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PubMed2026

Context-dependent effects of MIR100HG on tumorigenic phenotypes and p38/MAPK-AKT signaling in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide and is characterized by a hypoxic tumor microenvironment that promotes tumor progression, cellular adaptation, and therapeutic resistance. Increasing evidence indicates that long non-coding RNAs (lncRNAs) play critical roles in regulating tumor-associated signaling networks; however, the contribution of MIR100HG to hepatocellular carcinoma progression, particularly under hypoxic conditions, remains insufficiently understood. In this study, we investigated the expression pattern and functional significance of MIR100HG in hepatocellular carcinoma using epithelial-like Hep3B and mesenchymal-like SNU-398 cells, together with non-tumor hepatocytes (Clone-9). Gain- and loss-of-function approaches were employed to evaluate the impact of MIR100HG on tumor-associated cellular phenotypes under both normoxic and hypoxic conditions. Functional assays demonstrated that MIR100HG overexpression significantly enhanced cell proliferation, clonogenic potential, migration, and invasion, whereas MIR100HG silencing markedly suppressed these tumorigenic properties and increased apoptotic cell death. Mechanistic analyses revealed that MIR100HG promotes oncogenic signaling through the p38/MAPK and AKT pathways under normoxic conditions, whereas MIR100HG depletion reduced the phosphorylation of these key signaling proteins. Notably, additional pathway analyses under hypoxia-mimicking conditions revealed a distinct signaling response, in which the MIR100HG-associated activation of p38/MAPK and AKT observed under normoxia was not maintained. Moreover, the expression patterns of AKT-associated regulatory genes, including GAS6 and PTEN, were reversed under hypoxia-mimicking conditions. These findings suggest that the effects of MIR100HG on oncogenic signaling are highly dependent on the cellular oxygenation context and that hypoxia reshapes the downstream signaling consequences of MIR100HG expression in HCC cells. Collectively, our findings identify MIR100HG as a hypoxia-associated oncogenic regulator that enhances tumorigenic phenotypes and promotes survival signaling in hepatocellular carcinoma. These results highlight MIR100HG as a potential biomarker and therapeutic target in liver cancer and provide new insights into the molecular mechanisms underlying hypoxia-driven tumor progression.

Humans↗

PubMed2026

Integrated LiP-MS and quantitative proteomics reveal coordinated alterations in protein conformation and expression across tumor and peritumoral regions in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) exhibits substantial molecular heterogeneity, yet protein-level alterations beyond abundance remain insufficiently characterized. Here, we integrated limited proteolysis mass spectrometry (Lip-MS) with 4D label-free quantitative proteomics to investigate conformational accessibility and protein abundance across tumor, peritumoral-near, and peritumoral-far tissues from HCC patients. Differential LiP peptides identified by both DDA and DIA corresponded to 725, 674, and 33 differentially conformed proteins in the Tumor vs. Peritumor-far, Tumor vs. Peritumor-near, and Peritumor-near vs. Peritumor-far comparisons, respectively. Quantitative proteomics identified 405, 365, and 4 differentially expressed proteins in the corresponding comparisons. Integrated analysis identified 488 and 469 conformation-specific altered proteins (CSAPs), which showed altered conformational accessibility without significant abundance changes, and 237 and 205 conformation-expression coupled proteins (CECPs) in the two tumor-involved comparisons. LiP peptide and protein abundance changes were positively correlated, with Spearman coefficients of 0.69-0.72, and more than 99% of CECPs showed concordant directions. Among them, 169 region-conserved CECPs (rcCECPs) were predominantly associated with metabolic and redox-related pathways. Protein-protein interaction analysis identified 30 hub rcCECPs. ACLY, ALDH18A1, GMPS, and DHX9 showed increased representative LiP peptide signals and protein abundance, elevated transcript expression in HCC, and associations with poorer overall survival. Peptide mapping further localized their differential LiP signals to specific sequence regions and annotated domains. Collectively, these findings provide an integrated view of regional conformational accessibility and protein abundance alterations in HCC and identify candidate proteins for further structural and functional investigation.

