Hepatocellular Carcinoma Subgroups Research Articles

Alpha-fetoprotein-to-PIVKA-II ratio as a potential biomarker for hepatocellular carcinoma differentiation, imaging characteristics, and patient survival.

Alpha-fetoprotein-to-PIVKA-II ratio (APR) may serve as a new marker to predict the grade of differentiation, imaging characteristics, and prognosis of hepatocellular carcinoma (HCC). This study aimed to demonstrate the prognostic significance of high APR for poorly differentiated HCC (PD-HCC), imaging characteristics and overall survival (OS) in patients after intra-arterial therapies. Receiver operating characteristic (ROC) curves were constructed and areas under the curve (AUCs) were calculated to evaluate the predictive ability of APR to discriminate subgroup(s) of HCC with good or poor prognosis. Kaplan-Meier survival analysis was performed to evaluate the effect of tumor differentiation and change in APR on overall patient survival. The cut-off value of APR used in the diagnostic setting was 0.175. Almost all patients in the PD-HCC group (90.9%) had a high APR value, while 100% and 84.2% of well-differentiated and moderately differentiated HCC (WD-HCC and MD-HCC) patients, respectively, had a low APR value (P<0.001). APR had a high sensitivity (91%) and specificity (90%) in differentiating PD-HCCs from WD-HCCs/MD-HCCs (P<0.001). Patients with high APR tended to have large and multiple tumors, vascular invasion and high percentage signal ratio (PSR). OS was slightly shorter in the PD-HCC group and in the high (>0.175) APR group. This study showed that patients with high APR and those with PD-HCC had a worse prognosis, and APR could be an important non-invasive biomarker for predicting the degree of tumor differentiation, imaging characteristics and patient prognosis.

Serum thymosin beta 10 level as a potential prognosis prediction of hepatocellular carcinoma and hepatic diseases

Thymosin Beta 10 (TMSB10) is a thymosin family member that has been identified as being overexpressed in a wide variety of human cancers. This study aimed to determine the expression level of TMSB10 in sera of patients with hepatocellular carcinoma (HCC) and liver cirrhosis. And to reveal the association between TMSB10 and different stages in patients with HCC. We also wanted to know how TMSB10 is predictive in HCC patients and its relation to the Barcelona Clinic's staging system. The study included 41 HCC patients, 15 liver cirrhosis patients, and 15 normal control subjects. The enzyme-linked immunosorbent assay was used to determine serum levels of TMSB10 and alpha-fetoprotein (AFP) in serum of normal control individuals and patients with liver cirrhosis and different stages of HCC, and to evaluate the relationship of AFP with TMSB10. The TMSB10 levels in patients with HCC were statistically different than in the control group and in the different stages of HCC. We found a statistically significant difference in the distribution of TMSB10 between the three study groups (p&lt; 0.001). There was an association between TMSB10 concentration and AFP. The level of TMSB10 in the serum of the HCC subgroups was then analyzed. The TMSB10 level increased with the advance of HCC stages. The TMSB10 level in HCC patients did not correlate with levels of liver function tests including aminotransferase, aspartate aminotransferase, albumin, prothrombin, bilirubin, or alkaline phosphatase. In conclusion, serum TMSB10 levels can be used as a potential prognostic marker for clinical stages of HCC.

Genetic variants of Nuclear Factor-Kappa B were associated with different outcomes of Hepatitis C virus infection among Egyptian patients.

