Liver Hepatocellular Carcinoma Research Articles

Hepatic extracellular ATP/adenosine dynamics in zebrafish models of alcoholic and metabolic steatotic liver disease

Steatotic liver disease (SLD) is a burgeoning health problem predominantly associated with excessive alcohol consumption, which causes alcohol-related liver disease (ALD), and high caloric intake, which results in metabolic dysfunction-associated SLD (MASLD). The pathogenesis of ALD and MASLD, which can progress from steatohepatitis to more severe conditions such as liver fibrosis, cirrhosis, and hepatocellular carcinoma, is complicated by several factors. Recently, extracellular ATP and adenosine (Ado), as damage-associated molecular patterns, were reported to promote inflammation and liver fibrosis, contributing to SLD pathogenesis. Here, we explored the in vivo dynamics of hepatic extracellular ATP and Ado during the progression of steatohepatitis using a genetically encoded GPCR-activation-based sensor (GRAB) in zebrafish models. We established hepatocyte-specific GRABATP and GRABAdo in zebrafish and investigated the changes in in vivo hepatic extracellular ATP and Ado levels under ALD or MASLD conditions. Disease-specific changes in hepatocyte extracellular ATP and Ado levels were observed, clearly indicating a correlation between hepatocyte extracellular ATP/Ado dynamics and disease progression. Furthermore, clodronate, a vesicular nucleotide transporter inhibitor, alleviated the MASLD phenotype by reducing the hepatic extracellular ATP and Ado content. These findings provide deep insights into extracellular ATP/Ado dynamics in disease progression, suggesting therapeutic potential for ALD and MASLD.

Integrative analysis unveils ECM signatures and pathways driving hepatocellular carcinoma progression: A multi-omics approach and prognostic model development.

Liver hepatocellular carcinoma (LIHC) is a highly lethal form of cancer that is among the deadliest cancer types globally. In terms of cancer-related mortality rates, liver cancer ranks among the top three, underscoring the severity of this disease. Insufficient analysis has been conducted to fully understand the potential value of the extracellular matrix (ECM) in immune infiltration and the prognostic stratification of LIHC, despite its recognised importance in the development of this disease. The scRNA-seq data of GSE149614 was used to conduct single-cell analysis on 10 LIHC samples. CellChat scores were calculated for seven cell populations in the descending cohort to investigate cellular communication, while PROGENy scores were calculated to determine tumour-associated pathway scores in different cell populations. The pathway analysis using GO and KEGG revealed the enrichment of ECM-associated genes in the pathway, highlighting the potential role of the ECM in LIHC development. By utilizing the TCGA-LIHC cohort, an ECM-based prognostic model for LIHC was developed using Lasso regression. Immune infiltration scores were calculated using two methods, and the performance of the ECM-related risk score was evaluated using an independent cohort from the CheckMate study. To determine the precise expression of ECM-associated risk genes in LIHC, we evaluated hepatocellular carcinoma cell lines using a range of assays, including Western blotting, invasion assays and Transwell assays. Using single-cell transcriptome analysis, we annotated the spatially-specific distribution of major immune cell types in single-cell samples of LIHC. The main cell types identified and annotated included hepatocytes, T cells, myeloid cells, epithelial cells, fibroblasts, endothelial cells and B cells. The utilisation of cellchat and PROGENy analyses enabled the investigation and unveiling of signalling interactions, protein functionalities and the prominent influential pathways facilitated by the primary immune cell types within the LIHC. Numerous tumour pathways, including PI2K, EGFR and TGFb, demonstrated a close correlation with the involvement of ECM in LIHC. Moreover, an evaluation was conducted to assess the primary ECM-related functional changes and biological pathway enrichment in LIHC. Differential genes associated with ECM were identified and utilised to create prognostic models. The prognostic stratification value of these models for LIHC patients was confirmed through validation in multiple databases. Furthermore, through immune infiltration analysis, it was discovered that ECM might be linked to the irregular expression and regulation of numerous immune cells. Additionally, histone acetylation was mapped against gene mutation frequencies and differential expression profiles. The prognostic stratification efficacy of the ECM prediction model constructed in the context of PD-1 inhibitor therapy was also examined, and it exhibited strong stratification performance. Cellular experiments, including Western blotting, invasion and Transwell assays, revealed that ECM-associated risk genes have a promoting effect on the development of LIHC. The creation of biomarkers for LIHC using ECM-related genes unveiled substantial correlations with immune microenvironmental infiltration and functional mutations in various tumour pathways. This enlightens us to the possibility that the influence of ECM on tumours may extend beyond simply promoting the fibrotic process and the stromal composition of tumours.

Identification of PPAR-related differentially expressed genes liver hepatocellular carcinoma and construction of a prognostic model based on data analysis and molecular docking.

