Hepatocellular Carcinoma Samples Research Articles

Identification of a Macrophage marker gene signature to evaluate immune infiltration and therapeutic response in hepatocellular carcinoma

BackgroundOnly a minority of hepatocellular carcinoma (HCC) patients can benefit from systemic regimens. Macrophages, which abundantly infiltrate in HCC, could mediate tumour microenvironment remodelling and immune escape, proving to be powerful weapons in combating HCC. Thus, a deeper understanding of macrophages is necessary for improving existing antitumour treatments. MethodsWith a series of bioinformatic approaches, we comprehensively explored the role of macrophage-related genes in human HCCs from multiple single-cell and bulk RNA sequencing datasets. Unsupervised clustering was performed to cluster the macrophage marker genes (MMGs). GSVA and functional enrichment analysis were used to elucidate the functional differences among the MMG-associated clusters. Subsequently, a component analysis algorithm was used to construct a Macrosig score, and the prognosis, biological characteristics, mutation profile, TME cell infiltration status and drug response of patients with different Macrosig scores were further analysed. ResultsWe identified 13 MMGs in 574 HCC samples, based on which three MMG-associated clusters were defined. Overall survival time, clinicopathological features and immune infiltration scores differed among the different clusters. On this basis, 12 hub genes were identified among these clusters; subsequently, a scoring system was constructed to determine the Macrosig score. Importantly, patients with low-Macrosig scores, characterized by increased immune infiltration, increased mutation frequency and increased immune checkpoint expression, including CTLA-4, LAG3, PDCD1 and TIGIT, exhibited enhanced efficacy of immunotherapy when validated in an external database. Moreover, a low-Macrosig score indicates increased sensitivity to AZD.2281, A.443654, ABT.263, ABT.888, AG.014699 and ATRA, while a high Macrosig score indicates increased sensitivity to AZD6482, AKT inhibitor VIII, AS601245, AZ628, AZD.0530 and AZD6244. ConclusionsA novel scoring system was constructed to guide more effective prognostic evaluation and tailoring therapeutic regimens for HCC patients.

Targeting BMP2 for therapeutic strategies against hepatocellular carcinoma

ObjectivesThis study aimed to investigate the role of BMP2 in hepatocellular carcinoma (HCC) growth and metastasis using a dual approach combining single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq. MethodsscRNA-seq data from the GEO database and bulk RNA-seq data from the TCGA database were analyzed. Differentially expressed marker genes of endothelial cells were identified and analyzed using enrichment analysis, PPI analysis, correlation analysis, and GSEA. In vitro, experiments were conducted using the Huh-7 HCC cell line, and in vivo, models of HCC growth and metastasis were established by knocking down BMP2. ResultsThe scRNA-seq analysis identified BMP2 as a key marker gene in endothelial cells of HCC samples. Elevated BMP2 expression correlated with poor prognosis in HCC. In vitro experiments showed that silencing BMP2 inhibited the proliferation, migration, and invasion of liver cancer cells. In vivo studies confirmed increased BMP2 expression in HCC tissues, promoting angiogenesis and HCC growth. ConclusionThis study highlights the role of BMP2 in tumor angiogenesis and HCC progression. Targeting BMP2 could be a promising therapeutic strategy against HCC.

Transcription factor ASCL1 targets SLC6A13 to inhibit the progression of hepatocellular carcinoma via the glycine-inflammasome signaling.

The purpose of this research was to clarify the function of achaete-scute family bHLH transcription factor 1 (ASCL1) and solute carrier family 6 member 13 (SLC6A13) in influencing tumor cell behavior, inflammatory responses, and the regulation of inflammasomes. We analyzed the differentially expressed genes (DEGs) in the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) database, as well as in the GSE14520 and GSE67764 datasets, to identify the expression changes of SLC6A13 in liver cancer. The prognostic significance of SLC6A13 in LIHC was assessed through Kaplan-Meier survival curve analysis. Transcriptional regulation of SLC6A13 by ASCL1 was explored using the Joint Annotation of the Human Genome and other species by the Systematic Pipeline for the Annotation of Regulatory Regions (JASPAR) database and dual-luciferase assays. In vitro experiments investigated the impact of ASCL1 and SLC6A13 overexpression on hepatocellular carcinoma (HCC) cell growth. Additionally, the effects of ethanol treatment and glycine modulation on the inflammatory response in HCC cell lines were evaluated. HCC samples showed reduced levels of SLC6A13, which correlates with a better prognosis for liver metastases. Elevated SLC6A13 expression correlated with improved overall survival (OS), progression-free survival (PFS), recurrence-free survival (RFS), and disease-specific survival (DSS). ASCL1 upregulated SLC6A13 and inhibited proliferation, migration, and invasion of HCC cells. Ethanol induced the production of inflammatory cytokines, which was enhanced by overexpression of SLC6A13 but counteracted by glycine. This study highlighted elevated expression of SLC6A13 in LIHC which has been correlated with improved OS, PFS, RFS, and DSS. Overexpression of SLC6A13 and ASCL1 in HCC cells enhanced inflammasome activation, which was exacerbated by ethanol and attenuated by glycine.