Hepatitis C virus (HCV) is a major risk factor for chronic hepatitis and hepatocellular carcinoma (HCC). Nuclear factor kappa B (NF-κB) is a transcription factor that functions in health and disease. Genetic variants of the NF-κB gene can affect its function and are associated with chronic inflammatory changes and malignant transformation. This case-control study is aimed to determine the possible association between NF-κB genetic variants and different outcomes of HCV infection among Egyptian patients. 295 subjects were recruited with allocation of participants in the representative group according to results of serological and molecular tests. Patients in the case group (group A) were further divided into three subgroups; subgroup I, mild chronic HCV, subgroup II, cirrhosis, and subgroup III, HCC subgroups (59 for each subgroup), group B included participants who experienced spontaneous viral clearance (n=59). All were compared to matched healthy control subjects, Group C (n=59). All participants were genotyped for NF-κB polymorphisms, rs11820062 by TaqMan assay and rs28362491 by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Risk analysis indicated that subjects carrying the rs11820062 A genotype are more susceptible to HCV infection (OR: 3.1; 95%, CI= 1.4-6.9). Subjects carrying the rs28362491 insertion genotype are at more risk of progression to cirrhosis when compared to healthy-controls and patients with mild chronic HCV (OR:7.7; 95% CI=2.4-24.3 and OR:5.1, 95% CI= 1.7-15.7, respectively) and also are at more risk of developing HCC when compared to healthy controls (OR:2.6; 95% CI= 0.94-7.3). Polymorphisms affecting NF-κB different genes would modulate HCV infection susceptibility and clinical disease progression among Egyptian patients.

Syngeneic mouse model of YES-driven metastatic and proliferative hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a disease of high unmet medical need that has become a global health problem. The development of targeted therapies for HCC has been hindered by the incomplete understanding of HCC pathogenesis and the limited number of relevant preclinical animal models. We recently unveiled a previously uncharacterized YES kinase (encoded by YES1)-dependent oncogenic signaling pathway in HCC. To model this subset of HCC, we established a series of syngeneic cell lines from liver tumors of transgenic mice expressing activated human YES. The resulting cell lines (referred to as HepYF) were enriched for expression of stem cell and progenitor markers, proliferated rapidly, and were characterized by high SRC family kinase (SFK) activity and activated mitogenic signaling pathways. Transcriptomic analysis indicated that HepYF cells are representative of the most aggressive proliferation class G3 subgroup of HCC. HepYF cells formed rapidly growing metastatic tumors upon orthotopic implantation into syngeneic hosts. Treatment with sorafenib or the SFK inhibitor dasatinib markedly inhibited the growth of HepYF tumors. The new HepYF HCC cell lines provide relevant preclinical models to study the pathogenesis of HCC and test novel small-molecule inhibitor and immunotherapy approaches.

Does depressurization of the portal vein before liver transplantation affect the recurrence of HCC? A nested case-control study

BackgroundPortal hypertension (PHT) has been proven to be closely related to the development of hepatocellular carcinoma (HCC). Whether PHT before liver transplantation (LT) will affect the recurrence of HCC is not clear.Methods110 patients with depressurization of the portal vein (DPV) operations (Transjugular Intrahepatic Portosystemic Shunt—TIPS, surgical portosystemic shunt or/and splenectomy) before LT from a HCC LT cohort, matched with 330 preoperative non-DPV patients; this constituted a nested case-control study. Subgroup analysis was based on the order of DPV before or after the occurrence of HCC.ResultsThe incidence of acute kidney injury and intra-abdominal bleeding after LT in the DPV group was significantly higher than that in non-DPV group. The 5-year survival rates in the DPV and non-DPV group were 83.4% and 82.7% respectively (P = 0.930). In subgroup analysis, patients in the DPV prior to HCC subgroup may have a lower recurrence rate (4.7% vs.16.8%, P = 0.045) and a higher tumor free survival rate (88.9% vs.74.4%, P = 0.044) after LT under the up-to-date TNMI–II stage, while in TNM III stage, there was no difference for DPV prior to HCC subgroup compared with the DPV after HCC subgroup or the non-DPV group.ConclusionCompared with DPV after HCC, DPV treatment before HCC can reduce the recurrence rate of HCC after early transplantation (TNM I-II). DPV before LT can reduce the recurrence of early HCC.

Evaluation of models to predict prognosis in patients with advanced hepatocellular carcinoma treated with TACE combined with apatinib.

