony formation, Transwell and flow cytometry assays with loss-of-function experiments in vitro.

Results

Centromere protein N (CENPN) was screened as a hub gene affecting HCC tumorigenesis. Evaluation by Cox regression showed that a high level of CENPN expression was an independent danger variable for poor prognosis of HCC. GSEA showed that high CENPN expression was linked to the following pathways: liver cancer subclass proliferation, cell cycle, p53 signaling pathway, Rb1 pathway, positive regulation of cell cycle G1/S phase transition, and DNA damage response signal transduction by p53 class moderators. Further cell experiments showed that knocking down CENPN expression decreased the proliferation and colony-forming abilities of HepG2 and Huh7 cells as well as Ki67 expression in these cell lines. The cell cycle was arrested in G1 phase, which is consistent with previous experiments on CENPN downregulation., but neither migration nor invasion were significantly affected. Western blot results revealed that the expression of p53, p27, p21, CDK4, cyclin D1, CDK2, cyclin E, pRb, E2F1 and c-myc decreased after CENPN knockdown, but there was no significant change in total Rb levels. In addition, CENPN-knockdown cells subjected to irradiation showed significantly enhanced of γ-H2AX expression and reduced colony formation.

Conclusion

CENPN functions as an oncogene in HCC and may be a therapeutic target and promising prognostic marker for HCC.

Exploring prognostic indicators in the pathological images of hepatocellular carcinoma based on deep learning

OBJECTIVE

Tumour pathology contains rich information, including tissue structure and cell morphology, that reflects disease progression and patient survival. However, phenotypic information is subtle and complex, making the discovery of prognostic indicators from pathological images challenging.

DESIGN

An interpretable, weakly supervised deep learning framework incorporating prior knowledge was proposed to analyse hepatocellular carcinoma (HCC) and explore new prognostic phenotypes on pathological whole-slide images (WSIs) from the Zhongshan cohort of 1125 HCC patients (2451 WSIs) and TCGA cohort of 320 HCC patients (320 WSIs). A 'tumour risk score (TRS)' was established to evaluate patient outcomes, and then risk activation mapping (RAM) was applied to visualise the pathological phenotypes of TRS. The multi-omics data of The Cancer Genome Atlas(TCGA) HCC were used to assess the potential pathogenesis underlying TRS.

RESULTS

Survival analysis revealed that TRS was an independent prognosticator in both the Zhongshan cohort (p<0.0001) and TCGA cohort (p=0.0003). The predictive ability of TRS was superior to and independent of clinical staging systems, and TRS could evenly stratify patients into up to five groups with significantly different prognoses. Notably, sinusoidal capillarisation, prominent nucleoli and karyotheca, the nucleus/cytoplasm ratio and infiltrating inflammatory cells were identified as the main underlying features of TRS. The multi-omics data of TCGA HCC hint at the relevance of TRS to tumour immune infiltration and genetic alterations such as the FAT3 and RYR2 mutations.

CONCLUSION

Our deep learning framework is an effective and labour-saving method for decoding pathological images, providing a valuable means for HCC risk stratification and precise patient treatment.

Pathologic and molecular features of hepatocellular carcinoma: An update

Morphological diversity and several new distinct pathologic subtypes of hepatocellular carcinoma (HCC) are now well-recognized. Recent advances in tumor genomics and transcriptomics have identified several recurrent somatic/genetic alterations that are closely related with histomorphological subtypes and have therefore, greatly improved our understanding of HCC pathogenesis. Pathologic subtyping allows for a diagnosis which is clinically helpful and can have important implication in patient prognostication as some of these subtypes are extremely aggressive with vascular invasion, early recurrence, and worst outcomes. Several targeted treatments are now being considered in HCC, and the reporting of subtypes may be quite useful for personalized therapeutic purpose. This manuscript reviews the recently identified histomorphological subtypes and molecular alterations in HCC.

Can primary hepatocellular carcinoma histomorphology predict extrahepatic metastasis?

