Integrative proteogenomic characterization of hepatocellular carcinoma across etiologies and stages

Precision Strike Strategy for Liver Diseases Trilogy with Xiao-Chai-Hu Decoction: A Meta-Analysis with Machine Learning

BACKGROUND AND PURPOSE

The progression from hepatitis to liver fibrosis (LF) and ultimately to hepatic carcinoma (HCC) represents the advanced stages of various liver diseases. Currently, no universal treatment effectively addresses all three conditions. The Traditional Chinese Medicine formula Xiao-Chai-Hu decoction (XCHD) has shown promise in treating hepatitis, inhibiting LF, and serving as an adjunct therapy for HCC. This study evaluates the efficacy and optimal treatment durations of XCHD in managing these liver diseases using meta-analysis and machine learning techniques.

METHODS

Registered in the PROSPERO database (CRD42024534445), this meta-analysis systematically searched seven databases, including 54 studies with a total of 5,710 patients. Statistical analysis was performed using Stata 17.0. Five machine learning models-Random Forest (RF), XGBoost, Lasso, Multilayer Perceptron (MLP), and a stacking model combining these algorithms-were employed to analyze the data and predict the time-effect relationships. The optimal durations of XCHD treatment for the liver disease trilogy were subsequently projected.

RESULTS

XCHD significantly improved the primary outcome indicators for hepatitis, liver fibrosis, and HCC. Additionally, XCHD demonstrated a beneficial effect on liver dysfunction caused by these diseases. Machine learning predicted the optimal treatment durations of XCHD as 12 weeks for hepatitis, 20.31 weeks for liver fibrosis, and 12 weeks for HCC.

CONCLUSION

XCHD is effective in treating the liver disease trilogy, with optimal treatment durations of 12 weeks for hepatitis and HCC, and 20.31 weeks for liver fibrosis. These findings support the potential of XCHD in developing precise clinical strategies for managing liver diseases. This study innovatively integrates meta-analysis with machine learning to determine the optimal treatment durations, providing a novel approach for evidence-based precision medicine in Traditional Chinese Medicine.

A tissue-specific atlas of protein-protein associations enables prioritization of candidate disease genes

Despite progress in mapping protein-protein interactions, their tissue specificity is understudied. Here, given that protein coabundance is predictive of functional association, we compiled and analyzed protein abundance data of 7,811 proteomic samples from 11 human tissues to produce an atlas of tissue-specific protein associations. We find that this method recapitulates known protein complexes and the larger structural organization of the cell. Interactions of stable protein complexes are well preserved across tissues, while cell-type-specific cellular structures, such as synaptic components, are found to represent a substantial driver of differences between tissues. Over 25% of associations are tissue specific, of which <7% are because of differences in gene expression. We validate protein associations for the brain through cofractionation experiments in synaptosomes, curation of brain-derived pulldown data and AlphaFold2 modeling. We also construct a network of brain interactions for schizophrenia-related genes, indicating that our approach can functionally prioritize candidate disease genes in loci linked to brain disorders.

Increased expression of DNAJC7 promotes the progression of hepatocellular carcinoma by influencing the cell cycle and immune microenvironment

BACKGROUND

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related mortality worldwide owing to the lack of effective and early diagnostic tools and therapeutic approaches. DNAJC7, a member of the DnaJ heat shock family, is crucial in protein folding and stability; however, its specific functions and mechanisms in HCC remain unclear.

OBJECTIVE

This study aimed to explore the role of DNAJC7 in HCC progression and evaluate its potential clinical significance as a prognostic marker.

METHODS

Public databases (TCGA, ICGC, GEO, and TIMER) were used to assess DNAJC7 expression, correlations with clinical parameters, and related signaling pathways. Proliferation, migration, invasion, and cell cycle assays were performed to evaluate the function of DNAJC7 in HCC. Immune infiltration and associations with checkpoint proteins were analyzed using TIMER, and a Gene Set Enrichment Analysis (GSEA) was used to explore enriched pathways.

RESULTS

DNAJC7 expression was higher in HCC tissues than in adjacent normal tissues and was associated with advanced malignancy and poor prognosis, including a lower overall survival, progression-free survival, and disease-free survival. DNAJC7 knockdown resulted in reduced malignant behavior of HCC cells, leading to S-phase cell cycle arrest. Increased DNAJC7 expression was associated with immune cell infiltration and the presence of immunological checkpoint molecules, including CTLA4 and PD-1. GSEA highlighted the activation of key pathways, including WNT signaling and cell cycle regulation.

CONCLUSION

DNAJC7 regulates tumor cell proliferation, migration, invasion, and immune evasion by acting as an oncogene in HCC. It can serve as a diagnostic and prognostic biomarker and potential treatment target for HCC.

The Synergistic Mechanisms and Prospects of Transarterial Chemoembolization Combined with Immunotherapy for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) represents a highly aggressive form of liver neoplasm that presents various therapeutic obstacles. Recently, the synergistic use of transarterial chemoembolization (TACE) in conjunction with immunotherapy has attracted considerable interest within the medical community. This review aims to explore the synergistic mechanisms between TACE and immunotherapy, analyze the current research evidence, and discuss their potential applications in the treatment of HCC. By examining how TACE can enhance the efficacy of immunotherapy, we seek to provide direction for future research and emphasize the importance of personalized treatment strategies in managing HCC.

Comprehensive analysis of prognosis markers with molecular features derived from pan-cancer whole-genome sequences

Cancer prognosis markers are useful for treatment decisions; however, the omics-level landscape is not well understood across multiple cancer types. Pan-Cancer Analysis of Whole Genomes (PCAWG) provides unprecedented access to various types of molecular data, ranging from typical DNA mutations and RNA expressions to more deeply analyzed or whole-genomic features, such as HLA haplotypes and structural variations. We analyzed the PCAWG data of 13 cancer types from 1,514 patients to identify prognosis markers belonging to 17 molecular features in the survival analysis based on the Cox and Lasso regression methods. We found that germline features including HLA haplotypes, neoantigens, and the number of structural variations were associated with overall survival; however, mutational signatures were not. Measuring a few markers provided a sufficient prognostic performance evaluated by c-index for each cancer type. DNA markers demonstrated better or comparable prognostic performance compared to RNA markers in some cancer types. "Universal" markers strongly associated with overall survival across cancer types were not identified. These findings will give insights into the clinical implementation of prognosis markers.

Endogenous protein S100A14 stabilizes glutaminase to render hepatocellular carcinoma resistant to sorafenib

BACKGROUND

Many cases of advanced hepatocellular carcinoma (HCC) are resistant to the widely used drug sorafenib, which worsens prognosis. While many studies have explored how acquired resistance emerges during drug exposure, the mechanism underlying primary resistance before treatment still remain elusive.

METHODS

Single-cell lineage tracing and RNA sequencing were performed to identify primary sorafenib-resistant lineages in HCC. Differential gene expression analysis was employed to identify the biomarkers of drug-resistant lineage cells. Cell viability and colony formation assays were adopted to assess the involvement of S100A14 on sorafenib resistance. Co-immunoprecipitation (CO-IP) and mass spectrometry analysis were conducted to uncover the downstream targets and regulatory mechanisms of S100A14 in primary resistance to sorafenib. In vivo mouse xenograft experiments were carried out to assess the effect of S100A14 or its interacting protein glutaminase (GLS) on primary resistance to sorafenib in HCC.

RESULTS

Single-cell lineage tracing identified a cluster of sorafenib primary resistant cells, and S100A14, a Ca2+-binding protein, was determined to be a critical biomarker for primary resistance to sorafenib. Knockdown of S100A14 significantly increases sorafenib treatment sensitivity in HCC cells. Mechanistically, S100A14 binds to GLS and blocks its phosphorylation at residues Y308 and S314, which in turn inhibits its ubiquitination and subsequent degradation. By stabilizing GLS, S100A14 reduces oxidative stress in HCC cells, thereby antagonizing sorafenib-induced apoptosis. Inhibiting S100A14 or GLS significantly improved sorafenib efficacy against xenograft tumors in vivo.

CONCLUSIONS

Our results demonstrate that S100A14 plays a pivotal role in promoting primary resistance to sorafenib by stabilizing GLS to reduce oxidative stress, and acts as a potential therapeutic target to enhance the efficacy of sorafenib in HCC patients.

Comprehensive molecular characteristics of hepatocellular carcinoma based on multi-omics analysis

BACKGROUND

The high heterogeneity of hepatocellular carcinoma (HCC) poses challenges for precision treatment strategies. This study aims to use multi-omics methodologies to better understand its pathogenesis and discover biomarkers.

METHODS

Quantitative proteomics was used to investigate hepatocellular carcinoma tissues (HCT) and their corresponding adjacent non-tumor tissues (DNT), obtained from six HCC patients. Untargeted metabolomics was applied to analyze the metabolic profiles of HCT and DNT of ten HCC patients. Statistical analyses, such as the Student's t-test, were performed to identify differentially expressed proteins (DEPs) and metabolites (DEMs) between the two groups. The functions and metabolic pathways involving DEPs and DEMs were annotated and enriched using the gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) databases. Bioinformatics methods were then utilized to analyze consistency between proteomics and metabolomics results, leading to identification of potential biomarkers along with key altered pathways associated with HCC.

