Hepatocellular carcinoma: making sense of morphological heterogeneity, growth patterns, and subtypes

Clinicopathologic features and prognosis of steatohepatitic hepatocellular carcinoma based on varying cutoffs of tumoral steatohepatitic changes

OBJECTIVES

Steatohepatitic hepatocellular carcinoma (SH-HCC) is currently recognized as a distinct histologic subtype of HCC. The prognosis and specific criteria for determining the amount of steatohepatitis required to define SH-HCC are still unclear.

METHODS

After excluding all recognized HCC subtypes from 505 HCC cases (2010-2019), the remaining cases were categorized as conventional HCC (CV-HCC) (n = 223). The cases classified as SH-HCC (n = 171) were further divided into groups based on the percentage of steatohepatitis: 5% or more, 30% or more, and 50% or more.

RESULTS

Hepatitis C virus infection was the predominant underlying liver disease in both the CV-HCC and SH-HCC groups. Metabolic dysfunction-associated steatotic liver disease (formerly nonalcoholic fatty liver disease) was more prevalent in all cases of SH-HCC with different steatohepatitic cutoffs than in cases of CV-HCC. There were no differences in the stage of fibrosis of the background liver between the CV-HCC and SH-HCC groups. SH-HCC with different cutoffs exhibited a notable increase in the presence of glycogenated nuclei, Mallory-Denk bodies, and hyaline globules in tumor cells. Survival analysis did not reveal substantial differences in overall survival between the CV-HCC and SH-HCC groups and among patients with SH-HCC with different steatohepatitis cutoffs.

CONCLUSIONS

The degree of intratumoral steatohepatitis in patients with SH-HCC does not appear to be a notable prognostic factor. The presence of steatohepatitis in the tumor is better recognized as 1 of the histopathologic patterns of HCC.

Morphomolecular Pathology and Genomic Insights into the Cells of Origin of Cholangiocarcinoma and Combined Hepatocellular-Cholangiocarcinoma

Cholangiocarcinomas are a highly heterogeneous group of malignancies that, despite recent progress in the understanding of their molecular pathogenesis and clinical management, continue to pose a major challenge to public health. The traditional view posits that cholangiocarcinomas derive from the neoplastic transformation of cholangiocytes lining the biliary tree. However, increasing genetic and experimental evidence has recently pointed to a more complex, and nuanced, scenario for the potential cell of origin of cholangiocarcinomas. Hepatocytes as well as hepatic stem/progenitor cells are being considered as additional potential sources, depending on microenvironmental contexts, including liver injury. The hypothesis of potentially diverse cells of origin for cholangiocarcinoma, albeit controversial, is certainly not surprising given the plasticity of the cells populating the liver as well as the existence of liver cancer subtypes with mixed histologic and molecular features. This review carefully examines the current pathologic, genomic, and experimental evidence supporting the existence of multiple cells of origin of liver and biliary tract cancers, with particular focus on cholangiocarcinoma and combined hepatocellular-cholangiocarcinoma.

HepatoPredict Accurately Selects Hepatocellular Carcinoma Patients for Liver Transplantation Regardless of Tumor Heterogeneity

BACKGROUND/OBJECTIVES

Hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths rising worldwide. This is leading to an increased demand for liver transplantation (LT), the most effective treatment for HCC in its initial stages. However, current patient selection criteria are limited in predicting recurrence and raise ethical concerns about equitable access to care. This study aims to enhance patient selection by refining the HepatoPredict (HP) tool, a machine learning-based model that combines molecular and clinical data to forecast LT outcomes.

METHODS

The updated HP algorithm was trained on a two-center dataset and assessed against standard clinical criteria. Its prognostic performance was evaluated through accuracy metrics, with additional analyses considering tumor heterogeneity and potential sampling bias.

RESULTS

HP outperformed all clinical criteria, particularly regarding negative predictive value, addressing critical limitations in existing selection strategies. It also demonstrated improved differentiation of recurrence-free and overall survival outcomes. Importantly, the prognostic accuracy of HP remained largely unaffected by intra-nodule and intra-patient heterogeneity, indicating its robustness even when biopsies were taken from smaller or non-dominant nodules.

CONCLUSIONS

These findings support the usage of HP as a valuable tool for optimizing LT candidate selection, promoting fair organ allocation and enhancing patient outcomes through integrated analysis of molecular and clinical data.