Liver hepatocellular carcinoma (LIHC) is a significant global health issue with limited treatment options. In this study, single-cell RNA sequencing (scRNA-seq) data were used to explore the molecular mechanisms of LIHC development and identify potential targets for therapy. The expression of peroxisome proliferator-activated receptors (PPAR)-related genes was analysed in LIHC samples, and primary cell populations, including natural killer cells, T cells, B cells, myeloid cells, endothelial cells, fibroblasts and hepatocytes, were identified. Analysis of the differentially expressed genes (DEGs) between normal and tumour tissues revealed significant changes in gene expression in various cell populations. PPAR activity was evaluated using the 'AUCell' R software, which indicated higher scores in the normal versus the malignant hepatocytes. Furthermore, the DEGs showed significant enrichment of pathways related to lipid and glucose metabolism, cell development, differentiation and inflammation. A prognostic model was then constructed using 8 PPARs-related genes, including FABP5, LPL, ACAA1, PPARD, FABP4, PLIN1, HMGCS2 and CYP7A1, identified using least absolute shrinkage and selection operator-Cox regression analysis, and validated in the TCGA-LIHC, ICGI-LIRI and GSE14520 datasets. Patients with low-risk scores had better prognosis in all cohorts. Based on the expression of the eight model genes, two clusters of patients were identified by ConsensusCluster analysis. We also predicted small-molecule drugs targeting the model genes, and identified perfluorohexanesulfonic acid, triflumizole and perfluorononanoic acid as potential candidates. Finally, wound healing assay confirmed that PPARD can promote the migration of liver cancer cells. Overall, our study offers novel perspectives on the molecular mechanisms of LIHC and potential areas for therapeutic intervention, which may facilitate the development of more effective treatment regimens.

Comprehensive pan-cancer analysis: essential role of ABCB family genes in cancer.

The adenosine triphosphate-binding-cassette (ABC) transporter orchestrates the transmembrane transport of diverse substrates with the aid of ATP as an energy source. ABC transporter constitutes a widespread superfamily of transporters prominently present on the cellular membrane of organisms. Advancements in understanding have unveiled additional roles beyond mere intracellular or extracellular transport functions for the ABC protein family, encompassing involvement in DNA repair, protein translation, and gene expression regulation. Yet its role in tumors is still unknown. This study drew support from multiple databases, including Gene Expression Omnibus (GEO), European Genome-phenome Archive (EGA), The Cancer Genome Atlas (TCGA), and employed multidimensional bioinformatics analyses, incorporating online databases and the R-project. Through a comprehensive analysis, we seek to discern transcriptional-level disparities among genes and their consequential impacts on prognosis, tumor microenvironment (TME), stemness score, immune subtypes, clinical characteristics, and drug sensitivity across human cancers. ABC transporter subfamily B (ABCB) family genes exhibited heightened expression across diverse tumors, demonstrating a significant correlation with overall prognosis in pan-cancer contexts. Notably, gene expression levels manifested substantial associations with TME, stemness score, immune subtypes, clinical characteristics, and drug sensitivity in specific cancers, including kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), and pancreatic adenocarcinoma (PAAD). Within this subset, transporter associated with antigen processing 1 (TAP1), TAP2, and ABCB6 emerged as noteworthy oncogenes. The outcomes of this study contribute to a comprehensive understanding of the implications of ABCB family genes in tumor progression, offering insights into potential therapeutic targets for cancer. Notably, the identification of ABCB6 as a significant oncogene suggests promising avenues for targeted therapies in KIRP, LIHC, and PAAD.

A Novel Four-Gene Signature Based on Nonsense-Mediated RNA Decay for Predicting Prognosis in Hepatocellular Carcinoma: Bioinformatics Analysis and Functional Validation.

Nonsense-mediated RNA decay (NMD), a surveillance pathway for selective degradation of aberrant mRNAs, is associated with cancer progression. Its potential as a predictor for aggressive hepatocellular carcinoma (HCC) is unclear. Here, we present an innovative NMD risk model for predicting HCC prognosis. The Cancer Genome Atlas (TCGA) data of 374 liver HCC (LIHC) and 50 normal liver samples were extracted. A risk model based on NMD-related genes was developed through least absolute shrinkage and selection operator Cox (LASSO-Cox) regression of the LIHC-TCGA data. Prognostic validation was done using GSE54236, GSE116174, and GSE76427 data. Univariate and multivariate Cox regression analyses were conducted to assess the prognostic value of the model. We also constructed nomograms for survival prediction. Tumor immune infiltration was evaluated using the CIBERSORT algorithm, and the tumor cell phenotype was assessed. Finally, mouse experiments verified UPF3B knockdown effects on HCC tumor characteristics. We developed a risk model based on four NMD-related genes (PABPC1, RPL8, SMG5, and UPF3B) and validated it using GSE54236, GSE116174, and GSE76427 data. The model effectively distinguished high- and low-risk groups corresponding to unfavorable and favorable HCC outcomes. Its prognostic prediction accuracy was confirmed through time-dependent ROC analysis, and clinical-use nomograms with calibration curves were developed. Single-cell RNA sequencing results indicated significantly higher expression of SMG5 and UPF3B in tumor cells. Knockdown of SMG5 and UPF3B inhibited HCC cell proliferation, invasion, and migration, while affecting cell-cycle progression and apoptosis. In vivo, UPF3B knockdown delayed tumor growth and increased immune cell infiltration. Our NMD-related gene-based risk model can help identify therapeutic targets and biomarkers for HCC. Additionally, it assists clinicians in predicting the prognosis of HCC patients.