The HAP, Six-and-Twelve, Up to Seven, and ALBI scores have been substantiated as reliable prognostic markers in patients presenting with intermediate and advanced hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE) treatment. Given this premise, our research aims to assess the predictive efficacy of these models in patients with intermediate and advanced HCC receiving a combination of TACE and Apatinib. Additionally, we have conducted a meticulous comparative analysis of these four scoring systems to discern their respective predictive capacities and efficacies in combined therapy. Performing a retrospective analysis on the clinical data from 200 patients with intermediate and advanced HCC, we studied those who received TACE combined with Apatinib at the First Affiliated Hospital of the University of Science and Technology of China between June 2018 and December 2022. To identify the factors affecting survival, the study performed univariate and multivariate Cox regression analyses, with calculations of four different scores: HAP, Six-and-Twelve, Up to Seven, and ALBI. Lastly, Harrell's C-index was employed to compare the prognostic abilities of these scores. Cox proportional hazards model results revealed that the ALBI score, presence of portal vein tumor thrombus (PVTT, )and tumor size are independent determinants of prognostic survival. The Kaplan-Meier analyses showed significant differences in survival rates among patients classified by the HAP, Six-and-Twelve, Up to Seven, and ALBI scoring methods. Of the evaluated systems, the HAP scoring demonstrated greater prognostic precision, with a Harrell's C-index of 0.742, surpassing the alternative models (P < 0.05). In addition, an analysis of the area under the AU-ROC curve confirms the remarkable superiority of the HAP score in predicting short-term survival outcomes. Our study confirms the predictive value of HAP, Six-and-Twelve, Up to Seven, and ALBI scores in intermediate to advanced Hepatocellular Carcinoma (HCC) patients receiving combined Transarterial Chemoembolization (TACE) and Apatinib therapy. Notably, the HAP model excels in predicting outcomes for this specific HCC subgroup.

Distinct alterations of gut microbiota between viral- and non-viral-related hepatocellular carcinoma

Altered gut microbiota has been connected to hepatocellular carcinoma (HCC) occurrence and advancement. This study was conducted to identify a gut microbiota signature in differentiating between viral-related HCC (Viral-HCC) and non-hepatitis B-, non-hepatitis C-related HCC (NBNC-HCC). Fecal specimens were obtained from 16 healthy controls, 33 patients with viral-HCC (17 and 16 cases with hepatitis B virus (HBV) and hepatitis C virus (HCV) infection, respectively), and 18 patients with NBNC-HCC. Compositions of fecal microbiota were assessed by 16S rRNA sequencing. Bioinformatic analysis was performed by the DADA2 pipeline in the R program. Significantly different genera from the top 50 relative abundance were used to classify between subgroups of HCC by the Random Forest algorithm. Our data demonstrated that the HCC group had a significantly decreased alpha-diversity and changed microbial composition in comparison with healthy controls. Within the top 50 relative abundance, there were 11 genera including Faecalibacterium, Agathobacter, and Coprococcus that were significantly enhanced in Viral-HCC, while 5 genera such as Bacteroides, Streptococcus, Ruminococcus gnavus group, Parabacteroides, and Erysipelatoclostridium were enhanced in NBNC-HCC. Compared to Viral-HCC, the NBNC-HCC subgroup significantly reduced various short-chain fatty acid-producing bacteria, as well as declined fecal butyrate but elevated plasma surrogate markers of microbial translocation. Based on the machine learning algorithm, a high diagnostic accuracy to classify HCC subgroups was achieved with an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.94. Collectively, these data revealed that gut dysbiosis was distinct according to etiological factors of HCC, which might play an essential role in hepatocarcinogenesis. These findings underscore the possible use of a gut microbiota signature for the diagnosis and therapeutic approaches regarding different subgroups of HCC.Key points• Gut dysbiosis is connected to hepatocarcinogenesis and can be used as a novel biomarker.• Gut microbiota composition is significantly altered in different etiological factors of HCC.• Microbiota-based signature can accurately distinguish between Viral-HCC and NBNC-HCC.

SPP2 plays a role in the tumorigenesis of hepatocellular carcinoma: A bioinformatic based analysis.