Humans↗

PubMed2026

Serum Olink Proteomics Reveals Novel Biomarkers for Early Diagnosis of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly prevalent malignant tumor in China, and early diagnosis critically affects the prognosis. Current imaging and pathological biopsy techniques have limitations, including high invasiveness and limited accessibility, while the insufficient sensitivity of serum biomarkers (such as AFP) restricts their use in early screening. In this study, using the Olink proteomics platform based on the proximity extension assay (PEA), we screened for hepatocellular carcinoma-related differentially expressed proteins (DEPs) and constructed a multiprotein diagnostic model. In the discovery cohort, we included 15 patients with newly diagnosed HCCs and 16 healthy controls. DEPs were identified using Olink, and their diagnostic performance was analyzed to identify the candidate biomarkers. In an independent validation cohort, including 116 HCC patients (50 early stage, 66 late stage) and 83 healthy controls, we further validated the expression levels and diagnostic performance of identified proteins─C1QA and GFER. The C1QA and GFER expression levels were significantly higher in the serum of patients with early and late HCC stages compared to healthy controls. By constructing a multiprotein diagnostic model, we identified C1QA, GFER, and AFP as the optimal diagnostic combination, demonstrating a combined diagnostic AUC of 0.92 and 0.99 for early-stage and advanced-stage HCC, respectively.

Humans↗

PubMed2026

Integrating single-cell transcriptomics to construct an oncogene-driven prognostic model and elucidate metabolic-immune crosstalk in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths, its progression and treatment heterogeneity are mainly influenced by driver gene and tumor micro-environment (TME) interactions. Nevertheless, the mechanisms of this process at the single-cell level remain unclear. This study integrated TCGA and multi-center single-cell transcriptome data to identify a 575 genes HCC-specific core set, developing a single-cell "oncogene scoring" system to quantify individual carcinogenic activity. This score is significantly elevated in malignant and proliferative T cells and is closely associated with metabolic reprogramming, aberrant cell‒cell communication, and immunosuppressive phenotypes. Based on these characteristics, we constructed a machine learning-based Random Survival Forest (RSF) prognostic model validated in multiple independent cohorts, which classifies patients into distinct risk subtypes. The high-risk group exhibits genomic instability, increased tumor stemness, and immune evasion, while the low-risk group was more sensitive to drugs such as sorafenib. This study highlights the potential pathways by which high oncogenic activity is associated with HCC progression, suggesting a profound link with single-cell metabolic‒immune crosstalk. The constructed RSF model offers a promising computational framework for risk stratification and provides hypothesis-generating insights that may inform future personalized treatment strategies for HCC patients.

Hepatocellular carcinoma↗

PubMed2026

Sex Hormone Receptors, HBV Integrations and Their Prognostic Predictive Value Among Hepatocellular Carcinoma Patients.

Hepatocellular carcinoma (HCC) related to hepatitis B virus (HBV) infection predominantly affects males, yet few studies have investigated the association between sex hormones and HBV integrations, and their involvement in HCC prognosis. We assessed estrogen receptor alpha (ERα) and androgen receptor (AR) expression via immunohistochemistry on tissue microarrays constructed from 426 HBV-related HCC samples. HBV integration features were determined using HBV-captured sequencing data. Logistic regression models were utilized to evaluate the association between sex hormone receptor expression level and HBV integration features. Cox regression models, combined with machine learning (ML) methods, were implemented to investigate the prognostic value of sex hormone receptors and HBV integrations concerning overall survival. We found high AR expression level was significantly associated with higher HBV integration levels (adjusted odds ratio [aOR] = 1.84, 95% confidence interval [CI]: 1.09-3.11, P for trend = 0.012), TERT integration (aOR = 2.34, 95% CI: 1.16-4.74, P for trend = 0.047), intergenic integration (aOR = 2.25, 95% CI: 1.20-4.24, P for trend = 0.021), and promoter integration (aOR = 1.81, 95% CI: 1.00-3.31, P for trend = 0.034). The inclusion of sex hormone receptors and HBV integrations in the predictive models led to improvements across all performance metrics in the Cox regression analyses (AUC improvement: 0.014 [Training], 0.026 [Validation]) and the ML (AUC improvement: 0.022 [Training]), although a slight deterioration in performance was noted in the ML validation set. The results suggested a relationship between AR expression level and HBV integration events, as well as the potential utility of HBV integration biomarkers and sex hormone receptor profiles in assessing post-surgical prognosis among HCC patients.

