A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients

Validation of Two Prognostic Gene Scores in Patients Undergoing Liver Resection for Hepatocellular Carcinoma

Background/Aims

Several prognostic gene signatures have been proposed as predictors of the prognosis of hepatocellular carcinoma (HCC), yet none are implemented in the clinical setting. We aimed to validate two gene scores previously derived from European cohorts.

Methods

The patients who underwent liver resection for HCC at Copenhagen University Hospital, Rigshospitalet from 2014 to 2018 were included. RNA sequencing determined the expression of genes in the '5-gene score' (HN1, RAN, RAMP3, KRT19, TAF9B) and 'HepatoPredict' (CLU, DPT, SPRY2, CAPSN1). Univariable Cox regression assessed associations with overall and disease-free survival. These parameters were also analyzed in the The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) (n = 359) and National Institute of Health (NIH) (n = 178) cohorts.

Results

Among 51 patients (88% male), 59% had no underlying liver disease and 25% had cirrhosis. No individual genes were significantly associated with overall survival in the Danish cohort. In the TCGA-LIHC cohort, CLU was linked to better overall survival, and in the NIH cohort, high expression of SPRY2 was associated with poorer overall survival. In the TCGA-LIHC cohort, HN1, RAN, and TAF9B were associated with poorer overall survival, while RAMP3 was linked to better overall survival. No genes were associated with disease-free survival.

Conclusion

Few individual genes significantly predicted survival in the larger cohorts, and none in the Danish cohort. However, the clinical implication of this needs further investigation.

Impaired mitochondrial degradation of CHCHD2 promotes metabolic dysfunction-associated steatohepatitis-related hepatocellular carcinoma by upregulating VEGFA

Metabolic dysfunction-associated steatohepatitis (MASH) is the fastest-growing cause of liver cancer. The liver microenvironment of patients with MASH supports the development of hepatocellular carcinoma (HCC). Coiled-coil-helix-coiled-coil-helix domain-containing 2 (CHCHD2), which is located in both the mitochondria and nucleus, is increased in MASH liver. Its role in the development of MASH-HCC remain unknown. In this study, we found CHCHD2 protein levels were elevated in both tumor and para-tumor tissues of patients with MASH-HCC and diethylnitrosamine- and high-fat diet-induced MASH-HCC mice. Chchd2-knockout mice were generated. CHCHD2 was overexpressed in hepatocytes using AAV with TBG promoter. Chchd2 knockout inhibited the progression of MASH-HCC in mice. CHCHD2 protein-targeted ChIP-sequencing data revealed that CHCHD2 target genes encoding secretory proteins were enriched in cancer pathways. Among these genes, vascular endothelial growth factor A (VEGFA) level increased in CHCHD2-overexpressing livers and hepatocytes. Chchd2 knockdown reduced palmitate-induced VEGFA expression. Palmitate-treated hepatocyte increased the angiogenic activity of endothelial cells in a paracrine manner, and this was suppressed by Chchd2 knockdown in hepatocytes. CHCHD2-overexpressing hepatocytes promoted the angiogenic activity of endothelial cells. We futher employed an orthotopic murine model of HCC to demonstrate that elevated CHCHD2 protein levels in para-tumor tissues support HCC growth. In addition, we found that the degradation of CHCHD2 was primarily mediated by mitochondrial protease ClpXP, which was repressed in the MASH liver. In conclusion, the mitochondrial degradation of CHCHD2 is impaired in MASH, and elevated CHCHD2 levels in hepatocytes promote VEGFA transcription and support the growth of HCC.

RACGAP1 and MKI67 are potential prognostic biomarker in hepatocellular carcinoma caused by HBV/HCV via lactylation

Introduction

Hepatocellular carcinoma (HCC) is recognized as the prime and lethal form of liver cancer caused by the hepatitis B virus (HBV) and hepatitis C virus (HCV) globally. Lactate is an end product of glycolysis that influences epigenetic expression through histone lactylation. While MKI67 and RACGAP1 play crucial roles in HBV- and HCV-related HCC. However, the role of lactylation-related genes (LRGs) effects in this context remains unclear. This study innovatively explored the role of LRGs in HBV/HCV-associated HCC, identifying novel biomarkers for diagnosis and prognosis.

Methods

The present study used various online databases for analysis, and the findings were validated via immunohistochemical (IHC) analysis of HCC patient samples (n=60).

Results

We identified six signature LRGs (ALB, G6PD, HMGA1, MKI67, RACGAP1, and RFC4) possess prognostic potential, correlation with immune infiltration, and lactylation-related pathways, providing novel insights into tumor microenvironment (TME) of HCC. Moreover, MKI67 and RACGAP1 were significantly associated with HBV- and HCV-related HCC. IHC confirmed these findings, with high expression of MKI67 and RACGAP1 was significantly linked with HBV/HCV-associated HCC compared to non-viral HCC. The expression is also significantly associated with key clinical variables.

Conclusion

Our results suggest that MKI67 and RACGAP1 could serve as promising biomarkers for detecting and predicting HCC caused by HBV/HCV via lactylation, opening a new direction for immune-targeted therapies.

Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer and a leading cause of cancer-related deaths globally. The tumour microenvironment (TME) influences treatment response and prognosis, yet its heterogeneity remains unclear.

METHODS

The unsupervised machine learning methods- agglomerative hierarchical clustering, Multi-Omics Factor Analysis with K-means++, and an autoencoder with K-means++ - stratified patients using microarray data from HCC samples. Immune deconvolution algorithms estimated the proportions of infiltrating immune cells across identified clusters.

RESULTS

Thirteen genes were found to influence HCC subtyping in both primary and validation datasets, with three genes-TOP2A, DCN, and MT1E-showing significant associations with survival and recurrence. DCN, a known tumour suppressor, was significant across datasets and associated with improved survival, potentially by modulating the TME and promoting an anti-tumour immune response.

CONCLUSIONS

The discovery of the 13 conserved genes is an important step toward understanding HCC heterogeneity and the TME, potentially leading to the identification of more reliable biomarkers and therapeutic targets. We have stratified and validated the liver cancer populations. The findings suggest further research is needed to explore additional factors influencing the TME beyond gene expression, such as tumour microbiome and stromal cell interactions.

USP22 promotes the proliferation and Sorafenib resistance of hepatocellular carcinoma cells via its deubiquitinase activity

BACKGROUND

Hepatocellular carcinoma remains one of the most lethal cancers, characterized by poor prognosis and low life expectancy. Unfortunately, there are very few molecular therapeutic options available for it. Sorafenib is a current standard first-line treatment for advanced hepatocellular carcinoma, however, drug resistance significantly limits its therapeutic efficacy.

METHODS

Ubiquitin-specific protease 22 (USP22) expression level and its prognostic significance in hepatocellular carcinoma were analyzed using The Cancer Genome Atlas (TCGA) database. A series of cellular experiments related to cell proliferation and ferroptosis, and mouse tumor-bearing experiments were performed to investigate the role of USP22 in hepatocellular carcinoma cell growth and Sorafenib resistance. Flag affinity purification coupled with mass spectrometry, co-immunoprecipitation, and ubiquitination assays were conducted to identify direct substrates of USP22. Spike-in chromatin-immunoprecipitation (ChIP)-seq, RNA-seq, and ChIP assays were employed to explore the transcriptional substrates of USP22 as an H2BK120ub deubiquitinase.

RESULTS

Analysis of TCGA database reveals that USP22 is highly expressed in hepatocellular carcinoma tissues, which is closely associated with poor patient prognosis. Our data further indicates that USP22 promotes the proliferation of hepatocellular carcinoma cells via deubiquitinating and stabilizing cyclin-dependent kinase 11B (CDK11B). Additionally, USP22 acts as a novel inducer of Sorafenib resistance and suppresses Sorafenib-triggered ferroptosis in hepatocellular carcinoma cells. It reduces the transcription of transferrin receptor (TFRC) by decreasing H2BK120ub occupancy at TFRC transcription start site (TSS) downstream region, thereby inhibiting ferroptosis upon Sorafenib treatment. Finally, animal experiments confirm the role of USP22 in promoting hepatocellular carcinoma cell growth and Sorafenib resistance in vivo. Taken together, this study demonstrates that USP22 promotes hepatocellular carcinoma growth and inhibits Sorafenib-induced ferroptosis by deubiquitinating non-histone substrate CDK11B and histone H2B, respectively.

CONCLUSIONS

Our findings suggest USP22 as a promising prognostic biomarker and therapeutic target for hepatocellular carcinoma patients, particularly those with Sorafenib resistance.

KEY POINTS

USP22 promotes the proliferation of hepatocellular carcinoma cells by deubiquitinating and stabilizing cyclin-dependent kinase CDK11B. USP22 enhances Sorafenib resistance of hepatocellular carcinoma cells by inhibiting ferroptosis through the USP22/H2BK120ub/TFRC axis.

The molecular characteristics of DNA damage and repair related to P53 mutation for predicting the recurrence and immunotherapy response in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths globally, owing to its high recurrence rate of 50 to 70% within five years. Despite known associations of certain DNA damage and repair (DDR) genes with tumor recurrence and drug resistance, a comprehensive understanding of DDR pathways' role in predicting HCC recurrence and therapeutic responses remains elusive. Addressing this gap could offer significant advancements in prognostic and therapeutic strategies for HCC. This study used 769 RNA sequencing samples from public datasets and 53 samples from Xiangya Hospital for DDR model training and validation. It came out that DDR pathways were significantly enriched in samples with P53 mutations. Next, among the 173 combinations of algorithms and parameters, CoxBoost + RSF, Lasso [fold = 10] + RSF, and Lasso [fold = 50] + RSF demonstrated the best performance. The average AUC values of 1 to 5 years and the average concordance index (C-index) value were around 0.7. The risk scores were increased in tumors with recurrence, P53 mutation, and higher TNM stages. High-risk groups, characterized by enriched DDR pathways, exhibited lower CD8 + T cell infiltration and poorer responses to immunotherapy using atezolizumab and bevacizumab, emphasizing the potential of DDR signatures as valuable prognostic and therapeutic biomarkers. In conclusion, the DDR signatures associated with P53 mutations can predict recurrence and therapeutic response in HCC, highlighting their potential as prognostic and therapeutic biomarkers.