Role of CENPF and NDC80 in the rehabilitation nursing of hepatocellular carcinoma and cirrhosis: An observational study.

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally and often develops on the foundation of chronic liver disease or cirrhosis. Cirrhosis is a clinically prevalent chronic progressive liver disease characterized by diffuse liver damage resulting from long-term or repeated actions of 1 or more etiological factors. However, the impact of CENPF and nuclear division cycle 80 (NDC80) genes on rehabilitation nursing of HCC and cirrhosis remains unclear. HCC and cirrhosis datasets GSE63898 and GSE89377 profile files were downloaded from the gene expression omnibus database generated on platforms GPL13667 and GPL6947, respectively. Differentially expressed genes (DEGs) screening, weighted gene co-expression network analysis (WGCNA), construction and analysis of protein-protein interaction (PPI) networks, functional enrichment analysis, gene set enrichment analysis (GSEA), survival analysis, immune infiltration analysis, and comparative toxicogenomics database (CTD) analysis were conducted. Gene expression heatmaps were plotted. miRNAs regulating central DEGs were selected through TargetScan. A total of 626 DEGs were identified. According to gene ontology (GO) analysis, they were primarily enriched in small molecule metabolic processes, drug metabolic processes, binding of identical proteins, and lipid metabolic processes. Kyoto Encyclopedia of Gene and Genome (KEGG) analysis results indicated that the target genes were mainly enriched in metabolic pathways, phagosomes, glycine, serine, and threonine metabolism. The construction and analysis of the PPI network revealed 3 core genes (NDC80, CENPF, RRM2). Gene expression heatmaps showed that core genes (CENPF, NDC80) were highly expressed in HCC and cirrhosis samples. CTD analysis found that 2 genes (CENPF and NDC80) were associated with liver, jaundice, ascites, fever, dyspepsia, and hepatic encephalopathy. CENPF and NDC80 are highly expressed in HCC and cirrhosis, and CENPF and NDC80 might be the biomarkers of rehabilitation nursing of HCC and cirrhosis.

Impact of anesthesia-related genes on prognosis and tumor microenvironment in hepatocellular carcinoma: A comprehensive analysis.

Hepatocellular carcinoma (HCC), renowned for its bleak prognosis and high recurrence rates, necessitates innovative strategies for prognosis assessment and therapeutic intervention. In this pursuit, we systematically investigated the influence of anesthesia-related genes (ANARGs) on HCC outcomes. Leveraging data from The Cancer Genome Atlas (TCGA), our study scrutinized RNA sequencing data and clinical profiles from 374 HCC patients alongside 50 non-tumor liver samples to unravel ANARG expression patterns and their clinical relevance. Employing consensus clustering, we segregated HCC samples into two distinct subtypes based on ANARG profiles, unveiling significant survival disparities between them. Further differential expression analysis pinpointed pivotal genes and pathways distinguishing these subtypes, notably implicating lipid metabolism and the MTOR signaling pathway in HCC pathogenesis. A prognostic model, comprising five key ANARGs (DAGLA, CYP26B, HAVCR, G6PD and AKR1B), exhibited robust predictive capability for patient outcomes, validated across independent patient cohorts. Furthermore, immune infiltration analysis uncovered a nuanced interplay between ANARG expression and the tumor immune microenvironment, spotlighting variations in immune cell infiltration and function across the identified HCC subtypes. This comprehensive analysis underscores not only the prognostic significance of ANARGs in HCC but also their potential to modulate the tumor microenvironment, providing novel insights for tailoring anesthetic management and therapeutic strategies in HCC care. Our findings advocate for a more integrative approach to HCC management, amalgamating molecular profiling with traditional clinical parameters to refine patient stratification and personalize treatment strategies.

Integration of Single-Cell RNA Sequencing and Bulk RNA Sequencing to Identify an Immunogenic Cell Death-Related 5-Gene Prognostic Signature in Hepatocellular Carcinoma.