Humans↗

PubMed2026

Multimodal Analysis Reveals Aberrant Expression of SUMO2 and Its Significant Association With Key Mechanisms of Metabolic Pathways in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. However, the role of small ubiquitin-like modifier 2 (SUMO2), a core member of the small ubiquitin-like modifier (SUMO) family, regarding its expression patterns and metabolism-related functions in HCC remains inadequately understood. METHODS: A multidimensional analytical framework was applied, integrating immunohistochemistry (153 HCC vs. 21 non-HCC samples), proteomics (159 paired samples), bulk transcriptomics (3240 HCC vs. 2267 non-HCC samples), single-cell RNA sequencing (RNA-seq) (10 HCC vs. 8 non-HCC samples), spatial transcriptomics, and external CRISPR/Cas9 functional genomics data. Systematic analyses included standardized mean difference (SMD), pathway enrichment, pseudotime trajectory inference, in silico knockout, cell-cell communication, metabolic flux scoring, immune infiltration, clinical correlation, drug sensitivity prediction, and molecular docking. RESULTS: At the protein level, immunohistochemistry (nuclear positivity) and external proteomic data collectively demonstrated consistent SUMO2 overexpression in HCC. Consistent upregulation was also observed at the mRNA level across large-scale cohorts. Single-cell RNA-seq and spatial transcriptomics localized SUMO2 enrichment to malignant hepatocytes and tumor-dominant regions. CRISPR-mediated SUMO2 knockout suppressed proliferation in multiple HCC cell lines. Mechanistically, high SUMO2 expression was significantly associated with metabolic reprogramming involving glycolysis/gluconeogenesis, pyruvate metabolism, and the tricarboxylic acid cycle. SUMO2-high malignant hepatocyte subpopulations exhibited enhanced activity of the macrophage migration inhibitory factor signaling axis and enhanced iron-sensor interactions. Further, the immune infiltration analysis revealed a negative correlation between SUMO2 expression and M1 macrophages and a positive correlation between follicular helper T cells and regulatory T cells. Clinically, elevated SUMO2 levels were found to be associated with adverse prognostic features. Furthermore, high SUMO2 expression was associated with increased sensitivity to dasatinib, and molecular docking simulations predicted potential binding between SUMO2 and dasatinib, with a Vina score of -8.5 kcal/mol. CONCLUSIONS: SUMO2 is aberrantly expressed at the protein, mRNA, single-cell, and spatial transcriptomic levels in HCC and is significantly associated with metabolic reprogramming and altered migration inhibitory factor (MIF)-mediated intercellular communication, suggesting its potential as a novel biomarker for diagnosis and treatment.

Humans↗

PubMed2026

Construction of molecular signatures based on the co-expression network of NECSO-related gene TRPM4 and its prognostic value in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) demonstrates significant prognostic variability that is not entirely accounted for by traditional staging systems. Necrosis by sodium overload (NECSO) is an emerging programmed cell death pathway, but its clinical relevance in HCC remains undefined. Therefore, this study aimed to identify TRPM4-associated core genes, develop and validate a prognostic signature, and investigate its relationship with the tumor immune microenvironment, tumor mutational burden, and single-cell expression patterns in HCC. METHODS: We integrated transcriptomic, clinical, and mutational datasets from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) (n=421) and Gene Expression Omnibus (GEO) cohorts (n=115) to identify genes co-expressed with TRPM4-a key NECSO mediator-and those differentially expressed in HCC. A prognostic signature was developed using least absolute shrinkage and selection operator (LASSO)-Cox regression and validated through survival analysis, time-dependent receiver operating characteristic (ROC) curves, and multivariate Cox regression analysis. The immune landscape was characterized using CIBERSORT, somatic mutation data were used to calculate tumor mutational burden (TMB) and assess its correlation with the risk score, and single-cell RNA sequencing (scRNA-seq) resolved cell-type-specific expression patterns. RESULTS: From 294 TRPM4-associated core genes, we identified an 11-gene signature (BRSK1, MMP1, GRIN2D, GP6, MYOM2, N4BP3, CCDC112, TSEN54, MAP3K9, SPP1, B3GNT4) that independently predicted overall survival (OS) (hazard ratio =5.419, P<0.001) with areas under the curve (AUCs) of 0.779, 0.693, and 0.701 at 1, 3, and 5 years. These values were superior or comparable to conventional clinicopathologic variables after direct comparison. High-risk patients exhibited an immunosuppressive microenvironment, characterized by enrichment of M0 macrophage, a higher M2/M1 ratio (P<0.001) and distinct immune checkpoint profiles. When integrated with TMB, the prognostic stratification was further refined: high-TMB/high-risk patients had poorest outcomes (median OS, 15.3 months), while low-TMB/low-risk patients had the most favorable survival (median OS, 68.7 months). Single-cell analysis revealed that MMP1 was induced in cancer-associated fibroblasts (CAFs) and SPP1 was downregulated in macrophages, single-cell risk scores confirmed TAFs and macrophages as the main contributors to the prognostic model. CONCLUSIONS: The TRPM4-centered 11-gene signature provides robust and independent prognostic stratification in HCC by integrating immune, mutational, and single-cell features. This signature serves as a potential tool for prognostic evaluation and may help inform immunotherapeutic strategies for HCC.