Hepatocellular carcinoma (HCC) patients at the same stage exhibit different prognosis, and the underlying molecular mechanism remains unclear. This study aims to identify the key genes impacting the prognosis of HCC patients. Differentially expressed gene analyses were performed between HCC samples and normal ones, and between patients with long overall survival (OS) and those with short OS, in TCGA-LIHC and GSE14520 datasets. The Kaplan-Meier method with log-rank test was used to evaluate the role of secreted phosphoprotein 2 (SPP2) in the prognosis of HCC patients. Gene set enrichment analysis (GSEA) was used to understand the difference of enriched signaling pathways between SPP2-stratified HCC subgroups. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the potential functional pathways in which SPP2 might participate. SPP2 was significantly down-regulated in tumors when compared with normal tissues, or in tumor samples with short OS when compared with those with long OS [fold change (FC)>2 and false discovery rate (FDR)<0.05]. Low expression of SPP2 was associated with worse clinicopathological features like vascular invasion (P=1.6e-05), poor cancer status (with tumor, P=0.021), advanced T stage (T3 or T4, P=4.5e-04), advanced TNM stage (stage III or IV, P=3.1e-04), and with unfavorable prognosis (shorter OS, P=0.002). Gene enrichment analyses revealed that SPP2 might involve in the metabolic homeostasis of HCC and in the development of liver fibrosis and cirrhosis. SPP2 might inhibit the development of liver fibrosis and cirrhosis and the tumorigenesis of HCC, and analogs of SPP2 might be potential drugs in the prevention of these diseases.

Comprehensive analysis of ASB3 as a prognostic biomarker in hepatocellular carcinoma

BackgroundSome reports have indicated a high expression level of ASB3 in various cancers, but its role in hepatocellular carcinoma (HCC) remains elusive. MethodsASB3 levels and clinical features were obtained from the TCGA database. Meanwhile, the expression levels of ASB3 in tumor and paraneoplastic tissues were further verified by qRT-PCR and Imunohistochemistry (IHC). ASB3-related downstream molecular analysis was carried out with Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Pathways linked to ASB3 expression were identified by means of gene set enrichment analysis (GSEA). Single-sample GSEA (ssGSEA) aided in conducting a correlation analysis of ASB3 with immune infiltration. Functional experiments were performed in HepG2 cells by using the small interfering RNA. ResultsASB3 expression was remarkably higher in HCC tissues. Its remarkable precision in forecasting cancer suggests that ASB3 might serve as an unidentified diagnostic and prognostic indicator of HCC. Higher ASB3 expression led to worse overall survival (OS), particularly in various clinical subgroups of HCC. GO/KEGG analysis indicated that critical biological activities, such as the activation of complement systems and humoral immune response, could potentially underlie the progression of HCC. Furthermore, GSEA demonstrated enrichment of certain pathways, including the MAPK, IL17, and fibrinolysis pathways, in samples with elevated ASB3 levels. ASB3 exhibited a substantial association with T helper cells, dendritic cells (DCs), and central memory T (Tcm) cell infiltration level. Cell function experiments confirmed elevated ASB3 levels in HCC cell lines as opposed to hepatic epithelial cell lines. Moreover, the ability of HCC cells to proliferate and invade was remarkably reduced by ASB3 knockdown. ConclusionSummarize briefly, we found that ASB3 can be a promising biomarker in HCC.

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

BackgroundAlthough genome duplication, or polyploidization, is believed to drive cancer evolution and affect tumor features, its significance in hepatocellular carcinoma (HCC) is unclear. We aimed to determine the characteristics of polyploid HCCs by evaluating chromosome duplication and to discover surrogate markers to discriminate polyploid HCCs.MethodsThe ploidy in human HCC was assessed by fluorescence in situ hybridization for multiple chromosomes. Clinicopathological and expression features were compared between polyploid and near-diploid HCCs. Markers indicating polyploid HCC were explored by transcriptome analysis of cultured HCC cells.ResultsPolyploidy was detected in 36% (20/56) of HCCs and discriminated an aggressive subset of HCC that typically showed high serum alpha-fetoprotein, poor differentiation, and poor prognosis compared to near-diploid HCCs. Molecular subtyping revealed that polyploid HCCs highly expressed alpha-fetoprotein but did not necessarily show progenitor features. Histological examination revealed abundant polyploid giant cancer cells (PGCCs) with a distinct appearance and frequent macrotrabecular-massive architecture in polyploid HCCs. Notably, the abundance of PGCCs and overexpression of ubiquitin-conjugating enzymes 2C indicated polyploidy in HCC and efficiently predicted poor prognosis in combination.ConclusionsHistological diagnosis of polyploidy using surrogate markers discriminates an aggressive subset of HCC, apart from known HCC subgroups, and predict poor prognosis in HCC.