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.

Spinster Homologue 2 Expression Correlates With Improved Patient Survival in Hepatocellular Carcinoma Despite Association With Lymph-Angiogenesis.

Spinster homologue 2 (SPNS2) is a transporter of sphingosine-1-phosphate (S1P), a bioactive lipid linked to cancer progression. We studied the link between SPNS2 gene expression, tumor aggressiveness, and outcomes in patients with hepatocellular carcinoma (HCC). Gene expression in patients with HCC was analyzed from the Cancer Genome Atlas (TCGA) (n = 350) and GSE76427 (n = 115) as a validation cohort, as well as liver tissue cohort GSE6764 (n = 75). High-SPNS2 HCC was significantly associated with high level of lymph-angiogenesis-related factors. SPNS2 expression was significantly higher in normal liver and early HCC versus advanced HCC (P < 0.02). High SPNS2 levels enriched immune response-related gene sets; inflammatory, interferon (IFN)-α, IFN-γ responses, and tumor necrosis factor (TNF)-α, interleukin (IL)-6/Janus kinase/signal transducer and activator of transcription (JAK/STAT3) signaling, complement and allograft rejection, but did not significantly infiltrate specific immune cells nor cytolytic activity score. High-SPNS2 HCC enriched tumor aggravating pathway gene sets such as KRAS (Kirsten rat sarcoma virus) signaling, but inversely correlated with Nottingham histological grade, MKI67 (marker of proliferation Ki-67) expression, and cell proliferation-related gene sets. Further, high-SPNS2 HCC had significantly high infiltration of stromal cells, showing that low-SPNS2 HCC is highly proliferative. Finally, high-SPNS2 HCC was associated with better disease-free, disease-specific, and overall survival (P = 0.031, 0.046, and 0.040, respectively). Although SPNS2 expression correlated with lymph-angiogenesis and other cancer-promoting pathways, it also enriched immune response. SPNS2 levels were higher in normal liver compared to HCC, and inversely correlated with cancer cell proliferation and better survival. SPNS2 expression may be beneficial in HCC patients despite detrimental in-vitro effects.

Magnetic resonance elastography for the prediction of hepatocellular carcinoma in chronic hepatitis B.

Magnetic resonance elastography (MRE) is used for the evaluation of liver fibrosis; however, it remains unclear whether MRE-based liver stiffness is associated with hepatocellular carcinoma (HCC) development, particularly in patients with chronic hepatitis B. A total of 504 patients with chronic hepatitis B receiving MRE were enrolled. The primary endpoint was the association between MRE-based liver stiffness and HCC. In a cross-sectional analysis at the time of MRE measurement, the median (interquartile range) liver stiffness values in patients with presence or history of HCC and those without HCC were 3.68 (2.89-4.96) and 2.60 (2.22-3.45) kPa, respectively, and liver stiffness was significantly higher in patients with presence or history of HCC than in those without HCC (P < 0.001). In a longitudinal analysis of patients without HCC, the 1-, 3-, and 5-year cumulative incidence of HCC in patients with liver stiffness ≥3.6 kPa and those with liver stiffness <3.6 kPa were 3.8%, 7.0%, and 22.9%, and 0%, 0.9%, and 1.5%, respectively (P < 0.001). In the multivariable analysis, MRE-based liver stiffness (per 1 kPa) or liver stiffness ≥3.6 kPa was an independent factor for HCC development with an adjusted hazard ratio (aHR) of 1.61 (95% confidence interval [CI], 1.3-2.0) or aHR of 8.22 (95% CI, 2.1-31). MRE-based liver stiffness is associated with HCC risk in patients with chronic hepatitis B and may be used for the early prediction of HCC development and determination of indications for treatment.

Serum microRNA-16 as a potential biomarker for HCV-induced hepato-cellular carcinoma in Egyptian patients

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers in the world. Two risk factors that cause 80–90% of HCC cases globally are chronic infection with hepatitis B virus (HBV) and hepatitis C virus (HCV). The diagnostic value of circulating microRNAs (miRNAs) in numerous tumors has been described. Our research assessed microRNA-16 (miR-16) as a novel biomarker in patients with HCV-induced HCC. The study included three groups. Group 1 included 55 individuals with cirrhosis caused by liver HCV infection in addition to HCC. Group 2 included 55 individuals with cirrhosis brought on by HCV infection. Group 3 included 55 normal control individuals. Expression of miR-16 in blood was assessed by real-time polymerase chain reaction (RT-PCR). The mean level of miR-16 was significantly different in the three groups, with group 1 having the greatest value (1.098 ± 0.647), followed by group 2 (1.1035 ± 0.8567) and group 3 (control subjects) having the lowest value (0.3842 ± 0.21485). The receiver operating characteristic (ROC) curve analysis showed that miR-16 had a higher diagnostic value at area under the curve (AUC) of 0.935 than alpha-feto protein (AUC of 0.859) to differentiate between HCC and control subjects. MiR-16 has a sensitivity of 81.82 % and a specificity of 69.09%, to distinguish between patients with liver cirrhosis and HCC patients. Our findings illustrated that circulating miR-16 can be proposed as a marker for detection of patients with HCV-induced HCC.