AI-based phenotyping of hepatic fiber morphology to inform molecular alterations in metabolic dysfunction-associated steatotic liver disease

BACKGROUND AND AIMS

Hepatic fiber morphology may significantly enhance our understanding of molecular alterations in metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to comprehensively characterize hepatic fiber morphological phenotypes in MASLD and their associated molecular alterations using multilayer omics analyses.

APPROACH AND RESULTS

To quantify the morphological phenotypes of hepatic fibers, the artificial intelligence-based FibroNest algorithm (PharmaNest) was applied to 94 MASLD-affected liver biopsies, among which 12 (13%) had concurrent HCC. FibroNest identified 327 fiber phenotypes that were summarized into 8 major principal components, named FibroPC1-8. Next, molecular alterations captured by morphological fiber phenotypes were evaluated by comparison with genome-wide transcriptomics of paired liver samples. Pathway analyses revealed that FibroPCs more sensitively captured MASLD-related molecular alterations, such as upregulation of interleukin-6 and susceptibility to resmetirom, compared with the histological fibrosis stage. Among them, FibroPC4, which reflects reticular fibers, was associated with a gene signature predictive of incident HCC from MASLD. Furthermore, we used a spatial single-cell transcriptome, CosMx, to reveal the cell-cell interactions driving MASLD pathogenesis, as captured by FibroPC4. CosMx revealed that the FibroPC4-rich microenvironment contains HCC-promoting HSCs located adjacent to periportal endothelial cells. Neighboring cell analyses suggested that the HCC-promoting phenotype of HSCs was acquired by insulin growth factor-binding protein 7 secreted from senescent periportal endothelial cells. Consistently, in vitro experiments showed that insulin growth factor-binding protein 7 transformed HSCs into an HCC-promoting phenotype.

CONCLUSIONS

Hepatic morphological fiber phenotyping can reveal the disease progression and underlying mechanisms of MASLD.

The glycolytic characteristics of hepatocellular carcinoma and its interaction with the microenvironment: a comprehensive omics study

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignant tumor characterized by a high recurrence rate and poor prognosis. This study aimed to identify glycolysis-related prognostic markers and immunological abnormalities in patients with HCC.

METHODS

We collected samples from cancerous and adjacent non-cancerous tissues for transcriptomic, metabolomic, and 16 S rRNA sequencing analyses. Glycolysis-related prognostic markers were identified by integrating public data from The Cancer Genome Atlas, GSE14520, and GSE76427 datasets. Additionally, single-cell sequencing data (GSE202642) were used to analyze the significantly infiltrated cellular subpopulations in HCC and investigate the expression of prognostic markers across different cell types. Spatial transcriptomics and mass cytometry (CyTOF) data were used to examine the expression differences in immune cells across tumor, peritumoral, and control tissues. Key prognostic markers were validated using reverse transcription-quantitative polymerase chain reaction, western blotting, and immunohistochemistry.

RESULTS

Differentially expressed genes (DEGs) between HCC and control tissues were primarily clustered in cell cycle and metabolic pathways, particularly in the glycolysis pathway. Metabolomic analysis identified 175 differentially expressed metabolites that were mainly enriched in digestive and amino acid metabolism pathways. 16 S rRNA analysis revealed a significant increase in the abundance of Aenigmarchaeota and a decrease in the abundance of Proteobacteria in HCC tissues. The former was positively associated with glycolysis, whereas the latter showed a negative association. Through public data integration, 17 glycolysis-related DEGs were identified and 101 predictive models were constructed using machine learning. The StepCox[both] + random survival forest model using AGL, G6PD, GOT2, and KIF20A exhibited the best diagnostic performance among the three datasets. Single-cell RNA sequencing indicated significant infiltration of CD8 + Tex, CD8 + T, CD8 + Trm, and epithelial cells in HCC tissues. AGL, G6PD, GOT2, and KIF20A were highly expressed in CD8 + Tex cells, CD8 + Trm cells, macrophages, and monocytes, respectively. Spatial transcriptomics and CyTOF analyses showed greater infiltration of CD8 + Tex and CD8 + Trm cells in tumor tissues than in controls. Molecular assays further confirmed that G6PD and KIF20A expression levels were significantly higher, whereas AGL and GOT2 expression levels were lower, in HCC tissues than in control tissues.

CONCLUSION

Through integrative multi-omics analysis, we identified glycolysis-related prognostic markers with distinct expression profiles across immune cell subsets in HCC. Our findings identify potential biomarkers and therapeutic targets for the diagnosis and treatment of HCC.

ARL8B regulates lysosomal function and predicts poor prognosis in hepatocellular carcinoma

Adenosine 5'-diphosphate ribosylation factor-like 8B (ARL8B), a small GTPase, is involved in lysosome motility. Our study investigates the role of ARL8B in hepatocellular carcinoma (HCC) using in vitro and in vivo experiments, bioinformatics, and clinical data. We found that ARL8B expression is abnormally elevated in HCC and correlates with poor prognosis. ARL8B knockdown triggered lysosomal dysfunction-manifesting as abnormal morphology, decreased pH, reduced hydrolase activity, and impaired autophagic degradation-which subsequently led to cell cycle arrest and reduced cell viability. Additionally, tumors with high ARL8B expression (ARL8Bhigh) exhibited notable differences in tumor microenvironment composition compared to those with low ARL8B expression (ARL8Blow). ARL8Bhigh HCCs had significantly increased infiltration of NFKBIZ+/HIF1A+ and VEGFA+/SPP1+ neutrophils. EcoTyper analysis indicated that ARL8Bhigh HCCs had a lower proportion of carcinoma ecotype 6, a cellular ecosystem common in normal tissues but rare in tumors. Bioinformatics and real-world analysis showed a positive correlation between ARL8B and PD-L1 expression. Patients with high ARL8B expression exhibited increased sensitivity to sorafenib and immune checkpoint blockade therapy. In conclusion, our findings identify ARL8B as a key lysosomal regulator associated with tumor microenvironment composition in HCC, suggesting its potential as both a therapeutic target and a biomarker for predicting treatment response.

Natural Killer Cell-Associated Radiogenomics Model for Hepatocellular Carcinoma: Integrating CD2 and Enhanced CT-Derived Radiomics Signatures

RATIONALE AND OBJECTIVES

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality. Natural Killer (NK) cells play a crucial role in immune defense against HCC, but their activity is often impaired by the tumor microenvironment (TME). This study aims to integrate radiomics and transcriptomics to develop a prognostic model linking NK cell characteristics to clinical outcomes in HCC.

METHODS

Transcriptomic data from five cohorts (734 HCC patients) from the Gene Expression Omnibus and The Cancer Genome Atlas databases were analyzed using the Microenvironment Cell Populations-counter algorithm. NK cell-related prognostic biomarkers were identified via weighted gene co-expression network analysis and LASSO-Cox regression. Radiomics models were established using CT imaging features from 239 patients in three datasets from The Cancer Imaging Archive and Shanghai East Hospital. HCC radiogenomic subtypes were proposed by integrating genetic biomarkers and radiomics models.

RESULTS

CD2 expression was identified as an independent NK cell-related prognostic biomarker, with a positive impact on prognosis and a strong correlation with NK cell-associated biological processes in HCC. A robust radiomics model was constructed, and the integration of CD2 expression with radioscore identified potential radiogenomic subtypes of HCC.

CONCLUSION

Radiomics has potential to link TME immune phenotypes with HCC prognosis. CD2 is a key biomarker connecting NK cells with radiomic features, offering a new classification of HCC into radiogenomic subtypes. This approach supports the use of radiogenomics in personalized HCC treatment.

Identification of a Cancer Stem Cell-Related Gene Signature in Hepatocellular Carcinoma Based on Single-Cell RNA-Seq and Bulk RNA-Seq Analysis

Cancer stem cells (CSCs) are a heterogeneous group of tumor cells that play a significant role in tumorigenesis, therapeutic resistance, and recurrence in liver hepatocellular carcinoma (LIHC). This study combines clinical data sets from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) with bulk RNA sequencing data. This study also features the GSE156625 single-cell RNA sequencing (scRNA) data set from the GEO to explore the prognostic significance of CSC biomarkers (BCSCs) in LIHC. In this research, we introduce a developed prognostic risk model that relies on nine specific BCSCs, including ADM, CCL5, CD274, DLGAP5, HOXD9, IGF1, S100A9, SOCS2, and TNFRSF11B. It was found that high-risk patients experience shorter overall survival rates when compared to low-risk patients. Additionally, the study characterized the composition of immune cells within the tumor microenvironment (TME) and revealed significant variations in gene-expression levels and mutation rates between different risk groups. The model suggests that liver cancer progression might be driven by immune evasion independent of PD-L1 and highlights the potential of the low-risk BCSC group being sensitive to various treatments. Our findings offer a promising foundation for personalized LIHC therapy and highlight the need for further experimental validation of the roles of these CSCs in disease progression.

Integrated Analysis of Bulk and Single-Cell RNA Sequencing Data Reveal a Novel Prognostic Signature of Combining Cuproptosis- and Ferroptosis-Related Genes in Hepatocellular Carcinoma

As a common malignancy, hepatocellular carcinoma (HCC) proliferation and metastasis could be promoted by ferroptosis and cuproptosis. In this study, we screened out the differentially expressed cuproptosis- and ferroptosis-related genes (CFRGs) and identified the 17 informative prognosis-associated genes. A CFRG scoring model was constructed based on the subtypes identified by consensus clustering analysis and principal component analysis (PCA). Furthermore, the immune profile, expression of immune checkpoint genes (ICGs) and drug susceptibility were also compared between the two CFRG score groups. The results showed that patients with a high CFRG score had higher survival probabilities. The correlation analysis suggested that CFRG scores were negatively correlated with activated CD4.T.cell. The expression patterns of thirty ICGs and the half-maximal inhibitory concentration (IC50) values of 128 drugs displayed significant differences between the two CFRG score groups. A statistically significant difference in the efficacy of sorafenib was found between the two CFRG score groups. Moreover, based on multivariate COX regression analysis and weighted gene co-expression network analysis (WGCNA), we screened DLAT and SLC2A1 as signature genes. Molecular docking analysis revealed that DLAT and SLC2A1 had a strong binding affinity toward camptothecin, rapamycin, dactolisib, and luminespib. The correlation between the CFRG score and single-cell characteristics was further explored. The study depended on our understanding of the biological function of CFRGs in HCC and provided new insights for developing treatment strategies.