Hepatocellular carcinoma (HCC)↗

PubMed2026

scRNA-seq and bulk RNA-seq reveal the characteristics of macrophage copper metabolism and establish a risk signature in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent malignancy with an urgent need for improved prognostic stratification and treatment-response prediction. This study aimed to explore a macrophage copper metabolism-associated prognostic model and to investigate the relationship between this risk model and the tumor immune microenvironment. METHODS: The FindClusters function was used to analyze cell clusters, and CellChat and CellPhoneDB/LIANA were employed for cell-cell communication analysis. Copper metabolism-related genes were sourced from the MSigDB database. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis, and a nomogram was constructed by integrating the prognostic model with clinicopathological factors. Additional analyses were performed to map the seven model genes in single-cell data, assess model uncertainty and robustness, evaluate macrophage/copper/cuproptosis-related transcriptional programs, and examine the correlations between risk score, immune infiltration and predicted drug sensitivity. RESULTS: Using single-cell RNA sequencing (scRNA-seq) data, we identified four macrophage subpopulations. Macrophages with high SPP1 expression showed close interaction with T cell populations and were associated with copper ion metabolism. By incorporating 141 copper metabolism-related genes and using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort, we constructed a seven-gene risk prediction model. Additional single-cell mapping showed that the model genes were detectable in the HCC single-cell dataset and showed a macrophage-associated expression pattern. The model showed moderate prognostic discrimination in TCGA-LIHC, whereas its external performance was heterogeneous and remained evaluable across external cohorts, with performance varying among datasets. Immune and mechanism-related analyses suggested that the risk signature was associated with macrophage-related infiltration, copper metabolism and cuproptosis-related transcriptional programs. Drug sensitivity analysis nominated Daporinad as a computationally predicted candidate compound, supporting Daporinad as a pharmacogenomic candidate for follow-up investigation. CONCLUSIONS: By integrating scRNA-seq and bulk RNA sequencing (RNA-seq) data, we constructed a macrophage copper metabolism-associated prognostic signature for HCC. The risk score was associated with survival, immune microenvironment features and predicted drug response, providing a transcriptomic framework for risk stratification and therapeutic hypothesis generation.