Comprehensive prognostic and immune analysis of sterol O-acyltransferase 1 in patients with hepatocellular carcinoma.

Sterol O-acyltransferase 1 (SOAT1) is an important target in the diagnosis and treatment of liver cancer. However, the prognostic value of SOAT1 in patients with hepatocellular carcinoma (HCC) is still not clear. To investigate the correlation of SOAT1 expression with HCC, using RNA-seq and gene expression data of The Cancer Genome Atlas (TCGA)-liver hepatocellular carcinoma (LIHC) and pan-cancer. The correlation between SOAT1 expression and HCC was analyzed. Cox hazard regression models were conducted to investigate the prognostic value of SOAT1 in HCC. Overall survival and disease-specific survival were explored based on TCGA-LIHC data. Biological processes and functional pathways mediated by SOAT1 were characterized by gene ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of differentially expressed genes. In addition, the protein-protein interaction network and co-expression analyses of SOAT1 in HCC were performed to better understand the regulatory mechanisms of SOAT1 in this malignancy. SOAT1 and SOAT2 were highly expressed in unpaired samples, while only SOAT1 was highly expressed in paired samples. The area under the receiver operating characteristic curve of SOAT1 expression in tumor samples from LIHC patients compared with para-carcinoma tissues was 0.748, while the area under the curve of SOAT1 expression in tumor samples from LIHC patients compared with GTEx was 0.676. Patients with higher SOAT1 expression had lower survival rates. Results from GO/KEGG and gene set enrichment analyses suggested that the PI3K/AKT signaling pathway, the IL-18 signaling pathway, the calcium signaling pathway, secreted factors, the Wnt signaling pathway, the Jak/STAT signaling pathway, the MAPK family signaling pathway, and cell-cell communication were involved in such association. SOAT1 expression was positively associated with the abundance of macrophages, Th2 cells, T helper cells, CD56bright natural killer cells, and Th1 cells, and negatively linked to the abundance of Th17 cells, dendritic cells, and cytotoxic cells. Our findings demonstrate that SOAT1 may serve as a novel target for HCC treatment, which is helpful for the development of new strategies for immunotherapy and metabolic therapy.

Study of prognostic splicing factors in cancer using machine learning approaches.

Splicing factors (SFs) are the major RNA-binding proteins (RBPs) and key molecules that regulate the splicing of mRNA molecules through binding to mRNAs. The expression of splicing factors is frequently deregulated in different cancer types, causing the generation of oncogenic proteins involved in cancer hallmarks. In this study, we investigated the genes that encode RNA-binding proteins and identified potential splicing factors that contribute to the aberrant splicing applying a random forest classification model. The result suggested 56 splicing factors were related to the prognosis of 13 cancers, two SF complexes in liver hepatocellular carcinoma, and one SF complex in esophageal carcinoma. Further systematic bioinformatics studies on these cancer prognostic splicing factors and their related alternative splicing events revealed the potential regulations in a cancer-specific manner. Our analysis found high ILF2-ILF3 expression correlates with poor prognosis in LIHC through alternative splicing. These findings emphasize the importance of SFs as potential indicators for prognosis or targets for therapeutic interventions. Their roles in cancer exhibit complexity and are contingent upon the specific context in which they operate. This recognition further underscores the need for a comprehensive understanding and exploration of the role of SFs in different types of cancer, paving the way for their potential utilization in prognostic assessments and the development of targeted therapies.

Prognosis and chemotherapy drug sensitivity in liver hepatocellular carcinoma through a disulfidptosis-related lncRNA signature

Disulfidptosis, a new type of regulated cell death associated with the actin cytoskeleton, provides a new therapeutic tool for cancers. The direct relationship between disulfidptosis-related lncRNAs(DRLs) in liver hepatocellular carcinoma(HCC) remains unclear. We acquired transcriptomic data, corresponding clinical data, and tumor mutation data of HCC from the TCGA database. First of all, DRLs were determined through correlation analysis. Then, a prognostic model containing six DRLs was created by adopting univariate Cox regression, LASSO algorithm and multivariate Cox regression analysis. Based on the model, 424 HCC patients were divided into high- and low-risk groups. Next, we structured ROC curves and PCA through combining the model and clinical data. Enrichment analysis and immune infiltration analysis were adopted to further explore the relationship between the model and prognosis. In addition, we explored the relationship between the model and tumor mutation burden (TMB). There were significant differences between high- and low- risk groups, and patients in the high-risk group showed poor prognosis. Enrichment analysis suggested that metabolic progress was obviously different between the two groups. According to the analysis of immune infiltration, there were several differences in immune cells, function, and checkpoints. Patients with high-risk and high TMB demonstrated the least favorable prognosis. The two risk groups both manifested visiblly in chemotherapy drug sensitivity. To sum up, we set up a DRL-based signature and that may provide a predictable value for the prognosis and use of chemotherapy drugs for HCC patients.