RESULTS

This study identified 1556 DEPs between HCT and DNT samples. These DEPs were primarily enriched in crucial biological pathways such as amino acid degradation, fatty acid metabolism, and DNA replication. Subsequently, the analysis of metabolomics identified 500 DEMs that mainly participated in glycerophospholipid metabolism, the phospholipase D signaling pathway, and choline metabolism related to cancer. Integrated analysis of proteomics and metabolomics data unveiled significant dysfunctions in bile secretion, multiple amino acid and fatty acid metabolic pathways among HCC patients. Further investigation revealed that five proteins (PTP4A3, B4GALT5, GAB1, ME2, and PKM) along with seven metabolites (PI(6 keto-PGF1alpha/16:0), 13, 16, 19-docosatrienoic acid, PA(18:2(9Z, 12Z)/20:1(11Z)), Citric Acid, PG(20:3(6, 8, 11)-OH(5)/18:2(9Z, 12Z)), Spermidine, and N2-Acetylornithine) exhibited excellent diagnostic efficiency for HCC and could serve as its potential biomarkers.

CONCLUSION

Our integrated proteome and metabolome analysis revealed 10 key HCC-related pathways and proposed 12 potential biomarkers, which may enhance our understanding of HCC pathophysiology and be helpful in facilitating early diagnosis and treatment strategies.

Tracing specificity of immune landscape remodeling associated with distinct anticancer treatments

Immune cells within the tumor microenvironment impact cancer progression, resistance, response to treatments. Despite remarkable outcomes for some cancer patients, immunotherapies remain unsatisfactory for others. Here, we designed an experimental setting using the Alb-R26 Met "inside-out" mouse model, faithfully recapitulating molecular features of liver cancer patients, to explore the effects of distinct anticancer targeted therapies on the tumor immune landscape. Using two treatments in clinical trials for different cancer types, Decitabine and MEK+BCL-XL blockage, we show their capability to trigger tumor regression in Alb-R26 Met mice and to superimpose distinct profiles of immune cell types and immune-checkpoints, impacting immunotherapy response. A machine learning approach processing tumor imaging and immune profile data identified a putative signature predicting tumor treatment response in mice and patients. Outcomes exemplify how the tumor immune microenvironment is differentially reshaped by distinct anticancer agents and highlight the importance of measuring its modulation during treatment to optimize oncotherapy and immunotherapy combinations.

The hepatocellular model of fatty liver disease: from current imaging diagnostics to innovative proteomics technologies

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is a prevalent chronic liver condition characterized by lipid accumulation and inflammation, often progressing to severe liver damage. We aim to review the pathophysiology, diagnostics, and clinical care of MASLD, and review highlights of advances in proteomic technologies. Recent advances in proteomics technologies have improved the identification of novel biomarkers and therapeutic targets, offering insight into the molecular mechanisms underlying MASLD progression. We focus on the application of mass spectrometry-based proteomics including single cell proteomics, proteogenomics, extracellular vesicle (EV-omics), and exposomics for biomarker discovery, emphasizing the potential of blood-based panels for noninvasive diagnosis and personalized medicine. Future research directions are presented to develop targeted therapies and improve clinical outcomes for MASLD patients.

Molecular and immune landscape of hepatocellular carcinoma to guide therapeutic decision-making

Liver cancer, primarily HCC, exhibits highly heterogeneous histological and molecular aberrations across tumors and within individual tumor nodules. Such intertumor and intratumor heterogeneities may lead to diversity in the natural history of disease progression and various clinical disparities across the patients. Recently developed multimodality, single-cell, and spatial omics profiling technologies have enabled interrogation of the intertumor/intratumor heterogeneity in the cancer cells and the tumor immune microenvironment. These features may influence the natural history and efficacy of emerging therapies targeting novel molecular and immune pathways, some of which had been deemed undruggable. Thus, comprehensive characterization of the heterogeneities at various levels may facilitate the discovery of biomarkers that enable personalized and rational treatment decisions, and optimize treatment efficacy while minimizing the risk of adverse effects. Such companion biomarkers will also refine HCC treatment algorithms across disease stages for cost-effective patient management by optimizing the allocation of limited medical resources. Despite this promise, the complexity of the intertumor/intratumor heterogeneity and ever-expanding inventory of therapeutic agents and regimens have made clinical evaluation and translation of biomarkers increasingly challenging. To address this issue, novel clinical trial designs have been proposed and incorporated into recent studies. In this review, we discuss the latest findings in the molecular and immune landscape of HCC for their potential and utility as biomarkers, the framework of evaluation and clinical application of predictive/prognostic biomarkers, and ongoing biomarker-guided therapeutic clinical trials. These new developments may revolutionize patient care and substantially impact the still dismal HCC mortality.

PAXIP1 is regulated by NRF1 and is a prognosis‑related biomarker in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is characterized by a poor prognosis globally. PAX-interacting protein 1 (PAXIP1) serves a key role in the development of numerous human cancer types. Nevertheless, its specific involvement in HCC remains poorly understood. Public repository systems (Integrative Molecular Database of HCC, Gene Expression Omnibus, The Cancer Genome Atlas, University of Alabama at Birmingham Cancer Data Analysis Portal, Tumor Immune Estimation Resource and Human Protein Atlas) were utilized to explore PAXIP1 expression in HCC and evaluate the prognostic value of PAXIP1 in patients with HCC. PAXIP1 expression was investigated, and a notable relationship between PAXIP1 expression and various cancer types was found through analysis of The Cancer Genome Atlas data. More specifically, patients with HCC and lower PAXIP1 levels had improved survival rates. Furthermore, using LinkedOmics, the co-expression network of PAXIP1 in HCC was determined. Colocalization analysis of PAXIP1 using chromatin immunoprecipitation-sequencing data suggested that PAXIP1 might act as a cofactor for MYB proto-oncogene like 2 or FOXO1 in HCC. In addition, by predicting and analyzing the potential transcription factors related to PAXIP1, nuclear respiratory factor 1 was identified as a factor upstream of PAXIP1 in HCC. Notably, PAXIP1 expression exhibited a positive association with the infiltration of CD4+ and CD8+ T cells, macrophages, neutrophils and myeloid dendritic cells. Furthermore, PAXIP1 expression was associated with a range of immune markers such as programmed cell death protein 1, programmed death-ligand 1 and cytotoxic T-lymphocyte associated protein 4 in HCC. The findings of the present study highlighted the prognostic relevance of PAXIP1 and its function in modulating immune cell recruitment in HCC.

Advancements in proteogenomics for preclinical targeted cancer therapy research

Advancements in molecular characterization technologies have accelerated targeted cancer therapy research at unprecedented resolution and dimensionality. Integrating comprehensive multi-omic molecular profiling of a tumor, proteogenomics, marks a transformative milestone for preclinical cancer research. In this paper, we initially provided an overview of proteogenomics in cancer research, spanning genomics, transcriptomics, and proteomics. Subsequently, the applications were introduced and examined from different perspectives, including but not limited to genetic alterations, molecular quantifications, single-cell patterns, different post-translational modification levels, subtype signatures, and immune landscape. We also paid attention to the combined multi-omics data analysis and pan-cancer analysis. This paper highlights the crucial role of proteogenomics in preclinical targeted cancer therapy research, including but not limited to elucidating the mechanisms of tumorigenesis, discovering effective therapeutic targets and promising biomarkers, and developing subtype-specific therapies.

Integrated View of Baseline Protein Expression in Human Tissues Using Public Data Independent Acquisition Data Sets

The PRIDE database is the largest public data repository of mass spectrometry-based proteomics data and currently stores more than 40,000 data sets covering a wide range of organisms, experimental techniques, and biological conditions. During the past few years, PRIDE has seen a significant increase in the amount of submitted data-independent acquisition (DIA) proteomics data sets. This provides an excellent opportunity for large-scale data reanalysis and reuse. We have reanalyzed 15 public label-free DIA data sets across various healthy human tissues to provide a state-of-the-art view of the human proteome in baseline conditions (without any perturbations). We computed baseline protein abundances and compared them across various tissues, samples, and data sets. Our second aim was to compare protein abundances obtained here from the results of previous analyses using human baseline data-dependent acquisition (DDA) data sets. We observed a good correlation across some tissues, especially in the liver and colon, but weak correlations were found in others, such as the lung and pancreas. The reanalyzed results including protein abundance values and curated metadata are made available to view and download from the resource Expression Atlas.

Whole transcriptome and proteome analyses identify ncRNAs and mRNAs to predict competing endogenous RNA networks in hepatitis B virus-induced hepatocellular carcinoma

The presence of the Hepatitis B virus (HBV) is considered as a valuable risk factor of hepatocellular carcinoma (HCC). To more deeply comprehend the molecular mechanism and transcriptome of HBV-induced HCC, we utilized tandem mass tagging (TMT)-based quantitative proteomics analysis and whole-transcriptome sequencing to analyze three sets of matched HepG2 hepatoma cells and HBV-positive HepAD38 cells. The differentially expressed (DE) proteins (1596), mRNAs (5263), miRNAs (581), lncRNAs (2672) and circRNAs (222) were subjected to differential expression and enrichment analyses in order to thoroughly assess the gene-regulatory circuits of HBV-induced HCC. Subsequently, the amounts of 321 DEproteins-DEmRNAs with common alterations were confirmed. According to functional pathway analysis, the DEproteins-DEmRNAs were primarily linked to signaling pathways, amino acid metabolism, and cellular function. Furthermore, the viability and significance of the ceRNA regulatory networks, LOC105377730/miR-4726-5p/FHL2 and hsa_circ_0001098/miR-2110/IGF2BP1, were randomly chosen and confirmed. Our work provides a valuable asset in terms of understanding regulatory activities at the RNA level, and might reveal fresh information about the fundamental mechanism and potential therapeutic targets of HBV-induced HCC.

