Molecular and histological correlations in liver cancer

Combining a deep learning model with clinical data better predicts hepatocellular carcinoma behavior following surgery

Hepatocellular carcinoma (HCC) is among the most common cancers worldwide, and tumor recurrence following liver resection or transplantation is one of the highest contributors to mortality in HCC patients after surgery. Using artificial intelligence (AI), we developed an interdisciplinary model to predict HCC recurrence and patient survival following surgery. We collected whole-slide H&E images, clinical variables, and follow-up data from 300 patients with HCC who underwent transplant and 169 patients who underwent resection at the Cleveland Clinic. A deep learning model was trained to predict recurrence-free survival (RFS) and disease-specific survival (DSS) from the H&E-stained slides. Repeated cross-validation splits were used to compute robust C-index estimates, and the results were compared to those obtained by fitting a Cox proportional hazard model using only clinical variables. While the deep learning model alone was predictive of recurrence and survival among patients in both cohorts, integrating the clinical and histologic models significantly increased the C-index in each cohort. In every subgroup analyzed, we found that a combined clinical and deep learning model better predicted post-surgical outcome in HCC patients compared to either approach independently.

TMEM147: A Promising Cancer Biomarker Associated with Immune Cell Infiltration and Prognosis in LIHC-Insights from a Comprehensive Pan-Cancer Genomic Analysis

Previous studies have demonstrated the regulatory roles of Transmembrane protein 147 (TMEM147) in various diseases, including cancer. However, systematic pan-cancer analyses investigating the role of TMEM147 in diagnosis, prognosis, and immunological prediction are lacking. An analysis of data from The Cancer Genome Atlas (TCGA) revealed differential TMEM147 expression across various types of cancer as well as within immune and molecular cancer subtypes. Moreover, high TMEM147 expression was associated with poor disease-specific survival (DSS), overall survival (OS), and progression-free interval (PFI) across cancers, suggesting its potential as a prognostic biomarker. Our study further revealed a significant correlation between TMEM147 expression and T helper cell and Tcm cell infiltration in most cancer types. In the case of liver hepatocellular carcinoma (LIHC), the effect of TMEM147 on prognosis varied among different clinical subtypes. Additionally, functional enrichment analysis revealed an association between TMEM147 and metabolic pathways. Finally, experiments on the MIHA cell line and four LIHC cell lines confirmed the role of TMEM147 in promoting liver cancer cell proliferation, further confirming the clinical value of TMEM147 in liver cancer diagnosis. Our findings suggest that TMEM147 may serve as a diagnostic and prognostic biomarker across cancers while also playing a significant role in LIHC.

Sphingosine kinase 2 and p62 regulation are determinants of sexual dimorphism in hepatocellular carcinoma

OBJECTIVE

Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality, and its incidence is increasing due to endemic obesity. HCC is sexually dimorphic in both humans and rodents with higher incidence in males, although the mechanisms contributing to these correlations remain unclear. Here, we examined the role of sphingosine kinase 2 (SphK2), the enzyme that regulates the balance of bioactive sphingolipid metabolites, sphingosine-1-phosphate (S1P) and ceramide, in gender specific MASH-driven HCC.

METHODS

Male and female mice were fed a high fat diet with sugar water, a clinically relevant model that recapitulates MASH-driven HCC in humans followed by physiological, biochemical cellular and molecular analyses. In addition, correlations with increased risk of HCC recurrence were determined in patients.

RESULTS

Here, we report that deletion of SphK2 protects both male and female mice from Western diet-induced weight gain and metabolic dysfunction without affecting hepatic lipid accumulation or fibrosis. However, SphK2 deficiency decreases chronic diet-induced hepatocyte proliferation in males but increases it in females. Remarkably, SphK2 deficiency reverses the sexual dimorphism of HCC, as SphK2-/- male mice are protected whereas the females develop liver cancer. Only in male mice, chronic western diet induced accumulation of the autophagy receptor p62 and its downstream mediators, the antioxidant response target NQO1, and the oncogene c-Myc. SphK2 deletion repressed these known drivers of HCC development. Moreover, high p62 expression correlates with poor survival in male HCC patients but not in females. In hepatocytes, lipotoxicity-induced p62 accumulation is regulated by sex hormones and prevented by SphK2 deletion. Importantly, high SphK2 expression in male but not female HCC patients is associated with a more aggressive HCC differentiation status and increased risk of cancer recurrence.

CONCLUSIONS

This work identifies SphK2 as a potential regulator of HCC sexual dimorphism and suggests SphK2 inhibitors now in clinical trials could have opposing, gender-specific effects in patients.

Establishment of a circRNA-regulated E3 ubiquitin ligase signature and nomogram to predict immunotherapeutic efficacy and prognosis in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common type of malignant tumor where the prognosis is dismal. Circular RNA (CircRNA) is a novel RNA that regulates downstream gene transcription and translation to influence the progression of HCC. However, the regulatory relationship that exists between E3 ligases, which is a class of post-translational modifying proteins, and circRNA remains unclear.

METHODS

Based on the E3 ubiquitin ligase in the competitive endogenous RNA (ceRNA) network, a circRNA-regulated E3 ubiquitin ligase signature (CRE3UL) was developed. A CRE3UL signature was created using the least absolute shrinkage and selection operator (Lasso) and Cox regression analysis and merged it with clinicopathologic characteristics to generate a nomogram for prognosis prediction. The pRRophetic algorithm was utilized and immunological checkpoints were analyzed to compare the responses of patients in the high-risk group (HRG) and low-risk group (LRG) to targeted therapy and immunotherapy. Finally, experimental research will further elucidate the relationship between E3 ubiquitin ligase signature and HCC.

RESULTS

HRG patients were found to have a worse prognosis than LRG patients. Furthermore, significant variations in prognosis were observed among different subgroups based on various clinical characteristics. The CRE3UL signature was identified as being an independent prognostic indicator. The nomogram that combined clinical characteristics and the CRE3UL signature was found to accurately predict the prognosis of HCC patients and demonstrated greater clinical utility than the current TNM staging approach. According to anticancer medication sensitivity predictions, the tumors of HRG patients were more responsive to gefitinib and nilotinib. From immune-checkpoint markers analysis, immunotherapy was identified as being more probable to assist those in the HRG.

CONCLUSIONS

We found a significant correlation between the CRE3UL signature and the tumor microenvironment, enabling precise prognosis prediction for HCC patients. Additionally, a nomogram was developed that performs well in predicting the overall survival (OS) of HCC patients. This provides valuable guidance for clinicians in devising specific personalized treatment strategies.

Integrated Analysis of scRNA-Seq and Bulk RNA-Seq Reveals Metabolic Reprogramming of Liver Cancer and Establishes a Prognostic Risk Model

Liver cancer manifests as a profoundly heterogeneous malignancy, posing significant challenges in terms of both therapeutic intervention and prognostic evaluation. Given that the liver is the largest metabolic organ, a prognostic risk model grounded in single-cell transcriptome analysis and a metabolic perspective can facilitate precise prevention and treatment strategies for liver cancer. Hence, we identified 11 cell types in a scRNA-seq profile comprising 105,829 cells and found that the metabolic activity of malignant cells increased significantly. Subsequently, a prognostic risk model incorporating tumor heterogeneity, cell interactions, tumor cell metabolism, and differentially expressed genes was established based on eight genes; this model can accurately distinguish the survival outcomes of liver cancer patients and predict the response to immunotherapy. Analyzing the immune status and drug sensitivity of the high- and low-risk groups identified by the model revealed that the high-risk group had more active immune cell status and greater expression of immune checkpoints, indicating potential risks associated with liver cancer-targeted drugs. In summary, this study provides direct evidence for the stratification and precise treatment of liver cancer patients, and is an important step in establishing reliable predictors of treatment efficacy in liver cancer patients.