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

BackgroundMost 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. MethodsWe 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). ResultsIn 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. ConclusionsOur 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.

Abstract 1637: EPHB4 is a key regulator of G1/S transition in hepatocellular carcinoma

Abstract Effective therapeutic regimens against advanced hepatocellular carcinoma (HCCs) have recently improved but it remains very limited. Targeting receptor tyrosine kinases (RTKs) has proven to one of the main ways of achieving better survival outcome in HCC patients, yet the precise mechanism for this success remains to be elusive. We have systematically investigated the expression profiles of RTKs transcriptomic datasets i.e. The Cancer Genome Atlas - Liver hepatocellular carcinoma (TCGA-LIHC) (n=371) and our in-house cohort of paired i.e. HKU-QMH (n=41), and identified EPHB4 as one of the most abundantly expressed and frequently mutated RTKs in human HCCs. EPHB4 expression was found to be significantly correlated with Alpha Fetoprotein (AFP) expression, a factor commonly used in the diagnosis of HCCs. Furthermore, EphB4 has been demonstrated to play a regulatory role in VEGF/VEGFR-mediated angiogenesis, critical targets for current successful drugs. We confirmed abundant membrane EphB4 expression in HCC clinical specimens and human HCC cell line models using immunohistochemistry. Clinicopathological correlation analysis of EPHB4 mRNA expression revealed that its overexpression is associated with aggressive tumor features including presence of tumor microsatellite, liver invasion, venous invasion, and absence of tumor encapsulation. Functionally, stably knocking down EPHB4 (shEPHB4) resulted in a strong reduction of proliferation and self-renewal rates of multiple HCC cell lines in vitro. It significantly reduced tumor growth rates in subcutaneous and liver orthotopic models in vivo. Furthermore, limiting dilution assay showed EPHB4 plays a role in tumor initiation property of HCC cells. Mechanistically, we performed Gene Set Enrichment Analysis (GSEA) of transcriptome profiles for shEPHB4 with respective controls and found that knocking down EPHB4 causes HCC cells undergo drastic changes in several cell cycle checkpoints including G1/S transition. Using thymidine blockade, we further confirmed that knockdown of significantly hinders the transition of HCC cells from G1 to S phase of cell cycle. Our data suggests a strong link between EphB4 and cell cycle. Conclusion: We found EphB4 plays a functional role in regulating G1/S transition in human HCCs and understanding regulatory role of EphB4 on cell cycle progression may provide mechanistic insights into the how to effectively target HCC in the clinic. Citation Format: Abdullah Husain, Elley Y. Chiu, Hoi-Tang Ma, Daniel W. Ho, Karen M. Sze, Lo-Kong Chan, Irene O. Ng. EPHB4 is a key regulator of G1/S transition 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 1637.

Abstract 874: Expanded detection of BAP1 alterations in cancer and comparison of tumor type-specific gene expression scores

Abstract BAP1 is a tumor suppressor gene that was originally studied in uveal melanoma (UVM), kidney renal cell clear cell carcinoma (KIRC), and malignant mesothelioma (MESO). Early analyses focused on single-nucleotide variants, but other alteration types such as larger indels and gene-level copy number (CN) loss can also lead to loss of BAP1 expression. By incorporating these, we can improve our assessment of cancer type-specific consequences of BAP1 loss and broaden our findings beyond the initial small subset of cancer types which were studied in the context of mutations alone. We performed integrated multi-omic analyses using data from The Cancer Genome Atlas (TCGA), for 33 cancer types and more than 10,000 individuals. By combining and manually reviewing existing variant calls and new calls derived from a de novo local realignment pipeline across multiple independent variant callers including indel callers, we increased detection of high-quality somatic variant calls by 30% from 85 to 111, including 14 indels ≥5bp. Including CN loss alterations, we found a total of 1561 samples from 32 cancer types to be BAP1-altered, with alterations being predominantly CN-driven. We confirmed that expression of BAP1 was lower in altered versus unaltered tumors (p&amp;lt;0.001). Alteration frequencies across cancer types were highly variable, ranging from 0% in thyroid cancer to &amp;gt;30% in KIRC, cholangiocarcinoma (CHOL), UVM, MESO, lung squamous carcinoma (LUSC), and head-neck squamous cell carcinoma (HNSC). Tumor types such as CHOL, UVM, MESO, and liver hepatocellular carcinoma (LIHC) were relatively more mutation-driven whereas other tumor types like KIRC, LUSC, and HNSC were almost entirely CN-driven. To better understand the tissue and context-specific consequences of BAP1 alteration, we performed differential expression analyses across BAP1-altered and -unaltered samples. For each cancer type, we separately computed per-sample BAP1 alteration signature z-scores summarizing expression of the set of differentially expressed genes. In UVM, we observed distinct patterns of RNA expression, consistent with established literature on BAP1 loss and serving as a baseline for comparison for the biological effects of BAP1 loss in other less-studied cancer types. The BAP1 altered scores for 66% of cancer types were positively correlated with the UVM BAP1 altered signature, suggesting shared biological responses and affected pathways including immune responses, epithelial-mesenchymal transition, oxidative phosphorylation, and proliferation – all known roles of BAP1. In LIHC, we noted enrichment of bile duct gene expression in BAP1-altered tumors, suggesting a possible role for BAP1 in maintaining cell identity distinguishing hepatocytes and cholangiocytes. Our findings broadly emphasize the improvements that are gained by using new computational approaches in large cancer-genome studies such as TCGA. Citation Format: Ian R. Sturgill, Jesse R. Raab, Katherine A. Hoadley. Expanded detection of BAP1 alterations in cancer and comparison of tumor type-specific gene expression scores [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 874.