Artificial intelligence-based reticulin proportionate area - anovel histological outcome predictor in hepatocellular carcinoma.

Reticulin stain is used routinely in the histological evaluation of hepatocellular carcinoma (HCC). The goal of this study was to assess whether the histological reticulin proportionate area (RPA) in HCCs predicts tumour-related outcomes. We developed and validated a supervised artificial intelligence (AI) model that utilises a cloud-based, deep-learning AI platform (Aiforia Technologies, Helsinki, Finland) to specifically recognise and quantify the reticulin framework in normal livers and HCCs using routine reticulin staining. We applied this reticulin AI model to a cohort of consecutive HCC cases from patients undergoing curative resection between 2005 and 2015. A total of 101 HCC resections were included (median age = 68 years, 64 males, median follow-up time = 49.9 months). AI model RPA reduction of > 50% (compared to normal liver tissue) was predictive of metastasis [hazard ratio (HR) = 3.76, P = 0.004, disease-free survival (DFS, HR = 2.48, P < 0.001) and overall survival (OS), HR = 2.80, P = 0.001]. In a Cox regression model, which included clinical and pathological variables, RPA decrease was an independent predictor of DFS and OS and the only independent predictor of metastasis. Similar results were found in the moderately differentiated HCC subgroup (WHO grade 2), in which reticulin quantitative analysis was an independent predictor of metastasis, DFS and OS. Our data indicate that decreased RPA is a strong predictor of various HCC-related outcomes, including within the moderately differentiated subgroup. Reticulin, therefore, may represent a novel and important prognostic HCC marker, to be further explored and validated.

PANoptosis-based molecular subtyping and HPAN-index predicts therapeutic response and survival in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a highly prevalent and fatal cancer. The role of PANoptosis, a novel form of programmed cell death, in HCC is yet to be fully understood. This study focuses on identifying and analyzing PANoptosis-associated differentially expressed genes in HCC (HPAN_DEGs), aiming to enhance our understanding of HCC pathogenesis and potential treatment strategies. We analyzed HCC differentially expressed genes from TCGA and IGCG databases and mapped them to the PANoptosis gene set, identifying 69 HPAN_DEGs. These genes underwent enrichment analyses, and consensus clustering analysis was used to determine three distinct HCC subgroups based on their expression profiles. The immune characteristics and mutation landscape of these subgroups were evaluated, and drug sensitivity was predicted using the HPAN-index and relevant databases. The HPAN_DEGs were mainly enriched in pathways associated with the cell cycle, DNA damage, Drug metabolism, Cytokines, and Immune receptors. We identified three HCC subtypes (Cluster_1, SFN+PDK4-; Cluster_2, SFN-PDK4+; Cluster_3, SFN/PDK4 intermediate expression) based on the expression profiles of the 69 HPAN_DEGs. These subtypes exhibited distinct clinical outcomes, immune characteristics, and mutation landscapes. The HPAN-index, generated by machine learning using the expression levels of 69 HPAN_DEGs, was identified as an independent prognostic factor for HCC. Moreover, the high HPAN-index group exhibited a high response to immunotherapy, while the low HPAN-index group showed sensitivity to small molecule targeted drugs. Notably, we observed that the YWHAB gene plays a significant role in Sorafenib resistance. This study identified 69 HPAN_DEGs crucial to tumor growth, immune infiltration, and drug resistance in HCC. Additionally, we discovered three distinct HCC subtypes and constructed an HPAN-index to predict immunotherapeutic response and drug sensitivity. Our findings underscore the role of YWHAB in Sorafenib resistance, presenting valuable insights for personalized therapeutic strategy development in HCC.

Decreased GPX3 mRNA level in peripheral blood mononuclear cells is associated with HBV-related hepatocellular carcinoma.

Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) is one of the most common malignancies with increasing mortality. In this study, we aim to determine the alteration and diagnostic value of GXP3 expression for HBV-related HCC. We recruited 243 subjects, including 132 HBV-related HCC patients, 78 chronic hepatitis B (CHB) patients and 33 healthy controls (HCs). The mRNA level of GPX3 in peripheral blood mononuclear cells (PBMCs) was assessed by quantitative real-time PCR. The GPX3 plasma level was detected by ELISA. The GPX3 mRNA level was significantly decreased in HBV-related HCC patients compared with in CHB patients and HCs (p<0.05). The plasma GPX3 level was significantly lower in patients with HBV-related HCC than in CHB patients and HCs (p<0.05). In the HCC subgroup, the GPX3 mRNA level was significantly lower in patients with positive HBeAg, ascites, advanced stage and poor differentiation compared with in the other groups (p<0.05). The receiver operating characteristic curve was constructed to estimate the diagnostic value of the GPX3 mRNA level for HBV-related HCC. The GPX3 mRNA level showed a significantly better diagnostic ability compared with alpha fetoprotein (AFP) (area under the curve 0.769 vs 0.658, p<0.001). A decreased GPX3 mRNA level might be a potential non-invasive biomarker for HBV-related HCC. It showed better diagnostic ability than AFP.

HBV DNA Integration into Telomerase or MLL4 Genes and TERT Promoter Point Mutation as Three Independent Signatures in Subgrouping HBV-Related HCC with Distinct Features

Introduction: A set of genetic mutations to classify hepatocellular carcinoma (HCC) useful to clinical studies is an unmet need. Hepatitis B virus-related HCC (HBV-HCC) harbors a unique genetic mutation, namely, the HBV integration, among other somatic endogenous gene mutations. We explored a combination of HBV DNA integrations and common somatic mutations to classify HBV-HCC by using a capture-sequencing platform. Methods: A total of 153 HBV-HCCs after surgical resection were subjected to capture sequencing to identify HBV integrations and three common somatic mutations in genomes. Three mutually exclusive mutations, HBV DNA integration into the TERT promoter, HBV DNA integration into MLL4, or TERT promoter point mutation, were identified in HBV-HCC. Results: They were used to classify HBV-HCCs into four groups: G1 with HBV-TERT integration (25.5%); G2 with HBV-MLL4 integration (10.5%); G3 with TERT promoter mutation (30.1%); and G4 without these three mutations (34.0%). Clinically, G3 has the highest male-to-female ratio, cirrhosis rate, and associated with higher early recurrence and mortality after resection, but G4 has the best outcome. Transcriptomic analysis revealed a grouping different from the published ones and G2 with an active immune profile related to immune checkpoint inhibitor response. Analysis of integrated HBV DNA provided clues for HBV genotype and variants in carcinogenesis of different HCC subgroup. This new classification was also validated in another independent cohort. Conclusion: A simple and robust genetic classification was developed to aid in understanding HBV-HCC and in harmonizing clinical studies.

Hepatocellular carcinomas, exhibiting intratumor fibrosis, express cancer-specific extracellular matrix remodeling and WNT/TGFB signatures, associated with poor outcome.

HCC, the third leading cause of cancer-related death, arises in the context of liver fibrosis. Although HCC is generally poorly fibrogenic, some tumors harbor focal intratumor extracellular matrix (ECM) deposits called "fibrous nests." To date, the molecular composition and clinical relevance of these ECM deposits have not been fully defined. We performed quantitative matrisome analysis by tandem mass tags mass spectrometry in 20 human cancer specific matrisome (HCCs) with high or low-grade intratumor fibrosis and matched nontumor tissues, as well as in 12 livers from mice treated with vehicle, carbon tetrachloride, or diethylnitrosamine. We found 94 ECM proteins differentially abundant between high and low-grade fibrous nests, including interstitial and basement membrane components, such as several collagens, glycoproteins, proteoglycans, enzymes involved in ECM stabilization and degradation, and growth factors. Pathway analysis revealed a metabolic switch in high-grade fibrosis, with enhanced glycolysis and decreased oxidative phosphorylation. Integrating the quantitative proteomics with transcriptomics from HCCs and nontumor livers (n = 2,285 samples), we identified a subgroup of fibrous nest HCCs, characterized by cancer-specific ECM remodeling, expression of the WNT/TGFB (S1) subclass signature, and poor patient outcome. Fibrous nest HCCs abundantly expressed an 11-fibrous-nest - protein signature, associated with poor patient outcome, by multivariate Cox analysis, and validated by multiplex immunohistochemistry. Matrisome analysis highlighted cancer-specific ECM deposits, typical of the WNT/TGFB HCC subclass, associated with poor patient outcomes. Hence, histologic reporting of intratumor fibrosis in HCC is of clinical relevance.