Prediction of Hepatocellular Carcinoma Prognosis and Immunotherapy Response Using Mitochondrial Dysregulation Features

Hepatocellular carcinoma (HCC) is a major contributor to cancer-related deaths globally. Although there have been improvements in identifying treating the disease, patient outcomes are still unfavourable because of the significant variation in HCC. Mitochondrial-related genes (MRGs) are crucial in tumour metabolism, cell death and immune response, emerging as potential therapeutic targets. We analysed 2030 MRGs using TCGA, GEO and HCCDB18 databases. Differentially expressed genes were identified using edgeR and limma, and enrichment analysis was performed via the clusterProfiler package. A prognostic model was built using machine learning algorithms and evaluated using LOOCV. Immune infiltration was assessed with CIBERSORT, EPIC, MCPCounter and TIMER algorithms, and drug sensitivity was analysed using the CTRP and PRISM datasets. MRG expression levels are significantly associated with worse outcomes in HCC patients outperformed conventional clinical indicators in immune response revealed that individuals at high risk exhibited weaker immune responses, characterised by reduced immune scores, and elevated levels of CD8+ T cells and macrophages. Notably, high-risk patients also displayed heightened susceptibility to chemotherapy agents such as paclitaxel and irinotecan. Abnormal MRG expression serves as a significant biomarker for HCC prognosis. The developed model accurately predicts disease progression and can guide personalised treatment, especially for immune and chemotherapeutic therapies. Further validation with broader clinical samples is needed.

Clinicopathological Study on Morphological Subtypes of Hepatocellular Carcinoma: A Single Tertiary Referral Center Experience

AIM

We aimed to analyze hepatocellular carcinoma (HCC) morphological subtypes characterized according to the WHO classification and the International Collaboration on Cancer Reporting (ICCR) recommendations, and their prognostic features in a Dutch population.

METHODS AND RESULTS

This retrospective study in a tertiary referral center included the histopathological revision of 62 HCC resection specimens, obtained from 22 female and 40 male patients (median age: 67 years), in a period between 2011 and 2021 at the Maastricht University Medical Center +. Clinical data, morphological subtypes, growth pattern (GP), tumor grade, tumor extension, margins, and vascular and perineural invasion were collected. Eighteen cases were assigned a specific morphologic subtype and steatohepatic HCC was the most common in our cohort. Twenty-one tumors classified as conventional type HCC (HCC-NOS), commonly exhibiting two concurrent GPs. Twenty-three cases revealed a heterogeneous morphologic differentiation, compromising the combination of HCC-NOS with another morphologic subtype, most frequently a steatohepatitic component. Comparison of HCC-NOS and HCC with heterogeneous morphology did not show significant differences in the main clinicopathological characteristics and survival.

CONCLUSION

Although the most common morphologic subtype was steatohepatitic HCC, the majority of cases demonstrated multiple morphologic patterns. In case of HCC-NOS, heterogeneous GPs were often observed. Therefore, a histomorphological diagnosis based on a single tumor biopsy specimen may lead to incorrect classification of HCC. Sufficient tumor sampling of HCC resection specimens is required for the complete evaluation of all histomorphological features followed by correct subclassification in order to meet the clinical needs regarding prognostic relevance and patient follow-up.

A hepatocellular carcinoma model with and without parenchymal liver damage that integrates technical and pathophysiological advantages for therapy testing

Hepatocellular Carcinoma (HCC) is the most common form of primary liver cancer, with cirrhosis being its strongest risk factor. Interestingly, an increasing number of HCC cases is also observed without cirrhosis. We developed an HCC model via intrasplenic injection of highly tumorigenic HCC cells, which, due to cellular tropism, invade the liver and allow for a controllable disease progression. Specifically, C57BL/6JRj mice were intrasplenically inoculated with Dt81Hepa1-6 HCC cells, with a subgroup pre-treated with CCl4 to induce cirrhosis (C-HCC). At four weeks post-inoculation, mice were sacrificed, and diseased livers were analyzed via histology, flow cytometry, and RT-qPCR to profile the extracellular matrix (ECM), angiogenesis, and immune cells. In addition, tumor-bearing mice were treated with the first-line therapy, AtezoBev, to assess therapeutic responsiveness of the model. Dt81Hepa1-6 cells displayed similar gene expression as human HCC. After intrasplenic injection, all mice developed multifocal disease. C-HCC mice had a significantly higher tumor load than non-cirrhotic HCC mice. Both HCC and C-HCC models displayed extensive ECM formation, increased levels of vascularization, and immune cell infiltration compared to healthy and non-cancerous cirrhotic livers. AtezoBev treatment produced robust antitumor efficacy, validating the model's suitability for therapy testing. In conclusion, we established a rapidly developing and high-yield HCC model through a simple intrasplenic injection, with or without cirrhotic damage. The model overexpressed key human HCC genes and showed high responsiveness to first-line treatment. Our model uniquely combines all the above-mentioned features, promoting its use towards HCC therapy testing.