Pantoprazole suppresses carcinogenesis and growth of hepatocellular carcinoma by inhibiting glycolysis and Na+/H+ exchange

Hepatocellular carcinoma (HCC) is one of the deadliest cancers. The prevention and therapy for this deadly disease remain a global medical challenge. In this study, we investigated the effect of pantoprazole (PPZ) on the carcinogenesis and growth of HCC. Both diethylnitrosamine (DEN) plus CCl4-induced and DEN plus high fat diet (HFD)-induced HCC models in mice were established. Cytokines and cell proliferation-associated gene in the liver tissues of mice and HCC cells were analyzed. Cellular glycolysis and Na+/H+ exchange activity were measured. The preventive administration of pantoprazole (PPZ) at a clinically relevant low dose markedly suppressed HCC carcinogenesis in both DEN plus CCl4-induced and HFD-induced murine HCC models, whereas the therapeutic administration of PPZ at the dose suppressed the growth of HCC. In the liver tissues of PPZ-treated mice, inflammatory cytokines, IL1, CXCL1, CXCL5, CXCL9, CXCL10, CCL2, CCL5, CCL6, CCL7, CCL20, and CCL22, were reduced. The administration of CXCL1, CXCL5, CCL2, or CCL20 all reversed PPZ-suppressed DEN plus CCL4-induced HCC carcinogenesis in mice. PPZ inhibited the expressions of CCNA2, CCNB2, CCNE2, CDC25C, CDCA5, CDK1, CDK2, TOP2A, TTK, AURKA, and BIRC5 in HCC cells. Further results showed that PPZ reduced the production of these inflammatory cytokines and the expression of these cell proliferation-associated genes through the inhibition of glycolysis and Na+/H+ exchange. In conclusion, PPZ suppresses the carcinogenesis and growth of HCC, which is related to inhibiting the production of inflammatory cytokines and the expression of cell proliferation-associated genes in the liver through the inhibition of glycolysis and Na+/H+ exchange.

Trim21 deficiency in mice increases HCC carcinogenesis in a NASH context and is associated with immune checkpoint upregulation

The global pandemic of metabolic diseases has increased the incidence of hepatocellular carcinoma (HCC) in the context of non-alcoholic steatohepatitis (NASH). The downregulation of the E3 ubiquitin ligase TRIM21 has been linked to poor prognosis in different cancers including HCC. In order to investigate the role of TRIM21 in liver cancer progression on NASH, Trim21+/+ and Trim21-/- male mice were injected with streptozotocin at the neonatal stage. The hypoinsulinemic mice were then fed with a high-fat high-cholesterol diet (HFHCD) for 4, 8 or 12 weeks. All mice developed NASH which systematically resulted in HCC progression. Interestingly, compared to the Trim21+/+ control mice, liver damage was worsened in Trim21-/- mice, with more HCC nodules found after 12 weeks on HFHCD. Immune population analysis in the spleen and liver revealed a higher proportion of CD4+PD-1+ and CD8+PD-1+ T cells in Trim21-/- mice. The liver and HCC tumors of Trim21-/- mice also exhibited an increase in the number of PD-L1+ and CD68+ PD-L1+ cells. Thus, TRIM21 limits the emergence of HCC nodules in mice with NASH by potentially restricting the expression of PD-1 in lymphocytes and PD-L1 in tumors.

Radiomics features based on dual-area CT predict the expression levels of fatty acid binding protein 4 and outcome in hepatocellular carcinoma

RATIONALE AND OBJECTIVES

To evaluate the predictive value of tumor and peritumor radiomics in the fatty acid binding protein 4 (FABP4) expression levels and overall survival in patients with hepatocellular carcinoma.

MATERIALS AND METHODS

The genomic data of HCC patients were obtained from The Cancer Genome Atlas. The Dual-area CT images of corresponding patients were downloaded from The Cancer Imaging Archive, for radiomics feature extraction, model construction and prognosis analysis. Simultaneously, using patients from Sichuan Provincial People's Hospital, the prognostic value of the radiomics model in HCC patients was validated.

RESULTS

In the TCIA database, the area under the curve (AUC) values of the volumes of interest (VOI)whole model in the training set and internal validation set were 0.812 and 0.754, respectively, and the AUC value of VOIwhole+periphery in the training set and internal validation set were 0.866 and 0.779, respectively. In the VOIwhole and the VOIwhole+periphery model of the independent cohort, there were significant differences in OS between the high and low rad-score groups (P = 0.009, P = 0.021, respectively). Significant positive correlations can be observed between FABP4 expression and correlations with rad-score of VOIwhole model (r = 0.691) and VOIwhole+periphery model (r = 0.732) in the independent cohort.

CONCLUSION

Radiomics models of tumor and peritumor Dual-area CT images could predict stably the expression levels of FABP4 and may be helping in personalized treatment strategies.

The impact of matrix stiffness on hepatic cell function, liver fibrosis, and hepatocellular carcinoma-Based on quantitative data

Over the past few decades, extensive research has explored the development of supportive scaffold materials for in vitro hepatic cell culture, to effectively mimic in vivo microenvironments. It is crucial for hepatic disease modeling, drug screening, and therapeutic evaluations, considering the ethical concerns and practical challenges associated with in vivo experiments. This review offers a comprehensive perspective on hepatic cell culture using bioscaffolds by encompassing all stages of hepatic diseases-from a healthy liver to fibrosis and hepatocellular carcinoma (HCC)-with a specific focus on matrix stiffness. This review begins by providing physiological and functional overviews of the liver. Subsequently, it explores hepatic cellular behaviors dependent on matrix stiffness from previous reports. For hepatic cell activities, softer matrices showed significant advantages over stiffer ones in terms of cell proliferation, migration, and hepatic functions. Conversely, stiffer matrices induced myofibroblastic activation of hepatic stellate cells, contributing to the further progression of fibrosis. Elevated matrix stiffness also correlates with HCC by increasing proliferation, epithelial-mesenchymal transition, metastasis, and drug resistance of HCC cells. In addition, we provide quantitative information on available data to offer valuable perspectives for refining the preparation and development of matrices for hepatic tissue engineering. We also suggest directions for further research on this topic.

Prognostication of Hepatocellular Carcinoma Using Artificial Intelligence

Hepatocellular carcinoma (HCC) is a biologically heterogeneous tumor characterized by varying degrees of aggressiveness. The current treatment strategy for HCC is predominantly determined by the overall tumor burden, and does not address the diverse prognoses of patients with HCC owing to its heterogeneity. Therefore, the prognostication of HCC using imaging data is crucial for optimizing patient management. Although some radiologic features have been demonstrated to be indicative of the biologic behavior of HCC, traditional radiologic methods for HCC prognostication are based on visually-assessed prognostic findings, and are limited by subjectivity and inter-observer variability. Consequently, artificial intelligence has emerged as a promising method for image-based prognostication of HCC. Unlike traditional radiologic image analysis, artificial intelligence based on radiomics or deep learning utilizes numerous image-derived quantitative features, potentially offering an objective, detailed, and comprehensive analysis of the tumor phenotypes. Artificial intelligence, particularly radiomics has displayed potential in a variety of applications, including the prediction of microvascular invasion, recurrence risk after locoregional treatment, and response to systemic therapy. This review highlights the potential value of artificial intelligence in the prognostication of HCC as well as its limitations and future prospects.

Predictive Value of Serum CYFRA 21-1 and CK19-2G2 for Tumor Aggressiveness and Overall Survival in Hepatitis C-Related Hepatocellular Carcinoma Among Egyptians: A Prospective Study

PURPOSE

Cytokeratin 19 fragment 21-1 (CYFRA 21-1) and cytokeratin 19 fragment 2G2 (CK 19-2G2) are two soluble fragments of cytokeratin 19 (CK 19) that can be detected in serum. CK 19-positive hepatocellular carcinoma (HCC) is characterized by an aggressive behavior and a poor outcome. This study aimed to assess the prognostic value of serum CYFRA 21-1 and CK 19-2G2 in predicting tumor aggressiveness and overall survival (OS) in patients with hepatic C virus (HCV)-related HCC.