Identification of TIAM1 as a Potential Synthetic-Lethal-like Gene in a Defined Subset of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC), the most common type of liver cancer, has very poor outcomes. Current therapies often have low efficacy and significant toxicities. Thus, there is a critical need for the development of novel therapeutic approaches for HCC. We have developed a novel bioinformatics pipeline, which integrates genome-wide DNA methylation and gene expression data, to identify genes required for the survival of specific molecular cancer subgroups but not normal cells. Targeting these genes may induce cancer-specific "synthetic lethality". Initially, five potential HCC molecular subgroups were identified based on global DNA methylation patterns. Subgroup-2 exhibited the most unique methylation profile and two candidate subtype-specific vulnerability or SL-like genes were identified for this subgroup, including TIAM1, a guanine nucleotide exchange factor encoding gene known to activate Rac1 signalling. siRNA targeting TIAM1 inhibited cell proliferation in TIAM1-positive (subgroup-2) HCC cell lines but had no effect on the normal hepatocyte HHL5 cell line. Furthermore, TIAM1-positive/subgroup-2 cell lines were significantly more sensitive to the TIAM1/RAC1 inhibitor NSC23766 compared with TIAM1-negative HCC lines or the normal HHL5 cell line. The results are consistent with a synthetic lethal role for TIAM1 in a methylation-defined HCC subgroup and suggest it may be a viable therapeutic target in this subset of HCC patients.

Construction of Two Independent RAB Family-Based Scoring Systems Based on Machine Learning Algorithms and Definition of RAB13 as a Novel Therapeutic Target for Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) remains a global health challenge with a low early diagnosis rate and high mortality. The Rab GTPase (RAB) family plays an essential role in the occurrence and progression of HCC. Nonetheless, a comprehensive and systematic investigation of the RAB family has yet to be performed in HCC. We comprehensively assessed the expression landscape and prognostic significance of the RAB family in HCC and systematically correlated these RAB family genes with tumor microenvironment (TME) characteristics. Then, three RAB subtypes with distinct TME characteristics were determined. Using a machine learning algorithm, we further established a RAB score to quantify TME features and immune responses of individual tumors. Moreover, to better evaluate patient prognosis, we established a RAB risk score as an independent prognostic factor for patients with HCC. The risk models were validated in independent HCC cohorts and distinct HCC subgroups, and their complementary advantages guided clinical practice. Furthermore, we further confirmed that the knockdown of RAB13, a pivotal gene in risk models, suppressed HCC cell proliferation and metastasis by inhibiting the PI3K/AKT signaling pathway, CDK1/CDK4 expression, and epithelial-mesenchymal transition. In addition, RAB13 inhibited the activation of JAK2/STAT3 signaling and the expression of IRF1/IRF4. More importantly, we confirmed that RAB13 knockdown enhanced GPX4-dependent ferroptosis vulnerability, highlighting RAB13 as a potential therapeutic target. Overall, this work revealed that the RAB family played an integral role in forming HCC heterogeneity and complexity. RAB family-based integrative analysis contributed to enhancing our understanding of the TME and guided more effective immunotherapy and prognostic evaluation.

A novel liver zonation phenotype-associated molecular classification of hepatocellular carcinoma.