Pyruvate metabolism enzyme DLAT promotes tumorigenesis by suppressing leucine catabolism

Pyruvate and branched-chain amino acid (BCAA) metabolism are pivotal pathways in tumor progression, yet the intricate interplay between them and its implications for tumor progression remain elusive. Our research reveals that dihydrolipoamide S-acetyltransferase (DLAT), a pyruvate metabolism enzyme, promotes leucine accumulation and sustains mammalian target of rapamycin (mTOR) complex activation in hepatocellular carcinoma (HCC). Mechanistically, DLAT directly acetylates the K109 residue of AU RNA-binding methylglutaconyl-coenzyme A (CoA) hydratase (AUH), a critical enzyme in leucine catabolism, inhibiting its activity and leading to leucine accumulation. Notably, DLAT upregulation correlates with poor prognosis in patients with HCC. Therefore, we developed an AUHK109R-mRNA lipid nanoparticles (LNPs) therapeutic strategy, which effectively inhibits tumor growth by restoring leucine catabolism and inhibiting mTOR activation in vivo. In summary, our findings uncover DLAT's unexpected role as an acetyltransferase for AUH, suppressing leucine catabolism. Restoring leucine catabolism with AUHK109R-mRNA LNP effectively inhibits HCC development, highlighting a novel direction for cancer research.

Multi-omics analysis revealed the novel role of NQO1 in microenvironment, prognosis and immunotherapy of hepatocellular carcinoma

NAD(P)H dehydrogenase quinone 1 (NQO1) is overexpressed in various cancers and is strongly associated with an immunosuppressive microenvironment and poor prognosis. In this study, we explored the role of NQO1 in the microenvironment, prognosis and immunotherapy of Hepatocellular carcinoma (HCC) using multi-omics analysis and machine learning. The results revealed that NQO1 was significantly overexpressed in HCC cells. NQO1+HCC cells were correlated with poor prognosis and facilitated tumor-associated macrophages (TAMs) polarization to M2 macrophages. We identified core NQO1-related genes (NRGs) and developed the NRGs-related risk-scores in hepatocellular carcinoma (NRSHC). The comprehensive nomogram integrating NRSHC, age, and pathological tumor-node-metastasis (pTNM) Stage achieved an area under the curve (AUC) above 0.7, demonstrating its accuracy in predicting survival outcomes and immunotherapy responses of HCC patients. High-risk patients exhibited worse prognoses but greater sensitivity to immunotherapy. Additionally, a web-based prediction tool was designed to enhance clinical utility. In conclusion, NQO1 may play a critical role in M2 polarization and accelerates HCC progression. The NRSHC model and accompanying tools offer valuable insights for personalized HCC treatment.

VDAC2 and Bak scarcity in liver mitochondria enables targeting hepatocarcinoma while sparing hepatocytes

Differences between normal tissues and invading tumors that allow tumor targeting while saving normal tissue are much sought after. Here we show that scarcity of VDAC2, and the consequent lack of Bak recruitment to mitochondria, renders hepatocyte mitochondria resistant to permeabilization by truncated Bid (tBid), a Bcl-2 Homology 3 (BH3)-only, Bcl-2 family protein. Increased VDAC2 and Bak is found in most human liver cancers and mitochondria from tumors and hepatic cancer cell lines exhibit VDAC2- and Bak-dependent tBid sensitivity. Exploring potential therapeutic targeting, we find that combinations of activators of the tBid pathway with inhibitors of the Bcl-2 family proteins that suppress Bak activation enhance VDAC2-dependent death of hepatocarcinoma cells with little effect on normal hepatocytes. Furthermore, in vivo, combination of S63845, a selective Mcl-1 inhibitor, with tumor-nectrosis factor-related, apoptosis-induncing ligand (TRAIL) peptide reduces tumor growth, but only in tumors expressing VDAC2. Thus, we describe mitochondrial molecular fingerprint that discriminates liver from hepatocarcinoma and allows sparing normal tissue while targeting tumors.

Cytochrome P450 2E1 inhibitor Q11 is effective on hepatocellular carcinoma by promoting peritumor neutrophil chemotaxis

Current studies found that the peritumoral tissue of hepatocellular carcinoma (HCC) may be different from normal liver tissue based on proteomics, and related to progression, recurrence and metastasis of HCC. Our previous study proposed "peritumor microenvironment (PME)" to summarize the influence of peritumor tissue on occurrence and progression of HCC. Peritumor CYP2E1 activity was significantly elevated in HCC, and related to occurrence and progression of HCC. However, the effectiveness and mechanism of inhibiting CYP2E1 against HCC remain unclear. In this study, by integrating the advantages of proteomics and transcriptomics, we reanalyzed the various influencing factors in PME. Although there were large differences in the occurrence and progression, the immunity and inflammation still played crucial roles. Peritumor neutrophil were "pro-tumor" phenotype in the stage of progression, while it showed cytotoxicity for tumor cell in the occurrence stage. CYP2E1 activity is associated with peritumor neutrophil infiltration and occurrence of HCC. CYP2E1 inhibitor Q11 showed anti-tumor effects in an orthotopic HCC mouse model by promoting secretion of chemokines and infiltration of neutrophils in peritumor tissue. Overall, these findings provided a reasonable mechanism of anti-tumor effects of CYP2E1 inhibitors, which may be a new strategy for the prevention and treatment of HCC.

Hamid SS. Multiomics in silico analysis identifies TM4SF4 as a cell surface target in hepatocellular carcinoma

The clinical application of cellular immunotherapy in hepatocellular carcinoma (HCC) is impeded by the lack of a cell surface target frequently expressed in HCC cells and with minimal presence in normal tissues to reduce on-target, off-tumor toxicity. To address this, an in silico multomics analysis was conducted to identify an optimal therapeutic target in HCC. A longlist of genes (n = 12,948) expressed in HCCs according to The Human Protein Atlas database were examined. Eight genes were shortlisted to identify one with the highest expression in HCCs, without being shed into circulation, and with restrictive expression profile in other normal human tissues. A total of eight genes were shortlisted and subsequently ranked according to the combination of their transcript and protein expression levels in HCC cases (n = 791) derived from four independent datasets. TM4SF4 was the top-ranked target with the highest expression in HCCs. TM4SF4 showed more favorable expression profile with significantly lower expression in normal human tissues but more highly expressed in HCC compared with seven other common HCC therapeutic targets. Furthermore, scRNA-seq and immunohistochemistry datasets showed that TM4SF4 was absent in immune cell populations but highly expressed in the bile duct canaliculi of hepatocytes, regions inaccessible to immune cells. In scRNA-seq dataset of HCCs, TM4SF4 expression was positively associated with mitochondrial components and oxidative phosphorylation Gene Ontologies in HCC cells (n = 15,787 cells), suggesting its potential roles in mitochondrial-mediated oncogenic effects in HCC. Taken together, TM4SF4 is proposed as a promising cell surface target in HCC due to its high expression in HCC cells with restricted expression profile in non-cancerous tissues, and association with HCC oncogenic pathways.

Integration of single-cell and spatial transcriptomics reveals fibroblast subtypes in hepatocellular carcinoma: spatial distribution, differentiation trajectories, and therapeutic potential

BACKGROUND

Cancer-associated fibroblasts (CAFs) are key components of the hepatocellular carcinoma (HCC) tumor microenvironment (TME). regulating tumor proliferation, metastasis, therapy resistance, immune evasion via diverse mechanisms. A deeper understanding of the l diversity of CAFs is essential for predicting patient prognosis and guiding treatment strategies.

METHODS

We examined the diversity of CAFs in HCC by integrating single-cell, bulk, and spatial transcriptome analyses.

RESULTS

Using a training cohort of 88 HCC single-cell RNA sequencing (scRNA-seq) samples and a validation cohort of 94 samples, encompassing over 1.2 million cells, we classified three fibroblast subpopulations in HCC: HLA-DRB1 + CAF, MMP11 + CAF, and VEGFA + CAF based on highly expressed genes of which, which are primarily located in normal tissue, tumor boundaries, and tumor interiors, respectively. Cell trajectory analysis revealed that VEGFA + CAFs are at the terminal stage of differentiation, which, notably, is tumor-specific. VEGFA + CAFs were significantly associated with patient survival, and the hypoxic microenvironment was found to be a major factor inducing VEGFA + CAFs. Through cellular communication with capillary endothelial cells (CapECs), VEGFA + CAFs promoted intra-tumoral angiogenesis, facilitating tumor progression and metastasis. Additionally, a machine learning model developed using high-expression genes from VEGFA + CAFs demonstrated high accuracy in predicting prognosis and sorafenib response in HCC patients.

CONCLUSIONS

We characterized three fibroblast subpopulations in HCC and revealed their distinct spatial distributions within the tumor. VEGFA + CAFs, which was induced by hypoxic TME, were associated with poorer prognosis, as they promote tumor angiogenesis through cellular communication with CapECs. Our findings provide novel insights and pave the way for individualized therapy in HCC patients.

Statistical and machine learning based platform-independent key genes identification for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most prevalent and deadly form of liver cancer, and its mortality rate is gradually increasing worldwide. Existing studies used genetic datasets, taken from various platforms, but focused only on common differentially expressed genes (DEGs) across platforms. Consequently, these studies may missed some important genes in the investigation of HCC. To solve these problems, we have taken datasets from multiple platforms and designed a statistical and machine learning-based system to determine platform-independent key genes (KGs) for HCC patients. DEGs were determined from each dataset using limma. Individual combined DEGs (icDEGs) were identified from each platform and then determined grand combined DEGs (gcDEGs) from icDEGs of all platforms. Differentially expressed discriminative genes (DEDGs) was determined based on the classification accuracy using Support vector machine. We constructed PPI network on DEDGs and identified hub genes using MCC. This study determined the optimal modules using the MCODE scores of the PPI network and selected their gene combinations. We combined all genes, obtained from previous studies to form metadata, known as meta-hub genes. Finally, six KGs (CDC20, TOP2A, CENPF, DLGAP5, UBE2C, and RACGAP1) were selected by intersecting the overlapping hub genes, meta-hub genes, and hub module genes. The discriminative power of six KGs and their prognostic potentiality were evaluated using AUC and survival analysis.