METHODS

The current study included 138 patients with HCV-related HCC recruited from the Hepatobiliary and Interventional Radiology Units at Alexandria's main university hospitals and 40 healthy individuals as controls. Patients were assessed for clinical, radiological tumor characteristics, and aggressiveness index. Baseline serum CYFRA 21-1 and CK 19-2G2 levels were measured by enzyme-linked immunosorbent assay.

RESULTS

Elevated CYFRA 21-1 levels were associated with tumors size ≥ 5 cm (p < 0.001), malignant portal vein thrombosis (mPVT) (p < 0.001), distant metastasis (p = 0.030), ill-defined/infiltrative pattern (p = 0.010), and aggressiveness index > 4 (p = 0.045). Elevated CK19-2G2 levels were not associated with any clinical or radiological characteristics. Either or both elevated serum CYFRA 21-1 and CK 19-2G2 in combination with alpha-feto protein (AFP) ≥ 400 ng/ml have a better predictability for mPVT and ill-defined/infiltrative patterns (sensitivity (10-25%) and specificity (96-100%)). Elevated levels of CYFRA 21-1, CK 19-2G2, or AFP ≥ 400 ng/ml were associated with decreased 1-year OS.

CONCLUSIONS

Either or both elevated serum CYFRA 21-1 and CK 19-2G2 levels when added to AFP ≥ 400 ng/ml are specific but less sensitive biomarkers for predicting tumor aggressiveness. These biomarkers can be used independently to predict reduced 1-year OS in Egyptian patients with HCV-related HCC.

Proliferative hepatocellular carcinomas in cirrhosis: patient outcomes of LI-RADS category 4/5 and category M

OBJECTIVES

We aimed to compare Liver Imaging Reporting and Data System (LI-RADS) category 4/5 and category M (LR-M) of proliferative hepatocellular carcinomas (HCCs) in cirrhotic patients and evaluate their impacts on prognosis.

METHODS

This retrospective multi-reader study included cirrhotic patients with single treatment-naïve HCC ≤ 5.0 cm who underwent contrast-enhanced CT, MRI, and subsequent hepatic resection within 2 months. The percentages of CT/MRI LR-4/5 and LR-M in proliferative and non-proliferative HCCs were compared. Univariable and multivariable Cox proportional hazards regression analyses were performed to assess the association of LI-RADS categories (LR-4/5 vs. LR-M) and pathologic classification (proliferative vs. non-proliferative) with overall survival (OS) and recurrence-free survival (RFS). Subgroups of patients with proliferative and non-proliferative HCCs were analyzed to compare OS and RFS between LR-4/5 and LR-M.

RESULTS

Of the 204 included patients, 38 were classified as having proliferative HCC. The percentages of LR-M were higher in proliferative than non-proliferative HCC on both CT (15.8% vs. 3.0%, p = 0.007) and MRI (26.3% vs. 9.6%, p = 0.016). Independent of pathologic classification, CT and MRI LR-M were significantly associated with poorer OS (hazard ratio (HR) = 4.58, p = 0.013, and HR = 6.45, p < 0.001) and RFS (HR = 3.66, p = 0.005, and HR = 6.44, p < 0.001) than LR-4/5. MRI LR-M was associated with significantly poorer OS (p ≤ 0.003) and RFS (p < 0.001) than MRI LR-4/5 in both proliferative and non-proliferative HCCs.

CONCLUSIONS

This multi-reader study showed that the percentages of LR-M were significantly higher in proliferative than non-proliferative HCCs. CT/MRI LR-M was significantly associated with poor OS and RFS, independent of the pathologic classification of proliferative versus non-proliferative HCCs.

CLINICAL RELEVANCE STATEMENT

CT and MRI LI-RADS category M can be clinically useful in predicting poor outcomes in patients with proliferative and non-proliferative hepatocellular carcinomas.

KEY POINTS

• The percentages of LR-M tumors on both CT and MRI were significantly higher in proliferative than non-proliferative hepatocellular carcinomas. • Independent of pathologic classification, CT/MRI LR-M categories were correlated with poor overall survival and recurrence-free survival. • Patients with both proliferative and non-proliferative hepatocellular carcinomas categorized as MRI LR-M had significantly poorer overall survival and recurrence-free survival than those categorized as MRI LR-4/5.

Applying image features of proximal paracancerous tissues in predicting prognosis of patients with hepatocellular carcinoma

BACKGROUND

Most of the methods using digital pathological image for predicting Hepatocellular carcinoma (HCC) prognosis have not considered paracancerous tissue microenvironment (PTME), which are potentially important for tumour initiation and metastasis. This study aimed to identify roles of image features of PTME in predicting prognosis and tumour recurrence of HCC patients.

METHODS

We collected whole slide images (WSIs) of 146 HCC patients from Sun Yat-sen Memorial Hospital (SYSM dataset). For each WSI, five types of regions of interests (ROIs) in PTME and tumours were manually annotated. These ROIs were used to construct a Lasso Cox survival model for predicting the prognosis of HCC patients. To make the model broadly useful, we established a deep learning method to automatically segment WSIs, and further used it to construct a prognosis prediction model. This model was tested by the samples of 225 HCC patients from the Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC).

RESULTS

In predicting prognosis of the HCC patients, using the image features of manually annotated ROIs in PTME achieved C-index 0.668 in the SYSM testing dataset, which is higher than the C-index 0.648 reached by the model only using image features of tumours. Integrating ROIs of PTME and tumours achieved C-index 0.693 in the SYSM testing dataset. The model using automatically segmented ROIs of PTME and tumours achieved C-index of 0.665 (95% CI: 0.556-0.774) in the TCGA-LIHC samples, which is better than the widely used methods, WSISA (0.567), DeepGraphSurv (0.593), and SeTranSurv (0.642). Finally, we found the Texture SumAverage Skew HV on immune cell infiltration and Texture related features on desmoplastic reaction are the most important features of PTME in predicting HCC prognosis. We additionally used the model in prediction HCC recurrence for patients from SYSM-training, SYSM-testing, and TCGA-LIHC datasets, indicating the important roles of PTME in the prediction.

CONCLUSIONS

Our results indicate image features of PTME is critical for improving the prognosis prediction of HCC. Moreover, the image features related with immune cell infiltration and desmoplastic reaction of PTME are the most important factors associated with prognosis of HCC.

Facile engineering of aptamer-coupled silk fibroin encapsulated myogenic gold nanocomposites: investigation of antiproliferative activity and apoptosis induction

Nanocomposites selectively induce cancer cell death, holding potential for precise liver cancer treatment breakthroughs. This study assessed the cytotoxicity of gold nanocomposites (Au NCs) enclosed within silk fibroin (SF), aptamer (Ap), and the myogenic Talaromyces purpureogenus (TP) against a human liver cancer cell (HepG2). The ultimate product, Ap-SF-TP@Au NCs, results from a three-step process. This process involves the myogenic synthesis of TP@Au NCs derived from TP mycelial extract, encapsulation of SF on TP@Au NCs (SF-TP@Au NCs), and the conjugation of Ap within SF-TP@Au NCs. The synthesized NCs are analyzed by various characteristic techniques. Ap-SF-TP@Au NCs induced potential cell death in HepG2 cells but exhibited no cytotoxicity in non-cancerous cells (NIH3T3). The morphological changes in cells were examined through various biochemical staining methods. Thus, Ap-SF-TP@Au NCs emerge as a promising nanocomposite for treating diverse cancer cells.

Diagnostic Model for Proliferative HCC Using LI-RADS: Assessing Therapeutic Outcomes in Hepatectomy and TKI-ICI Combination

BACKGROUND

Proliferative hepatocellular carcinoma (HCC), aggressive with poor prognosis, and lacks reliable MRI diagnosis.

PURPOSE

To develop a diagnostic model for proliferative HCC using liver imaging reporting and data system (LI-RADS) and assess its prognostic value.

STUDY TYPE

Retrospective.

POPULATION

241 HCC patients underwent hepatectomy (90 proliferative HCCs: 151 nonproliferative HCCs), divided into the training (N = 167) and validation (N = 74) sets. 57 HCC patients received combination therapy with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs).