RNA nanotherapeutics for hepatocellular carcinoma treatment

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, particularly due to the limited effectiveness of current therapeutic options for advanced-stage disease. The efficacy of traditional treatments is often compromised by the intricate liver microenvironment and the inherent heterogeneity. RNA-based therapeutics offer a promising alternative, utilizing the innovative approach of targeting aberrant molecular pathways and modulating the tumor microenvironment. The integration of nanotechnology in this field, through the development of advanced nanocarrier delivery systems, especially lipid nanoparticles (LNPs), polymer nanoparticles (PNPs), and bioinspired vectors, enhances the precision and efficacy of RNA therapies. This review highlights the significant progress in RNA nanotherapeutics for HCC treatment, covering micro RNA (miRNA), small interfering RNA (siRNA), message RNA (mRNA), and small activating RNA (saRNA) mediated gene silencing, therapeutic protein restoration, gene activation, cancer vaccines, and concurrent therapy. It further comprehensively discusses the prevailing challenges within this therapeutic landscape and provides a forward-looking perspective on the potential of RNA nanotherapeutics to transform HCC treatment.

Pathomics signatures and cuproptosis-related genes signatures for prediction of prognosis in patients with hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a common malignant tumor with high heterogeneity and poor prognosis, so early prediction and treatment are still difficult. Cuproptosis is a newly discovered type of programmed cell death that has been shown to be closely related to the occurrence and progression of HCC. Cancer morphology is influenced by genetic drivers, and computational pathology methods typically use tissue images such as entire slide images as input to predict clinical or genetic features. Therefore, the comprehensive analysis of pathological features and genomic data provides a feasible way to explore the potential mechanism of the tumor. The objective of this study was to develop a prediction model for HCC prognosis based on the pathomics signatures (PS) and the genomics signatures (GS).

Methods

A dataset comprising 315 HCC patients was randomly divided into a training set (n=200) and a validation set (n=115). Prognostic models related to PS and GS were constructed by univariate and multivariate Cox regression analyses and least absolute shrinkage and selection operator (LASSO) regression analysis. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve, univariate and multivariate Cox analyses, and nomogram were used to evaluate the predictive performance of the prognostic model. The prognostic value of the model was internally validated.

Results

A prognostic model incorporating clinical features, PS, and GS was developed using Cox regression analysis and LASSO regression analyses. Kaplan-Meier survival analysis revealed statistically significant differences in survival time between high-risk and low-risk subgroups in both the training and validation datasets (PS: P=0.003 and <0.001, respectively; GS: P=0.008 and 0.004, respectively). The time-dependent ROC curve showed favorable predictive value for survival in both the training and validation sets. The area under the ROC curves at 1, 3, and 5 years was 0.750, 0.830, and 0.870 in the training set, and 0.780, 0.810, and 0.760 in the validation set, respectively. A nomogram model based on the risk model score could effectively predict the survival probability of HCC patients. The calibration curves further demonstrated the good predictive capability of the nomogram model.

Conclusions

The prognostic model incorporating PS and GS could effectively predict the prognosis of HCC patients.

Heterogeneity of hepatocellular carcinoma: from mechanisms to clinical implications

Hepatocellular Carcinoma (HCC) is one of the most common types of primary liver cancer. Current treatment options have limited efficacy against this malignancy, primarily owing to difficulties in early detection and the inherent resistance to existing drugs. Tumor heterogeneity is a pivotal factor contributing significantly to treatment resistance and recurrent manifestations of HCC. Intratumoral heterogeneity is an important aspect of the spectrum of complex tumor heterogeneity and contributes to late diagnosis and treatment failure. Therefore, it is crucial to thoroughly understand the molecular mechanisms of how tumor heterogeneity develops. This review aims to summarize the possible molecular dimensions of tumor heterogeneity with an emphasis on intratumoral heterogeneity, evaluate its profound impact on the diagnosis and therapeutic strategies for HCC, and explore the suitability of appropriate pre-clinical models that can be used to best study tumor heterogeneity; thus, opening new avenues for cancer treatment.

Understanding the heterogeneity in liver hepatocellular carcinoma with a special focus on malignant cell through single-cell analysis

INTRODUCTION

Hepatocellular carcinoma (HCC) is the most common form of liver cancer globally and remains a major cause of cancer-related deaths. HCC exhibits significant intra-tumoral and interpatient heterogeneity, impacting treatment efficacy and patient prognosis.

METHODS

We acquired transcriptome data from the TCGA and ICGC databases, as well as liver cancer chip data from the GEO database, and processed the data for subsequent analysis. We also obtained single cell data from the GEO database and performed data analysis using the Seurat package. To further investigate epithelial cell subgroups and their copy number variations, we used the Seurat workflow for subgroup classification and the InferCNV software for CNV analysis, utilizing endothelial cells as a reference. Pseudo-time analysis and transcription factor analysis of epithelial cells were performed using the monocle2 and SCENIC software, respectively. To assess intercellular communication, we employed the CellChat package to identify potential ligand-receptor interactions. We also analyzed gene expression differences and conducted enrichment analysis using the limma and clusterProfiler packages. Additionally, we established tumor-related risk characteristics using Cox analysis and Lasso regression, and predicted immunotherapy response using various datasets.