Novel genetic variants in the NLRP3 inflammasome-related PANX1 and APP genes predict survival of patients with hepatitis B virus-related hepatocellular carcinoma

BACKGROUND

The nod-like receptor protein 3 (NLRP3) is one of the most characterized inflammasomes involved in the pathogenesis of several cancers, including hepatocellular carcinoma (HCC). However, the effects of genetic variants in the NLRP3 inflammasome-related genes on survival of hepatitis B virus (HBV)-related HCC patients are unclear.

METHODS

We performed multivariable Cox proportional hazards regression analysis to evaluate associations between 299 single-nucleotide polymorphisms (SNPs) in 16 NLRP3 inflammasome-related genes and overall survival (OS) of 866 patients with HBV-related HCC. We further performed expression quantitative trait loci (eQTL) analysis using the data from the GTEx project and 1000 Genomes projects, and performed differential expression analysis using the TCGA dataset to explore possible molecular mechanisms underlying the observed associations.

RESULTS

We found that two functional SNPs (PANX1 rs3020013 A > G and APP rs9976425 C > T) were significantly associated with HBV-related HCC OS with the adjusted hazard ratio (HR) of 0.83 [95% confidence interval (CI) = 0.73-0.95, P = 0.008], and 1.26 (95% CI = 1.02-1.55, P = 0.033), respectively. Moreover, the eQTL analysis revealed that the rs3020013 G allele was correlated with decreased mRNA expression levels of PANX1 in both normal liver tissues (P = 0.044) and whole blood (P < 0.001) in the GTEx dataset, and PANX1 mRNA expression levels were significantly higher in HCC samples and associated with a poorer survival of HCC patients. However, we did not observe such correlations for APP rs9976425.

CONCLUSIONS

These results indicated that SNPs in the NLRP3 inflammasome-related genes may serve as potential biomarkers for HBV-related HCC survival, once replicated by additional larger studies.

Diagnostic accuracy of preoperative MRI in assessing macrotrabecular-massive subtype of hepatocellular carcinoma: a systematic review and meta-analysis

OBJECTIVES

To determine the value of preoperative magnetic resonance imaging (MRI) in predicting macrotrabecular-massive hepatocellular carcinoma (MTM-HCC).

MATERIALS AND METHODS

A search was conducted on PubMed, Web of Science, Cochrane Library databases, and Embase for studies evaluating the performance of MRI in assessing MTM-HCC. The quality assessment of diagnostic studies (QUADAS-2) tool was used to assess the risk of bias. Diagnostic accuracy measures, including sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR), were pooled. Summary receiver operating characteristic (SROC) curves with the area under the curve (AUC) were generated. Meta-regression analysis was performed to explore potential sources of heterogeneity.

RESULTS

A total of ten eligible studies including 2074 lesions in 2053 patients were analyzed. The pooled sensitivity, specificity, PLR, NLR, DOR, and AUC were 0.65 (0.52, 0.76), 0.88 (0.80, 0.94), 5.6 (3.70, 8.60), 0.40 (0.30, 0.53), 14 (10, 20), and 0.84 (0.81, 0.87), respectively. High heterogeneity was observed (I2 was 78.61% and 90.95% for sensitivity and specificity, respectively) along with a threshold effect (Spearman's correlation coefficient = 0.927, p < 0.001). Meta-regression analysis demonstrated that the MRI method (radiomics or non-radiomics) affected the heterogeneity.

CONCLUSION

MRI has diagnostic value for MTM-HCC due to its higher specificity and moderate sensitivity, but its clinical application remains suboptimal due to significant heterogeneity. Thus, further prospective studies with large sample sizes are needed to confirm these results.

KEY POINTS

Question What is the value of MRI for preoperatively predicting MTM-HCC? Findings Meta-regression analyses revealed that the MRI method (radiomics or non-radiomics) is a significant factor contributing to heterogeneity. Clinical relevance This study demonstrates the high diagnostic accuracy of MRI for early detection of MTM-HCC, which can assist in guiding individualized management.

Phosphoproteomics profiling of sorafenib-resistant hepatocellular carcinoma patient-derived xenografts reveals potential therapeutic strategies

Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer with poor prognosis. Sorafenib, a first-line treatment for advanced HCC, has shown limited clinical benefits due to the onset of drug resistance. Thus, it is imperative to comprehend the mechanisms underlying sorafenib resistance and explore strategies to overcome or delay it. Here, we established HCC patient-derived xenograft (PDX) models with acquired resistance to sorafenib and performed comprehensive proteomic and phosphoproteomic analyses on these models. The active cell cycle pathway along with the active cyclin-dependent kinase CDK1 and DNA-dependent protein kinase PRKDC was identified through KEGG pathway enrichment and kinase substrate enrichment analyses. Upon investigating the potential of combining sorafenib with putative kinase inhibitors, we found that the combination displays synergistic anti-proliferative effects in the sorafenib-resistant liver cancer cell line, thus providing a proof of concept for phosphoproteomic-guided design of precision medicine.

Quantitative proteomic analysis unveils a critical role of VARS1 in hepatocellular carcinoma aggressiveness through the modulation of MAGI1 expression

BACKGROUND

Hepatocellular carcinoma (HCC) genetic/transcriptomic signatures have been widely described. However, its proteomic characterization is incomplete. We performed non-targeted quantitative proteomics of HCC samples and explored its clinical, functional, and molecular consequences.

METHODS

Non-targeted quantitative proteomics were performed on cytosolic and nuclear fractions of liver samples [HCC vs. non-tumour adjacent tissue (NTAT), n = 42 patients]. Changes were confirmed in 7 in silico HCC cohorts. Functional and molecular implications were evaluated on HCC-derived cell lines after silencing/overexpressing VARS1 and/or MAGI1. VARS1-overexpressing Hep3B cells were used for in vivo studies [Extreme Limiting Dilution Assay (ELDA) and orthotopic tumour formation]. Quantitative proteomics were performed on VARS1-overexpressing HCC cell lines.

RESULTS

Quantitative proteomics revealed the dysregulation of the cytosolic and nuclear proteomes in HCC, and defined two proteomic HCC subgroups, the most aggressive associated to the dysregulation of the aminoacyl-tRNA synthetases (ARSs). ARSs dysregulation was corroborated in in silico HCC cohorts and associated to poor prognosis. Patients with ARSs upregulation had genomic/transcriptomic characteristics of the proliferative HCC. Valine tRNA-aminoacyl synthetase (VARS1) was the ARSs most consistently overexpressed and associated to aggressiveness. VARS1 modulation (silencing/overexpression) altered tumour establishment-associated parameters in vitro and/or in vivo. Quantitative proteomics on cells overexpressing VARS1 and rescue experiments identified the downregulation of MAGI1, a tumour suppressor in HCC, as a mediator of VARS1 function.

CONCLUSIONS

Quantitative proteomics defines two prognosis-related proteomic HCC subgroups. ARSs machinery is dysregulated in the aggressive subgroup, bearing potential as prognostic biomarkers. VARS1 promotes aggressiveness through the modulation of MAGI1, representing a novel targetable vulnerability in HCC.

Proteomic Characterization of Liver Cancer Cells Treated with Clinical Targeted Drugs for Hepatocellular Carcinoma

Background/Objectives: Hepatocellular carcinoma (HCC) remains a significant global health concern, primarily due to the limited efficacy of targeted therapies, which are often compromised by drug resistance and adverse side effects. Methods: In this study, we utilized a Tandem Mass Tag (TMT)-based quantitative proteomic approach to analyze global protein expression and serine/threonine/tyrosine (S/T/Y) phosphorylation modifications in HepG2 cells following treatment with three clinically relevant hepatocellular carcinoma-targeted agents: apatinib, regorafenib, and lenvatinib. Results: Utilizing KEGG pathway enrichment analysis, biological process enrichment analysis, and protein interaction network analysis, we elucidated the common and specific metabolic pathways, biological processes, and protein interaction regulatory networks influenced by three liver cancer therapeutics. The study additionally proposed potential combinational treatment strategies, highlighting a possible synergistic interaction between HCC-targeted drugs and the DNA methyltransferase inhibitor. Furthermore, through the integration of clinical phosphorylation site data, we identified several phosphorylation sites that exhibited higher abundance in tumor tissues compared to adjacent non-tumor tissues. These sites were associated with poor prognosis and elevated functional scores. Conclusions: In summary, this study conducted an in-depth analysis of the molecular alterations in proteins and phosphorylation modifications induced by clinical HCC-targeted drugs, predicting drug combination strategies and therapeutic targets.

WEE Family Kinase Inhibitors Combined with Sorafenib Can Selectively Inhibit HCC Cell Proliferation

BACKGROUND

Sorafenib is currently the first choice for the treatment of patients with advanced hepatocellular carcinoma, but its therapeutic effect is still limited.