FIELD STRENGTH/SEQUENCE

3.0 T, T1- and T2-weighted, diffusion-weighted, in- and out-phase, T1 high resolution isotropic volume excitation and dynamic gadoxetic acid-enhanced imaging.

ASSESSMENT

LI-RADS v2018 and other MRI features (intratumoral artery, substantial hypoenhancing component, hepatobiliary phase peritumoral hypointensity, and irregular tumor margin) were assessed. A diagnostic model for proliferative HCC was established, stratifying patients into high- and low-risk groups. Follow-up occurred every 3-6 months, and recurrence-free survival (RFS), progression-free survival (PFS) and overall survival (OS) in different groups were compared.

STATISTICAL TESTS

Fisher's test or chi-square test, t-test or Mann-Whitney test, logistic regression, Harrell's concordance index (C-index), Kaplan-Meier curves, and Cox proportional hazards. Significance level: P < 0.05.

RESULTS

The diagnostic model, incorporating corona enhancement, rim arterial phase hyperenhancement, infiltrative appearance, intratumoral artery, and substantial hypoenhancing component, achieved a C-index of 0.823 (training set) and 0.804 (validation set). Median follow-up was 32.5 months (interquartile range [IQR], 25.1 months) for postsurgery patients, and 16.8 months (IQR: 13.2 months) for combination-treated patients. 99 patients experienced recurrence, and 30 demonstrated tumor nonresponse. Differences were significant in RFS and OS rates between high-risk and low-risk groups post-surgery (40.3% vs. 65.8%, 62.3% vs. 90.1%, at 5 years). In combination-treated patients, PFS rates differed significantly (80.6% vs. 7.7% at 2 years).

DATA CONCLUSION

The MR-based model could pre-treatment identify proliferative HCC and assist in prognosis evaluation.

LEVEL OF EVIDENCE: 4

TECHNICAL EFFICACY

Stage 2.

Hepatocellular Carcinoma: Current Drug Therapeutic Status, Advances and Challenges

Hepatocellular carcinoma (HCC) is the most common form of liver cancer, accounting for ~90% of liver neoplasms. It is the second leading cause of cancer-related deaths and the seventh most common cancer worldwide. Although there have been rapid developments in the treatment of HCC over the past decade, the incidence and mortality rates of HCC remain a challenge. With the widespread use of the hepatitis B vaccine and antiviral therapy, the etiology of HCC is shifting more toward metabolic-associated steatohepatitis (MASH). Early-stage HCC can be treated with potentially curative strategies such as surgical resection, liver transplantation, and radiofrequency ablation, improving long-term survival. However, most HCC patients, when diagnosed, are already in the intermediate or advanced stages. Molecular targeted therapy, followed by immune checkpoint inhibitor immunotherapy, has been a revolution in HCC systemic treatment. Systemic treatment of HCC especially for patients with compromised liver function is still a challenge due to a significant resistance to immune checkpoint blockade, tumor heterogeneity, lack of oncogenic addiction, and lack of effective predictive and therapeutic biomarkers.

A hypoxia-glycolysis-lactate-related gene signature for prognosis prediction in hepatocellular carcinoma

BACKGROUND

Liver cancer ranks sixth in incidence and third in mortality globally and hepatocellular carcinoma (HCC) accounts for 90% of it. Hypoxia, glycolysis, and lactate metabolism have been found to regulate the progression of HCC separately. However, there is a lack of studies linking the above three to predict the prognosis of HCC. The present study aimed to identify a hypoxia-glycolysis-lactate-related gene signature for assessing the prognosis of HCC.

METHODS

This study collected 510 hypoxia-glycolysis-lactate genes from Molecular Signatures Database (MSigDB) and then classified HCC patients from TCGA-LIHC by analyzing their hypoxia-glycolysis-lactate genes expression. Differentially expressed genes (DEGs) were screened out to construct a gene signature by LASSO-Cox analysis. Univariate and multivariate regression analyses were used to evaluate the independent prognostic value of the gene signature. Analyses of immune infiltration, somatic cell mutations, and correlation heatmap were conducted by "GSVA" R package. Single-cell analysis conducted by "SingleR", "celldex", "Seurat", and "CellCha" R packages revealed how signature genes participated in hypoxia/glycolysis/lactate metabolism and PPI network identified hub genes.

RESULTS

We classified HCC patients from TCGA-LIHC into two clusters and screened out DEGs. An 18-genes prognostic signature including CDCA8, CBX2, PDE6A, MED8, DYNC1LI1, PSMD1, EIF5B, GNL2, SEPHS1, CCNJL, SOCS2, LDHA, G6PD, YBX1, RTN3, ADAMTS5, CLEC3B, and UCK2 was built to stratify the risk of HCC. The risk score of the hypoxia-glycolysis-lactate gene signature was further identified as a valuable independent factor for estimating the prognosis of HCC. Then we found that the features of clinical characteristics, immune infiltration, somatic cell mutations, and correlation analysis differed between the high-risk and low-risk groups. Furthermore, single-cell analysis indicated that the signature genes could interact with the ligand-receptors of hepatocytes/fibroblasts/plasma cells to participate in hypoxia/glycolysis/lactate metabolism and PPI network identified potential hub genes in this process: CDCA8, LDHA, YBX1.

CONCLUSION

The hypoxia-glycolysis-lactate-related gene signature we built could provide prognostic value for HCC and suggest several hub genes for future HCC studies.

Preparation and Evaluation of Chitosan Coated PLGA Nanoparticles Encapsulating Ivosidenib with Enhanced Cytotoxicity Against Human Liver Cancer Cells

Purpose

Ivosidenib (IVO), an isocitrate dehydrogenase-1 (IDH1) used for treatment of acute myeloid leukemia (AML) and cholangiocarcinoma. However, poor solubility, low bioavailability, high dose and side effects limit clinical application of IVO.

Methods

Ivosidenib-loaded PLGA nanoparticles (IVO-PLGA-NPs) and Ivosidenib-loaded chitosan coated PLGA nanoparticles (IVO-CS-PLGA-NPs) were prepared using emulsification and solvent evaporation method for the treatment of liver cancer.

Results

The developed IVO-PLGA-NPs were evaluated for their particle size (171.7±4.9 nm), PDI (0.333), ZP (-23.0±5.8 mV), EE (96.3±4.3%), and DL (9.66±1.1%); similarly, the IVO-CS-PLGA-NPs were evaluated for their particle size (177.3±5.2 nm), PDI (0.311), ZP +25.9±5.7 mV, EE (90.8±5.7%), and DL (9.42±0.7%). The chitosan coating of IVO-PLGA-NPs was evidenced by an increase in mean particle size and positive ZP value. Because of the chitosan coating, the IVO-CS-PLGA-NPs showed a more stable and prolonged release of IVO than IVO-PLGA-NPs. In comparison to pure-IVO, the IVO-PLGA-NPs and IVO-CS-PLGA-NPs were found to be more effective against HepG2 cells, with IC50 values for the MTT assay being approximately half of those of pure-IVO. In HepG2 cells, the expressions of caspase-3, caspase-9, and p53 were significantly (p < 0.05) elevated.

Conclusion

Overall, these findings suggest that chitosan coating of IVO-PLGA-NPs improves the delivery and efficacy of ivosidenib in liver cancer treatment.

Bioengineered Organoids Offer New Possibilities for Liver Cancer Studies: A Review of Key Milestones and Challenges

Hepatic cancer is widely regarded as the leading cause of cancer-related mortality worldwide. Despite recent advances in treatment options, the prognosis of liver cancer remains poor. Therefore, there is an urgent need to develop more representative in vitro models of liver cancer for pathophysiology and drug screening studies. Fortunately, an exciting new development for generating liver models in recent years has been the advent of organoid technology. Organoid models hold huge potential as an in vitro research tool because they can recapitulate the spatial architecture of primary liver cancers and maintain the molecular and functional variations of the native tissue counterparts during long-term culture in vitro. This review provides a comprehensive overview and discussion of the establishment and application of liver organoid models in vitro. Bioengineering strategies used to construct organoid models are also discussed. In addition, the clinical potential and other relevant applications of liver organoid models in different functional states are explored. In the end, this review discusses current limitations and future prospects to encourage further development.