Hepatocellular carcinoma (HCC)↗

PubMed2026

Comprehensive In Silico Analysis Identifies MSTO1 and LIG1 as Candidate Biomarkers With Diagnostic and Prognostic Relevance in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and remains a major cause of cancer-related mortality worldwide. Its poor clinical outcomes are largely attributed to late-stage diagnosis and the limited accuracy of currently available diagnostic and prognostic biomarkers. Therefore, identifying novel molecular markers with improved sensitivity, specificity, and therapeutic relevance is essential for enhancing early detection and guiding personalized treatment strategies. AIMS: To identify and prioritize novel candidate HCC biomarkers with diagnostic and prognostic value and potential therapeutic vulnerability using integrated multi-omics, survival, functional dependency, and tumor microenvironment analyses. METHODS AND RESULTS: We examined the mRNA and protein expression levels of 8 DEGs in HCC tissues in the TCGA and CPTAC datasets using UALCAN, which showed that MSTO1 and LIG1 were overexpressed consistently in HCC relative to normal liver tissues. Moreover, elevated expression levels of these genes were significantly associated with higher tumor grade and advanced stage. Kaplan-Meier plotter survival data confirmed that increased expression of MSTO1 and LIG1 was associated with poorer overall survival. The DepMap CRISPR knockout data confirmed a functional dependency of both genes in HCC cell lines. CBioPortal analyses provided characterization of genomic alterations and enabled enrichment analysis of co-expressed genes, and the TCGA-UALCAN pan-cancer analyses supported the assessment of tissue specificity across tumor types. TIMER3 analyses linked candidate gene expression with immune cell infiltration patterns. Diagnostic performance by ROC analysis showed excellent discrimination for MSTO1 (AUC = 0.987) and good discrimination for LIG1 (AUC = 0.897). Multivariate Cox regression with Benjamini-Hochberg FDR correction across the eight genes supported MSTO1 as a candidate independent prognostic factor after adjustment for tumor stage, grade, etiology, age, and sex (HR = 1.29, p = 0.035), whilst LIG1 showed no independent prognostic value. Promoter methylation of MSTO1 and ADH4, assessed via UALCAN, showed that both genes were significantly differentially methylated in the promoter region of primary HCC tissues compared with normal liver tissues. Our study also confirmed the biological and clinical relevance of established HCC biomarkers: TERT, IRAK1, and ADH4. CONCLUSION: MSTO1 and LIG1 emerged as candidate diagnostic biomarkers in HCC. Additionally, MSTO1 showed a candidate prognostic association with overall survival that remained significant after adjusting for tumor stage, grade, and etiology, as well as patients' age, but not after further adjustment for AFP status. Functional data also highlighted MSTO1 as a candidate therapeutic dependency. On the other hand, LIG1 showed no independent prognostic association in either multivariate model. Their differential expression and functional essentiality in HCC cell lines highlighted their value for further experimental and independent-cohort validation before potential integration into biomarker development pipelines aimed at improving early detection and targeted therapy in HCC.

Humans↗

PubMed2026

Kynurenine metabolism-related gene signature for prognostic stratification in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major global health burden with high mortality rates and limited therapeutic options. The identification of reliable biomarkers for early diagnosis and prognosis prediction is urgently needed. Kynurenine metabolism, a critical pathway in immune regulation and tumor progression, has been implicated in various cancers. However, its prognostic value in HCC has not been fully elucidated. This study aimed to develop a prognostic risk model based on kynurenine metabolism-related genes (KMRGs) for HCC patients. METHODS: Transcriptomic and clinical data of HCC patients were retrieved from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. Survival analysis and functional enrichment analysis were conducted to validate the predictive performance of the model and to investigate the underlying mechanisms. ALDH8A1 was ultimately identified as a target gene based on survival analysis, and its impact on tumor cell migration was assessed using the HCC cell line. RESULTS: A prognostic model based on seven KMRGs was established. The high-risk group exhibited significantly worse overall survival compared to the low-risk group. Functional enrichment analysis in high-risk patients highlighted significant enrichment in core biological processes, including spliceosome assembly and ribonucleoprotein complex biogenesis. Furthermore, a nomogram integrating the risk score and clinical pathological features was developed, demonstrating moderate predictive performance for HCC prognosis. CONCLUSIONS: This study successfully constructed a prognostic risk model based on seven KMRGs, providing a valuable tool for predicting clinical outcomes in HCC patients. These findings highlight the potential role of kynurenine metabolism in HCC progression and offer new insights for future therapeutic strategies.

ALDH8A1↗

PubMed1979

Ultrastructural morphology of three-dimensional colonies of cells derived from a hepatocellular carcinoma.