OBJECTIVES

This study aims to examine whether WEE family kinase inhibitors can enhance the anticancer effect of sorafenib.

METHODS

We analyzed the expression levels of PKMYT1 kinase and WEE1 kinase in HCC, studied the inhibitory effect of PKMYT1 kinase inhibitor RP-6306, WEE1 kinase inhibitor adavosertib combined with sorafenib on the proliferation of HCC cells, and detected the effect of drug combination on CDK1 phosphorylation.

RESULTS

We found that PKMYT1 and WEE1 were upregulated in HCC and were detrimental to patient survival. Cell experiments showed that both RP-6306 and adavosertib (1-100 μM) inhibited the proliferation of HCC cell lines in a dose-dependent manner alone, and the combination of the two drugs had a synergistic effect. In HCC cell lines, sorafenib combined with RP-6306 or adavosertib showed a synergistic antiproliferation effect and less toxicity to normal cells. Sorafenib combined with RP-6306 and adavosertib further inhibited the proliferation of HCC cells and caused complete dephosphorylation of CDK1.

CONCLUSION

Taken together, our findings provide experimental evidence for the future use of sorafenib in combination with RP-6306 or adavosertib for the treatment of HCC.

MPCD Index for Hepatocellular Carcinoma Patients Based on Mitochondrial Function and Cell Death Patterns

Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer with a poor prognosis. During the development of cancer cells, mitochondria influence various cell death patterns by regulating metabolic pathways such as oxidative phosphorylation. However, the relationship between mitochondrial function and cell death patterns in HCC remains unclear. In this study, we used a comprehensive machine learning framework to construct a mitochondrial functional activity-associated programmed cell death index (MPCDI) based on scRNA-seq and RNA-seq data from TCGA, GEO, and ICGC datasets. The index signature was used to classify HCC patients, and studied the multi-omics features, immune microenvironment, and drug sensitivity of the subtypes. Finally, we constructed the MPCDI signature consisting of four genes (S100A9, FYN, LGALS3, and HMOX1), which was one of the independent risk factors for the prognosis of HCC patients. The HCC patients were divided into high- and low-MPCDI groups, and the immune status was different between the two groups. Patients with a high MPCDI had higher TIDE scores and poorer responses to immunotherapy, suggesting that high-MPCDI patients might not be suitable for immunotherapy. By analyzing the drug sensitivity data of CTRP, GDSC, and PRISM databases, it was found that staurosporine has potential therapeutic significance for patients with a high MPCDI. In summary, based on the characteristics of mitochondria function and PCD patterns, we used single-cell and transcriptome data to identify four genes and construct the MPCDI signature, which provided new perspectives and directions for the clinical diagnosis and personalized treatment of HCC patients.

Integrative multi-omics characterization of hepatocellular carcinoma in Hispanic patients

BACKGROUND

The incidence and mortality rates of hepatocellular carcinoma among Hispanic individuals in the United States are much higher than in non-Hispanic White people. We conducted multi-omics analyses to elucidate molecular alterations in hepatocellular carcinoma among Hispanic patients.

METHODS

Paired tumor and adjacent nontumor samples were collected from 31 Hispanic hepatocellular carcinomas in South Texas for genomic, transcriptomic, proteomic, and metabolomic profiling. Serum lipids were profiled in 40 Hispanic and non-Hispanic patients with or without clinically diagnosed hepatocellular carcinoma.

RESULTS

Exome sequencing revealed high mutation frequencies of AXIN2 and CTNNB1 in South Texas Hispanic hepatocellular carcinoma patients, suggesting a predominant activation of the Wnt/β-catenin pathway. TERT promoter mutations were also statistically significantly more frequent in the Hispanic cohort (Fisher exact test, P < .05). Cell cycles and liver function were positively and negatively enriched, respectively, with gene set enrichment analysis. Gene sets representing specific liver metabolic pathways were associated with dysregulation of corresponding metabolites. Negative enrichment of liver adipogenesis and lipid metabolism corroborated with a significant reduction in most lipids in serum samples of hepatocellular carcinoma patients (paired t test, P < .0001). Two hepatocellular carcinoma subtypes from our Hispanic cohort were identified and validated with the Cancer Genome Atlas liver cancer cohort. Patients with better overall survival showed higher activity of immune and angiogenesis signatures and lower activity of liver function-related gene signatures. They also had higher levels of immune checkpoint and immune exhaustion markers.

CONCLUSIONS

Our study revealed specific molecular features of Hispanic hepatocellular carcinoma and potential biomarkers for therapeutic management. It provides a unique resource for studying Hispanic hepatocellular carcinoma.

Proceedings of the 5th Meeting of Translational Hepatology, organized by the Spanish Association for the Study of the Liver (AEEH)

This is the summary report of the 5th Translational Hepatology Meeting, endorsed by the Spanish Association for the Study of the Liver (AEEH) and held in Seville, Spain, in October 2023. The meeting aimed to provide an update on the latest advances in the field of basic and translational hepatology, covering different molecular, cellular, and pathophysiological aspects of the most relevant clinical challenges in liver pathologies. This includes the identification of novel biomarkers and diagnostic tools, the understanding of the relevance of immune response and inflammation in liver diseases, the characterization of current medical approaches to reverse liver diseases, the incorporation of novel molecular insights through omics techniques, or the characterization of the impact of toxic and metabolic insults, as well as other organ crosstalk, in liver pathophysiology.

Adenosine Receptor 3 in Liver Cancer: Expression Variability, Epigenetic Modulation, and Enhanced Histone Deacetylase Inhibitor Effects

Background and Aims

Primary liver cancer, including hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), has low response rates to existing treatments, highlighting the urgent need for novel treatment options. Adenosine A3 receptor (ADORA3) signaling has emerged as a potential target. Namodenoson, an ADORA3 agonist, has shown promise in early clinical trials for HCC. However, further data are required to clarify ADORA3 expression patterns in liver cancer, mechanisms of action, and the potential for combination therapies to inform patient selection for future clinical trials.

Methods

Patient-derived tissue microarrays and RNA-sequencing were employed to investigate ADORA3 expression. Cellular responses to ADORA3 stimulation and combination treatments were studied in HCC and CCA cell lines and patient-derived organoids (PDOs). Genome-wide RNA-Seq analysis, mRNA analysis, and DigiWest protein profiling were performed.

Results

Tissue microarray analysis revealed higher ADORA3 expression in nonmalignant samples and a subset of tumors with weak or absent ADORA3 expression. This was supported by RNA sequencing data from The Cancer Genome Atlas and needle biopsy samples. Cell lines and PDOs exhibited antiproliferative effects with the ADORA3 agonist Namodenoson, confirmed by receptor dependency tests with specific antagonists and siRNA experiments. Genome-wide RNA-Seq analysis suggested chromatin remodeling events after ADORA3 stimulation. mRNA expression and DigiWest profiling identified downregulation of histone deacetylases and histone H3 modifications. Combination treatments with different ADORA3 agonists and histone deacetylase inhibitors significantly enhanced antiproliferative effects in almost all selected combinations, supported by investigations in PDOs.

Conclusion

ADORA3 expression varies considerably in HCC or CCA, ranging from high to absent receptor detection. This observation might help to identify patients for clinical studies. Additionally, Namodenoson's epigenetic modulating activity suggests epigenetic drugs as promising candidates for combination treatment.

Oncogenic cholesterol rewires lipid metabolism in hepatocellular carcinoma via the CSNK2A1-IGF2R Ser2484 axis

INTRODUCTION

Alcohol consumption and hepatitis B virus (HBV) infection are common risk factors for hepatocellular carcinoma (HCC). However, few studies have focused on elucidating the mechanisms of HCC with combined alcohol and HBV etiology.

OBJECTIVES

We aimed to investigate the molecular features of alcohol and HBV on HCC and to seek out potential therapeutic strategies.

METHODS

Two independent cohorts of HCC patients (n = 539 and n = 140) were included to investigate HCC with synergetic alcohol and HBV (AB-HCC) background. Patient-derived cell lines, organoids, and xenografts were used to validate the metabolic fragile. High-throughput drug screening (1181 FDA-approved anticancer drugs) was leveraged to explore the potential therapeutic agents.

RESULTS

Here, we delineated AB-HCC as a distinctive metabolic subtype, hallmarked by oncogenic cholesterol, through the integration of clinical cohorts, proteomics, phosphoproteomics, and spatial transcriptome. Mechanistically, our findings revealed that cholesterol directly binds to CSNK2A1 (Casein Kinase 2 Alpha 1), augmenting its kinase activity and leading to phosphorylation of IGF2R (Insulin-Like Growth Factor 2 Receptor) at Ser2484. This cascade rewires lipid-driven mitochondrial oxidative phosphorylation, spawns reactive oxygen species measured by malondialdehyde assay, and perpetuates a positive feedback loop for cholesterol biosynthesis, ultimately culminating in tumorigenesis. Initial transcriptional activation of CSNK2A1 is driven by upregulation of RAD21 in AB-HCC. Our cholesterol profiling exposes AB-HCC's compensatory mechanism of AB-HCC, which capitalizes on both uptake and biosynthesis of cholesterol to confer survival edge. Moreover, high-throughput drug screening coupled with in vivo validation has uncovered the susceptibilities of AB-HCC, which can be effectively addressed by a combination of dietary cholesterol restriction and oral administration of Fostamatinib. The CSNK2A1-mediated cholesterol biosynthesis pathway has been implicated in various cancers characterized by cholesterol metabolism.