Nuclear KRT19 is a transcriptional corepressor promoting histone deacetylation and liver tumorigenesis

BACKGROUND AND AIMS

Epigenetic reprogramming and escape from terminal differentiation are poorly understood enabling characteristics of liver cancer. Keratin 19 (KRT19), classically known to form the intermediate filament cytoskeleton, is a marker of stemness and worse prognosis in liver cancer. This study aimed to address the functional roles of KRT19 in liver tumorigenesis and to elucidate the underlying mechanisms.

APPROACH AND RESULTS

Using multiplexed genome editing of hepatocytes in vivo, we demonstrated that KRT19 promoted liver tumorigenesis in mice. Cell fractionation revealed a previously unrecognized nuclear fraction of KRT19. Tandem affinity purification identified histone deacetylase 1 and REST corepressor 1, components of the corepressor of RE-1 silencing transcription factor (CoREST) complex as KRT19-interacting proteins. KRT19 knockout markedly enhanced histone acetylation levels. Mechanistically, KRT19 promotes CoREST complex formation by enhancing histone deacetylase 1 and REST corepressor 1 interaction, thus increasing the deacetylase activity. ChIP-seq revealed hepatocyte-specific genes, such as hepatocyte nuclear factor 4 alpha ( HNF4A ), as direct targets of KRT19-CoREST. In addition, we identified forkhead box P4 as a direct activator of aberrant KRT19 expression in liver cancer. Furthermore, treatment of primary liver tumors and patient-derived xenografts in mice suggest that KRT19 expression has the potential to predict response to histone deacetylase 1 inhibitors especially in combination with lenvatinib.

CONCLUSIONS

Our data show that nuclear KRT19 acts as a transcriptional corepressor through promoting the deacetylase activity of the CoREST complex, resulting in dedifferentiation of liver cancer. These findings reveal a previously unrecognized function of KRT19 in directly shaping the epigenetic landscape in cancer.

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%.

Hypoxia-driven tumor stromal remodeling and immunosuppressive microenvironment in scirrhous HCC

BACKGROUND AND AIMS

Scirrhous HCC (SHCC) is one of the unique subtypes of HCC, characterized by abundant fibrous stroma in the tumor microenvironment. However, the molecular traits of SHCC remain unclear, which is essential to develop specialized therapeutic approaches for SHCC.

APPROACH AND RESULTS

We presented an integrative analysis containing single-cell RNA-sequencing, whole-exome sequencing, and bulk RNA-sequencing in SHCC and usual HCC samples from 134 patients to delineate genomic features, transcriptomic profiles, and stromal immune microenvironment of SHCC. Multiplexed immunofluorescence staining, flow cytometry, and functional experiments were performed for validation. Here, we identified SHCC presented with less genomic heterogeneity while possessing a unique transcriptomic profile different from usual HCC. Insulin-like growth factor 2 was significantly upregulated in SHCC tumor cells compared to usual HCC, and could serve as a potential diagnostic biomarker for SHCC. Significant tumor stromal remodeling and hypoxia were observed in SHCC with enrichment of matrix cancer-associated fibroblasts and upregulation of hypoxic pathways. Insulin-like growth factor 2 was identified as a key mediator in shaping the hypoxic stromal microenvironment of SHCC. Under this microenvironment, SHCC exhibited an immunosuppressive niche correlated to enhanced VEGFA signaling activity, where CD4 + T cells and CD8 + T cells were dysfunctional. Furthermore, we found that another hypoxic-related molecule SPP1 from SHCC tumor cells suppressed the function of dendritic cells via the SPP1-CD44 axis, which also probably hindered the activation of T cells.

CONCLUSION

We uncovered the genomic characteristics of SHCC, and revealed a hypoxia-driven tumor stroma remodeling and immunosuppressive microenvironment in SHCC.

Diagnostic and Prognostic Ability of Contrast-Enhanced Unltrasound and Biomarkers in Hepatocellular Carcinoma Subtypes

OBJECTIVE

To investigate the diagnostic and prognostic value of contrast-enhanced ultrasound (CEUS) and clinical indicators of the vessels encapsulating tumor clusters (VETC) pattern and macrotrabecular-massive subtype in hepatocellular carcinoma (MTM-HCC).

METHODS

This retrospective study included patients who underwent preoperative CEUS and hepatectomy for HCC between August 2018 and August 2021. Multivariable logistic regression was performed to select independent correlated factors of VETC-HCC and MTM-HCC to develop nomogram models. The association between model outcomes and early postoperative HCC recurrence was assessed using Kaplan-Meier curve and Cox regression analysis.

RESULTS

The training cohort included 182 patients (54.3 ± 11.3 years, 168 males) and the validation cohort included 91 patients (54.8 ± 10.6 years, 81 males). Multivariate logistic regression analysis revealed that α-fetoprotein (AFP) levels (odds ratio [OR]: 2.26, 95% confidence interval [CI]: 1.49-3.42, p < 0.001), intratumoral nonenhancement (OR: 2.40, 95% CI: 1.02-5.64, p = 0.044), and the perfusion pattern in the CEUS arterial phase (OR: 2.27, 95% CI: 1.05-4.91, p = 0.038) were independent predictors of VETC-HCC. Besides, the former two were also independently associated with MTM-HCC (AFP level: OR: 2.36, 95% CI: 1.36-4.09, p = 0.002; intratumoral nonenhancement: OR: 3.72, 95% CI: 1.02-13.56, p = 0.046). Nomogram models were constructed based on the aforementioned indicators. Kaplan-Meier curve analysis indicated that predicted VETC-HCC or MTM-HCC exhibited higher rates of early recurrence (log-rank p < 0.001 and p = 0.002, respectively). Cox regression analysis showed that a high risk of VETC-HCC was independently correlated with early recurrence (p = 0.011).

CONCLUSION

CEUS combined with AFP levels can predict VETC-HCC/MTM-HCC and prognosis preoperatively.

Hepatitis B virus-related hepatocellular carcinoma has superior overall survival compared with other etiologies

BACKGROUND

Whether the etiology of chronic liver disease (CLD) impacts the overall survival (OS) of patients with hepatocellular carcinoma (HCC) remains unclear. We aim to clarify this issue.

MATERIALS AND METHODS

Between 2011 and 2020, 3941 patients who were newly diagnosed with HCC at our institution were enrolled in this study. In patients with multiple CLD etiologies, etiology was classified using the following hierarchy: hepatitis C virus (HCV) > hepatitis B virus (HBV) > alcohol-related > all negative. All negative was defined as negative for HCV, HBV, and alcohol use disorder.

RESULTS

Among 3941 patients, 1407 patients were classified with HCV-related HCC, 1677 patients had HBV-related HCC, 145 patients had alcohol-related HCC, and 712 patients had all-negative HCC. Using the all-negative group as the reference group, multivariate analysis showed that HBV is an independent predictor of mortality (hazard ratio: 0.856; 95% confidence interval: 0.745-0.983; p = 0.027). Patients with HBV-related HCC had superior OS compared with patients with other CLD etiologies (p<0.001). Subgroup analyses were performed, for Barcelona Clinic Liver Cancer (BCLC) stages 0-A (p<0.001); serum alpha-fetoprotein (AFP) levels≧20 ng/ml (p<0.001); AFP levels < 20 ng/ml (p<0.001); age > 65 years (p<0.001); and the use of curative treatments (p = 0.002). No significant difference in OS between HBV and other etiologies was observed among patients aged ≤ 65 years (p = 0.304); with BCLC stages B-D (p = 0.973); or who underwent non-curative treatments (p = 0.1).

CONCLUSION

Patients with HBV-related HCC had superior OS than patients with other HCC etiologies.