Single-cell landscape of dynamic changes in CD8+ T cells, CD4+ T cells and exhausted T cells in hepatocellular carcinoma

Hepatocellular carcinoma has a high incidence and poor prognosis. In this study, we investigated the value of T-cell-related genes in prognosis by single-cell sequencing data in hepatocellular carcinoma. Twelve cases of hepatocellular carcinoma single-cell sequencing were included in the study. The high dimensional weighted gene co-expression network analysis (hdWGCNA) was used to identify gene modules associated with CD4+ T cells, CD8+ T cells and exhausted T cells. Altered signaling pathway activity in exhausted T cells was uncovered by the AUCell algorithm. xCELL, TIMER, QUANTISEQ, CIBERSORT and CIBERSORT-abs were performed to explore immune cell infiltration. Immune checkpoint inhibitor genes and TIDE methods were used to predict immunotherapy response. Finally, immunohistochemistry and real-time PCR were used to verify gene expression. The hdWGCNA algorithm identified 40 genes strongly associated with CD4+ T cells, CD8+ T cells and exhausted T cells. Seven genes were finally selected for transcriptome data modeling. The results of the three independent datasets suggested that the model had strong prognostic value. Model genes were critical factors influencing CD4+ T cell and CD8+ T cell infiltration in patients. The efficacy of PD-1 immunotherapy was higher in patients belonging to the low-risk group. Alterations in signaling pathways' activity within exhausted T cells were crucial factors contributing to the decline in immune function. Differential expression of seven genes in CD8+ T cells, CD4+ T cells and exhausted T cells were key targets for improving immunotherapy response in HCC.

SERPING1 Reduces Cell Migration via ERK-MMP2-MMP-9 Cascade in Sorafenib- Resistant Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignant tumor, and it ranks 2nd in terms of mortality rate among all malignancies in Taiwan. Sorafenib is a multiple tyrosine kinase inhibitor that suppresses tumor cell proliferation and angiogenesis around tumors via different pathways. However, the survival outcome of advanced HCC patients treated with sorafenib is still unsatisfactory. Unfortunately, there are no clinically applicable biomarkers to predict sorafenib therapeutic efficiency in HCC thus far. We found that serpin peptidase inhibitor, clade G, member 1 (SERPING1) is highly associated with overall and recurrence-free survival rates in HCC patients and is also highly correlated with several clinical parameters. SERPING1 expression was increased with sorafenib in both the HCC cell extract and conditioned medium, which was also observed in sorafenib-resistant HepG2 and Huh7 cells. Sorafenib decreased cell viability and migration, which was similar to the effect of SERPING1 in HCC progression. Moreover, sorafenib inhibited both MMP-2 and MMP-9 activity and enhanced the expression of p-ERK in HCC cells. In summary, sorafenib reduces HCC cancer progression might through the p-ERK-MMP-2-MMP-9 cascade via upregulation of SERPING1. In the present study, the roles and molecular mechanisms of SERPING1 and its value as a marker for predicting sorafenib resistance and progression in HCC patients were examined. The results of the present study provide a deep understanding of the roles of SERPING1 in HCC sorafenib resistance, which can be applied to develop early diagnosis and prognosis evaluation methods and establish novel therapeutic targets for specifically treating HCC.

ANGPTL3 overcomes sorafenib resistance via suppression of SNAI1 and CPT1A in liver cancer

Liver cancer, encompassing hepatocellular carcinoma (HCC) and hepatoblastoma, the latter of which primarily occurs in early childhood, is the most common malignant tumor arising from liver and is responsible for a significant number of cancer-related deaths worldwide. Targeted drugs have been used for anti-liver cancer treatment in the advanced stage, while their efficacy is greatly compromised by development of drug resistance. Drug resistance is a complicated process regulated by intrinsic and extrinsic signals and has been associated with poorer prognosis in cancer patients. In the current study, online available dataset analysis uncovered that angiopoietin-like protein 3 (ANGPTL3) manifested lower expression in sorafenib-resistant liver cancer cell lines. Additionally, ANGPTL3 was downregulated in HCC tissues, with its expression positively correlated with good prognosis. Functionally, ectopic expression of ANGPTL3 re-sensitized sorafenib-resistant cells, enhancing the sorafenib-induced reduction in cell viability and migration by suppressing zinc finger protein SNAI1 (SNAI1) expression and the protein stability of carnitine O-palmitoyltransferase 1, liver isoform (CPT1A). Clinical correlation analysis revealed that ANGPTL3 was negatively associated with SNAI1 expression. In conclusion, we identify a novel association between ANGPTL3, SNAI1 and CPT1A on sorafenib therapeutic response. Targeting ANGPTL3/SNAI1/CPT1A axis may serve as a therapeutic approach to improve prognosis of liver cancer patients with sorafenib resistance.

ADARp110 promotes hepatocellular carcinoma progression via stabilization of CD24 mRNA

ADAR is highly expressed and correlated with poor prognosis in hepatocellular carcinoma (HCC), yet the role of its constitutive isoform ADARp110 in tumorigenesis remains elusive. We investigated the role of ADARp110 in HCC and underlying mechanisms using clinical samples, a hepatocyte-specific Adarp110 knock-in mouse model, and engineered cell lines. ADARp110 is overexpressed and associated with poor survival in both human and mouse HCC. It creates an immunosuppressive microenvironment by inhibiting total immune cells, particularly cytotoxic GZMB+CD8+ T cells infiltration, while augmenting Treg cells, MDSCs, and exhausted CD8+ T cells ratios. Mechanistically, ADARp110 interacts with SNRPD3 and RNPS1 to stabilize CD24 mRNA by inhibiting STAU1-mediated mRNA decay. CD24 protects HCC cells from two indispensable mechanisms: macrophage phagocytosis and oxidative stress. Genetic knockdown or monoclonal antibody treatment of CD24 inhibits ADARp110-overexpressing tumor growth. Our findings unveil different mechanisms for ADARp110 modulation of tumor immune microenvironment and identify CD24 as a promising therapeutic target for HCCs.

Exploring prognosis and therapeutic strategies for HBV-HCC patients based on disulfidptosis-related genes

Background

Hepatocellular carcinoma (HCC) accounts for over 80% of primary liver cancers and is the third leading cause of cancer-related deaths worldwide. Hepatitis B virus (HBV) infection is the primary etiological factor. Disulfidptosis is a newly discovered form of regulated cell death. This study aims to develop a novel HBV-HCC prognostic signature related to disulfidptosis and explore potential therapeutic approaches through risk stratification based on disulfidptosis.

Methods

Transcriptomic data from HBV-HCC patients were analyzed to identify BHDRGs. A prognostic model was established and validated using machine learning, with internal datasets and external datasets for verification. We then performed immune cell infiltration analysis, tumor microenvironment (TME) analysis, and immunotherapy-related analysis based on the prognostic signature. Besides, RT-qPCR and immunohistochemistry were conducted.

Results

A prognostic model was constructed using five genes (DLAT, STC2, POF1B, S100A9, and CPS1). A corresponding prognostic nomogram was developed based on riskScores, age, stage. Stratification by median risk score revealed a significant correlation between the prognostic signature and TME, tumor immune cell infiltration, immunotherapy efficacy, and drug sensitivity. The results of the experiments indicate that DLAT expression is higher in tumor tissues compared to adjacent tissues. DLAT expression is higher in HBV-HCC tumor tissues compared to normal tissues.

Conclusion

This study stratifies HBV-HCC patients into distinct subgroups based on BHDRGs, establishing a prognostic model with significant implications for prognosis assessment, TME remodeling, and personalized therapy in HBV-HCC patients.

The Cell Polarity Protein MPP5/PALS1 Controls the Subcellular Localization of the Oncogenes YAP and TAZ in Liver Cancer

The oncogenes yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) are potent liver oncogenes. Because gene mutations cannot fully explain their nuclear enrichment, we aim to understand which mechanisms cause YAP/TAZ activation in liver cancer cells. The combination of proteomics and functional screening identified numerous apical cell polarity complex proteins interacting with YAP and TAZ. Co-immunoprecipitation (Co-IP) experiments confirmed that membrane protein palmitoylated 5 (MPP5; synonym: PALS1) physically interacts with YAP and TAZ. After removing different MPP5 protein domains, Co-IP analyses revealed that the PDZ domain plays a crucial role in YAP binding. The interaction between YAP and MPP5 in the cytoplasm of cancer cells was demonstrated by proximity ligation assays (PLAs). In human hepatocellular carcinoma (HCC) tissues, a reduction in apical MPP5 expression was observed, correlating with the nuclear accumulation of YAP and TAZ. Expression data analysis illustrated that MPP5 is inversely associated with YAP/TAZ target gene signatures in human HCCs. Low MPP5 levels define an HCC patient group with a poor clinical outcome. In summary, MPP5 facilitates the nuclear exclusion of YAP and TAZ in liver cancer. This qualifies MPP5 as a potential tumor-suppressor gene and explains how changes in cell polarity can foster tumorigenesis.