Studies comparing the histomorphologic features and phenotypic heterogeneity between primary and its corresponding metastatic hepatocellular carcinoma (HCC) are lacking. The aim of this study was to assess and compare the histomorphologic features and heterogeneity between primary and metastatic HCC. A total of 39 cases with both primary and metastatic tissues were identified from pathology archives (2000-2019). The common sites of metastasis included lung (28.21%), abdominal cavity (25.64%), lymph nodes (20.51%), bone (17.95%), soft tissue (15.38%), and adrenal gland (10.26%). Both the primary and metastatic tumors showed heterogeneity in intratumoral histologic patterns (87.18% and 76.92%, respectively). The most common histologic pattern was solid in both primary (61.54%) and metastases (56.41%), followed by macrotrabecular in primary (17.95%) and metastases (10.26%). Among HCC-subtypes, macrotrabecular-massive HCC was the most common subtype in both primary and metastases (28.21% each). Primary tumors in noncirrhotic livers were more likely to have larger size and microvascular invasion than those in cirrhotic livers. The histomorphology (histologic pattern, subtype, and grade) between the primary and metastases was discordant in about 50% cases (48.72%, 48.72%, and 51.28%, respectively). Our findings exhibit significant intratumoral heterogeneity and histomorphologic discordance between primary and metastatic HCCs. The solid and macrotrabecular histologic patterns and the macrotrabecular-massive subtype were the most common histomorphologic features seen in primary tumors associated with metastasis. Further studies to identify and explore different pathways that promote HCC metastasis and to compare the differences between primary and metastatic tumors on a larger cohort are needed to better understand the pathogenesis of metastasis.

Host Epigenetic Alterations and Hepatitis B Virus-Associated Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most frequent primary malignancy of the liver and a leading cause of cancer-related deaths worldwide. Although much progress has been made in HCC drug development in recent years, treatment options remain limited. The major cause of HCC is chronic hepatitis B virus (HBV) infection. Despite the existence of a vaccine, more than 250 million individuals are chronically infected by HBV. Current antiviral therapies can repress viral replication but to date there is no cure for chronic hepatitis B. Of note, inhibition of viral replication reduces but does not eliminate the risk of HCC development. HBV contributes to liver carcinogenesis by direct and indirect effects. This review summarizes the current knowledge of HBV-induced host epigenetic alterations and their association with HCC, with an emphasis on the interactions between HBV proteins and the host cell epigenetic machinery leading to modulation of gene expression.

Small Steatotic HCC: A Radiological Variant Associated With Improved Outcome After Ablation

Percutaneous thermal ablation is a validated treatment option for small hepatocellular carcinoma (HCC). Steatotic HCC can be reliably detected by magnetic resonance imaging. To determine the clinical relevance of this radiological variant, we included 235 patients (cirrhosis in 92.3%, classified Child-Pugh A in 97%) from a prospective database on percutaneous thermal ablation for <3 cm HCC. Among these patients, 52 (22.1%) had at least one steatotic HCC nodule. Nonalcoholic steatohepatitis was more frequent in patients with than without steatotic HCC (P = 0.057), whereas body mass index, diabetes mellitus, liver steatosis, and liver fat content did not differ between groups. Liver disease was less advanced in patients with than without steatotic HCC: lower total bilirubin ( - 2.1 µmol/L; P = 0.035), higher albumin (+0.8 g/L; P = 0.035), and lower Model for End-Stage Liver Disease score (-0.8; P = 0.014). Tumor phenotype was less aggressive in patients with steatotic HCC: lower alpha-fetoprotein (AFP) concentration (P = 0.019), less frequent AFP > 100 ng/mL (P = 0.045), and multifocality (P = 0.015). During the follow-up (median: 28.3 months), overall mortality (3.8% vs. 23.5%; P = 0.001) and HCC-specific mortality (0.0% vs. 14.2%; P = 0.002) rates were lower in patients with steatotic HCC. Early (<2 years) recurrence was also less frequent (32.7% vs. 49.2%; P = 0.041). The mean time to intrahepatic distant recurrence (16.4 vs. 9 months, P = 0.006) and the median time to recurrence and recurrence-free survival (32.4 vs. 18.6 months, P = 0.024 and 30.4 vs. 16.4 months, P = 0.018) were longer in patients with steatotic versus nonsteatotic HCC. The 3-year overall survival was 94.4% and 70.9% in steatotic and nonsteatotic HCC (P = 0.008). In multivariate analysis, steatotic HCC (hazard ratio = 0.12; P = 0.039) and AFP (HR=1.002; P < 0.001) independently predicted overall survival. Conclusion: Small steatotic HCC detected by magnetic resonance imaging is associated with a less aggressive tumor phenotype. In patients with such radiological variant, percutaneous thermal ablation results in improved outcome.