Abstract 5689: miR-21: A therapeutic target that delays severe liver disease and hepatocellular carcinoma under high-fat-diet conditions

Abstract Liver disease is a major global health concern, claiming approximately 2 million lives worldwide annually, yet curative treatments remain elusive. In our study, we aimed to investigate the role of microRNA-21-5p (miR-21) in metabolic dysfunction-associated steatotic liver disease (previously NAFLD), metabolic-associated steatohepatitis (previously NASH), and hepatocellular carcinoma (HCC) within the context of a Western high-fat diet (HFD) and offering potential therapeutic insights. We found that reduced miR-21 levels correlated with liver disease progression in WT mice fed on HFD, while miR-21 knockout mice showed exacerbated metabolic dysfunction, including obesity, hepatomegaly, hyperglycemia, insulin resistance, steatosis, fibrosis, and HCC. Our study reveals that miR-21 plays a protective role in metabolic syndrome and in the progression of liver disease to cancer. miR-21 directly targets Transforming growth factor beta-induced (Tgfbi), a gene also known to be significantly upregulated and a potential oncogene in HCC. Further, our study showed that intervention with the administration of a miR-21 mimic in WT livers in HFD conditions effectively improves insulin sensitivity, steatosis, fibrosis, tumor burden, as well as Tgfbi expression. These findings indicate that miR-21 could serve as an effective strategy to delay or prevent liver disease in high-fat-diet environments. Citation Format: Urmila Jagtap, Anan Quan, Yuho Ono, Jonathan Lee, Kylie A. Shen, Sergei Manakov, Gyongyi Szabo, Imad Nasser, Frank J. Slack. miR-21: A therapeutic target that delays severe liver disease and hepatocellular carcinoma under high-fat-diet conditions [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 5689.

Abstract 5335: Immune cell population variations in the livers of commonly used mouse strains

Abstract Previous studies have shown that the distribution of major immune cell populations differ across mouse strains in peripheral blood and hematopoietic organs at baseline. Additionally, variations in immune responses exist between mouse strains in Leishmania spp. and Melanoma models, but these studies in the context of liver diseases including Non Alcoholic Fatty Liver Disease (NAFLD) and Hepatocellular Carcinoma (HCC) have not been carried out. With the effort to state if these variations exist within the liver, we performed comprehensive spectral flow cytometry analysis on the liver and spleens of three female mouse strains commonly used in cancer research (BALB/c, C57BL/6, and FVBN). NAFLD was induced by providing mice with a methionine choline deficient diet. To promote HCC, a single genotype (myc/p53+/-) was induced by administering transposon-based vectors to overexpress Myc-Luc and CRISPR/Cas-9 vectors to knock down p53 via hydrodynamic tail-vein injection. To confirm vector integration and monitor tumor growth (luciferase activity), in vivo imaging was performed at different time points. As a result, we confirm throughout this study that differences exist within immune cell populations of the liver and spleen at baseline. Moreover, we depict differences in the shift of immune cell populations across mouse strains in the pathologic states included. In NAFLD, there is an increase of dendritic cells (DCs), macrophages, NK cells, ILC1s, T regulatory cells (Tregs), TH1, and TH2, and a decrease of CD4+ T cells, B cells, γδ-T cells, and NKT cells in the liver across all mouse strains, when compared to controls. However, the population of neutrophils in BALB/c decreases, and the population of CD8+ T cells increases in C57BL/6 mice, which differs from the patterns of change seen in the other mouse strains. Moreover, in spleens, NAFLD promotes an increase of TH1 and NK cells, and a decrease of TH2 and NKT Cells across the mouse strains included in the study, whereas the patterns of change differ between mouse strains among the remaining immune cell types. When evaluating liver immune cell population shifts on our HCC model, BALB/c mice showed a decrease in macrophages and ILC1s, C57BL/6 mice showed a decrease in γδ-T cells, prominent shifts across Neutrophils, TH1, and NKT cells, and null changes in TH2 and CD4+ T cell shifts, and FVBN mice had a less prominent decrease of B cells, which differed from the shifts observed in the mouse strains used for comparison. Immune cell populations in the spleens of our HCC mouse model also presented with differences across the mouse strains studied. In conclusion, we highlight that key differences in immune profiles exist across commonly used mouse strains for cancer research in the presence of liver pathology including HCC, suggesting that mouse strains could be possible confounders in the study of immune oncology of HCC. Citation Format: Francisco J. Rodriguez-Matos, Patrick Huang, Rajiv Trehan, Benjamin Ruf, Chi Ma, Tim F. Greten. Immune cell population variations in the livers of commonly used mouse strains [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 5335.