CONCLUSION

These findings not only pinpoint the oncogenic metabolite cholesterol as a hidden culprit in AB-HCC subtype, but also enlighten a novel combination strategy to rejuvenate tumor metabolism.

The ncRNA-AURKA Interaction in Hepatocellular Carcinoma: Insights into Oncogenic Pathways, Therapeutic Opportunities, and Future Challenges

Hepatocellular carcinoma (HCC) represents a major public health concern and ranks among the leading cancer-related mortalities globally. Due to the frequent late-stage diagnosis of HCC, therapeutic options remain limited. Emerging evidence highlights the critical role of non-coding RNAs (ncRNAs) in the regulation of Aurora kinase A (AURKA), one of the key hub genes involved in several key cancer pathways. Indeed, the dysregulated interaction between ncRNAs and AURKA contributes to tumor development, progression, and therapeutic resistance. This review delves into the interplay between ncRNAs and AURKA and their role in hepatocarcinogenesis. Recent findings underscore the involvement of the ncRNAs and AURKA axis in tumor development and progression. Furthermore, this review also discusses the clinical significance of targeting ncRNA-AURKA axes, offering new perspectives that could lead to innovative therapeutic strategies aimed at improving outcomes for HCC patients.

Clinical proteomics towards multiomics in cancer

Recent technological advancements in mass spectrometry (MS)-based proteomics technologies have accelerated its application to study greater and greater numbers of human tumor specimens. Over the last several years, the Clinical Proteomic Tumor Analysis Consortium, the International Cancer Proteogenome Consortium, and others have generated MS-based proteomic profiling data combined with corresponding multiomics data on thousands of human tumors to date. Proteomic data sets in the public domain can be re-examined by other researchers with different questions in mind from what the original studies explored. In this review, we examine the increasing role of proteomics in studying cancer, along with the potential for previous studies and their associated data sets to contribute to improving the diagnosis and treatment of cancer in the clinical setting. We also explore publicly available proteomics and multi-omics data from cancer cell line models to show how such data may aid in identifying therapeutic strategies for cancer subsets.

Prognostic Implications of MRI-assessed Intratumoral Fat in Hepatocellular Carcinoma: An Asian and European Cohort Study

Background The clinicopathologic-radiologic and prognostic characteristics of intratumoral fat in hepatocellular carcinoma (HCC) are critical for personalized treatment but remain understudied. Purpose To investigate the clinicopathologic-radiologic associations and prognostic implications of MRI-assessed intratumoral fat in HCCs. Materials and Methods This retrospective cohort study included consecutive adult patients who underwent resection for solitary HCCs and preoperative contrast-enhanced MRI from two tertiary-care hospitals in East Asia (March 2011 to December 2021) and Western Europe (September 2012 to December 2019). MRI scans were independently evaluated by three radiologists at each hospital. Based on Liver Imaging Reporting and Data System (LI-RADS) version 2018, intratumoral fat was defined as "fat in mass more than adjacent liver," and the homogeneous subtype was defined as intratumoral fat "in absence of mosaic and nodule-in-nodule architecture." Recurrence-free survival (RFS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared using the log-rank test. Cox regression analyses were conducted to identify factors associated with RFS and OS. Results A total of 933 patients were included in the Asian (n = 736; median age, 53 years [IQR, 45-62 years]; 626 male) and European (n = 207; median age, 64 years [IQR, 55-70 years]; 161 male) cohorts. MRI-assessed intratumoral fat was detected in 30% (215 of 726) and 31% (64 of 207) of patients in the Asian and European cohorts, respectively (P = .72). In both cohorts, the steatohepatitic subtype, nonperipheral washout, enhancing capsule, and mosaic architecture were more frequent in tumors with intratumoral fat (P value range, <.001 to .04). Intratumoral fat in general was not associated with RFS or OS in either cohort (P value range, .48-.97). However, in the Asian cohort, homogeneous intratumoral fat was associated with longer RFS (hazard ratio [HR], 0.60; P = .009) and OS (HR, 0.33; P = .008) in multivariable Cox regression analyses. Conclusion MRI-assessed intratumoral fat was more frequent in steatohepatitic HCCs and associated with nonperipheral washout, enhancing capsule, and mosaic architecture. Although intratumoral fat was generally nonprognostic, homogeneous intratumoral fat was associated with longer RFS and OS in the Asian cohort. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Harmath in this issue.

Percutaneous Delivery of Oncogel for Targeted Liver Tumor Ablation and Controlled Release of Therapeutics

Advanced-stage liver cancers are associated with poor prognosis and have limited treatment options, often leading the patient to hospice care. Percutaneous intratumoral injection of anticancer agents has emerged as a potential alternative to systemic therapy to overcome tumor barriers, increase bioavailability, potentiate immunotherapy, and avoid systemic toxicity, which advanced-stage cancer patients cannot tolerate. Here, an injectable OncoGel (OG) comprising of a nanocomposite hydrogel loaded with an ionic liquid (IL) is developed for achieving a predictable and uniform tumor ablation and long-term slow release of anticancer agents into the ablation zone. Rigorous mechanical, physiochemical, drug release, cytotoxicity experiments, and ex vivo human tissue testing identify an injectable version of the OG with bactericidal properties against highly resistant bacteria. Intratumoral injection of OG loaded with Nivolumab (Nivo) and doxorubicin (Dox) into highly malignant tumor models in mice, rats, and rabbits demonstrates enhanced survival and tumor regression associated with robust tissue ablation and drug distribution throughout the tumor. Mass cytometry and proteomic studies in a mouse model of colorectal cancer that often metastasizes to the liver indicate an enhanced anticancer immune response following the intratumoral injection of OG. OG may augment immunotherapy and potentially improve outcomes in liver cancer patients.

Mass spectrometry-based multi-omics analysis reveals distinct molecular features in early and advanced stages of hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is a serious primary solid tumor that is prevalent worldwide. Due to its high mortality rate, it is crucial to explore both early diagnosis and advanced treatment for HCC. In recent years, multi-omics approaches have emerged as promising tools to identify biomarkers and investigate molecular mechanisms of biological processes and diseases. In this study, we performed proteomics, phosphoproteomics, metabolomics, and lipidomics to reveal the molecular features of early- and advanced-stage HCC. The data obtained from these omics were analyzed separately and then integrated to provide a comprehensive understanding of the disease. The multi-omics results unveiled intricate biological pathways and interaction networks underlying the initiation and progression of HCC. Moreover, we proposed specific potential biomarker panels for both early- and advanced-stage HCC by overlapping our data with CPTAC database for HCC diagnosis, and deduced novel insights and mechanisms related to HCC origination and development, such as glucose depletion during tumor progression, ROCK1 deactivation and GSK3A activation.

Activation of Wnt/β-catenin signaling promotes immune evasion via the β-catenin/IKZF1/CCL5 axis in hepatocellular carcinoma

Immune checkpoint therapy (ICT) has been shown to produce durable responses in various cancer patients. However, its efficacy is notably limited in hepatocellular carcinoma (HCC), with only a small percentage of patients responding positively to treatment. The mechanism underlying resistance to ICT in HCC remains poorly understood. Here, we showed that combination treatment of ICG-001, an inhibitor of the Wnt/β-catenin signaling pathway, with anti-PD-1 antibody effectively suppresses tumor growth and promotes the infiltration of immune cells such as DCs and CD8+ T cells in the tumor microenvironment (TME). By inhibiting the activity of β-catenin and blocking its binding to the transcription factor IKAROS family zinc finger 1 (IKZF1), ICG-001 upregulated the expression of CCL5. Moreover, IKZF1 regulated the activity of the CCL5 promoter and its endogenous expression. Through inhibition of the WNT/β-catenin signaling pathway, upregulation of the expression of CCL5 was achieved, which subsequently recruited more DCs into the TME via C-C motif chemokine receptor 5 (CCR5). This, in turn, resulted in an increase in the infiltration of CD8+ T cells in the TME, thereby enhancing the antitumor immune response. Analysis of a tissue microarray derived from HCC patient samples revealed a positive correlation between survival rate and prognosis and the expression levels of CCL5/CD8. In conclusion, our findings suggest that combined application of ICG-001 and anti-PD-1 antibody exhibits significantly enhanced antitumor efficacy. Hence, combining a WNT/β-catenin signaling pathway inhibitor with anti-PD-1 therapy may be a promising treatment strategy for patients with HCC.

Prognostic Protein Biomarker Screening for Thyroid Carcinoma Based on Cancer Proteomics Profiles

Thyroid carcinoma (THCA) ranks among the most prevalent cancers globally. Integrating advanced genomic and proteomic analyses to construct a protein-based prognostic model promises to identify effective biomarkers and explore new therapeutic avenues. In this study, proteomic data from The Cancer Proteomics Atlas (TCPA) and clinical data from The Cancer Genome Atlas (TCGA) were utilized. Using Kaplan-Meier, Cox regression, and LASSO penalized Cox analyses, we developed a prognostic risk model comprising 13 proteins (S100A4, PAI1, IGFBP2, RICTOR, B7-H3, COLLAGENVI, PAR, SNAIL, FAK, Connexin-43, Rheb, EVI1, and P90RSK_pT359S363). The protein prognostic model was validated as an independent predictor of survival time in THCA patients, based on risk curves, survival analysis, receiver operating characteristic curves and independent prognostic analysis. Additionally, we explored the immune cell infiltration and tumor mutational burden (TMB) related to these features. Notably, our study proved a novel approach for predicting treatment responses in THCA patients, including those undergoing chemotherapy and targeted therapy.