Immunogenic cell death (ICD) can enhance the potency of immunotherapy in cancer treatment. Nevertheless, it is ambiguous how ICD-related genes (ICDRGs) contribute to hepatocellular carcinoma (HCC). Single-cell RNA sequencing (scRNA-seq) data were used to distinguish malignant cells from normal cells in the HCC tumor microenvironment(TME). Bulk RNA sequencing data was employed to acquire the landscape of the 33 ICDRGs. Unsupervised clustering identified two ICD molecular subtypes. The cellular infiltration characteristics and biological behavior in different subtypes were analyzed by ssGSEA. Subsequently, differentially expressed genes (DEGs) between the two subtypes were determined, based on which patients were classified into three gene clusters. Then, the prognostic model was constructed by Lasso-Cox analysis. Finally, we investigated the expression of risk genes in cancer cell line encyclopedia (CCLE) and validated the function of NKX3-2 in vitro experiments. ICD scores and ICDRGs expression in malignant cells were significantly lower than in normal cells by scRNA-seq analysis. ICD-high subtype was characterized by ICD-related gene overexpression and high levels of immune infiltration abundance and immune checkpoints; Three DEGs-related gene clusters were likewise strongly linked to stromal and immunological activation. In the ICD-related prognostic model consisting of NKX3-2, CHODL, MMP1, NR0B1, and CTSV, the low-risk group patients had a better endpoint and displayed increased susceptibility to immunotherapy and chemotherapeutic drugs like 5-Fluorouracil, afatinib, bortezomib, cediratinib, lapatinib, dasatinib, gefitinib and crizotinib. Moreover, NKX3-2 amplification in HCC samples has been verified by experiments, and its disruption suppressed the proliferation and invasion of tumor cells. Our study highlighted the potential of the ICDRGs risk score as a prognostic indicator to aid in the accurate diagnosis and immunotherapy sensitivity of HCC.

Cancer-associated fibroblasts derived fibronectin extra domain A promotes sorafenib resistance in hepatocellular carcinoma cells by activating SHMT1

Resistance to sorafenib, an effective first-line treatment for advanced hepatocellular carcinoma (HCC), greatly compromised the prognosis of patients. The extracellular matrix is one of the most abundant components of the tumor microenvironment. Beyond acting as a physical barrier, it remains unclear whether cell interactions and signal transduction mediated by the extracellular matrix contribute to sorafenib resistance. With the analysis of primary HCC organoid RNA-seq data combined with in vivo and in vitro experiments validation, we discovered that fibronectin extra domain A (FN-EDA) derived from cancer-associated fibroblasts played a critical role in sorafenib resistance. Mechanistically, FN-EDA stimulates the up-regulation of the key one-carbon metabolism enzyme SHMT1 in HCC cells via the TLR4/NF-κB signaling pathway, thereby countering the oxidative stress induced by sorafenib. Moreover, we reinforced the clinical significance of our discoveries by conducting in vivo assays with an immunodeficiency subcutaneous xenograft tumor model, which was established using primary cancer-associated fibroblasts derived from clinical HCC tissues, and through the analysis of HCC samples obtained from The Cancer Genome Atlas (TCGA) database. Our findings suggest that targeting the FN-EDA/SHMT1 pathway could be a potential strategy to improve sorafenib responsiveness in HCC patients.

Deciphering the latent biomarkers in HBV and HDV- associated HepatoCellular carcinoma – An integrated bioinformatics analysis

Abundant studies convey chronic viral hepatitis (HBV and HDV) infection to be associated with development and promotion of HepatoCellular Carcinoma (HCC), making HBV and HDV contamination as one of the foremost source of HCC development worldwide. In the present study we intended to identify potential therapeutic biomarkers for HBV and HDV induced HCC development and progression. Hereby, we executed meta-analysis of micro-array datasets: GSE121248 comprising 107 viral infected samples categorized as 37 normal adjacent samples and 70 tumor samples along with GSE107170 containing 307 virus-positive tissue samples of which 155 samples were considered for further analysis encompassing 105 normal tissues and 50 HCC tumor samples. Eventually by analyzing an aggregate of 262 samples through GeneSpring Software, 486 Differentially Expressed Genes (DEGs) were identified among HBV and HDV infected samples leading to HCC including 152 up-regulated and 334 down-regulated genes. Subsequently resulted DEGs were processed for functional annotation by using OmicsBox, Pathway enrichment and disease association analysis by using EnrichR webserver. Additionally, Protein-Protein Interaction Network was constructed to identify top 10 most significant hub nodes by using Cytoscape tool and cytohubba plugin. Furthermore the identified top 10 noteworthy hub nodes were analyzed for overall survival, disease free survival and expression validation in HCC samples by employing GEPIA2 and HPA databases. Consequently hub genes were assessed for diagnostic efficacy by Receiver Operating Characteristic curves (ROC) which demonstrates promising performance of all the hub genes. Conclusively, our findings postulate TOP2A, PBK, NUF2, CCNB1, CDC20, BUB1B, NDC80, MAD2L1, DLGAP5 and KIF4A as the plausible biomarkers occupied in oncogenic pathways having a probable function in progression of HBV and HDV contaminated cells to HCC, proliferation of HCC and tumorogenesis. The present study also aids for elevated understanding of virus-associated HCC progression.