Abstract 4876: Data-driven discovery of cancer-specific targets for hepatocellular carcinoma using spatial transcriptomics

Abstract Background: Hepatocellular carcinoma (HCC) is frequently diagnosed in advanced stages, with limited options available for systemic treatment. Given the significant investment of time, the high costs, and the notable failure rates involved in developing new drugs, it is crucial to identify appropriate cancer-specific surface targets, especially aiming at antibody drug conjugates and radioligand therapy. This study aims to propose a pipeline utilizing spatial transcriptomics (ST) to prioritize potential cancer-specific surface targets for HCC. Methods: Visium ST samples were collected from fresh-frozen tissues of HCC patients undergoing hepatectomy. The spots with over 500 expressed genes and a mitochondrial gene percentage below 20% were selected. Counts were normalized with sctransform, and the tumor cell proportion in each spot was predicted using CellDART. Cancer region-specific genes were identified based on three criteria: high topological overlap with tumor cell distribution (using STopover), a high correlation coefficient with tumor cell proportion, or significantly higher expression in the tumor cell cluster compared to others in single-cell RNA-sequencing dataset. Genes identified through these methods were pooled and filtered based on average expression in the whole tissue using human normal cell atlas data and surface proteins. To select drug candidates with low normal organ toxcity, Tabula Sapiens datasets were used. Genes expressed in over 50% of cells and with an average expression above 1 in any critical organs were excluded. Results: One ST sample was obtained from each of the 7 HCC patients. The topology, correlation, and single-cell-based criteria resulted in 42, 15, and 7 genes, respectively, with only 1 gene (P4HB) overlapping across all three methods. After filtering genes with high expression in normal organs based on Tabula Sapiens, 25 genes remained. In the GEPIA databases, GPC3 exhibited the highest log fold change in RNA expression between HCC and normal liver (6.280), followed by TM4SF4 (2.156), EFNA1 (0.581), GJB1 (0.498), and IRS1 (0.391). To externally validate the results, 17 ST datasets from 5 patients provided by HCCDB were used. Among the selected genes, only GPC3 and EFNA1 had higher average expression in the tumor compared to other compartments (normal, stromal, and immune) in at least 3 out of 5 patients. Conclusion: The proposed platform prioritizes cancer-specific surface targets for HCC, focusing primarily on spatial gene expression profiles obtained from ST and gene expression data from external databases. This analytical tool can be further utilized to identify molecular targets for developing antibody drug conjugates or radioligand therapies, which are designed to specifically deliver therapeutic agents to the tumor. Citation Format: Sungwoo Bae, Dongjoo Lee, Daeseung Lee, Kwon Joong Na, Suk Kyun Hong, YoungRok Choi, Nam-Joon Yi, Kwang-Woong Lee, Kyung-Suk Suh, Hongyoon Choi. Data-driven discovery of cancer-specific targets for hepatocellular carcinoma using spatial transcriptomics [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 4876.

Abstract 771: A TGF-β superfamily member, myostatin contributes to MASH and HCC via muscle atrophy by disrupting TGF-β signaling, and is a potential marker with PKM2 for human HCC