Unraveling the potential mechanism and prognostic value of pentose phosphate pathway in hepatocellular carcinoma: a comprehensive analysis integrating bulk transcriptomics and single-cell sequencing data

Hepatocellular carcinoma (HCC) remains a malignant and life-threatening tumor with an extremely poor prognosis, posing a significant global health challenge. Despite the continuous emergence of novel therapeutic agents, patients exhibit substantial heterogeneity in their responses to anti-tumor drugs and overall prognosis. The pentose phosphate pathway (PPP) is highly activated in various tumor cells and plays a pivotal role in tumor metabolic reprogramming. This study aimed to construct a model based on PPP-related Genes for risk assessment and prognosis prediction in HCC patients. We integrated RNA-seq and microarray data from TCGA, GEO, and ICGC databases, along with single-cell RNA sequencing (scRNA-seq) data obtained from HCC patients via GEO. Based on the "Seurat" R package, we identified distinct gene clusters related to the PPP within the scRNA-seq data. Using a penalized Cox regression model with least absolute shrinkage and selection operator (LASSO) penalties, we constructed a risk prognosis model. The validity of our risk prognosis model was further confirmed in external cohorts. Additionally, we developed a nomogram capable of accurately predicting overall survival in HCC patients. Furthermore, we explored the predictive potential of our risk model within the immune microenvironment and assessed its relevance to biological function, particularly in the context of immunotherapy. Subsequently, we performed in vitro functional validation of the key genes (ATAD2 and SPP1) in our model. A ten-gene signature associated with the PPP was formulated to enhance the prediction of HCC prognosis and anti-tumor treatment response. Following this, the ROC curve, nomogram, and calibration curve outcomes corroborated the model's robust clinical predictive capability. Functional enrichment analysis unveiled the engagement of the immune system and notable variances in the immune infiltration landscape across the high and low-risk groups. Additionally, tumor mutation frequencies were observed to be elevated in the high-risk group. Based on our analyses, the IC50 values of most identified anticancer agents demonstrated a correlation with the RiskScore. Additionally, the high-risk and low-risk groups exhibited differential sensitivity to various drugs. Cytological experiments revealed that silencing ATAD2 or SPP1 suppresses malignant phenotypes, including viability and migration, in liver cancer cells. In this study, a novel gene signature related to the PPP was developed, demonstrating favorable predictive performance. This signature holds significant guiding value for assessing the prognosis of HCC patients and directing individualized treatment strategies.

Integrative multi-omics analysis reveals a novel subtype of hepatocellular carcinoma with biological and clinical relevance

Background

Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor, and the development of accurate predictive models for prognosis and drug sensitivity remains challenging.

Methods

We integrated laboratory data and public cohorts to conduct a multi-omics analysis of HCC, which included bulk RNA sequencing, proteomic analysis, single-cell RNA sequencing (scRNA-seq), spatial transcriptomics sequencing (ST-seq), and genome sequencing. We constructed a tumor purity (TP) and tumor microenvironment (TME) prognostic risk model. Proteomic analysis validated the TP-TME-related signatures. Joint analysis of scRNA-seq and ST-seq revealed characteristic clusters associated with TP high-risk subtypes, and immunohistochemistry confirmed the expression of key genes. We conducted functional enrichment analysis, transcription factor activity inference, cell-cell interaction, drug efficacy analysis, and mutation information analysis to identify a novel subtype of HCC.

Results

Our analyses constructed a robust HCC prognostic risk prediction model. The patients with TP-TME high-risk subtypes predominantly exhibit hypoxia and activation of the Wnt/beta-catenin, Notch, and TGF-beta signaling pathways. Furthermore, we identified a novel subtype, XPO1+Epithelial. This subtype expresses signatures of the TP risk subtype and aligns with the biological behavior of high-risk patients. Additional analyses revealed that XPO1+Epithelial is influenced primarily by fibroblasts via ligand-receptor interactions, such as FN1-(ITGAV+ITGB1), and constitute a significant component of the TP-TME subtype. Moreover, XPO1+Epithelial interact with monocytes/macrophages, T/NK cells, and endothelial cells through ligand-receptor pairs, including MIF-(CD74+CXCR4), MIF-(CD74+CD44), and VEGFA-VEGFR1R2, respectively, thereby promoting the recruitment of immune-suppressive cells and angiogenesis. The ST-seq cohort treated with Tyrosine Kinase Inhibitors (TKIs) and Programmed Cell Death Protein 1 (PD-1) presented elevated levels of TP and TME risk subtype signature genes, as well as XPO1+Epithelial, T-cell, and endothelial cell infiltration in the treatment response group. Drug sensitivity analyses indicated that TP-TME high-risk subtypes, including sorafenib and pembrolizumab, were associated with sensitivity to multiple drugs. Further exploratory analyses revealed that CTLA4, PDCD1, and the cancer antigens MSLN, MUC1, EPCAM, and PROM1 presented significantly increase expression levels in the high-risk subtype group.

Conclusions

This study constructed a robust prognostic model for HCC and identified novel subgroups at the single-cell level, potentially assisting in the assessment of prognostic risk for HCC patients and facilitating personalized drug therapy.

Machine learning approach identifies inflammatory gene signature for predicting survival outcomes in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, often linked to chronic inflammation. Our study aimed to probe inflammation pathways at the genetic level and pinpoint biomarkers linked to HCC patient survival.

METHODS

We analyzed gene transcriptome data from 246 resectable stage I and II HCC patients from The Cancer Genome Atlas (TCGA). After selecting 917 inflammation-related genes (IRGs), we identified 104 differentially expressed genes (DEGs) through differential expression analysis. Two significant prognostic DEGs, S100A9 and PBK, were identified using LASSO and Cox regression, forming the basis of a risk score model. We conducted functional enrichment and immune landscape analyses, validated our findings on 170 patients from the GSE14520 dataset, and performed mutational analysis using TCGA somatic mutation data.

RESULTS

We analyzed 296 samples (246 HCC, 50 normal liver), showing significant survival differences between high and low-risk groups based on our risk score model. Functional enrichment analysis unveiled inflammation-associated pathways. Validation using the GSE14520 dataset confirmed our risk score's predictive ability, and we explored clinical correlations.

CONCLUSION

Our study delineates inflammation-related genomic changes in HCC, unveiling prognostic biomarkers with potential therapeutic implications. These findings deepen our understanding of HCC molecular mechanisms and may guide personalized therapeutic approaches, ultimately improving patient outcomes.

The novel role of LOC344887 in the enhancement of hepatocellular carcinoma progression via modulation of SHP1-regulated STAT3/HMGA2 signaling axis

Pseudogene-derived long non-coding RNAs (lncRNAs) have become crucial regulators in cancer progression. Extensive research highlights the pivotal role of signal transducer and activator of transcription 3 (STAT3) in promoting hepatocellular carcinoma (HCC) progression. As a result, targeting aberrant STAT3 activation presents a promising therapeutic strategy for HCC. Our study aims to identify the key pseudogene-derived lncRNA involved in modulating STAT3 activation and driving HCC progression. Our study is the first to identify a significant upregulation of LOC344887, a pseudogene-derived lncRNA, in HCC tissues. Elevated LOC344887 levels correlated with poor overall survival (OS) and recurrence-free survival (RFS), highlighting its potential as a biomarker for HCC. The rapid amplification of cDNA ends (RACE) and RT-PCR experiments revealed the expression of a novel LOC344887 transcript, named LOC344887-v2, alongside the annotated RefSeq transcript NR_151491 (LOC344887-v1) in both HCC tissues and hepatoma cell lines. Functional assays demonstrated that LOC344887 enhances cellular migration and invasion, with its variant LOC344887-v2 exhibiting a more pronounced effect. Further, LOC344887 mechanistically regulates STAT3 phosphorylation at tyrosine 705, which is crucial for maintaining STAT3 activation in HCC. Our findings unravel that LOC344887 not only physically interacts with p-STAT3 but also prevents its dephosphorylation by src homology region 2 domain-containing phosphatase 1 (SHP-1), thereby sustaining oncogenic signaling. In addition, we identified HMGA2 as a target of the LOC344887/SHP-1/STAT3 axis, with higher HMGA2 expression correlating with poorer prognosis in HCC patients. The ability of LOC344887 to regulate HMGA2 through direct binding of STAT3 to its promoter underlines its role in HCC progression. Collectively, these findings elucidate a novel oncogenic role of LOC344887 in HCC and suggest that targeting this lncRNA and its associated pathways may provide novel therapeutic strategies for improving patient outcomes in HCC.

UBAP2 contributes to radioresistance by enhancing homologous recombination through SLC27A5 ubiquitination in hepatocellular carcinoma

Radiotherapy stands as an effective method in the clinical treatment of hepatocellular carcinoma (HCC) patients. However, both primary and acquired radioresistance limit its clinical application in HCC. Therefore, investigating the mechanism of radioresistance may provide other options for treating HCC. Based on single-cell RNA sequencing (scRNA-seq) and HCC transcriptome datasets, 227 feature genes with prognostic value were selected to establish the tSNE score. The tSNE score emerged as an independent prognostic factor for HCC and correlated with cell proliferation and radioresistance-related biological functions. UBAP2 was identified as the most relevant gene with the tSNE score, consistently elevated in human HCC samples, and positively associated with patient prognosis. Functionally, UBAP2 knockdown impeded HCC development and reduced radiation resistance in vitro and in vivo. The ectopic expression of SLC27A5 reversed the effects of UBAP2. Mechanically, we uncovered that UBAP2, through the ubiquitin-proteasome system, decreased the homologous recombination-related gene RAD51, not the non-homologous end-joining (NHEJ)-related gene CTIP, by degrading the antioncogene SLC27A5, thereby generating radioresistance in HCC. The findings recapitulated that UBAP2 promoted HCC progression and radioresistance via SLC27A5 stability mediated by the ubiquitin-proteasome pathway. It was also suggested that targeting the UBAP2/SLC27A5 axis could be a valuable radiosensitization strategy in HCC.

Single cell landscape of potential mechanisms in primary and metastatic hepatocellular carcinoma

Hepatocellular carcinoma metastasis occurs mainly in the portal vein and lymph node metastasis, and is the main cause of patient death. However, the cellular origins and driving mechanisms of hepatocellular carcinoma metastasis have not been elucidated. In this study, we found that different tumor metastasis samples originated from different branches of the primary tumor subclone. A large number of sequence data confirmed the correlation between tumor metastasis index and metastasis and prognosis. Patients with a high index generally had a poor prognosis and abnormal metabolic function. Finally, we recommended a candidate therapy for each metastatic direction. This study explains the cellular origin and underlying mechanisms of hepatocellular carcinoma metastasis at the single-cell level and identifies drugs for its targeted therapy. It also provides a new research idea for the study of hepatocellular carcinoma metastasis and early identification of cancer metastasis from cellular resolution.