Tumor-associated macrophage-induced circMRCKα encodes a peptide to promote glycolysis and progression in hepatocellular carcinoma

The tumor-associated macrophages (TAMs) play multifaceted roles in the progression of hepatocellular carcinoma (HCC). However, the involvement of circular RNAs in the interplay between TAMs and HCC remains unclear. Based on Transwell co-culturing and circular RNA sequencing, this study revealed that TAMs enhanced tumor glycolysis and progression by upregulating circMRCKα in HCC cells. Patients with HCC who exhibited elevated circMRCKα levels presented significantly reduced overall survival and greater cumulative recurrence. Notably, we identified a novel functional peptide of 227 amino acids named circMRCKα-227aa, encoded by circMRCKα. Mechanistically, circMRCKα-227aa bound to USP22 and enhanced its protein level to obstruct HIF-1α degradation via the ubiquitin-proteasome pathway, thereby augmenting HCC glycolysis and progression. In clinical HCC samples, a positive correlation was observed between the expression of circMRCKα and the number of infiltrating CD68+ TAMs and expression of USP22. Furthermore, circMRCKα emerged as an independent prognostic risk factor both individually and in conjunction with CD68+ TAMs and USP22. This study illustrated that circMRCKα-227aa, a novel TAM-induced peptide, promotes tumor glycolysis and progression via USP22 binding and HIF-1α upregulation, suggesting that circMRCKα and TAMs could be combined as therapeutic targets in HCC.

Construction of CDKN2A-related competitive endogenous RNA network and identification of GAS5 as a prognostic indicator for hepatocellular carcinoma.

Competitive endogenous RNA (ceRNA) is an innovative way of gene expression modulation, which plays a crucial part in neoplasia. However, the intricacy and behavioral characteristics of the ceRNA network in hepatocellular carcinoma (HCC) remain dismal. To establish a cyclin dependent kinase inhibitor 2A (CDKN2A)-related ceRNA network and recognize potential prognostic indicators for HCC. The mutation landscape of CDKN2A in HCC was first explored using the cBioPortal database. Differential expression analysis was implemented between CDKN2Ahigh and CDKN2Alow expression HCC samples. The targeted microRNAs were predicted by lncBasev3.0, and the targeted mRNAs were predicted by miRDB, and Targetscan database. The univariate and multivariate analysis were utilized to identify independent prognostic indicators. CDKN2A was frequently mutated and deleted in HCC. The single-cell RNA-sequencing analysis revealed that CDKN2A participated in cell cycle pathways. The CDKN2A-related ceRNA network-growth arrest specific 5 (GAS5)/miR-25-3p/SRY-box transcription factor 11 (SOX11) was successfully established. GAS5 was recognized as an independent prognostic biomarker, whose overexpression was correlated with a poor prognosis in HCC patients. The association between GAS5 expression and methylation, immune infiltration was explored. Besides, traditional Chinese medicine effective components targeting GAS5 were obtained. This CDKN2A-related ceRNA network provides innovative insights into the molecular mechanism of HCC formation and progression. Moreover, GAS5 might be a significant prognostic biomarker and therapeutic target in HCC.

A prognostic signature established based on genes related to tumor microenvironment for patients with hepatocellular carcinoma.

Complex cellular signaling network in the tumor microenvironment (TME) could serve as an indicator for the prognostic classification of hepatocellular carcinoma (HCC) patients. Univariate Cox regression analysis was performed to screen prognosis-related TME-related genes (TRGs), based on which HCC samples were clustered by running non-negative matrix factorization (NMF) algorithm. Furthermore, the correlation between different molecular HCC subtypes and immune cell infiltration level was analyzed. Finally, a risk score (RS) model was established by LASSO and Cox regression analyses (CRA) using these TRGs. Functional enrichment analysis was performed using gene set enrichment analysis (GSEA). HCC patients were divided into three molecular subtypes (C1, C2, and C3) based on 704 prognosis-related TRGs. HCC subtype C1 had significantly better OS than C2 and C3. We selected 13 TRGs to construct the RS model. Univariate and multivariate CRA showed that the RS could independently predict patients' prognosis. A nomogram integrating the RS and clinicopathologic features of the patients was further created. We also validated the reliability of the model according to the area under the receiver operating characteristic (ROC) curve value, concordance index (C-index), and decision curve analysis. The current findings demonstrated that the RS was significantly correlated with CD8+ T cells, monocytic lineage, and myeloid dendritic cells. This study provided TRGs to help classify patients with HCC and predict their prognoses, contributing to personalized treatments for patients with HCC.