AICAR and compound C negatively modulate HCC-induced primary human hepatic stellate cell activation in vitro

Tumor stroma and microenvironment have been shown to affect hepatocellular carcinoma (HCC) growth, with activated hepatic stellate cells (HSC) as a major contributor in this process. Recent evidence suggests that the energy sensor adenosine monophosphate-activated kinase (AMPK) may mediate a series of essential processes during carcinogenesis and HCC progression. Here, we investigated the effect of different HCC cell lines with known TP53 or CTNBB1 mutations on primary human HSC activation, proliferation, and AMPK activation. We show that conditioned media obtained from multiple HCC cell lines differently modulate human hepatic stellate cell (hHSC) proliferation and hHSC AMPK activity in a paracrine manner. Pharmacological treatment of hHSC with AICAR and Compound C inhibited the HCC-induced proliferation/activation of hHSC through AMPK-dependent and AMPK-independent mechanisms, which was further confirmed using mouse embryonic fibroblasts (MEFs) deficient of both catalytic AMPKα isoforms (AMPK^α1/α2-/-) and wild type (wt) MEF. Both compounds induced S-phase cell-cycle arrest and, in addition, AICAR inhibited the mTORC1 pathway by inhibiting phosphorylation of 4E-BP1 and S6 in hHSC and wt MEF. Data mining of the Cancer Genome Atlas (TCGA) and the Liver Cancer (LICA-FR) showed that AMPKα1 (PRKAA1) and AMPKα2 (PRKAA2) expression differed depending on the mutation (TP53 or CTNNB1), tumor grading, and G1-G6 classification, reflecting the heterogeneity in human HCC. Overall, we provide evidence that AMPK modulating pharmacological agents negatively modulate HCC-induced hHSC activation and may therefore provide a novel approach to target the mutual, tumor-promoting interactions between hHSC and HCC.NEW & NOTEWORTHY HCC is marked by genetic heterogeneity and activated hepatic stellate cells (HSC) are considered key players during HCC development. The paracrine effect of different HCC cell lines on the activation of primary hHSC was accompanied by differential AMPK activation depending on the HCC line used. Pharmacological treatment inhibited the HCC-induced hHSC activation through AMPK-dependent and AMPK-independent mechanisms. This heterogenic effect on HCC-induced AMPK activation was confirmed by data mining TCGA and LICA-FR databases.

Prognostic Cancer Gene Expression Signatures: Current Status and Challenges

Current staging systems of cancer are mainly based on the anatomical extent of disease. They need refinement by biological parameters to improve stratification of patients for tumor therapy or surveillance strategies. Thanks to developments in genomic, transcriptomic, and big-data technologies, we are now able to explore molecular characteristics of tumors in detail and determine their clinical relevance. This has led to numerous prognostic and predictive gene expression signatures that have the potential to establish a classification of tumor subgroups by biological determinants. However, only a few gene signatures have reached the stage of clinical implementation so far. In this review article, we summarize the current status, and present and future challenges of prognostic gene signatures in three relevant cancer entities: breast cancer, colorectal cancer, and hepatocellular carcinoma.

Global DNA hypermethylation pattern and unique gene expression signature in liver cancer from patients with Indigenous American ancestry

Hepatocellular carcinoma (HCC) usually afflicts individuals in their maturity after a protracted liver disease. Contrasting with this pattern, the age structure of HCC in Andean people displays a bimodal distribution with half of the patients developing HCC in adolescence and early adulthood. To deepen our understanding of the molecular determinants of the disease in this population, we conducted an integrative analysis of gene expression and DNA methylation in HCC developed by 74 Peruvian patients, including 39 adolescents and young adults. While genome-wide hypomethylation is considered as a paradigm in human HCCs, our analysis revealed that Peruvian tumors are associated with a global DNA hypermethylation. Moreover, pathway enrichment analysis of transcriptome data characterized an original combination of signatures. Peruvian HCC forgoes canonical activations of IGF2, Notch, Ras/MAPK, and TGF-β signals to depend instead on Hippo/YAP1, MYC, and Wnt/β-catenin pathways. These signatures delineate a homogeneous subtype of liver tumors at the interface of the proliferative and non-proliferative classes of HCCs. Remarkably, the development of this HCC subtype occurs in patients with one of the four Native American mitochondrial haplogroups A-D. Finally, integrative characterization revealed that Peruvian HCC is apparently controlled by the PRC2 complex that mediates cell reprogramming with massive DNA methylation modulating gene expression and pinpointed retinoid signaling as a potential target for epigenetic therapy.