Network pharmacology and bioinformatic integrative analysis reveals candidate gene targets and potential therapeutic of East Kalimantan propolis against hepatocellular carcinoma

Introduction

Hepatocellular Carcinoma (HCC) is commonly treated with surgery, liver transplantation, and chemotherapy, but recurrence and metastasis remain challenges. Natural complementary therapies like propolis, known for its hepatoprotective properties, are gaining interest due to limited efficacy and toxicity of conventional chemotherapy. This study aims to identify core targets for HCC, assess the therapeutic potential of East Kalimantan propolis (EKP) from stingless bees, and analyze the molecular interactions.

Methods

EKP compounds were analyzed using target prediction tools related to HCC, alongside clinical data from the Gene Expression Omnibus (GEO) database, to identify overlapping genes with clinical relevance. The selected genes were then subjected to protein-protein interaction (PPI), GO and KEGG enrichment, immunohistochemical comparison and survival analysis to identify potential core targets and related pathways for HCC therapy. Furthermore, molecular docking and dynamics were conducted to verify the molecular interactions and stability of EKP compounds with targets.

Results

108 genes have been selected as HCC potential targets, which mostly associated with MicroRNAs in cancer, chemical carcinogenesis, and viral carcinogenesis pathways. These targets were obtained by overlapping genes from GEO clinical databases and target predictors. PPI network analysis revealed 4 main targets of propolis in HCC. Furthermore, differential expression genes, survival analysis, and Immunohistochemical analysis from databases suggested that AKR1C3 and MAPK1 promote HCC progression and shorten survival rate of HCC patients. Molecular docking and dynamic studies confirmed strong binding affinity and stability of Baicalein, Chrysin, Quercetin, and Myricetin with receptor targets within simulation time.

Conclusions

This study provides insight into the mechanism of action of EKP on HCC and identifies AKR1C3 and MAPK1 as candidate target treatments for future drug development.

Integration of epigenomic and transcriptomic profiling uncovers EZH2 target genes linked to cysteine metabolism in hepatocellular carcinoma

Enhancer of zeste homolog 2 (EZH2), a key protein implicated in various cancers including hepatocellular carcinoma (HCC), is recognized for its association with epigenetic dysregulation and pathogenesis. Despite clinical explorations into EZH2-targeting therapies, the mechanisms underlying its role in gene suppression in HCC have remained largely unexplored. Here, we integrate epigenomic and transcriptomic analyses to uncover the transcriptional landscape modulated by selective EZH2 inhibition in HCC. By reanalyzing transcriptomic data of HCC patients, we demonstrate that EZH2 overexpression correlates with poor patient survival. Treatment with the EZH2 inhibitor tazemetostat restored expression of genes involved in cysteine-methionine metabolism and lipid homeostasis, while suppressing angiogenesis and oxidative stress-related genes. Mechanistically, we demonstrate EZH2-mediated H3K27me3 enrichment at cis-regulatory elements of transsulfuration pathway genes, which is reversed upon inhibition, leading to increased chromatin accessibility. Among 16 EZH2-targeted candidate genes, BHMT and CDO1 were notably correlated with poor HCC prognosis. Tazemetostat treatment of HCC cells increased BHMT and CDO1 expression while reducing levels of ferroptosis markers FSP1, NFS1, and SLC7A11. Functionally, EZH2 inhibition dose-dependently reduced cell viability and increased lipid peroxidation in HCC cells. Our findings reveal a novel epigenetic mechanism controlling lipid peroxidation and ferroptosis susceptibility in HCC, providing a rationale for exploring EZH2-targeted therapies in this malignancy.

The TGF-β1 target WISP1 is highly expressed in liver cirrhosis and cirrhotic HCC microenvironment and involved in pro- and anti-tumorigenic effects

INTRODUCTION

WNT1-inducible signalling pathway protein 1 (WISP1) promotes progression of several tumor entities often correlating with worse prognosis. Here its expression regulation and role in the progression of chronic liver diseases (CLD) was investigated.

METHODS

WISP1 expression was analyzed in human HCC datasets, in biopsies and serum samples and an HCC patient tissue microarray (TMA) including correlation to clinicopathological parameters. Spatial distribution of WISP1 expression was determined using RNAscope analysis. Regulation of WISP1 expression was investigated in cytokine-stimulated primary mouse hepatocytes (PMH) by array analysis and qRT-PCR. Outcome of WISP1 stimulation was analyzed by IncuCyte S3-live cell imaging, qRT-PCR, and immunoblotting in murine AML12 cells.

RESULTS

In a TMA, high WISP1 expression was positively correlated with early HCC stages and male sex. Highest WISP1 expression levels were detected in patients with cirrhosis as compared to healthy individuals, patients with early fibrosis, and non-cirrhotic HCC in liver biopsies, expression datasets and serum samples. WISP1 transcripts were predominantly detected in hepatocytes of cirrhotic rather than tumorous liver tissue. High WISP1 expression was associated with better survival. In PMH, AML12 and HepaRG, WISP1 was identified as a specific TGF-β1 target gene. Accordingly, expression levels of both cytokines positively correlated in human HCC patient samples. WISP1-stimulation induced the expression of Bcl-xL, PCNA and p21 in AML12 cells.

CONCLUSIONS

WISP1 expression is induced by TGF-β1 in hepatocytes and is associated with cirrhotic liver disease. We propose a crucial role of WISP1 in balancing pro- and anti-tumorigenic effects during premalignant stages of CLD.

Oncogenic role of PMEPA1 and its association with immune exhaustion and TGF-β activation in HCC

Background & Aims

Transforming growth factor β (TGF-β) plays an oncogenic role in advanced cancer by promoting cell proliferation, metastasis and immunosuppression. PMEPA1 (prostate transmembrane protein androgen induced 1) has been shown to promote TGF-β oncogenic effects in other tumour types. Thus, we aimed to explore the role of PMEPA1 in hepatocellular carcinoma (HCC).

Methods

We analysed 1,097 tumours from patients with HCC, including discovery (n = 228) and validation (n = 361) cohorts with genomic and clinicopathological data. PMEPA1 levels were assessed by qPCR (n = 228), gene expression data (n = 869) and at the single-cell level (n = 54). Genetically engineered mouse models overexpressing MYC+PMEPA1 compared to MYC were generated and molecular analyses were performed on the HCCs obtained.

Results

PMEPA1 was overexpressed in 18% of HCC samples (fold-change >2; n = 201/1,097), a feature associated with TGF-β signalling activation (p <0.05) and absence of gene body hypomethylation (p <0.01). HCCs showing both TGF-β signalling and high PMEPA1 levels (12% of cases) were linked to immune exhaustion, late TGF-β activation, aggressiveness and higher recurrence rates after resection, in contrast to HCCs with only TGF-β signalling (8%) or PMEPA1 overexpression (9%). Single-cell RNA sequencing analysis identified PMEPA1 expression in HCC and stromal cells. PMEPA1-expressing tumoural cells were predicted to interact with CD4+ regulatory T cells and CD4+ CXCL13+ and CD8+ exhausted T cells. In vivo, overexpression of MYC+PMEPA1 led to HCC development in ∼60% of mice and a decreased survival compared to mice overexpressing MYC alone (p = 0.014). MYC+PMEPA1 tumours were enriched in TGF-β signalling, paralleling our human data.

Conclusions

In human HCC, PMEPA1 upregulation is linked to TGF-β activation, immune exhaustion, and an aggressive phenotype. Overexpression of PMEPA1+MYC led to tumoural development in vivo, demonstrating the oncogenic role of PMEPA1 in HCC for the first time.

Impact and implications

PMEPA1 can enhance the tumour-promoting effects of TGF-β in cancer. In this study, we demonstrate that PMEPA1 is highly expressed in ∼18% of patients with hepatocellular carcinoma (HCC), a feature associated with poor prognosis, TGF-β activation and exhaustion of immune cells. Similarly, in mouse models, PMEPA1 overexpression promotes HCC development, which demonstrates its oncogenic role. The identification of PMEPA1 as oncogenic driver in HCC and its role in immune exhaustion and poor clinical outcomes enhances our understanding of HCC pathogenesis and opens new avenues for targeted therapeutic interventions.

A prognostic model for hepatocellular carcinoma patients based on polyunsaturated fatty acid-related genes

OBJECTIVE

Polyunsaturated fatty acids (PUFAs) have attracted increasing attention for their role in liver cancer development. The objective of this study is to develop a prognosis prediction model for patients with liver cancer based on PUFA-related metabolic gene characteristics.

METHOD

Transcriptome data and clinical data were obtained from public databases, while gene sets related to PUFAs were acquired from the gene set enrichment analysis (GSEA) database. Univariate Cox analysis was conducted on the training set, followed by LASSO logistic regression and multivariate Cox analysis on genes with p < .05. Subsequently, the stepwise Akaike information criterion method was employed to construct the model. The high- and low-risk groups were divided based on the median score, and the model's survival prediction ability, diagnostic efficiency, and risk score distribution of clinical features were validated. The above procedures were also validated in the validation set. Immune infiltration levels were evaluated using four algorithms, and the immunotherapeutic potential of different groups was explored. Significant enrichment pathways among different groups were selected based on the GSEA algorithm, and mutation analyses were conducted. Nomogram prognostic models were constructed by incorporating clinical factors and risk scores using univariate and multivariate Cox regression analysis, validated through calibration curves and clinical decision curves. Additionally, sensitivity analysis of drugs was performed to screen potential targeted drugs.

RESULTS

We constructed a prognostic model comprising eight genes (PLA2G12A, CYP2C8, ABCCI, CD74, CCR7, P2RY4, P2RY6, and YY1). Validation across multiple datasets indicated the model's favorable prognostic prediction ability and diagnostic efficiency, with poorer grading and staging observed in the high-risk group. Variations in mutation status and pathway enrichment were noted among different groups. Incorporating Stage, Grade, T.Stage, and RiskScore into the nomogram prognostic model demonstrated good accuracy and clinical decision benefits. Multiple immune analyses suggested greater benefits from immunotherapy in the low-risk group. We predicted multiple targeted drugs, providing a basis for drug development.