Abstract Background: In patients with cirrhosis and hepatocellular carcinoma (HCC), sarcopenia or skeletal muscle loss, as well as metabolic alterations are frequent and progressive comorbidities. Myostatin, a TGF-β superfamily member is expressed primarily in skeletal muscle, inhibits muscle growth, and causes sarcopenia in cirrhosis. Previously, we had observed liver-specific knockout of the SMAD3 adaptor, βII-spectrin -Sptbn1 (βS-LSKO) or siRNA targeting βII-spectrin blocks sarcopenia, fatty liver disease-MASH and HCC (Sci TM 2021), suggesting that βII-spectrin may be a viable strategy to identify mechanisms, as well as new biomarkers of MASH and HCC. Methods: 1. SPTBN1Flox (control) and liver-specific βII-spectrin knockout (SPTBN1LSKO) mice were fed Western diet (WD) and treated with Diethylnitrosamine (DEN) for obesity-associated HCC. Muscle mass, body weight and multiple enzymes involved in glycolysis as well as sarcopenia were measured in mutant mice. 2. In tumors, a rate-limiting enzyme in glycolysis, pyruvate kinase isozyme M2 (PKM2) that mediates inflammation and aerobic glycolysis in Warburg effect. Therefore, we further examined TGF-β pathway-enriched biomarkers such as Myostatin and PKM2 for markers of HCC and whether these could stratify risk in patients with cirrhosis for HCC, in a four-institution cohort, (n=157) compared to cirrhosis patients (n=380). Results: 1. Like human fatty liver disease, obese mutant mice show marked sarcopenia with increased PKM2 and Myostatin levels with decreased p-RPS6/total-RPS6 ratio (indicating mTOR signaling inhibition) in striated muscle tissue. In contrast, levels are restored to normal in the liver specific knockout of SPTBN1. 2. Using the 108 markers as well as PKM2 and myostatin (MSTN), we found 31 markers with false discovery rate (FDR) p values &amp;lt; 0.10 from univariable Kruskal-Wallis tests for the associations of markers with HCC vs. cirrhosis. Conclusions: Our results reveal that SMAD3 adaptor, βII-spectrin liver-specific knockout decreases Myostatin and PKM2 expression, providing new insight into molecular mechanisms in MASH and HCC. These studies reflect that these are biologically functional circuits that could provide new serum markers, such as Myostatin and PKM2 for risk stratification of HCC. Citation Format: Kazufumi Ohshiro, Krishanu Bhowmick, Xiyan Xiang, Shivani Kapoor, Richard Amdur, Srinivasan Dasarathy, Adrian R. Krainer, Lopa Mishra. A TGF-β superfamily member, myostatin contributes to MASH and HCC via muscle atrophy by disrupting TGF-β signaling, and is a potential marker with PKM2 for human HCC [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 771.

Abstract 3402: Integration of microRNAs and transcriptome signatures identifies the persistent infection of hepatitis C virus-induced hepatocellular carcinoma

Abstract MicroRNAs (miRNAs) are short non-coding RNAs (ncRNAs) of ~22 nucleotides that mediate gene expression through various functions, including gene silencing, which can lead to translation repression and degradation of target mRNAs. Dysregulation of miRNA function has been associated with numerous diseases, particularly cancer, including hepatocellular carcinoma (HCC). During the progression of HCV-HCC, the function of miRNAs may be altered thereby altering gene expression to favor HCC. Therefore, the involved miRNA-mRNA interaction needs to be further studied. In addition, there are many clinical studies have shown that HCV patients who do not adequately control their diet which are prone to fatty liver accumulation (steatosis), it may increase the possibility of liver cirrhosis. In the current study, we aim to investigate the function and effects of persistent HCV-induced miRNAs expression in liver hepatocellular carcinoma progression and gene expression and to explore the mechanisms and regulatory genes of liver steatosis caused by HCV patients in a high-fat environment. We used the Huh751 cell line and the infected with the HCV JFH1 replicon of low-viral load S2 cells. We used an HCV miRNA array for initial identification of potential candidates. These miRNAs were analyzed for KEGG pathways via DIANA. Next, we identified miRNA-mRNA targets in 3 databases (miRDB; miRPathDB; TargetScan) and analyzed the targets for KEGG pathways using ShinyGO. The target miRNA-mRNA candidate genes were then compared with long-term JFH1 replicon infectious cell (L-HCV) NGS mRNA data to integrate miRNA-mRNA. The identified genes were analyzed in The Cancer Genome Atlas (TCGA) for survival, biological process, and expression in LIHC Big Data. Hsa-miR-215, hsa-mir-10b, and hsa-let-7a of L-HCV miRNAs group showed high significance for LIHC overall survival with a hazard ratio &amp;gt;1.0. Moreover, miRNAs associated with L-HCV survival were LIHC-specific but not in other cancers. Through systematic integration of these findings, we identified HMOX1 and BMF genes as being specifically associated with HCC and regulated by hsa-miR-215-5p, hsa-miR-10b-5p, and hsa-miR-7a-5p. In addition, we also found that the expression of the adipogenesis genes, FABP4 and adipogenesis gene, SREBP1, as well as the viral non-structural protein, NS3, was significantly increased in the HCV-high-fat group; and the expression of the gene IRS1, which is involved in hyperinsulinemia, showed a decreasing trend. The main cause of HCC is that HCV inhibits the expression of hsa-miR-215-5p, hsa-miR-10b-5p, and hsa-miR-7a-5p, leading to alter the expression of target genes, these have a significant effect on survival, suggesting that an essential role in virus-related liver cancer. In the future, we will further explore the regulatory mechanisms between these genes and HCV in a high-fat environment. Citation Format: Wen-Hsiu (Vivian) Su, Ciniso Sylvester Shabangu, Shu-Chi Wang. Integration of microRNAs and transcriptome signatures identifies the persistent infection of hepatitis C virus-induced 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 3402.