RESULTS

The samples were classified into 23 clusters, with malignant epithelial cells being the majority. Trajectory analysis revealed the differentiation states of the malignant epithelial cells, with cluster 1 being in the terminal state. Functional analysis revealed higher aggressiveness and epithelial-mesenchymal transition (EMT) scores in cluster 1, indicating a higher propensity for metastasis. RBP4+ tumor cells were highly enriched with hypoxia process and intensive cell-to-cell communication. A prognostic model was established, and immune infiltration analysis showed increased infiltration in the high-risk group. TP53 demonstrated significant differences in mutation rate between the two risk groups. Validation analysis confirmed the up-regulation of model genes, including AKR1B10, ARL6IP4, ATP6V0B, and BSG in tumor tissues.

CONCLUSION

A prognostic model was established based on HCC malignant cell associated gene signature, displaying decent prognosis guiding effectiveness in the multiple cohorts. The study provided comprehensive insights into the heterogeneity and potential therapeutic targets of LIHC.

Quantitative information from gadobenate dimeglumine-enhanced MRI can predict proliferative subtype of solitary hepatocellular carcinoma: a multicenter retrospective study

OBJECTIVES

To investigate the value of quantitative parameters derived from gadobenate dimeglumine-enhanced magnetic resonance imaging (MRI) for predicting molecular subtype of hepatocellular carcinoma (HCC) and overall survival.

METHODS

This multicenter retrospective study included 218 solitary HCC patients who underwent gadobenate dimeglumine-enhanced MRI. All HCC lesions were resected and pathologically confirmed. The lesion-to-liver contrast enhancement ratio (LLCER) and lesion-to-liver contrast (LLC) were measured in the hepatobiliary phase. Potential risk factors for proliferative HCC were assessed by logistic regression. The ability of LLCER and LLC to predict proliferative HCC was assessed by the receiver operating characteristic (ROC) curve. Prognostic factors were evaluated using the Cox proportional hazards regression model for survival outcomes.

RESULTS

LLCER was an independent predictor of proliferative HCC (odds ratio, 0.015; 95% confidence interval [CI], 0.008-0.022; p < 0.001). The area under the ROC curve was 0.812 (95% CI, 0.748-0.877), higher than that of LLC, alpha-fetoprotein > 100 ng/ml, satellite nodules, and rim arterial phase hyperenhancement (all p ≤ 0.001). HCC patients with LLCER < -4.59% had a significantly higher incidence of proliferative HCC than those with the LLCER ≥ -4.59%. During the follow-up period, LLCER was an independent predictor of overall survival (hazard ratio, 0.070; 95% CI, 0.015-0.324; p = 0.001) in HCC patients.

CONCLUSIONS

Gadobenate dimeglumine-enhanced quantitative parameter in the hepatobiliary phase can predict the proliferative subtype of solitary HCC with a moderately high accuracy.

CLINICAL RELEVANCE STATEMENT

Quantitative information from gadobenate dimeglumine-enhanced MRI can provide crucial information on hepatocellular carcinoma subtypes. It might be valuable to design novel therapeutic strategies, such as targeted therapies or immunotherapy.

KEY POINTS

• The lesion-to-liver contrast enhancement ratio (LLCER) is an independent predictor of proliferative hepatocellular carcinoma (HCC). • The ability of LLCER to predict proliferative HCC outperformed lesion-to-liver contrast, alpha-fetoprotein > 100 ng/ml, satellite nodules, and rim arterial phase hyperenhancement. • HCC patients with LLCER < -4.59% had a significantly higher incidence of proliferative HCC than those with the LLCER ≥ -4.59%.

Battle of the biopsies: Role of tissue and liquid biopsy in hepatocellular carcinoma

The diagnosis and management of hepatocellular carcinoma (HCC) have improved significantly in recent years. With the introduction of immunotherapy-based combination therapy, there has been a notable expansion in treatment options for patients with unresectable HCC. Simultaneously, innovative molecular tests for early detection and management of HCC are emerging. This progress prompts a key question: as liquid biopsy techniques rise in prominence, will they replace traditional tissue biopsies, or will both techniques remain relevant? Given the ongoing challenges of early HCC detection, including issues with ultrasound sensitivity, accessibility, and patient adherence to surveillance, the evolution of diagnostic techniques is more relevant than ever. Furthermore, the accurate stratification of HCC is limited by the absence of reliable biomarkers which can predict response to therapies. While the advantages of molecular diagnostics are evident, their potential has not yet been fully harnessed, largely because tissue biopsies are not routinely performed for HCC. Liquid biopsies, analysing components such as circulating tumour cells, DNA, and extracellular vesicles, provide a promising alternative, though they are still associated with challenges related to sensitivity, cost, and accessibility. The early results from multi-analyte liquid biopsy panels are promising and suggest they could play a transformative role in HCC detection and management; however, comprehensive clinical validation is still ongoing. In this review, we explore the challenges and potential of both tissue and liquid biopsy, highlighting that these diagnostic methods, while distinct in their approaches, are set to jointly reshape the future of HCC management.

Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma

Background

This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response.

Methods

Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients.

Results

Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients.

Conclusion

Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.

Advances in Histological and Molecular Classification of Hepatocellular Carcinoma

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

Cell line-specific features of 3D chromatin organization in hepatocellular carcinoma

Liver cancer, particularly hepatocellular carcinoma (HCC), poses a significant global threat to human lives. To advance the development of innovative diagnostic and treatment approaches, it is essential to examine the hidden features of HCC, particularly its 3D genome architecture, which is not well understood. In this study, we investigated the 3D genome organization of four HCC cell lines-Hep3B, Huh1, Huh7, and SNU449-using in situ Hi-C and assay for transposase-accessible chromatin sequencing. Our findings revealed that HCC cell lines had more long-range interactions, both intra-and interchromosomal, compared to human mammary epithelial cells (HMECs). Unexpectedly, HCC cell lines displayed cell line-specific compartmental modifications at the megabase (Mb) scale, which could potentially be leveraged in determining HCC subtypes. At the sub-Mb scale, we observed decreases in intra-TAD (topologically associated domain) interactions and chromatin loops in HCC cell lines compared to HMECs. Lastly, we discovered a correlation between gene expression and the 3D chromatin architecture of SLC8A1, which encodes a sodium-calcium antiporter whose modulation is known to induce apoptosis by comparison between HCC cell lines and HMECs. Our findings suggest that HCC cell lines have a distinct 3D genome organization that is different from those of normal and other cancer cells based on the analysis of compartments, TADs, and chromatin loops. Overall, we take this as evidence that genome organization plays a crucial role in cancer phenotype determination. Further exploration of epigenetics in HCC will help us to better understand specific gene regulation mechanisms and uncover novel targets for cancer treatment.

MLXIPL promotes the migration, invasion, and glycolysis of hepatocellular carcinoma cells by phosphorylation of mTOR

BACKGROUND

Hepatocellular carcinoma (HCC) is associated with a high occurrence, mortality, and poor prognosis. MLX interacting protein like (MLXIPL) is an important regulator of glucolipid metabolism and is involved in tumor progression. We aimed to clarify the role of MLXIPL in HCC and its underlying mechanisms.

METHODS

The level of MLXIPL was predicted using bioinformatic analysis and verified using quantitative real-time PCR (qPCR), immunohistochemical analysis, and western blot. We assessed the effects of MLXIPL on biological behaviors using the cell counting kit-8, colony formation, and Transwell assay. Glycolysis was evaluated using the Seahorse method. The interaction between MLXIPL and mechanistic target of rapamycin kinase (mTOR) was confirmed using RNA immunoprecipitation and co-immunoprecipitation. mTOR expression was detected in HCC cells using qPCR, immunofluorescence analysis, and western blot.

RESULTS

The results showed that MLXIPL levels were elevated in both HCC tissues and HCC cell lines. Knockdown of MLXIPL impeded HCC cell growth, invasion, migration, and glycolysis. Moreover, MLXIPL combined with mTOR to induce phosphorylation of mTOR. Activated mTOR abrogated the effects on cellular processes induced by MLXIPL.

CONCLUSION

MLXIPL promoted the malignant progression of HCC by activating phosphorylation of mTOR, suggesting an important role of the combination of MLXIPL and mTOR in HCC.

A water-soluble polysaccharide from Eucommia folium: the structural characterization and anti-tumor activity in vivo

In this study, a water-soluble polysaccharide from Eucommia folium was extracted by hot water and purified using Sephadex G-200 gel columns. The results showed that the purified fraction (EFP) has a molecular weight of 9.98 × 10⁵ Da and consisted of rhamnose, arabinose, galactose, glucose, mannose, xylose, galacturonic acid, and glucuronic acid (molar ratio: 0.226: 1.739: 2.183: 1: 0.155: 0.321: 0.358: 0.047). The combination of infrared spectroscopy and NMR analysis proved that EFP is an acidic polysaccharide whose main chain consists of α-L-Araf-(1 → , → 3,5)-α-Araf-(1 → , → 3)-β-Galp-(1 → , → 3,6)-β-Glcp-(1 → , → 2)-α-D-Manp-(1 → , → 4)-α-GalpA-(1 → , → 2,4)-α-Rhap-(1 → . In addition, the in vivo antitumoral activity of EFP was studied using a H22 tumor-bearing mice model. EFP effectively inhibited tumor growth in mice following intragastric administration. By Combining with the results of the apoptosis assay and JC-1 staining analysis, we confirmed that EFP induces apoptosis through the mitochondrial pathway. Furthermore, cell cycle analysis demonstrated that EFP blocks the cell cycle at S phase.