Construction of an Immunogenic Cell Death-Related Gene Signature and Genetic Subtypes for Predicting Prognosis, Immune Microenvironments, and Drug Sensitivity in Hepatocellular Carcinoma.

Immunogenic cell death (ICD) is a type of regulated cell death that modifies the immune response by releasing DAMPs or danger signals. Herein, we aimed to develop an ICD-related predictive model for patients with hepatocellular carcinoma (HCC) and investigate its applicability for predicting prognostic outcomes and immunotherapeutic responses. Differentially expressed genes of ICD were identified in the HCC and normal liver samples. A prognostic risk model and a nomogram containing clinicopathological features were created. To validate the effectiveness of the model, an external dataset was used. Clinical characteristics, prognosis, tumor mutation burden, immune microenvironments, biological function and chemotherapeutic drug sensitivity were evaluated for different genetic subtypes and risk groups. A total of 35 ICD-related genes (ICDRGs) were identified between HCC and normal samples, 11 of which were significantly associated with overall survival (OS) in HCC patients. Four different genetic subtypes were formed and eight ICDRGs were selected to develop a risk prognostic model. The risk scores were shown to be an independent prognostic factor for HCC and positively correlated with pathological severity. Patients in the high-risk group had a higher frequency of TP53 mutations, increased expression of immune checkpoints and human leukocyte antigen genes. The inhibitory concentrations of chemotherapeutic drugs differed in different populations. In this study, we developed an ICDRG risk model and demonstrated its applicability in predicting survival outcomes, immune and chemotherapeutic responses in HCC patients. ICDRGs are expected to be used as novel biomarkers in the medical decision-making of HCC.

Identification of molecular characteristics of hepatocellular carcinoma with microvascular invasion based on deep targeted sequencing.

As an indicator of tumor invasiveness, microvascular invasion (MVI) is a crucial risk factor for postoperative relapse, metastasis, and unfavorable prognosis in hepatocellular carcinoma (HCC). Nevertheless, the genetic mechanisms underlying MVI, particularly for Chinese patients, remain mostly uncharted. We applied deep targeted sequencing on 66 Chinese HCC samples. Focusing on the telomerase reverse transcriptase (TERT) promoter (TERTp) and TP53 co-mutation (TERTp+/TP53+) group, gene set enrichment analysis (GSEA) was used to explore the potential molecular mechanisms of the TERTp+/TP53+ group on tumor progression and metastasis. Additionally, we evaluated the tumor immune microenvironment of the TERTp+/TP53+ group in HCC using multiplex immunofluorescence (mIF) staining. Among the 66 HCC samples, the mutated genes that mostly appeared were TERT, TP53, and CTNNB1. Of note, we found 10 cases with TERTp+/TP53+, of which nine were MVI-positive and one was MVI-negative, and there was a co-occurrence of TERTp and TP53 (p < 0.05). Survival analysis demonstrated that patients with the TERTp+/TP53+ group had lower the disease-free survival (DFS) (p = 0.028). GSEA results indicated that telomere organization, telomere maintenance, DNA replication, positive regulation of cell cycle, and negative regulation of immune response were significantly enriched in the TERTp+/TP53+ group (all adjusted p-values (p.adj) < 0.05). mIF revealed that the TERTp+/TP53+ group decreased CD8+ T cells infiltration (p = 0.25) and enhanced PDL1 expression (p = 0.55). TERTp+/TP53+ was significantly enriched in MVI-positive patients, leading to poor prognosis for HCC patients by promoting proliferation of HCC cell and inhibiting infiltration of immune cell surrounding HCC. TERTp+/TP53+ can be utilized as a potential indicator for predicting MVI-positive patients and poor prognosis, laying a preliminary foundation for further exploration of co-mutation in HCC with MVI and clinical treatment.

Establishment and verification of a prognostic model based on coagulation and fibrinolysis-related genes in hepatocellular carcinoma.