Proteogenomic Analysis Identifies a Causal Association between Plasma Apolipoprotein B Levels and Liver Cancer Risk

Liver oncogenesis is accompanied by discernible protein changes in the bloodstream. By employing plasma proteomic profiling, we can delve into the molecular mechanisms of liver cancer and pinpoint potential biomarkers. In this nested case-control study, we applied liquid chromatography-tandem mass spectrometry for proteome profiling in baseline plasma samples. Differential protein expression was determined and was subjected to functional enrichment, network, and Mendelian randomization (MR) analyses. We identified 193 proteins with notable differential levels between the groups. Of these proteins, MR analysis offered a compelling negative association between apolipoprotein B (APOB) and liver cancer. This association was further corroborated in the UK Biobank cohort: genetically predicted APOB levels were associated with a 31% (95% CI 19-42%) decreased risk of liver cancer; and phenotypic analysis indicated an 11% (95% CI 8-14%) decreased liver cancer risk for every 0.1 g/L increase of circulating APOB levels. Multivariable MR analysis suggested that the hepatic fat content might fully mediate the APOB-liver cancer connection. In summary, we identified some plasma proteins, particularly APOB, as potential biomarkers of liver cancer. Our findings underscore the intricate link between lipid metabolism and liver cancer, offering hints for targeted prophylactic strategies and early detection.

Comprehensive molecular classification predicted microenvironment profiles and therapy response for HCC

BACKGROUND AND AIMS

Tumor microenvironment (TME) heterogeneity leads to a discrepancy in survival prognosis and clinical treatment response for patients with HCC. The clinical applications of documented molecular subtypes are constrained by several issues.

APPROACH AND RESULTS

We integrated 3 single-cell data sets to describe the TME landscape and identified 6 prognosis-related cell subclusters. Unsupervised clustering of subcluster-specific markers was performed to generate transcriptomic subtypes. The predictive value of these molecular subtypes for prognosis and treatment response was explored in multiple external HCC cohorts and the Xiangya HCC cohort. TME features were estimated using single-cell immune repertoire sequencing, mass cytometry, and multiplex immunofluorescence. The prognosis-related score was constructed based on a machine-learning algorithm. Comprehensive single-cell analysis described TME heterogeneity in HCC. The 5 transcriptomic subtypes possessed different clinical prognoses, stemness characteristics, immune landscapes, and therapeutic responses. Class 1 exhibited an inflamed phenotype with better clinical outcomes, while classes 2 and 4 were characterized by a lack of T-cell infiltration. Classes 5 and 3 indicated an inhibitory tumor immune microenvironment. Analysis of multiple therapeutic cohorts suggested that classes 5 and 3 were sensitive to immune checkpoint blockade and targeted therapy, whereas classes 1 and 2 were more responsive to transcatheter arterial chemoembolization treatment. Class 4 displayed resistance to all conventional HCC therapies. Four potential therapeutic agents and 4 targets were further identified for high prognosis-related score patients with HCC.

CONCLUSIONS

Our study generated a clinically valid molecular classification to guide precision medicine in patients with HCC.

Short-Term Statin Therapy Induces Hepatic Insulin Resistance Through HNF4α/PAQR9/PPM1α Axis Regulated AKT Phosphorylation

Statins, the first-line medication for dyslipidemia, are linked to an increased risk of type 2 diabetes. But exactly how statins cause diabetes is yet unknown. In this study, a developed short-term statin therapy on hyperlipidemia mice show that hepatic insulin resistance is a cause of statin-induced diabetes. Statin medication raises the expression of progesterone and adiponectin receptor 9 (PAQR9) in liver, which inhibits insulin signaling through degradation of protein phosphatase, Mg2+/Mn2+ dependent 1 (PPM1α) to activate ERK pathway. STIP1 homology and U-box containing protein 1 (STUB1) is found to mediate ubiquitination of PPM1α promoted by PAQR9. On the other hand, decreased activity of hepatocyte nuclear factor 4 alpha (HNF4α) seems to be the cause of PAQR9 expression under statin therapy. The interventions on PAQR9, including deletion of PAQR9, caloric restriction and HNF4α activation, are all effective treatments for statin-induced diabetes, while liver specific over-expression of PPM1α is another possible tactic. The results reveal the importance of HNF4α-PAQR9-STUB1-PPM1α axis in controlling the statin-induced hepatic insulin resistance, offering a fresh insight into the molecular mechanisms underlying statin therapy.

Unveiling EFNB2 as a Key Player in Sorafenib Resistance: Insights from Bioinformatics Analysis and Functional Validation in Hepatocellular Carcinoma

Sorafenib resistance has become a big hurdle for treating advanced HCC; thus, identifying novel targets to overcome sorafenib resistance is of great importance. Thanks to the massive progress in the sequencing and data analysis, high-throughput screening of novel targets in HCC development has been extensively used in recent years. In present study, we harnessed the public dataset and aimed to identify novel targets related to sorafenib resistance in HCC via bioinformatics analysis and in vitro validation. This study examined three GEO datasets (GSE140202, GSE143233, GSE182593) and identified 20 common DEGs. Functional enrichment analysis suggested these DEGs might play a role in regulating drug resistance pathways. PPI network analysis pinpointed 14 hub genes, with EFNB2 showing high connectivity to other genes. Subsequent in vitro experiments demonstrated that EFNB2 was up-regulated in sorafenib-resistant HCC cells. EFNB2 suppression sensitized HepG2 and Huh7 sorafenib-resistant cells. Furthermore, EFNB2 knockdown increased caspase-3/-7 activities and hindered EMT in sorafenib-resistant HCC cells. Conversely, EFNB2 overexpression promoted sorafenib resistance, decreased caspase-3/-7 activity, and enhanced EMT in HCC cells. Overall, this study identified 14 promising genes potentially linked to sorafenib resistance in HCC, with EFNB2 emerging as a potential contributor to this resistance mechanism.

SignalingProfiler 2.0 a network-based approach to bridge multi-omics data to phenotypic hallmarks

Unraveling how cellular signaling is remodeled upon perturbation is crucial for understanding disease mechanisms and identifying potential drug targets. In this pursuit, computational tools generating mechanistic hypotheses from multi-omics data have invaluable potential. Here, we present a newly implemented version (2.0) of SignalingProfiler, a multi-step pipeline to draw mechanistic hypotheses on the signaling events impacting cellular phenotypes. SignalingProfiler 2.0 derives context-specific signaling networks by integrating proteogenomic data with the prior knowledge-causal network. This is a freely accessible and flexible tool that incorporates statistical, footprint-based, and graph algorithms to accelerate the integration and interpretation of multi-omics data. Through a benchmarking process on three proof-of-concept studies, we demonstrate the tool's ability to generate hierarchical mechanistic networks recapitulating novel and known perturbed signaling and phenotypic outcomes, in both human and mice contexts. In summary, SignalingProfiler 2.0 addresses the emergent need to derive biologically relevant information from complex multi-omics data by extracting interpretable networks.

Effects of drug-induced liver injury on the in vivo fate of liposomes

Liposomes represent one of the most extensively studied nano-carriers due to their potential in targeted drug delivery. However, the complex in vivo fate, particularly under pathological conditions, presents challenges for clinical translation of liposomal therapeutics. Liver serves as the most important organ for liposome accumulation and metabolism. Unfortunately, the fate of liposomes under pathological liver conditions has been significantly overlooked. This study aimed to investigate the in vivo pharmacokinetic profile and biodistribution profile of liposomes under drug-induced liver injury (DILI) conditions. Two classic DILI animal models, i.e. acetaminophen-induced acute liver injury (AILI) and triptolide-induced subacute liver injury (TILI), were established to observe the effect of pathological liver conditions on the in vivo performance of liposomes. The study revealed significant changes in the in vivo fate of liposomes following DILI, including prolonged blood circulation and enhanced hepatic accumulation of liposomes. Changes in the composition of plasma proteins and mononuclear phagocyte system (MPS)-related cell subpopulations collectively led to the altered in vivo fate of liposomes under liver injury conditions. Despite liver injury, macrophages remained the primary cells responsible for liposomes uptake in liver, with the recruited monocyte-derived macrophages exhibiting enhanced ability to phagocytose liposomes under pathological conditions. These findings indicated that high capture of liposomes by the recruited hepatic macrophages not only offered potential solutions for targeted delivery, but also warned the clinical application of patients under pathological liver conditions.