Silva cumulative score and its relationship with prognosis in Endocervical adenocarcinoma

Background

The Silva system has been demonstrated to have a good predictive value of lymph node metastasis (LNM) in endocervical adenocarcinoma (EAC). Tumours were classified based on the highest identified pattern of invasion in this system, this may not exactly reflect the true situation when it presents with a “mixed pattern” in some cases. Recent study has shown that patients with lymphovascular invasion (LVI) have worse prognosis in EAC. Here we design a Silva cumulative score (SCS) system which also combined the LVI status to explore its prognostic role in EAC patients.

Methods

A total of 120 patients with EAC were included in this study. Clinicopathological characteristics were retrospectively retrieved from the medical records and follow-up data were obtained. The clinicopathological information included age at diagnosis, depth of invasion (DOI), LNM, LVI, Silva classification, and SCS. SCS is a classification system based on the sum score of different Silva pattern which is founded on morphological phenomena. The relationships between the pathological characteristics and prognoses were analyzed.

Results

According to the Silva system, 11 (9.2%), 22 (18.3%) and 87 (72.5%) patients had patterns A, B, and C, respectively. Patients with pattern C had the highest incidence of LVI and LNM (p < 0.05). Although the Kaplan-Meier curves demonstrated that survival decreased with increasing Silva classification for A-C cancers, there was no statistically significant difference [disease-free survival (DFS): p = 0.181; overall survival (OS): p = 0.205]. There were 45 cases presented as mixed-type of Silva patterns. According to the SCS, 23 cases (19.2%) were rated as grade I, 31 cases (25.8%) as grade II and 66 (55.0%) cases as grade III. Patients with SCS grade III had the highest incidence of LVI and LNM (p < 0.05). Kaplan–Meier analysis revealed that patients with higher SCS had significantly shorter DFS and OS than those with lower SCS (p < 0.05). High SCS was an independent predictor of poorer OS and DFS (p < 0.05) in patients with EAC.

Conclusions

The application of the Silva system could effectively predict the LNM of patients and may be helpful in selecting an appropriate surgical procedure. The SCS system we designed showed a good predictive value for DFS and OS in EAC.

Hepatocellular Carcinoma in a Free-Ranging Three-Toed Sloth (Bradypus variegatus)

The increasing interest of tumors in wildlife is important for biodiversity conservation and for monitoring environmental agents and/or contaminants with potential impact on human health. Here we described the occurrence of hepatocellular carcinoma (HCC) in noncirrhotic liver of a free-ranging three-toed sloth (Bradypus variegatus) from the Atlantic Forest biome in Brazil. The HCC showed a moderate mononuclear inflammatory infiltrate within the tumor tissue but with no inflammation and fibrosis in the adjacent liver tissue. Upon immunohistochemistry, neoplastic cells were diffusely positive for HepPar-1 and glutamine-synthetase presenting an irregular and random immunostaining pattern; β-catenin was positive in the cytoplasmic membrane of malignant hepatocytes; and cytokeratin 19 immunostaining was restricted to bile duct epithelial cells. The liver tissue was negative for HBV-like and HCV-like viruses assessed by molecular tests. The potential similarity of pathogenesis may reinforce the need for research on environmental and/or infectious agents associated with HCC that may contribute to the understanding of cancer in wildlife.

Etiology, Pathogenesis, Diagnosis, and Practical Implications of Hepatocellular Neoplasms

Hepatocellular carcinoma (HCC), a major global contributor of cancer death, usually arises in a background of chronic liver disease, as a result of molecular changes that deregulate important signal transduction pathways. Recent studies have shown that certain molecular changes of hepatocarcinogenesis are associated with clinicopathologic features and prognosis, suggesting that subclassification of HCC is practically useful. On the other hand, subclassification of hepatocellular adenomas (HCAs), a heterogenous group of neoplasms, has been well established on the basis of genotype–phenotype correlations. Histologic examination, aided by immunohistochemistry, is the gold standard for the diagnosis and subclassification of HCA and HCC, while clinicopathologic correlation is essential for best patient management. Advances in clinico-radio-pathologic correlation have introduced a new approach for the diagnostic assessment of lesions arising in advanced chronic liver disease by imaging (LI-RADS). The rapid expansion of knowledge concerning the molecular pathogenesis of HCC is now starting to produce new therapeutic approaches through precision oncology. This review summarizes the etiology and pathogenesis of HCA and HCC, provides practical information for their histologic diagnosis (including an algorithmic approach), and addresses a variety of frequently asked questions regarding the diagnosis and practical implications of these neoplasms.