Studies have shown that coagulation and fibrinolysis (CFR) are correlated with Hepatocellular carcinoma (HCC) progression and prognosis. We aim to build a model based on CFR-correlated genes for risk assessment and prediction of HCC patient. HCC samples were selected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases respectively. The Molecular Signatures Database (MSigDB) was used to select the CFR genes. RiskScore model were established by single sample gene set enrichment analysis (ssGSEA), weighted correlation network analysis (WGCNA), multivariate Cox regression analysis, LASSO regression analysis. PCDH17, PGF, PDE2A, FAM110D, FSCN1, FBLN5 were selected as the key genes and designed a RiskScore model. Those key genes were Differential expressions in HCC cell and patients. Overexpression PDE2A inhibited HCC cell migration and invasion. The higher the RiskScore, the lower the probability of survival. The model has high AUC values in the first, third and fifth year prediction curves, indicating that the model has strong prediction performance. The difference analysis of clinicopathological features found that a great proportion of high clinicopathological grade samples showed higher RiskScore. RiskScore were positively correlated with immune scores and TIDE scores. High levels of immune checkpoints and immunomodulators were observed in high RiskScore group. High RiskScore groups may benefit greatly from taking traditional chemotherapy drugs. We screened CFR related genes to design a RiskScore model, which could accurately evaluate the prognosis and survival status of HCC patients, providing certain value for optimizing the clinical treatment of cancer in the future.

RASSF4 Attenuates Metabolic Dysfunction-Associated Steatotic Liver Disease Progression via Hippo Signaling and Suppresses Hepatocarcinogenesis

Background & AimsMetabolic dysfunction-associated steatotic liver disease (MASLD) is a dynamic chronic liver disease closely related to metabolic abnormalities, such as diabetes and obesity. MASLD can further progress to metabolic dysfunction-associated steatohepatitis (MASH), fibrosis, cirrhosis and even hepatocellular carcinoma (HCC). However, the mechanisms underlying the progression of MASLD and further progression to liver fibrosis and liver cancer are unknown. MethodsIn this study, we performed transcriptome analysis in livers from mice with MASLD and found suppression of a potential anti-oncogene, RAS association domain protein 4 (RASSF4). RASSF4 expression levels were measured in liver or tumor tissues of patients with MASH or HCC, respectively. We established RASSF4 overexpression and knockout mouse models. The effects of RASSF4 were evaluated by qPCR, western blotting, histopathological analysis, wound healing assays, Transwell assays, EdU incorporation assays, colony formation assays, sorafenib sensitivity assays and tumorigenesis assays. ResultsRASSF4 was significantly downregulated in MASH and HCC samples. Using liver-specific RASSF4 knockout mice, we demonstrated that loss of hepatic RASSF4 exacerbated hepatic steatosis and fibrosis. In contrast, RASSF4 overexpression prevented steatosis in MASLD mice. In addition, RASSF4 in hepatocytes suppressed the activation of hepatic stellate cells (HSCs) by reducing TGF-β secretion. Moreover, we found that RASSF4 is an independent prognostic factor for HCC. Mechanistically, we found that RASSF4 in the liver interacts with MST1 to inhibit YAP nuclear translocation through the Hippo pathway. ConclusionsThese findings establish RASSF4 as a therapeutic target for MASLD and HCC.

Rspo2-LGR4 exacerbates hepatocellular carcinoma progression via activation of Wnt/β-catenin signaling pathway

BackgroundThe leucine-rich repeat-containing G-protein-coupled receptor 4 (LGR4) plays an important role in stem cell differentiation, organ development and cancer. Whether LGR4 affects the progression of hepatocellular carcinoma (HCC) remains unknown. This study aimed to reveal the role of LGR4 in HCC. MethodsClinical samples of HCC were collected to assess the expression of LGR4 and its correlation with patients’ clinical characteristics. The expression level of LGR4 in HCC cells was altered by pharmacological and genetic methods, and the role of LGR4 in HCC progression was analyzed by in vivo and in vitro assays. HCC was induced by diethylnitrosamine (DEN) and carbon tetrachloride (CCl4) in wild-type and LGR4 deficient mice, the effect of LGR4 on HCC was examined by histopathological evaluation and biochemical assays. ResultsLGR4 expression was up-regulated in HCC samples, and its expression level was positively correlated with tumor size, microvascular invasion (MVI), TNM stage and pathological differentiation grade of HCC patients. In the mouse HCC model induced by DEN+CCl4, knockdown of LGR4 effectively inhibited the progression of HCC. Silencing of LGR4 inhibited the proliferation, migration, invasion, stem cell-like properties and Warburg effect of HCC cells. These phenotypes were promoted by R-spondin2 (Rspo2), an endogenous ligand for LGR4. Rspo2 markedly increased the nuclear translocation of β-catenin, whereas IWR-1, an inhibitor of Wnt/β-catenin signaling, reversed its effect. Deficiency of LGR4 significantly reduced the nuclear translocation of β-catenin and the expression of its downstream target genes cyclinD1 and c-Myc. ConclusionsLGR4 promotes HCC progression via Wnt/β-catenin signaling pathway.