Integrated vector genomes may contribute to long-term expression in primate liver after AAV administration

The development of liver-based adeno-associated virus (AAV) gene therapies is facing concerns about limited efficiency and durability of transgene expression. We evaluated nonhuman primates following intravenous dosing of AAV8 and AAVrh10 vectors for over 2 years to better define the mechanism(s) of transduction that affect performance. High transduction of non-immunogenic transgenes was achieved, although expression declined over the first 90 days to reach a lower but stable steady state. More than 10% of hepatocytes contained single nuclear domains of vector DNA that persisted despite the loss of transgene expression. Greater reductions in vector DNA and RNA were observed with immunogenic transgenes. Genomic integration of vector sequences, including complex concatemeric structures, were detected in 1 out of 100 cells at broadly distributed loci that were not in proximity to genes associated with hepatocellular carcinoma. Our studies suggest that AAV-mediated transgene expression in primate hepatocytes occurs in two phases: high but short-lived expression from episomal genomes, followed by much lower but stable expression, likely from integrated vectors.

TLK2 promotes progression of hepatocellular carcinoma through Wnt/β-catenin signaling

Background

Hepatocellular carcinoma is a widespread cancer worldwide, ranking as the fifth most frequent cancer and the fourth leading cause of cancer-related deaths. According to comprehensive research, TLK2, a phosphorylated kinase, has been discovered to play a crucial role in promoting tumor development. However, the prognostic significance and influence of TLK2 on hepatocellular carcinoma tumor cells and the immune microenvironment remain unexplored, warranting further investigation. The aim of this study was to investigate the role of TLK2 in promoting the development of hepatocellular carcinoma.

Methods

The present study utilized The Cancer Genome Atlas (TCGA) database and other databases as training sets to examine the expression of TLK2 and its prognostic significance. The findings were subsequently validated through cell proliferation assays and cell colony assays. Gene set enrichment analysis (GSEA) was employed to investigate the tumor-related biological processes associated with TLK2 in hepatocellular carcinoma, while the relationship between TLK2 expression and Wnt/β-catenin signaling pathway was analyzed via TCGA dataset analysis. Western blotting and immunofluorescence assays were used to confirm the experimental results.

Results

TLK2 showed higher expression levels in tumor tissues than in normal tissues. Alpha fetoprotein (AFP), T stage, pathological stage, and histological grade were significantly associated with TLK2 expression. High TLK2 expression correlated with worse overall survival (OS) [hazard ratio (HR) =1.62, 95% confidence interval (CI): 1.14-2.29, P=0.007], progression-free survival (PFS) (HR =1.88, 95% CI: 1.40-2.52, P<0.001) and disease specific survival (DSS) (HR =1.86, 95% CI: 1.18-2.93, P=0.007) in the training and validation sets. Both univariate and multivariate analyses showed that TLK2 was an independent prognostic factor. GSEA showed that TLK2 was significantly enriched in tumor-related biological processes. TLK2 induced the activation of β-catenin signaling, resulting in sustained tumor growth. Methyl thiazolyl tetrazolium (MTT) and colony formation assays demonstrated that TLK2 could promote hepatocellular carcinoma progression. Furthermore, TLK2 showed a significant association with β-catenin in the Wnt pathway.

Conclusions

TLK2 represents an independent prognostic factor in hepatocellular carcinoma and can promote cancer progression via the β-catenin signaling pathway.

Global Gene Expression Profiling and Bioinformatics Analysis Reveal Downregulated Biomarkers as Potential Indicators for Hepatocellular Carcinoma

Objective: The study aimed to elucidate the significance of CLEC4G, CAMK2β, SLC22A1, CBFA2T3, and STAB2 in the prognosis of hepatocellular carcinoma (HCC) patients and their associated molecular biological characteristics. Additionally, the research sought to identify new potential biomarkers with therapeutic and diagnostic relevance for clinical applications. Methods and Materials: We utilized a publicly available high throughput phosphoproteomics and proteomics data set of HCC to focus on the analysis of 12 downregulated phosphoproteins in HCC. Our approach integrates bioinformatic analysis with pathway analysis, encompassing gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and the construction of a protein-protein interaction (PPI) network. Results: In total, we quantified 11547 phosphorylation sites associated with 4043 phosphoproteins from a cohort of 159 HCC patients. Within this extensive data set, our specific focus was on 19 phosphorylation sites displaying significant downregulation (log2 FC ≤ -2 with p-values < 0.0001). Remarkably, our investigation revealed distinct pathways exhibiting differential regulation across multiple dimensions, including the genomic, transcriptomic, proteomic, and phosphoproteomic levels. These pathways encompass a wide range of critical cellular processes, including cellular component organization, cell cycle control, signaling pathways, transcriptional and translational control, and metabolism. Furthermore, our bioinformatics analysis unveiled noteworthy insights into the subcellular localizations, biological processes, and molecular functions associated with these proteins and phosphoproteins. Within the context of the PPI network, we identified 12 key genes CLEC4G, STAB2, ADH1A, ADH1B, CAMK2B, ADH4, CHGB, PYGL, ADH1C, AKAP12, CBFA2T3, and SLC22A1 as the top highly interconnected hub genes. Conclusions: The findings related to CLEC4G, ADH1B, SLC22A1, CAMK2β, CBFA2T3, and STAB2 indicate their reduced expression in HCC, which is associated with an unfavorable prognosis. Furthermore, the results of KEGG and GO pathway analyses suggest that these genes may impact liver cancer by engaging various targets and pathways, ultimately promoting the progression of hepatocellular carcinoma. These results underscore the significant potential of CLEC4G, ADH1B, SLC22A1, CAMK2β, CBFA2T3, and STAB2 as key contributors to HCC development and advancement. This insight holds promise for identifying therapeutic targets and charting research avenues to enhance our understanding of the intricate molecular mechanisms underlying hepatocellular carcinoma.

Metadherin-driven promotion of cancer stem cell phenotypes and its effect on immunity in hepatocellular carcinoma

In this editorial we provide commentary on the article published by Wang et al, featured in the recent issue of the World Journal of Gastroenterology in 2024. We focus on the metadherin (MTDH), also known as astrocyte elevated gene-1 or lysine rich CEACAM1, and its effects on cancer stem cells (CSCs) and immunity in hepatocellular carcinoma (HCC). HCC is the most common primary liver cancer and one of the leading causes of cancer-related deaths worldwide. Most HCC cases develop in the context of liver cirrhosis. Among the pivotal mechanisms of carcinogenesis are gene mutations, dysregulation of diverse signaling pathways, epigenetic alterations, hepatitis B virus-induced hepatocarcinogenesis, chronic inflammation, impact of tumor microenvironment, oxidative stress. Over the years, extensive research has been conducted on the MTDH role in various tumor pathologies, such as lung, breast, ovarian, gastric, hepatocellular, colorectal, renal carcinoma, neuroblastoma, melanoma, and leukemias. Specifically, its involvement in tumor development processes including transformation, apoptosis evasion, angiogenesis, invasion, and metastasis via multiple signaling pathways. It has been demonstrated that knockdown or knockout of MTDH disrupt tumor development and metastasis. In addition, numerous reports have been carried out regarding the MTDH influence on HCC, demonstrating its role as a predictor of poor prognosis, aggressive tumor phenotypes prone to metastasis and recurrence, and exhibiting significant potential for therapy resistance. Finally, more studies finely investigated the influence of MTDH on CSCs. The CSCs are a small subpopulation of tumor cells that sharing traits with normal stem cells like self-renewal and differentiation abilities, alongside a high plasticity that alters their phenotype. Beyond their presumed role in tumor initiation, they can drive also disease relapse, metastasis, and resistance to chemo and radiotherapy.

Inhibition of the transmembrane transporter ABCB1 overcomes resistance to doxorubicin in patient-derived organoid models of HCC

BACKGROUND

Transarterial chemoembolization is the first-line treatment for intermediate-stage HCC. However, the response rate to transarterial chemoembolization varies, and the molecular mechanisms underlying variable responses are poorly understood. Patient-derived hepatocellular carcinoma organoids (HCCOs) offer a novel platform to investigate the molecular mechanisms underlying doxorubicin resistance.

METHODS

We evaluated the effects of hypoxia and doxorubicin on cell viability and cell cycle distribution in 20 patient-derived HCCO lines. The determinants of doxorubicin response were identified by comparing the transcriptomes of sensitive to resistant HCCOs. Candidate genes were validated by pharmacological inhibition.

RESULTS

Hypoxia reduced the proliferation of HCCOs and increased the number of cells in the G0/G1 phase of the cell cycle, while decreasing the number in the S phase. The IC50s of the doxorubicin response varied widely, from 29nM to >1µM. Doxorubicin and hypoxia did not exhibit synergistic effects but were additive in some HCCOs. Doxorubicin reduced the number of cells in the G0/G1 and S phases and increased the number in the G2 phase under both normoxia and hypoxia. Genes related to drug metabolism and export, most notably ABCB1, were differentially expressed between doxorubicin-resistant and doxorubicin-sensitive HCCOs. Small molecule inhibition of ABCB1 increased intracellular doxorubicin levels and decreased drug tolerance in resistant HCCOs.

CONCLUSIONS

The inhibitory effects of doxorubicin treatment and hypoxia on HCCO proliferation are variable, suggesting an important role of tumor-cell intrinsic properties in doxorubicin resistance. ABCB1 is a determinant of doxorubicin response in HCCOs. Combination treatment of doxorubicin and ABCB1 inhibition may increase the response rate to transarterial chemoembolization.

Integrative multi-omics characterization of hepatocellular carcinoma in Hispanic patients

Background

The incidence and mortality rates of hepatocellular carcinoma (HCC) among Hispanics in the United States are much higher than those of non-Hispanic whites. We conducted comprehensive multi-omics analyses to understand molecular alterations in HCC among Hispanic patients.