LncRNA ZNF674-AS1 Hinders Proliferation and Invasion of Hepatic Carcinoma Cells through the Glycolysis Pathway

Purpose. Long noncoding RNAs (lncRNAs) play important roles in regulating various functions of cells at the levels of transcription and posttranscription. Extensive investigations have illustrated that lncRNAs are critical in the glucose metabolism of tumor cells, but their mechanisms of action need to be further explored. This study evaluates the role of lncRNA ZNF674-AS1 on the apoptosis and proliferation of human hepatic carcinoma cells in vitro through the glucose metabolism and its related mechanisms. Methods. Real-time quantitative PCR was employed for detecting the level of expressions for lncRNA ZNF674-AS1 in liver cancer tissues (25 cases), paracancerous tissues, and liver cancer cell lines. The lncRNA ZNF674-AS1 high expression cell strain was constructed by the lentiviral overexpression vector. CCK-8, plate colony formation, transwell assay, lactate production, glucose consumption, and ATP levels were used to detect the change of cell proliferation, colony formation, migration, and invasion, as well as glycolytic capability. Western blot was carried out to detect the expression of HK2, PFKL, PKM2, GLUT1, and PKM1, which are the key proteins of glycolysis in cells. Result. The lncRNA ZNF674-AS1 was undesirably expressed in liver cancer cell lines and tissues. Cell function assessments showed that compared with the blank control group (vector), overexpression of lncRNA ZNF674-AS1 could substantially hinder the proliferation, colony formation, migration, and invasion capability of liver cancer cells. Furthermore, overexpression of lncRNA ZNF674-AS1 could inhibit cell glycolysis (inhibit glucose consumption and reduce intracellular lactate and ATP levels) by inhibiting the expression of key proteins (such as PFKL, HK2, PKM2, and GLUT1) in the process of glycolysis. Conclusion. As a tumor repressor gene, lncRNA ZNF674-AS1 inhibits the expression of key proteins in glycolysis to inhibit glycolysis level, thereby inhibiting cell migration and proliferation. Therefore, lncRNA ZNF674-AS1 could be a potent therapeutic target or a novel diagnostic molecule for patients suffering from liver cancer.

Morphomolecular Classification Update on Hepatocellular Adenoma, Hepatocellular Carcinoma, and Intrahepatic Cholangiocarcinoma

Hepatocellular adenomas (HCAs), hepatocellular carcinomas (HCCs), and intrahepatic cholangiocarcinomas (iCCAs) are a highly heterogeneous group of liver tumors with diverse pathomolecular features and prognoses. High-throughput gene sequencing techniques have allowed discovery of distinct genetic and molecular underpinnings of these tumors and identified distinct subtypes that demonstrate varied clinicobiologic behaviors, imaging findings, and complications. The combination of histopathologic findings and molecular profiling form the basis for the morphomolecular classification of liver tumors. Distinct HCA subtypes with characteristic imaging findings and complications include HNF1A-inactivated, inflammatory, β-catenin-activated, β-catenin-activated inflammatory, and sonic hedgehog HCAs. HCCs can be grouped into proliferative and nonproliferative subtypes. Proliferative HCCs include macrotrabecular-massive, TP53-mutated, scirrhous, clear cell, fibrolamellar, and sarcomatoid HCCs and combined HCC-cholangiocarcinoma. Steatohepatitic and β-catenin-mutated HCCs constitute the nonproliferative subtypes. iCCAs are classified as small-duct and large-duct types on the basis of the level of bile duct involvement, with significant differences in pathogenesis, molecular signatures, imaging findings, and biologic behaviors. Cross-sectional imaging modalities, including multiphase CT and multiparametric MRI, play an essential role in diagnosis, staging, treatment response assessment, and surveillance. Select imaging phenotypes can be correlated with genetic abnormalities, and identification of surrogate imaging markers may help avoid genetic testing. Improved understanding of morphomolecular features of liver tumors has opened new areas of research in the targeted therapeutics and management guidelines. The purpose of this article is to review imaging findings of select morphomolecular subtypes of HCAs, HCCs, and iCCAs and discuss therapeutic and prognostic implications. Online supplemental material is available for this article. ^©RSNA, 2022.