A Case of Lymphocyte-Rich Hepatocellular Carcinoma in a Patient Who Was Treated for Colon Cancer

Hepatocellular carcinoma (HCC) primarily originates in the liver with hepatic differentiation. However, HCCs are not homogenous, and approximately 35% of HCC cases are classified as histopathological variants that present distinct pathologic characteristics. In particular, the lymphocyte-rich variant is the rarest subtype accounting for less than 1% of HCCs, which is not well known to date about molecular features and pathophysiology. Herein, we present a case of a patient who was suspected of metastatic liver cancer and confirmed as lymphocyte-rich HCC pathologically. A 78-year-old woman who underwent a right hemicolectomy for colon cancer was referred to our hospital for a newly detected liver mass. We could not make a decision because of insufficient evidence for diagnosis from imaging studies. After resection, we found that it was a lymphocyte-rich HCC. The pathologic features and prognostic trends of this subtype are also discussed.

Notch activity characterizes a common hepatocellular carcinoma subtype with unique molecular and clinicopathologic features

BACKGROUND & AIMS

The hepatocyte Notch pathway is a pathogenic factor in non-alcoholic steatohepatitis (NASH)-associated fibrosis, but its role in hepatocellular carcinoma (HCC) is less well defined. Herein, we aimed to characterize the molecular and clinical features of Notch-active human HCC, and to investigate the mechanisms by which Notch affects NASH-driven HCC.

METHODS

Using a 14-gene Notch score, we stratified human HCCs from multiple comprehensively profiled datasets. We performed gene set enrichment analyses to compare Notch-active HCCs with published HCC subtype signatures. Next, we sorted Notch-active hepatocytes from Notch reporter mice for RNA sequencing and characterized Notch-active tumors in an HCC model combining a carcinogen and a NASH-inducing diet. We used genetic mouse models to manipulate hepatocyte Notch to investigate the sufficiency and necessity of Notch in NASH-driven tumorigenesis.

RESULTS

Notch-active signatures were found in ~30% of human HCCs that transcriptionally resemble cholangiocarcinoma-like HCC, exhibiting a lack of activating CTNNB1 (β-catenin) mutations and a generally poor prognosis. Endogenous Notch activation in hepatocytes is associated with repressed β-catenin signaling and hepatic metabolic functions, in lieu of increased interactions with the extracellular matrix in NASH. Constitutive hepatocyte Notch activation is sufficient to induce β-catenin-inactive HCC in mice with NASH. Notch and β-catenin show a pattern of mutual exclusivity in carcinogen-induced HCC; in this mouse model, chronic blockade of Notch led to β-catenin-dependent tumor development.

CONCLUSIONS

Notch activity characterizes a distinct HCC molecular subtype with unique histology and prognosis. Sustained Notch signaling in chronic liver diseases can drive tumor formation without acquiring specific genomic driver mutations.

LAY SUMMARY

The Notch signaling pathway is known to be involved in the pathogenesis of liver fibrosis. However, its role in liver cancer has not been well defined. Herein, we show that Notch activity is increased in a subset of liver cancers and is associated with poor outcomes. We also used a mouse model to show that aberrant Notch activity can drive cancer progression in obese mice.

Potential therapeutic targets in the tumor microenvironment of hepatocellular carcinoma: reversing the protumor effect of tumor-associated macrophages

In hepatocellular carcinoma patients, due to the microenvironmental specificity of liver, the tumor microenvironment exhibits high immunosuppression and drug resistance, resulting in excessive or insufficient responses to immunotherapy. The dynamic interactions between tumor cells and immune modulators in the TME significantly impact the occurrence and development of tumors, efficacy, and drug resistance, which can create a much more positive response to immunotherapy. Moreover, with the wide application of single-cell sequencing technology in the TME, increasing evidence shows an interaction network among cells. Sequencing results suggest that specific tumor-associated macrophages are a hub node, connecting different cell populations in the cell interaction network, and can could regulate tumor generation and antitumor immunity. This review focused on therapeutic targets that could be targeted to remodel the tumor microenvironment and reprogram the tumor-associated macrophage phenotype in hepatocellular carcinoma patients, thereby improving immunotherapeutic efficacy.

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.