Periodic changes of cyclin D1 mRNA stability are regulated by PC4 modifications in the cell cycle

The cell cycle is a highly regulated process in which proteins involved in cell cycle progression exhibit periodic expression patterns, controlled by specific mechanisms such as transcription, translation, and degradation. However, the precise mechanisms underlying the oscillations of mRNA levels in cell cycle regulators are not fully understood. In this study, we observed that the stability of cyclin D1 (CCND1) mRNA fluctuates during the cell cycle, with increased stability during interphase and decreased stability during the M phase. Additionally, we identified a key RNA binding protein, positive coactivator 4 (PC4), which plays a crucial role in stabilizing CCND1 mRNA and regulating its periodic expression. Moreover, the binding affinity of PC4 to CCND1 mRNA is modulated by two cell cycle-specific posttranslational modifications: ubiquitination of K68 enhances binding and stabilizes the CCND1 transcript during interphase, while phosphorylation of S17 inhibits binding during the M phase, leading to degradation of CCND1 mRNA. Remarkably, PC4 promotes the transition from G1 to S phase in the cell cycle, and depletion of PC4 enhances the efficacy of CDK4/6 inhibitors in hepatocellular carcinoma, suggesting that PC4 could serve as a potential therapeutic target. These findings provide valuable insights into the intricate regulation of cell cycle dynamics.

Bioinformatics and machine learning driven key genes screening for hepatocellular carcinoma

Liver cancer, a global menace, ranked as the sixth most prevalent and third deadliest cancer in 2020. The challenge of early diagnosis and treatment, especially for hepatocellular carcinoma (HCC), persists due to late-stage detections. Understanding HCC's complex pathogenesis is vital for advancing diagnostics and therapies. This study combines bioinformatics and machine learning, examining HCC comprehensively. Three datasets underwent meticulous scrutiny, employing various analytical tools such as Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein interaction assessment, and survival analysis. These rigorous investigations uncovered twelve pivotal genes intricately linked with HCC's pathophysiological intricacies. Among them, CYP2C8, CYP2C9, EPHX2, and ESR1 were significantly positively correlated with overall patient survival, while AKR1B10 and NQO1 displayed a negative correlation. Moreover, the Adaboost prediction model yielded an 86.8 % accuracy, showcasing machine learning's potential in deciphering complex dataset patterns for clinically relevant predictions. These findings promise to contribute valuable insights into the elusive mechanisms driving liver cancer (HCC). They hold the potential to guide the development of more precise diagnostic methods and treatment strategies in the future. In the fight against this global health challenge, unraveling HCC's intricacies is of paramount importance.

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.

Blockade of PD-1 and CTLA-4: A potent immunotherapeutic approach for hepatocellular carcinoma

Immune checkpoints (ICPs) can promote tumor growth and prevent immunity-induced cancer cell apoptosis. Fortunately, targeting ICPs, such as programmed cell death 1 (PD-1) or cytotoxic T lymphocyte associated protein 4 (CTLA-4), has achieved great success in the past few years and has gradually become an effective treatment for cancers, including hepatocellular carcinoma (HCC). However, many patients do not respond to ICP therapy due to acquired resistance and recurrence. Therefore, clarifying the specific mechanisms of ICP in the development of HCC is very important for enhancing the efficacy of anti-PD-1 and anti-CTLA-4 therapy. In particular, antigen presentation and interferon-γ (IFN-γ) signaling were reported to be involved in the development of resistance. In this review, we have explained the role and regulatory mechanisms of ICP therapy in HCC pathology. Moreover, we have also elaborated on combinations of ICP inhibitors and other treatments to enhance the antitumor effect. Collectively, recent advances in the pharmacological targeting of ICPs provide insights for the development of a novel alternative treatment for HCC.

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

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

Modelling-based joint embedding of histology and genomics using canonical correlation analysis for breast cancer survival prediction

Traditional approaches to predicting breast cancer patients' survival outcomes were based on clinical subgroups, the PAM50 genes, or the histological tissue's evaluation. With the growth of multi-modality datasets capturing diverse information (such as genomics, histology, radiology and clinical data) about the same cancer, information can be integrated using advanced tools and have improved survival prediction. These methods implicitly exploit the key observation that different modalities originate from the same cancer source and jointly provide a complete picture of the cancer. In this work, we investigate the benefits of explicitly modelling multi-modality data as originating from the same cancer under a probabilistic framework. Specifically, we consider histology and genomics as two modalities originating from the same breast cancer under a probabilistic graphical model (PGM). We construct maximum likelihood estimates of the PGM parameters based on canonical correlation analysis (CCA) and then infer the underlying properties of the cancer patient, such as survival. Equivalently, we construct CCA-based joint embeddings of the two modalities and input them to a learnable predictor. Real-world properties of sparsity and graph-structures are captured in the penalized variants of CCA (pCCA) and are better suited for cancer applications. For generating richer multi-dimensional embeddings with pCCA, we introduce two novel embedding schemes that encourage orthogonality to generate more informative embeddings. The efficacy of our proposed prediction pipeline is first demonstrated via low prediction errors of the hidden variable and the generation of informative embeddings on simulated data. When applied to breast cancer histology and RNA-sequencing expression data from The Cancer Genome Atlas (TCGA), our model can provide survival predictions with average concordance-indices of up to 68.32% along with interpretability. We also illustrate how the pCCA embeddings can be used for survival analysis through Kaplan-Meier curves.

Improving radiomics reproducibility using deep learning-based image conversion of CT reconstruction algorithms in hepatocellular carcinoma patients

OBJECTIVES

CT reconstruction algorithms affect radiomics reproducibility. In this study, we evaluate the effect of deep learning-based image conversion on CT reconstruction algorithms.

METHODS

This study included 78 hepatocellular carcinoma (HCC) patients who underwent four-phase liver CTs comprising non-contrast, late arterial (LAP), portal venous (PVP), and delayed phase (DP), reconstructed using both filtered back projection (FBP) and advanced modeled iterative reconstruction (ADMIRE). PVP images were used to train a convolutional neural network (CNN) model to convert images from FBP to ADMIRE and vice versa. LAP, PVP, and DP images were used for validation and testing. Radiomic features were extracted for each patient with a semi-automatic segmentation tool. We used concordance correlation coefficients (CCCs) to evaluate the radiomics reproducibility for original FBP (oFBP) vs. original ADMIRE (oADMIRE), oFBP vs. converted FBP (cFBP), and oADMIRE vs. converted ADMIRE (cADMIRE).

RESULTS

In the test group including 30 patients, the CCC and proportion of reproducible features (CCC ≥ 0.85) for oFBP vs. oADMIRE were 0.65 and 32.9% (524/1595) for LAP, 0.65 and 35.9% (573/1595) for PVP, and 0.69 and 43.8% (699/1595) for DP. For oFBP vs. cFBP, the values increased to 0.92 and 83.9% (1339/1595) for LAP, 0.89 and 71.0% (1133/1595) for PVP, and 0.90 and 79.7% (1271/1595) for DP. Similarly, for oADMIRE vs. cADMIRE, the values increased to 0.87 and 68.1% (1086/1595) for LAP, 0.91 and 82.1% (1309/1595) for PVP, and 0.89 and 76.2% (1216/1595) for DP.

CONCLUSIONS

CNN-based image conversion between CT reconstruction algorithms improved the radiomics reproducibility of HCCs.

CLINICAL RELEVANCE STATEMENT

This study demonstrates that using a CNN-based image conversion technique significantly improves the reproducibility of radiomic features in HCCs, highlighting its potential for enhancing radiomics research in HCC patients.

KEY POINTS

Radiomics reproducibility of HCC was improved via CNN-based image conversion between two different CT reconstruction algorithms. This is the first clinical study to demonstrate improvements across a range of radiomic features in HCC patients. This study promotes the reproducibility and generalizability of different CT reconstruction algorithms in radiomics research.