Morphological heterogeneity in beta-catenin-mutated hepatocellular carcinomas: implications for tumor molecular classification

Beta-catenin (CTNNB1) is commonly mutated in hepatocellular carcinoma (HCC). CTNNB1-mutated HCC has important clinical correlates, such as being immune cold and less likely to respond to immune checkpoint inhibitor therapies. It remains unclear, however, if they are a morphologically homogenous group of tumors. To better understand the association between the morphology, CTNNB1 mutations, and other molecular features, a detailed study of 338 The Cancer Genome Atlas cases was performed. A characteristic histological morphology was strongly associated with CTNNB1 mutations but was present in only 58% of CTNNB1-mutated HCCs. Tumors with APC mutations tended to have the classic morphology; those with AXIN mutations did not. Pseudoglands are a key feature of the classic morphology, and they were associated with CTNNB1 mutations, male gender, specific CTNNB1 mutation site, and lack of TP53 mutations. Differential gene expression analysis stratified by the presence/absence of pseudoglands identified 60 differentially expressed genes (FDR <5%); clustering according to these differentially expressed genes revealed three groups of tumors, one with pseudoglands and a strong association with genes regulated by Wnt signaling; within this group, TP53 mutations were associated with a loss of the typical morphology of CTNNB1-mutated HCCs. When stratified by gender, further differential gene expression showed Wnt-regulated genes were associated with pseudoglands in men but not women. These findings indicate HCC with CTNNB1 mutations are morphologically heterogeneous, with gene penetrance for morphology dependent in part on gender, specific CTNNB1 mutations, and co-occurring TP53 mutations. This heterogeneity has important implications for the classification of HCC.

Wnt/β-Catenin Signaling as a Driver of Hepatocellular Carcinoma Progression: An Emphasis on Molecular Pathways

Liver cancers cause a high rate of death worldwide and hepatocellular carcinoma (HCC) is considered as the most common primary liver cancer. HCC remains a challenging disease to treat. Wnt/β-catenin signaling pathway is considered a tumor-promoting factor in various cancers; hence, the present review focused on the role of Wnt signaling in HCC, and its association with progression and therapy response based on pre-clinical and clinical evidence. The nuclear translocation of β-catenin enhances expression level of genes such as c-Myc and MMPs in increasing cancer progression. The mutation of CTNNB1 gene encoding β-catenin and its overexpression can lead to HCC progression. β-catenin signaling enhances cancer stem cell features of HCC and promotes their growth rate. Furthermore, β-catenin prevents apoptosis in HCC cells and increases their migration via triggering EMT and upregulating MMP levels. It is suggested that β-catenin signaling participates in mediating drug resistance and immuno-resistance in HCC. Upstream mediators including ncRNAs can regulate β-catenin signaling in HCC. Anti-cancer agents inhibit β-catenin signaling and mediate its proteasomal degradation in HCC therapy. Furthermore, clinical studies have revealed the role of β-catenin and its gene mutation (CTNBB1) in HCC progression. Based on these subjects, future experiments can focus on developing novel therapeutics targeting Wnt/β-catenin signaling in HCC therapy.

Distinct diagnostic and prognostic values of Glypicans gene expression in patients with hepatocellular carcinoma

Backgroud

In our current work, we aimed to investigate the expressions of glypican (GPC) family genes at the mRNA level and assess their prognostic significances in patients with hepatocellular carcinoma (HCC).

Methods

The pathological roles of GPC family genes were examined using bioinformatics analysis. The diagnostic values of GPC genes were explored with the Gene Expression Profiling Interactive Analysis. Moreover, the mRNA expression and prognostic values of GPC genes were assessed via the KM plotter database.

Results

Our data showed that the expression of GPC-3 was dramatically increased in the liver tumor tissue. Moreover, the expressions of the other five GPC family members were not significantly different between the tumor and normal liver tissues (P > 0.05). Furthermore, the up-regulation of GPC-1 at the mRNA level was dramatically correlated to the reduced overall survival (OS) for all HCC patients (hazard ratio = 2.03, 95% confidence intervals =1.44–2.87, P = 4.1e-05) compared with its low-expression group. Besides, the prognosis of the Caucasians was related to most GPC family genes, while the prognosis of the Asian race was only related to the expression of GPC-2. Besides, for pathological factors, including stage, grade, AJCC, and vascular invasion, the higher the pathological grade and vascular invasiveness, the lower the expression levels of GPC family genes (P < 0.05). Finally, the expression levels of GPC-1, 2, and 3 in the hepatitis group were related to the poor prognosis of HCC in the risk factor (alcohol consumption and hepatitis) subgroup (P < 0.05).

Conclusions

Our findings indicated that GPC-3 was dysregulated in HCC compared with paracancerous tissues. The expression of GPC-1 could be used as a potent predictive index for the general prognosis of HCC. The pathology, patients, and risk factors might affect the prognostic value of GPC family genes in HCC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08104-z.