Clinical Significance of Upregulation of EZH1 Expression in Hepatocellular Carcinoma Tissues.

The incidence and mortality of hepatocellular carcinoma (HCC) are increasing. It is urgent to develop more effective HCC biomarkers for diagnosis and treatment. This project intends to verify the expression of enhancer of zeste 1 polycomb repressive complex 2 subunit (EZH1) and its mechanism in HCC. This study integrates global microarray and high-throughput sequencing datasets, combined with internal immunohistochemistry, to analyze the expression and prognostic value of EZH1 in HCC. Functional enrichment analysis was conducted to investigate transcriptional targets, which were achieved by intersecting HCC over-expressed genes, EZH1 co-expressed genes and putative transcriptional targets. The relationship between EZH1 and anticancer drugs was detected by drug sensitivity analysis. In this study, 84 datasets from 40 platforms (3,926 HCC samples and 3,428 non-cancerous liver tissues) were included to show the high expression of EZH1 in HCC. Immunohistochemistry with 159 HCC samples and 62 non-HCC samples confirmed the high expression level. HCC patients with high EZH1 expression had worse survival prognoses. Gene ontology and Reactome analysis revealed that metabolism-related pathways, including autophagy, are critical for HCC. Interestingly, as one of the EZH1 potential transcriptional targets, autophagy-related 7 (ATG7) appeared in the above pathways. ATG7 was positively correlated with EZH1, upregulated in HCC, and mediated poor prognosis. Upregulation of EZH1 was found to be in contact with HCC anti-tumor drug resistance. The upregulation of EZH1 expression can promote the occurrence of HCC and lead to poor clinical progression and drug resistance; these effects may be mediated by regulating ATG7.

Abstract 865: Single-cell sequencing identification of malignant cell subpopulations linked to recurrence in hepatocellular carcinoma

Abstract Introduction: Hepatocellular Carcinoma (HCC) is a highly malignant and challenging-to-treat tumor, with early recurrence affecting up to 35-50% of patients within two years after surgery, significantly impacting prognosis. Identifying high-risk patients for recurrence is critical for guiding postoperative adjuvant therapy. The rapidly advancing field of single-cell RNA sequencing technology offers an unprecedented opportunity to discover clinically relevant cell subpopulations. Here, we harnessed single-cell techniques to unveil a cell subpopulation closely linked with HCC recurrence, highlighting its clinical significance. Methods and Results: We conducted single-cell RNA sequencing on four HCC samples and harmonized data from three public datasets (GSE112271, GSE125449, CNP0000650) to elucidate the heterogeneity of malignant cells in HCC. Our investigation revealed a distinctive HCC subpopulation enriched in patients with early recurrence (11.4% vs. 3.8%, P=0.02). This subpopulation exhibited up-regulated STMN1 and EZH2, signifying high proliferative potential and a propensity for epithelial-mesenchymal transition (EMT). Applying the CIBERSORTx algorithm to the TCGA-LIHC dataset (N=323 patients), we inferred the proportion of this recurrence subpopulation among all malignant cells. Notably, patients with a higher proportion of this subpopulation (N=160) demonstrated significantly shorter recurrence-free survival (31.2 vs. 42.9 months, P=0.002), reduced median survival (45.9 vs 55.7 months, P=0.03) and a higher rate of microvascular invasion (35% vs. 23%, P=0.01). To validate this recurrence-related subpopulation in clinical samples, we conducted multiplex immunohistochemistry staining on paraffin-embedded (FFPE) HCC samples (including CD45, CD31, ARG1, STMN1, EZH2) and used machine learning for its identification. Our findings revealed that patients with a higher proportion of this recurrence subpopulation (N=40) experienced significantly shorter median survival (38.5 vs. 51.0 months, P&amp;lt;0.005) and progression-free survival (25.1 vs. 33.4 months, P=0.01) compared to a lower proportion (N=40). Multivariate Cox regression analysis confirmed that the proportion of this recurrence subpopulation is an independent predictor of worse prognosis (P=0.003). Conclusion: Through the power of single-cell RNA sequencing technology, we have unearthed and characterized a malignant cell subpopulation intricately connected with HCC recurrence. Importantly, this subpopulation can be identified in FFPE tissue samples and correlates robustly with patient prognosis. Our study underscores the transformative possibility of single-cell techniques in developing cell subpopulation-based biomarkers, emphasizing their clinical relevance and potential utility in guiding postoperative adjuvant therapy for HCC patients. Citation Format: Yucheng Dong, Xin Guo, Xuezhu Wang, Fan Yang, Yongchang Zheng, Yang Chen. Single-cell sequencing identification of malignant cell subpopulations linked to recurrence in hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 865.