Liver zonation is a unique phenomenon in which the liver exhibits distinct functions among hepatocytes along the radial axis of the lobule. This phenomenon can cause the sectionalized initiation of several liver diseases, including hepatocellular carcinoma (HCC). However, few studies have explored the zonation features of HCC. Four single-cell RNA sequencing datasets were used to identify hepatocyte-specific zonation markers. Integrative analysis was then performed with a training RNA-seq cohort (616 HCC samples) and an external validating microarray cohort (285 HCC samples) from the International Cancer Genome Consortium, The Cancer Genome Atlas, Gene Expression Omnibus, and EMBL's European Bioinformatics Institute for clustering using non-negative matrix factorization consensus clustering based on zonation genes. Afterward, we evaluated the prognostic value, clinical characteristics, transcriptome and mutation features, immune infiltration, and immunotherapy response of the HCC subclasses. A total of 94 human hepatocyte-specific zonation markers (39 central markers and 55 portal markers) were identified for the first time. Subsequently, three subgroups of HCC, namely Cluster1, Cluster2, and Cluster3 were identified. Cluster1 exhibited a non-zonational-like signature with the worst prognosis. Cluster2 was intensively associated with a central-like signature and exhibited low immune infiltration and sensitivity toward immune blockade therapy. Cluster3 was intensively correlated with a portal-like signature with the best prognosis. Finally, we identified candidate therapeutic targets and agents for Cluster1 HCC samples. The current study established a novel HCC classification based on liver zonation signature. By classifying HCC into three clusters with non-zonational-like (Cluster1), central-like (Cluster2), and portal-like (Cluster3) features, this study provided new perspectives on the heterogeneity of HCC and shed new light on delivering precision medicine for HCC patients.

Construction and validation of an IRF4 risk score to predict prognosis and response to immunotherapy in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) remains a global health challenge due to high recurrence and metastasis rates. The interferon regulatory factor (IRF) family plays an essential role in the tumour immune microenvironment. However, an IRF family-based score that can predict prognosis and response to immunotherapy in HCC patients has not been adequately investigated. Here, we comprehensively evaluated the expression landscape and prognostic significance of IRF family genes as well as their relationship with the immune microenvironment. We further screened IRF4-associated genes to construct a signature and explored their biological features. Then, we established an IRF4 risk score consisting of nine IRF4-associated genes. Importantly, we demonstrated significant differences in the prognostic stratification and immune characteristics of HCC patients with different IRF4 risk scores. The predictive capability of the IRF4 risk score was validated in different HCC subgroups and independent HCC cohorts. Moreover, immunohistochemical analysis of our HCC cohort revealed a positive correlation between IRF4 and PD-1 expression. In vitro experiments demonstrated that the overexpression of IRF4 inhibited the proliferation and migration capacity of HCC cells by restricting the JAK2/STAT3 signalling pathway and epithelial-mesenchymal transition. Overall, our study identified a novel IRF4 risk score that could serve as a robust prognostic biomarker and provide therapeutic benefits for immunotherapy in HCC patients, which may be helpful for clinical decision-making for HCC patients.

Animal Models of Hepatocellular Carcinoma: Current Applications in Clinical Research.

In the last decade, relevant advances have occurred in the treatment of hepatocellular carcinoma (HCC), with novel drugs entering the clinical practice, among which tyrosine kinase inhibitors (TKIs) such as lenvatinib, cabozantinib and regorafenib, and immune checkpoint inhibitors (ICPIs) either alone or in combination with VEGF inhibitors. Clinical trials have driven the introduction of such novel molecules into the clinics but, at present, no biomarker drives the choice of first-line options, which relies only upon clinical and imaging assessment. Remarkably, clinical and imaging-based evaluations do not consider the huge heterogeneity of HCC and do not allow to realize the potential of personalized treatments. Preclinical research still does not inform the design of clinical trials, even though many animal models mimicking specific subgroups of HCC are available and might provide relevant information. Although animal models directly informing the clinical practice, such as patients-derived xenografts, are not used to help the choice of treatment in advanced HCC, however, the preclinical research can count on a wide range of valuable models. Here we will review some HCC models which might turn informative for specific questions in defined patient subgroups, and we will describe recent preclinical studies for the mechanistic evaluation of immunotherapy-based treatment approaches. To this aim, we will mainly focus on two issues: (i) HCC models informative on NAFLD-NASH HCC and (ii) HCC models helping to elucidate mechanisms underneath immunotherapy. We have chosen these two settings since they represent, respectively, the most rapidly arising cause of chronic liver disease (CLD) and HCC in western countries and the most promising therapeutic option for advanced HCC.