CMTM6 promotes hepatocellular carcinoma progression through stabilizing β-catenin

CMTM6, a regulator of PD-L1 stability, has been implicated in the development of various cancers. However, the expression and role of CMTM6 in hepatocellular carcinoma (HCC) remains controversial. Our study revealed a negative correlation between CMTM6 expression and HCC prognosis through bioinformatics analysis and immunofluorescence staining. CMTM6 expression was also positively associated with alpha-fetoprotein (AFP) levels, supporting its potential as a prognostic marker for HCC. Using Cmtm6 knockout mice, we found that Cmtm6 deficiency inhibited HCC formation and cell proliferation in primary liver cancer models induced by DEN and DEN/CCl4. In HCC cell lines, CMTM6 promoted cell proliferation and interacted with β-catenin, stabilizing it by preventing ubiquitination. In conclusion, our study suggested that CMTM6 upregulation promotes HCC cell proliferation through the β-catenin pathway, making it a potential therapeutic target for HCC treatment.

Clinical-Radiologic Morphology-Radiomics Model on Gadobenate Dimeglumine-Enhanced MRI for Identification of Highly Aggressive Hepatocellular Carcinoma: Temporal Validation and Multiscanner Validation

BACKGROUND

Highly aggressive hepatocellular carcinoma (HCC) is characterized by high tumor recurrence and poor outcomes, but its definition and imaging characteristics have not been clearly described.

PURPOSE

To develop and validate a fusion model on gadobenate dimeglumine-enhanced MRI for identifying highly aggressive HCC.

STUDY TYPE

Retrospective.

POPULATION

341 patients (M/F = 294/47) with surgically resected HCC, divided into a training cohort (n = 177), temporal validation cohort (n = 77), and multiscanner validation cohort (n = 87).

FIELD STRENGTH/SEQUENCE

3T, dynamic contrast-enhanced MRI with T1-weighted volumetric interpolated breath-hold examination gradient-echo sequences, especially arterial phase (AP) and hepatobiliary phase (HBP, 80-100 min).

ASSESSMENT

Clinical factors and diagnosis assessment based on radiologic morphology characteristics associated with highly aggressive HCCs were evaluated. The radiomics signatures were extracted from AP and HBP. Multivariable logistic regression was performed to construct clinical-radiologic morphology (CR) model and clinical-radiologic morphology-radiomics (CRR) model. A nomogram based on the optimal model was established. Early recurrence-free survival (RFS) was evaluated in actual groups and risk groups calculated by the nomogram.

STATISTICAL TESTS

The performance was evaluated by receiver operating characteristic curve (ROC) analysis, calibration curves analysis, and decision curves. Early RFS was evaluated by using Kaplan-Meier analysis. A P value <0.05 was considered statistically significant.

RESULTS

The CRR model incorporating corona enhancement, cloud-like hyperintensity on HBP, and radiomics signatures showed the highest diagnostic performance. The area under the curves (AUCs) of CRR were significantly higher than those of the CR model (AUC = 0.883 vs. 0.815, respectively, for the training cohort), 0.874 vs. 0.769 for temporal validation, and 0.892 vs. 0.792 for multiscanner validation. In both actual and risk groups, highly and low aggressive HCCs showed statistically significant differences in early recurrence.

DATA CONCLUSION

The clinical-radiologic morphology-radiomics model on gadobenate dimeglumine-enhanced MRI has potential to identify highly aggressive HCCs and non-invasively obtain prognostic information.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

Integrated characterization of hepatobiliary tumor organoids provides a potential landscape of pharmacogenomic interactions

Despite considerable efforts to identify human liver cancer genomic alterations that might unveil druggable targets, the systematic translation of multiomics data remains challenging. Here, we report success in long-term culture of 64 patient-derived hepatobiliary tumor organoids (PDHOs) from a Chinese population. A divergent response to 265 metabolism- and epigenetics-related chemicals and 36 anti-cancer drugs is observed. Integration of the whole genome, transcriptome, chromatin accessibility profiles, and drug sensitivity results of 64 clinically relevant drugs defines over 32,000 genome-drug interactions. RUNX1 promoter mutation is associated with an increase in chromatin accessibility and a concomitant gene expression increase, promoting a cluster of drugs preferentially sensitive in hepatobiliary tumors. These results not only provide an annotated PDHO biobank of human liver cancer but also suggest a systematic approach for obtaining a comprehensive understanding of the gene-regulatory network of liver cancer, advancing the applications of potential personalized medicine.

Precision treatment in advanced hepatocellular carcinoma

The past decade has witnessed significant advances in the systemic treatment of advanced hepatocellular carcinoma (HCC). Nevertheless, the newly developed treatment strategies have not achieved universal success and HCC patients frequently exhibit therapeutic resistance to these therapies. Precision treatment represents a paradigm shift in cancer treatment in recent years. This approach utilizes the unique molecular characteristics of individual patient to personalize treatment modalities, aiming to maximize therapeutic efficacy while minimizing side effects. Although precision treatment has shown significant success in multiple cancer types, its application in HCC remains in its infancy. In this review, we discuss key aspects of precision treatment in HCC, including therapeutic biomarkers, molecular classifications, and the heterogeneity of the tumor microenvironment. We also propose future directions, ranging from revolutionizing current treatment methodologies to personalizing therapy through functional assays, which will accelerate the next phase of advancements in this area.

A pathologic scoring system for predicting postoperative prognosis in patients with ruptured hepatocellular carcinoma

BACKGROUND

The accuracy of pathological factors to predict the prognosis of patients with ruptured hepatocellular carcinoma (rHCC) is unclear. We aimed to develop and validate a novel scoring system based on pathological factors to predict the postoperative survival of patients with rHCC.

METHOD

Patients with rHCC who underwent hepatectomy were recruited from three hospitals and allocated to the training (n = 221) and validation (n = 194) cohorts. A new scoring system, namely the MSE (microvascular invasion-satellite foci-Edmondson Steiner) score, was established based on three pathological factors using univariate and multivariate Cox proportional hazards regression analyses, including microvascular invasion, satellite foci, and differentiation grade. Finally, patients were stratified into three groups based on their risk of prognosis (low, intermediate, or high) according to their MSE score. We also constructed MSE score-based nomograms. The performance of the nomograms was assessed by receiver operating characteristic and calibration curve analyses and validated using the validation cohort.

RESULTS

Three pathological factors were significantly correlated with overall survival (OS) and recurrence-free survival (RFS), three of which were included in the MSE score. The score can clearly stratify rHCC patients after hepatectomy (P < 0.05). And we established nomograms based on the MSE score (MSE score, Barcelona Clinic Liver Cancer stage, and alpha-fetoprotein concentration) to predict postoperative OS and RFS in patients with rHCC. The nomograms showed good discrimination, with C-indices over 0.760 for OS and RFS at 1, 3, and 5 years, respectively. The calibration curve showed excellent nomogram calibration, which was also verified in the validation cohort.

CONCLUSION

The clinical MSE score were accurate in predicting OS and RFS in patients with rHCC with resectable lesions after hepatectomy.

Combined hepatocellular-cholangiocarcinoma compared to hepatocellular carcinoma and intrahepatic cholangiocarcinoma: Different survival, similar recurrence: Report of a large study on repurposed databases with propensity score matching

BACKGROUND

Combined hepatocholangiocarcinoma is a rare cancer with a grim prognosis composed of both hepatocellular carcinoma and intrahepatic cholangiocarcinoma morphologic patterns in the same tumor. The aim of this multicenter, international cohort study was to compare the oncologic outcomes after surgery of combined hepatocholangiocarcinoma to hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

METHODS

Patients treated by surgery for combined hepatocholangiocarcinoma, hepatocellular carcinoma, and intrahepatic cholangiocarcinoma from 2000 to 2021 from multicenter international databases were analyzed retrospectively. Patients with combined hepatocholangiocarcinoma (cases) were compared with 2 control groups of hepatocellular carcinoma or intrahepatic cholangiocarcinoma, sequentially matched using a propensity score based on 8 preoperative characteristics. Overall and disease-free survival were compared, and predictors of mortality and recurrence were analyzed with Cox regression after propensity score matching.