Abstract 3172: Significance of PELP1 signaling in liver cancer progression

Abstract Background: Hepatocellular carcinoma (HCC) is the fastest-rising cause of cancer-related mortality in the United States. Furthermore, advanced HCC has a very poor prognosis, with a median survival time of only about ten months. Effective new targeted therapies are urgently needed for the treatment of HCC. Proline, glutamic acid-, and leucine-rich protein 1 (PELP1) is a protooncogene. PELP1 signaling has been implicated in the development of several cancers, however, its role in the progression of HCC remains unclear. The goal of this project is to investigate the significance and therapeutic potential of targeting PELP1 in HCC. Methods: In this investigation, we have used six HCC cell lines (HUH7, HEP3B, SNU398, SNU475, SNU423, and SNU449). Using immunohistochemistry (IHC), the expression of PELP1 in HCC tissue microarrays was examined. PELP1shRNA lentiviral particles were used to create PELP1 knockdown (KD) cells. Using well-established in vitro tests for cell proliferation, colony formation, and apoptosis, the effects of PELP1 KD or PELP1 inhibitor (SMIP34) were investigated. RNA-seq, RT-qPCR, Western blotting, IHC, reporter gene assays, and signaling pathway analysis were used in mechanistic investigations. Preclinical evaluations were conducted using mice xenograft models. Results: TNM plot analysis showed that HCC samples had increased PELP1 expression relative to normal tissue. Immunohistochemistry analysis of tissue microarray confirmed that HCC specimens overexpressed PELP1 in comparison to normal specimens. PELP1 knockdown with shRNA dramatically decreased HCC cell invasion, clonogenicity, and proliferation. Similarly, PELP1 inhibitor SMIP34 treatment significantly reduced cell viability, invasiveness, colony forming capacity, and induced apoptosis of HCC cells. RNA-seq analyses using PELP1 KD cells confirmed that PELP1 modulates the ribosome and the eukaryotic translation elongation pathways. Mechanistic studies confirmed that SMIP34 treatment contributed to the disruption of the Rix complex, which is crucial for ribosomal biogenesis. Puromycin labelling studies confirmed that PELP1 KD or SMIP34 treatment contributes to the reduction of ribosomal biogenesis and new protein synthesis. Furthermore, PELP1 KD or treatment with SMIP34 dramatically slowed the progression of HCC tumors in xenograft models. IHC analysis revealed reduced levels of the proliferation marker Ki67 in PELP1 KD/SMIP34 treated HCC xenograft tumors compared to controls. Conclusions: Overall, the results of our study point to PELP1 as a potential therapeutic target for HCC intervention. Citation Format: Uday Pratap, Khaled Mohamed Nassar, Xue Yang, Adriana Baker, Rahul Gopalam, William C. Arnold, Timilehin Adeniran, Marian Helena Hernandez Fernandez, Gangadhara R. Sareddy, Suryavathi Viswanadhapalli, Luzhe Sun, Ratna K. Vadlamudi. Significance of PELP1 signaling in liver cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3172.

Abstract 1482: FKBP52 drives diverse HCC phenotypes through context-dependent targeting of p53

Abstract p53 is notably the most frequently mutated protein in hepatocellular carcinoma (HCC), one of the major causes of cancer-related fatalities globally. These mutations often result in some of the most adverse outcomes in HCC, making p53 a prime target for therapeutic intervention. The concept of “hyperstability”of p53 is essential in understanding its gain-of-function and dominant-negative effects in tumorigenesis. However, the mechanisms driving this hyperstability are not completely understood. In this study, we have identified FKBP52, a member of the FK506-binding protein family, as a crucial factor in stabilizing and accumulating p53, irrespective of the type of mutation. Furthermore, our study suggests that FKBP52 could be a valuable biomarker for predicting HCC outcomes. We observed a notable link between FKBP52 levels and the histological differentiation in HCC samples. To corroborate these observations, we performed a series of in vitro and in vivo experiments using liver cancer models. These experiments highlighted the dual nature of FKBP52’s impact on hepatocytes, which varies according to cell type. Given its connection to HCC severity, FKBP52 seems to contribute negatively to the disease’s progression. The insights gained from this study on how FKBP52 influences p53 stabilization are critical. We suggest that targeting the processes upstream of FKBP52 could lead to more effective HCC treatments. These findings emphasize the importance of further investigating this pathway, potentially paving the way for new strategies in liver cancer therapy. Citation Format: Xing Wang, Jingfeng Wu, Chengyan Tang, Xiang Li, Li Zhu, Yaoyu Liu. FKBP52 drives diverse HCC phenotypes through context-dependent targeting of p53 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1482.