Methods

Paired tumor and adjacent non-tumor samples were collected from 31 Hispanic HCC in South Texas (STX-Hispanic) for genomic, transcriptomic, proteomic, and metabolomic profiling. Additionally, serum lipids were profiled in 40 Hispanic and non-Hispanic patients with or without clinically diagnosed HCC.

Results

Exome sequencing revealed high mutation frequencies of AXIN2 and CTNNB1 in STX Hispanic HCCs, suggesting a predominant activation of the Wnt/β-catenin pathway. The TERT promoter mutation frequency was also remarkably high in the Hispanic cohort. Cell cycles and liver functions were identified as positively- and negatively-enriched, respectively, with gene set enrichment analysis. Gene sets representing specific liver metabolic pathways were associated with dysregulation of corresponding metabolites. Negative enrichment of liver adipogenesis and lipid metabolism corroborated with a significant reduction in most lipids in the serum samples of HCC patients. Two HCC subtypes from our Hispanic cohort were identified and validated with the TCGA liver cancer cohort. The subtype with better overall survival showed higher activity of immune and angiogenesis signatures, and lower activity of liver function-related gene signatures. It also had higher levels of immune checkpoint and immune exhaustion markers.

Conclusions

Our study revealed some specific molecular features of Hispanic HCC and potential biomarkers for therapeutic management of HCC and provides a unique resource for studying Hispanic HCC.

Comparison of LIRADS 5 Image Guided Core Biopsy Derived From Formalin Fixed and Frozen Tissue Cores for Radiogenomics and Radioproteomics Analysis in Well, Moderate and Poorly Differentiated Hepatocellular Carcinoma

The aim of this pilot study is to evaluate and compare the quality of the genomics and proteomics data obtained from paired Formalin Fixed Paraffin Embedded (FFPE) and frozen (FF) tissue percutaneous core biopsies of Liver Imaging Reporting and Data System 5 (LIRADS 5) hepatocellular carcinoma (HCC) of varying histological grades. The preliminary data identified differentially expressed proteins and genes in poor, moderate and well differentiated HCC biopsies, with a greater efficacy in fresh frozen samples. The data offered valuable insights into the characteristics and suitability of samples for future studies.

KinPred-RNA-kinase activity inference and cancer type classification using machine learning on RNA-seq data

Kinases as important enzymes can transfer phosphate groups from high-energy and phosphate-donating molecules to specific substrates and play essential roles in various cellular processes. Existing algorithms for kinase activity from phosphorylated proteomics data are often costly, requiring valuable samples. Moreover, methods to extract kinase activities from bulk RNA sequencing data remain undeveloped. In this study, we propose a computational framework KinPred-RNA to derive kinase activities from bulk RNA-sequencing data in cancer samples. KinPred-RNA framework, using the extreme gradient boosting (XGBoost) regression model, outperforms random forest regression, multiple linear regression, and support vector machine regression models in predicting kinase activities from cancer-related RNA sequencing data. Efficient gene signatures from the LINCS-L1000 dataset were used as inputs for KinPred-RNA. The results highlight its potential to be related to biological function. In conclusion, KinPred RNA constitutes a significant advance in cancer research by potentially facilitating the identification of cancer.

Targeting C21orf58 is a Novel Treatment Strategy of Hepatocellular Carcinoma by Disrupting the Formation of JAK2/C21orf58/STAT3 Complex

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death worldwide. Functionally uncharacterized genes are an attractive repository to explore candidate oncogenes. It is demonstrated that C21orf58 displays an oncogenic role in promoting cell growth, tumorigenesis and sorafenib resistance of HCC cells by abnormal activation of STAT3 signaling. Mechanistically, a novel manner to regulate STAT3 signaling that adaptor C21orf58 forms a ternary complex is reveal with N-terminal domain of STAT3 and SH2 domain of JAK2, by which C21orf58 overactivates wild-type STAT3 by facilitating its phosphorylation mediated by JAK2, and hyper-activates of constitutively mutated STAT3 due to preferred binding with C21orf58 and JAK2. Moreover, it is validated that inhibition of C21orf58 with drug alminoprofen, selected by virtual screening, could effectively repress the viability and tumorigenesis of HCC cells. Therefore, it is identified that C21orf58 functions as an oncogenic adaptor, reveal a novel regulatory mechanism of JAK2/STAT3 signaling, explain the cause of abnormal activity of activated mutants of STAT3, and explore the attractive therapeutic potential by targeting C21orf58 in HCC.

Cancer cell genetics shaping of the tumor microenvironment reveals myeloid cell-centric exploitable vulnerabilities in hepatocellular carcinoma

Myeloid cells are abundant and plastic immune cell subsets in the liver, to which pro-tumorigenic, inflammatory and immunosuppressive roles have been assigned in the course of tumorigenesis. Yet several aspects underlying their dynamic alterations in hepatocellular carcinoma (HCC) progression remain elusive, including the impact of distinct genetic mutations in shaping a cancer-permissive tumor microenvironment (TME). Here, in newly generated, clinically-relevant somatic female HCC mouse models, we identify cancer genetics' specific and stage-dependent alterations of the liver TME associated with distinct histopathological and malignant HCC features. Mitogen-activated protein kinase (MAPK)-activated, NrasG12D-driven tumors exhibit a mixed phenotype of prominent inflammation and immunosuppression in a T cell-excluded TME. Mechanistically, we report a NrasG12D cancer cell-driven, MEK-ERK1/2-SP1-dependent GM-CSF secretion enabling the accumulation of immunosuppressive and proinflammatory monocyte-derived Ly6Clow cells. GM-CSF blockade curbs the accumulation of these cells, reduces inflammation, induces cancer cell death and prolongs animal survival. Furthermore, GM-CSF neutralization synergizes with a vascular endothelial growth factor (VEGF) inhibitor to restrain HCC outgrowth. These findings underscore the profound alterations of the myeloid TME consequential to MAPK pathway activation intensity and the potential of GM-CSF inhibition as a myeloid-centric therapy tailored to subsets of HCC patients.

Scutellaria baicalensis Induces Cell Apoptosis and Elicits Mesenchymal-Epithelial Transition to Alleviate Metastatic Hepatocellular Carcinoma via Modulating HSP90β

Hepatocellular carcinoma is one of the most common malignant tumors in the world and shows strong metastatic potential. Current medicine for hepatocellular carcinoma therapy is invalid, while Scutellaria baicalensis Georgi exhibits the pharmaceutical potential to treat liver diseases and liver cancer. Herein, we verified the inhibitory properties and the pivotal molecules regimented by Scutellaria baicalensis on advanced hepatocellular carcinoma. At first, the viability of SK-Hep-1 cells was significantly reduced under treatment of Scutellaria baicalensis extract in a dose-dependent manner without affecting the growth of normal hepatocyte. Scutellaria baicalensis extract application could remarkably cause apoptosis of SK-Hep-1 cells through p53/cytochrome C/poly-ADP ribose polymerase cascades and arrest the cell cycle at the G1/S phase by downregulating cyclin-dependent kinases. Meanwhile, administration of Scutellaria baicalensis extract remarkably attenuated the migration capability as well as suppressed matrix metalloproteinase activity of advanced hepatocellular carcinoma cells. The proteome profiles and network analysis particularly implied that exposure to Scutellaria baicalensis extract downregulated the expression of HSP90β, and the clinical stage of hepatocellular carcinoma is also positively correlated with the HSP90β level. Combined treatment of Scutellaria baicalensis extract and HSP90β siRNAs could markedly enhance the ubiquitination activity and the degradation of vimentin to subsequently inhibit the metastatic property of SK-Hep-1 cells. Moreover, application of Scutellaria baicalensis extract and HSP90β siRNAs depleted phosphorylation of AKT, which stimulated the expression of p53 and consecutively triggered cell apoptosis. These findings suggest that HSP90β may be a prospective target for the effective therapy of advanced hepatocellular carcinoma via accelerating apoptosis of hepatocellular carcinoma cells and eliciting mesenchymal-epithelial transition with the administration of Scutellaria baicalensis extract.

WNT/β-catenin signaling in hepatocellular carcinoma: The aberrant activation, pathogenic roles, and therapeutic opportunities

Hepatocellular carcinoma (HCC) is a liver cancer, highly heterogeneous both at the histopathological and molecular levels. It arises from hepatocytes as the result of the accumulation of numerous genomic alterations in various signaling pathways, including canonical WNT/β-catenin, AKT/mTOR, MAPK pathways as well as signaling associated with telomere maintenance, p53/cell cycle regulation, epigenetic modifiers, and oxidative stress. The role of WNT/β-catenin signaling in liver homeostasis and regeneration is well established, whereas in development and progression of HCC is extensively studied. Herein, we review recent advances in our understanding of how WNT/β-catenin signaling facilitates the HCC development, acquisition of stemness features, metastasis, and resistance to treatment. We outline genetic and epigenetic alterations that lead to activated WNT/β-catenin signaling in HCC. We discuss the pivotal roles of CTNNB1 mutations, aberrantly expressed non-coding RNAs and complexity of crosstalk between WNT/β-catenin signaling and other signaling pathways as challenging or advantageous aspects of therapy development and molecular stratification of HCC patients for treatment.