RESULTS

During the study period, 3,196 patients were included. Propensity score adjustment and 2 sequential matching processes produced a new cohort (n = 244) comprising 3 balanced groups was obtained (combined hepatocholangiocarcinoma = 56, intrahepatic cholangiocarcinoma = 66, and hepatocellular carcinoma = 122). Kaplan-Meier overall survival estimations at 1, 3, and 5 years were 67%, 45%, and 28% for combined hepatocholangiocarcinoma, 92%, 75%, and 55% for hepatocellular carcinoma, and 86%, 53%, and 42% for the intrahepatic cholangiocarcinoma group, respectively (P = .0014). Estimations of disease-free survival at 1, 3, and 5 years were 51%, 25%, and 17% for combined hepatocholangiocarcinoma, 63%, 35%, and 26% for the hepatocellular carcinoma group, and 51%, 31%, and 28% for the intrahepatic cholangiocarcinoma group, respectively (P = .19). Predictors of mortality were combined hepatocholangiocarcinoma subtype, metabolic syndrome, preoperative tumor markers alpha-fetoprotein and carbohydrate antigen 19-9, and satellite nodules, and recurrence was associated with satellite nodules rather than cancer subtype.

CONCLUSION

Despite data limitations, overall survival among patients with combined hepatocholangiocarcinoma was worse than both groups and closer intrahepatic cholangiocarcinoma, whereas disease-free survival was similar among the 3 groups. Future research on immunophenotypic profiling may hold more promise than traditional nonmodifiable clinical characteristics (as found in this study) in predicting recurrence or response to salvage treatments.

Molecular profiling in the management of hepatocellular carcinoma

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Metabolic reprogramming in the tumor microenvironment of liver cancer

The liver is essential for metabolic homeostasis. The onset of liver cancer is often accompanied by dysregulated liver function, leading to metabolic rearrangements. Overwhelming evidence has illustrated that dysregulated cellular metabolism can, in turn, promote anabolic growth and tumor propagation in a hostile microenvironment. In addition to supporting continuous tumor growth and survival, disrupted metabolic process also creates obstacles for the anticancer immune response and restrains durable clinical remission following immunotherapy. In this review, we elucidate the metabolic communication between liver cancer cells and their surrounding immune cells and discuss how metabolic reprogramming of liver cancer impacts the immune microenvironment and the efficacy of anticancer immunotherapy. We also describe the crucial role of the gut-liver axis in remodeling the metabolic crosstalk of immune surveillance and escape, highlighting novel therapeutic opportunities.

Emerging trends in gastrointestinal cancers: Targeting developmental pathways in carcinogenesis and tumor progression

Gastrointestinal carcinomas are a group of cancers associated with the digestive system and its accessory organs. The most prevalent cancers related to the gastrointestinal tract are colorectal, gall bladder, gastric, hepatocellular, and esophageal cancers, respectively. Molecular aberrations in different signaling pathways, such as signal transduction systems or developmental pathways are the chief triggering mechanisms in different cancers Though a massive advancement in diagnostic and therapeutic interventions results in improved survival of patients with gastrointestinal cancer; the lower malignancy stages of these carcinomas are comparatively asymptomatic. Various gastrointestinal-related cancers are detected at advanced stages, leading to deplorable prognoses and increased rates of recurrence. Recent molecular studies have elucidated the imperative roles of several signaling pathways, namely Wnt, Hedgehog, and Notch signaling pathways, play in the progression, therapeutic responsiveness, and metastasis of gastrointestinal-related cancers. This book chapter gives an interesting update on recent findings on the involvement of developmental signaling pathways their mechanistic insight in gastrointestinalcancer. Subsequently, evidences supporting the exploration of gastrointestinal cancer related molecular mechanisms have also been discussed for developing novel therapeutic strategies against these debilitating carcinomas.

Comprehensive analysis of the role of Netrin G1 (NTNG1) in hepatocellular carcinoma cells

Netrin G1 (NTNG1) is a member of the Netrin family and plays a crucial role in various human cancers. However, the molecular functions of NTNG1 in HCC and the underlying mechanisms remain unclear. HCC expression data was obtained from the GEO database and analyzed using various bioinformatics tools. The expression of NTNG1 in HCC tissues and liver cancer cells was evaluated through RT-qPCR and western blotting. Cells with stable NTNG1 overexpression and knockdown were established, and CCK-8, colony formation, and flow cytometry assays were conducted in vitro. The xenograft model was utilized to verify the tumorigenesis capacity of NTNG1 in vivo. IHC was employed to analyze the expression of NTNG1 and CD163 proteins. HCC-specific genes were screened, followed by functional enrichment and immune cell infiltration analysis. Finally, the Co-IP was used to detect the interaction between NTNG1 and N-cadherin. NTNG1 was highly expressed in HCC tissues and liver cancer cells, and associated with significantly poorer OS rates. In addition, NTNG1 overexpression in liver cancer cells significantly increased their proliferation, colony growth, invasion, migration, and EMT, while inhibiting apoptosis. Bioinformatics analyses indicated that NTNG1 was closely related to EMT and tumor infiltration. IHC staining revealed a positive correlation between NTNG1 expression and CD163 in HCC tissues. Additionally, an EMT inhibitor attenuated the expression levels of EMT-related markers and counteracted the effects of NTNG1 overexpression in liver cancer cells. This study is the first to identify NTNG1 as a potential therapeutic target in HCC, promoting tumor development and progression by regulating EMT.

Targeting the SphK1/S1P/PFKFB3 axis suppresses hepatocellular carcinoma progression by disrupting glycolytic energy supply that drives tumor angiogenesis

BACKGROUND

Hepatocellular carcinoma (HCC) remains a leading life-threatening health challenge worldwide, with pressing needs for novel therapeutic strategies. Sphingosine kinase 1 (SphK1), a well-established pro-cancer enzyme, is aberrantly overexpressed in a multitude of malignancies, including HCC. Our previous research has shown that genetic ablation of Sphk1 mitigates HCC progression in mice. Therefore, the development of PF-543, a highly selective SphK1 inhibitor, opens a new avenue for HCC treatment. However, the anti-cancer efficacy of PF-543 has not yet been investigated in primary cancer models in vivo, thereby limiting its further translation.

METHODS

Building upon the identification of the active form of SphK1 as a viable therapeutic target in human HCC specimens, we assessed the capacity of PF-543 in suppressing tumor progression using a diethylnitrosamine-induced mouse model of primary HCC. We further delineated its underlying mechanisms in both HCC and endothelial cells. Key findings were validated in Sphk1 knockout mice and lentiviral-mediated SphK1 knockdown cells.

RESULTS

SphK1 activity was found to be elevated in human HCC tissues. Administration of PF-543 effectively abrogated hepatic SphK1 activity and significantly suppressed HCC progression in diethylnitrosamine-treated mice. The primary mechanism of action was through the inhibition of tumor neovascularization, as PF-543 disrupted endothelial cell angiogenesis even in a pro-angiogenic milieu. Mechanistically, PF-543 induced proteasomal degradation of the critical glycolytic enzyme 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3, thus restricting the energy supply essential for tumor angiogenesis. These effects of PF-543 could be reversed upon S1P supplementation in an S1P receptor-dependent manner.

CONCLUSIONS

This study provides the first in vivo evidence supporting the potential of PF-543 as an effective anti-HCC agent. It also uncovers previously undescribed links between the pro-cancer, pro-angiogenic and pro-glycolytic roles of the SphK1/S1P/S1P receptor axis. Importantly, unlike conventional anti-HCC drugs that target individual pro-angiogenic drivers, PF-543 impairs the PFKFB3-dictated glycolytic energy engine that fuels tumor angiogenesis, representing a novel and potentially safer therapeutic strategy for HCC.

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

Background

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

Materials and Methods

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

Results

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

Conclusion

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

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

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

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

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

Liquid Liver Biopsy for Disease Diagnosis and Prognosis

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

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

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