CONCLUSION

Our study's multifactorial prognostic model across multiple datasets demonstrates good applicability, offering a reliable tool for personalized therapy. Immunological and mutation-related analyses provide theoretical foundations for further research. Drug predictions offer important insights for future drug development and treatment strategies. Overall, this study provides comprehensive insights into tumor prognosis assessment and personalized treatment planning.

Integrated analysis of tumor and adjacent non-tumor proteomic data reveals SERPINH1 as a recurrence biomarker and drug target in hepatocellular carcinoma

The high rate of postoperative recurrence contributes to the poor outcome in hepatocellular carcinoma (HCC), and effective strategies for managing recurrence are currently lacking. Based on seven pairs of tumors and non-tumor adjacent tissues (NATs) proteomic datasets across five cancer types, this study systematically investigates the stratified and therapeutic value of tumors and NATs for tumor recurrence. NATs exhibited stable and irreplaceable independent prognostic capabilities for recurrence, complementing clinical indicators and tumor characteristics. In comparison to tumor tissues, NATs exhibit higher enrichment levels of recurrence-related proteins in pathways such as immunity, extracellular matrix, and angiogenesis. Taking HCC as an example, we identified SERPINH1 as a recurrent biomarker with drug-targeting potential that applied to both tumors and NATs and then validated them through independent immunohistochemistry cohorts and animal experiments. Patients with high SERPINH1 expression in both tumors and NATs have the highest 5-year recurrence rates, even among clinically low recurrence risk groups. Targeting SERPINH1 can effectively delay tumor occurrence and progression. This study highlights the significant importance of NATs in recurrence prediction and postoperative management, proposing a recurrence management strategy that focuses on both tumors and NATs. SERPINH1 emerges as a valuable biomarker and drug target for addressing postoperative recurrence in HCC.

ACSL6-activated IL-18R1-NF-κB promotes IL-18-mediated tumor immune evasion and tumor progression

Aberrant activation of IL-18 signaling regulates tumor immune evasion and progression. However, the underlying mechanism remains unclear. Here, we report that long-chain acyl-CoA synthase 6 (ACSL6) is highly expressed in liver cancer and correlated with poor prognosis. ACSL6 promotes tumor growth, metastasis, and immune evasion mediated by IL-18, independent of its metabolic enzyme activity. Mechanistically, upon IL-18 stimulation, ACSL6 is phosphorylated by ERK2 at S674 and recruits IL-18RAP to interact with IL-18R1, thereby reinforcing the IL-18R1-IL-18RAP heterodimer and triggering NF-κB-dependent gene expression to facilitate tumor development. Furthermore, the up-regulation of CXCL1 and CXCL5 by ACSL6 promotes tumor-associated neutrophil and tumor-associated macrophage recruitment, thereby inhibiting cytotoxic CD8+ T cell infiltration. Ablation or S674A mutation of ACSL6 potentiated anti-PD-1 therapeutic efficacy by increasing the effector activity of intertumoral CD8+ T cells. We revealed that ACSL6 is a potential adaptor that activates IL-18-NF-κB axis-mediated tumor immune evasion and provides valuable insights for developing effective immunotherapy strategies for cancer.

Differences in Prediagnostic Serum Metabolomic and Lipidomic Profiles Between Cirrhosis Patients with and without Incident Hepatocellular Carcinoma

Background

Early detection of hepatocellular carcinoma (HCC) is crucial for improving patient outcomes, but we lack robust clinical biomarkers. This study aimed to identify a metabolite and/or lipid panel for early HCC detection.

Methods

We developed a high-resolution liquid chromatography mass spectrometry (LC-MS)-based profiling platform and evaluated differences in the global metabolome and lipidome between 28 pre-diagnostic serum samples from patients with cirrhosis who subsequently developed HCC (cases) and 30 samples from patients with cirrhosis and no HCC (controls). We linked differentially expressed metabolites and lipids to their associated genes, proteins, and transcriptomic signatures in publicly available datasets. We used machine learning models to identify a minimal panel to distinguish between cases and controls.

Results

Among cases compared with controls, 124 metabolites and 246 lipids were upregulated, while 208 metabolites and 73 lipids were downregulated. The top upregulated metabolites were glycoursodeoxycholic acid, 5-methyltetrahydrofolic acid, octanoyl-coenzyme A, and glycocholic acid. Elevated lipids comprised glycerol lipids, cardiolipin, and phosphatidylethanolamine, whereas suppressed lipids included oxidized phosphatidylcholine and lysophospholipids. There was an overlap between differentially expressed metabolites and lipids and previously published transcriptomic signatures, illustrating an association with liver disease severity. A panel of 12 metabolites that distinguished between cases and controls with an area under the receiver operating curve of 0.98 for the support vector machine (interquartile range, 0.9-1).

Conclusion

Using prediagnostic serum samples, we identified a promising metabolites panel that accurately identifies patients with cirrhosis who progressed to HCC. Further validation of this panel is required.

WNK1 Interaction with KEAP1 Promotes NRF2 Stabilization to Enhance the Oxidative Stress Response in Hepatocellular Carcinoma

Cellular oxidative stress plays a key role in the development and progression of hepatocellular carcinoma (HCC). A better understanding of the processes that regulate reactive oxygen species (ROS) homeostasis could uncover improved strategies for treating HCC. Herein, we identified protein kinase with-no-lysine kinase 1 (WNK1) as an antioxidative factor and therapeutic target in HCC. In human HCC, WNK1 expression was increased and correlated with poor patient prognosis. WNK1 knockdown significantly inhibited cell proliferation and xenograft tumor growth. Mechanistically, WNK1 competed with nuclear factor erythroid 2-related factor 2 (NRF2) for binding with the partial Kelch domain of Kelch-like ECH-associated protein 1 (KEAP1), reducing NRF2 ubiquitination and promoting NRF2 accumulation and nuclear translocation to increase antioxidant response. WNK1 silencing increased H2O2-induced apoptosis and inhibited cell growth by elevating ROS levels, which could be rescued by treatment with the antioxidant N-acetylcysteine and NRF2 activator tert-butylhydroquinone. Liver-specific WNK1 knockout mouse models of HCC substantiated that WNK1 promoted HCC development by regulating ROS levels. WNK463, an inhibitor of the WNK kinase family, suppressed HCC progression and altered the redox status. These findings suggest that WNK1 plays a critical role in HCC development and progression and that the WNK1-oxidative stress axis may be a promising therapeutic target for HCC. Significance: Inhibiting WNK1 induces NRF2 degradation and reduces the oxidative stress response to suppress hepatocellular carcinoma growth, indicating that targeting the WNK1-KEAP1-NRF2 axis is a potential strategy to treat liver cancer.

Intron Retention of DDX39A Driven by SNRPD2 is a Crucial Splicing Axis for Oncogenic MYC/Spliceosome Program in Hepatocellular Carcinoma

RNA splicing is a dynamic molecular process in response to environmental stimuli and is strictly regulated by the spliceosome. Sm proteins, constituents of the spliceosome, are key components that mediate splicing reactions; however, their potential role in hepatocellular carcinoma (HCC) is poorly understood. In the study, SNRPD2 (PD2) is found to be the most highly upregulated Sm protein in HCC and to act as an oncogene. PD2 modulates DDX39A intron retention together with HNRNPL to sustain the DDX39A short variant (39A_S) expression. Mechanistically, 39A_S can mediate MYC mRNA nuclear export to maintain high MYC protein expression, while MYC in turn potentiates PD2 transcription. Importantly, digitoxin can directly interact with PD2 and has a notable cancer-suppressive effect on HCC. The study reveals a novel mechanism by which DDX39A senses oncogenic MYC signaling and undergoes splicing via PD2 to form a positive feedback loop in HCC, which can be targeted by digitoxin.

Pattern-centric transformation of omics data grounded on discriminative gene associations aids predictive tasks in TCGA while ensuring interpretability

The increasing prevalence of omics data sources is pushing the study of regulatory mechanisms underlying complex diseases such as cancer. However, the vast quantities of molecular features produced and the inherent interplay between them lead to a level of complexity that hampers both descriptive and predictive tasks, requiring custom-built algorithms that can extract relevant information from these sources of data. We propose a transformation that moves data centered on molecules (e.g., transcripts and proteins) to a new data space focused on putative regulatory modules given by statistically relevant co-expression patterns. To this end, the proposed transformation extracts patterns from the data through biclustering and uses them to create new variables with guarantees of interpretability and discriminative power. The transformation is shown to achieve dimensionality reductions of up to 99% and increase predictive performance of various classifiers across multiple omics layers. Results suggest that omics data transformations from gene-centric to pattern-centric data supports both prediction tasks and human interpretation, notably contributing to precision medicine applications.

HMGB2 drives tumor progression and shapes the immunosuppressive microenvironment in hepatocellular carcinoma: insights from multi-omics analysis

Background

Hepatocellular carcinoma (HCC) poses a significant health burden globally, with high mortality rates despite various treatment options. Immunotherapy, particularly immune-checkpoint inhibitors (ICIs), has shown promise, but resistance and metastasis remain major challenges. Understanding the intricacies of the tumor microenvironment (TME) is imperative for optimizing HCC management strategies and enhancing patient prognosis.

Methods

This study employed a comprehensive approach integrating multi-omics approaches, including single-cell RNA sequencing (scRNA-seq), bulk RNA sequencing (Bulk RNA-seq), and validation in clinical samples using spatial transcriptomics (ST) and multiplex immunohistochemistry (mIHC). The analysis aimed to identify key factors influencing the immunosuppressive microenvironment associated with HCC metastasis and immunotherapy resistance.

Results

HMGB2 is significantly upregulated in HCCTrans, a transitional subgroup associated with aggressive metastasis. Furthermore, HMGB2 expression positively correlates with an immunosuppressive microenvironment, particularly evident in exhausted T cells. Notably, HMGB2 expression correlated positively with immunosuppressive markers and poor prognosis in HCC patients across multiple cohorts. ST combined with mIHC validated the spatial expression patterns of HMGB2 within the TME, providing additional evidence of its role in HCC progression and immune evasion.

Conclusion

HMGB2 emerges as a critical player of HCC progression, metastasis, and immunosuppression. Its elevated expression correlates with aggressive tumor behavior and poor patient outcomes, suggesting its potential as both a therapeutic target and a prognostic indicator in HCC management.

An Oxidative Stress-Related Prognostic Signature Predicts Treatment Response and Outcomes for Hepatocellular Carcinoma After Transarterial Chemoembolization

Purpose

Oxidative stress plays a critical role in promoting tumor resistance to hypoxia and chemotherapeutic drugs. However, the prognostic role of oxidative stress-related genes (OSRGs) in hepatocellular carcinoma (HCC) treated with transarterial chemoembolization (TACE) has not been fully explored.

Methods

We used transcriptome data from the GSE104580 cohort containing patients marked as responders or nonresponders to TACE therapy to identify differentially expressed OSRGs associated with TACE response (TR-OSRGs). We created a TR-OSRG prognostic signature based on TR-OSRGs using least absolute shrinkage and selection operator Cox and stepwise Cox regression analyses in a training cohort of patients with HCC (TCGA-LIHC). We verified this prognostic signature in two external cohorts of patients who received TACE for HCC (GSE14520-TACE and ZS-TACE-37). Finally, we constructed a prognostic nomogram model for predicting survival probability of patients with HCC based on Cox regression analysis.

Results

The TR-OSRG prognostic signature was created and shown to be a robust independent prognostic factor for treatment response and outcomes for HCC after TACE therapy. Risk scores based on this signature correlated with tumor stage and grade. Tumor samples from patients with higher risk scores exhibited more infiltration of immune cells and significantly increased expression of immune checkpoint genes. We also developed a nomogram for patients with HCC based on the TR-OSRG prognostic signature and clinical parameters; this nomogram was a useful quantitative analysis tool for predicting patient survival.

Conclusion

The TR-OSRGs signature exhibited good performance in predicting treatment response and outcomes in patients with HCC treated with TACE.

CRKL Enhances YAP Signaling through Binding and JNK/JUN Pathway Activation in Liver Cancer

The Hippo pathway transducers yes-associated protein (YAP) and WW-domain containing transcription regulator 1 (WWTR1/TAZ) are key regulators of liver tumorigenesis, promoting tumor formation and progression. Although the first inhibitors are in clinical trials, targeting the relevant upstream regulators of YAP/TAZ activity could prove equally beneficial. To identify regulators of YAP/TAZ activity in hepatocarcinoma (HCC) cells, we carried out a proximity labelling approach (BioID) coupled with mass spectrometry. We verified CRK-like proto-oncogene adaptor protein (CRKL) as a new YAP-exclusive interaction partner. CRKL is highly expressed in HCC patients, and its expression is associated with YAP activity as well as poor survival prognosis. In vitro experiments demonstrated CRKL-dependent cell survival and the loss of YAP binding induced through actin disruption. Moreover, we delineated the activation of the JNK/JUN pathway by CRKL, which promoted YAP transcription. Our data illustrate that CRKL not only promoted YAP activity through its binding but also through the induction of YAP transcription by JNK/JUN activation. This emphasizes the potential use of targeting the JNK/JUN pathway to suppress YAP expression in HCC patients.

Stratifin-mediated activation of AKT signaling and therapeutic targetability in hepatocellular carcinoma progression

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide and presents a significant threat to human health. Despite its prevalence, the underlying regulatory mechanisms of HCC remain unclear. In this study, we integrated RNA-seq datasets, proteome dataset and survival analysis and unveiled Stratifin (SFN) as a potential prognostic biomarker for HCC. SFN knockdown inhibited HCC progression in cell cultures and mouse models. Conversely, ectopic expression of Sfn in primary mouse HCC model accelerated HCC progression. Mechanistically, SFN acted as an adaptor protein, activating AKT1 signaling by fostering the interaction between PDK1 and AKT1, with the R56 and R129 sites on SFN proving to be crucial for this binding. In the syngeneic implantation model, the R56A/R129A mutant of SFN inhibited Akt signaling activation and impeded HCC growth. Additionally, peptide inhibitors designed based on the binding motif of AKT1 to SFN significantly inhibited HCC progression. In summary, our findings establish that SFN promotes HCC progression by activating AKT signaling through the R56 and R129 binding sites. This discovery opens new avenues for a promising therapeutic strategy for the treatment of HCC.

DAP3 promotes mitochondrial activity and tumour progression in hepatocellular carcinoma by regulating MT-ND5 expression

Cancer cells often exhibit fragmented mitochondria and dysregulated mitochondrial dynamics, but the underlying mechanism remains elusive. Here, we found that the mitochondrial protein death-associated protein 3 (DAP3) is localized to mitochondria and promotes the progression of hepatocellular carcinoma (HCC) by regulating mitochondrial function. DAP3 can promote the proliferation, migration, and invasion of HCC cells in vitro and in vivo by increasing mitochondrial respiration, inducing the epithelial-mesenchymal transition (EMT), and slowing cellular senescence. Mechanistically, DAP3 can increase mitochondrial complex I activity in HCC cells by regulating the translation and expression of MT-ND5. The phosphorylation of DAP3 at Ser185 mediated by AKT is the key event mediating the mitochondrial localization and function of DAP3 in HCC cells. In addition, the DAP3 expression in HCC samples is inversely correlated with patient survival. Our results revealed a mechanism by which DAP3 promotes mitochondrial function and HCC progression by regulating MT-ND5 translation and expression, indicating that DAP3 may be a therapeutic target for HCC.

POSTN+ cancer-associated fibroblasts determine the efficacy of immunotherapy in hepatocellular carcinoma

OBJECTIVE

Hepatocellular carcinoma (HCC) poses a significant clinical challenge because the long-term benefits of immune checkpoint blockade therapy are limited. A comprehensive understanding of the mechanisms underlying immunotherapy resistance in HCC is imperative for improving patient prognosis.

DESIGN

In this study, to systematically investigate the characteristics of cancer-associated fibroblast (CAF) subsets and the dynamic communication among the tumor microenvironment (TME) components regulated by CAF subsets, we generated an HCC atlas by compiling single-cell RNA sequencing (scRNA-seq) datasets on 220 samples from six datasets. We combined spatial transcriptomics with scRNA-seq and multiplexed immunofluorescence to identify the specific CAF subsets in the TME that determine the efficacy of immunotherapy in HCC patients.

RESULTS

Our findings highlight the pivotal role of POSTN+ CAFs as potent immune response barriers at specific tumor locations, as they hinder effective T-cell infiltration and decrease the efficacy of immunotherapy. Additionally, we elucidated the interplay between POSTN+ CAFs and SPP1+ macrophages, whereby the former recruits the latter and triggers increased SPP1 expression via the IL-6/STAT3 signaling pathway. Moreover, we demonstrated a spatial correlation between POSTN+ CAFs and SPP1+ macrophages, revealing an immunosuppressive microenvironment that limits the immunotherapy response. Notably, we found that patients with elevated expression levels of both POSTN+ CAFs and SPP1+ macrophages achieved less therapeutic benefit in an immunotherapy cohort.

CONCLUSION

Our research elucidates light on the role of a particular subset of CAFs in immunotherapy resistance, emphasizing the potential benefits of targeting specific CAF subpopulations to improve clinical responses to immunotherapy.

Transcriptome Analyses of Liver Sinusoidal Endothelial Cells Reveal a Consistent List of Candidate Genes Associated with Endothelial Dysfunction and the Fibrosis Progression

Liver fibrosis is an important step in the transformation of chronic liver disease into cirrhosis and liver cancer, and structural changes and functional disorders of liver sinusoidal endothelial cells (LSECs) are early events in the occurrence of liver fibrosis. Therefore, it is necessary to identify the key regulatory genes of endothelial dysfunction in the process of liver fibrosis to provide a reference for the diagnosis and treatment of liver fibrosis. In this study, we identified 230 common differentially expressed genes (Co-DEGs) by analyzing transcriptomic data of primary LSECs from three different liver fibrosis mouse models (carbon tetrachloride; choline-deficient, l-amino acid-defined diet; and nonalcoholic steatohepatitis). Enrichment analysis revealed that the Co-DEGs were mainly involved in regulating the inflammatory response, immune response, angiogenesis, formation and degradation of the extracellular matrix, and mediating chemokine-related pathways. A Venn diagram analysis was used to identify 17 key genes related to the progression of liver cirrhosis. Regression analysis using the Lasso-Cox method identified genes related to prognosis among these key genes: SOX4, LGALS3, SERPINE2, CD52, and LPXN. In mouse models of liver fibrosis (bile duct ligation and carbon tetrachloride), all five key genes were upregulated in fibrotic livers. This study identified key regulatory genes for endothelial dysfunction in liver fibrosis, namely SOX4, LGALS3, SERPINE2, CD52, and LPXN, which will provide new targets for the development of therapeutic strategies targeting endothelial dysfunction in LSECs and liver fibrosis.

Transposable elements-mediated recruitment of KDM1A epigenetically silences HNF4A expression to promote hepatocellular carcinoma

Transposable elements (TEs) contribute to gene expression regulation by acting as cis-regulatory elements that attract transcription factors and epigenetic regulators. This research aims to explore the functional and clinical implications of transposable element-related molecular events in hepatocellular carcinoma, focusing on the mechanism through which liver-specific accessible TEs (liver-TEs) regulate adjacent gene expression. Our findings reveal that the expression of HNF4A is inversely regulated by proximate liver-TEs, which facilitates liver cancer cell proliferation. Mechanistically, liver-TEs are predominantly occupied by the histone demethylase, KDM1A. KDM1A negatively influences the methylation of histone H3 Lys4 (H3K4) of liver-TEs, resulting in the epigenetic silencing of HNF4A expression. The suppression of HNF4A mediated by KDM1A promotes liver cancer cell proliferation. In conclusion, this study uncovers a liver-TE/KDM1A/HNF4A regulatory axis that promotes liver cancer growth and highlights KDM1A as a promising therapeutic target. Our findings provide insight into the transposable element-related molecular mechanisms underlying liver cancer progression.