Cultured hepatocellular carcinoma cells were studied during anchorage-independent growth in semi solid medium (Methocel). The regular occurrence of mitotic figures both at the surface and within the colonies precludes the possibility of such colonies being formed by re-aggregation. The estimated population doubling time in the three-dimensional (3-D) colonies is consistent with those two-dimensional of (2-D) colonies. Structures resembling bile canaliculi were observed between the closely opposed membranes from the well packed adjacent cells. Cell surface and ultrastructural features of the colonies and individual cells are presented and comparisons made with 2-D growth of normal and malignant liver cells in vitro. The formation of 3-D colonies may not only be an assay for transformed cells but also for predicting the type of tumors produced by re-innoculation of the in vitro transformed cells.

Animals↗

PubMed2025

In Vivo CRISPR Activation Screening Reveals Chromosome 1q Genes VPS72, GBA1, and MRPL9 Drive Hepatocellular Carcinoma.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) frequently undergoes regional chromosomal amplification, resulting in elevated gene expression levels. We aimed to elucidate the role of these poorly understood genetic changes by using CRISPR activation (CRISPRa) screening in mouse livers to identify which genes within these amplified loci are cancer driver genes. METHODS: We used data from The Cancer Genome Atlas to identify that frequently copy number-amplified and up-regulated genes all reside on human chromosomes 1q and 8q. We generated CRISPRa screening transposons that contain oncogenic Myc to drive tumor formation. We conducted CRISPRa screens in vivo in the liver to identify tumor driver genes. We extensively validated the findings in separate mice and performed RNA sequencing analysis to explore mechanisms driving tumorigenesis. RESULTS: We targeted genes that frequently undergo amplification in human HCC using an in vivo CRISPRa screening system in mice, which induced extensive liver tumorigenesis. Human chromosome 1q genes Zbtb7b, Vps72, Gba1, and Mrpl9 emerged as drivers of liver tumorigenesis. In human HCC there is a trend in correlation between levels of MRPL9, VPS72, or GBA1 and poor survival. In validation assays, activation of Vps72, Gba1, or Mrpl9 resulted in extensive liver tumorigenesis and decreased survival in mice. RNA sequencing revealed different mechanisms driving HCC, with Mrpl9 activation altering genes functionally related to mitochondrial function, Vps72 levels altering phospholipid metabolism, and Gba1 activation enhancing endosomal-lysosomal activity, all leading to promotion of cellular proliferation. Analysis of human tumor tissues with high levels of MRPL9, VPS72, or GBA1 revealed congruent results, indicating conserved mechanisms driving HCC. CONCLUSIONS: This study reveals chromosome 1q genes Vps72, Gba1, and Mrpl9 as drivers of HCC. Future efforts to prevent or treat HCC can focus on these new driver genes.

Animals↗

PubMed2025

Genome-wide CRISPR Screening Identifies NFκB and c-MET as Druggable Targets to Sensitize Lenvatinib Treatment in Hepatocellular Carcinoma.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC), the dominant form of liver cancer, is a leading cause of cancer death worldwide. Sorafenib and lenvatinib have long been the 2 limited options of first-line treatments for patients with unresectable advanced HCC. However, the single-drug treatment strategy only shows modest survival benefit, mostly because of the survival ability of cancer cells to activate alternative pathways for compensation. In this study, we aim to identify druggable targets contributing to lenvatinib resistance and evaluate the efficacy of combining respective inhibitors and lenvatinib on HCC. METHODS: Genome-scale clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 knockout library screening was applied on the vehicle group and lenvatinib treatment group. Identified druggable candidates were validated individually on HCC cell models. Therapeutic effects of the combined treatment of inhibitors of candidate genes and lenvatinib were evaluated in vitro and in vivo. RESULTS: We successfully identified NFKB1 and MET as critical drivers for the development of lenvatinib resistance in HCC cells. By perturbing the 2 genes with either CRISPR knockout or RNA interference approaches, lenvatinib treatments were significantly sensitized. Moreover, using small molecules QNZ and cabozantinib to target NFKB1 and MET, respectively, this together with lenvatinib could synergistically induce apoptosis and suppress HCC growth in vitro and in vivo. CONCLUSION: Our results demonstrated that genome-wide CRISPR/Cas9 screening is a powerful tool for the design of rational combinational cancer therapy and provided candidate genes possible for combined treatments with lenvatinib to improve therapy efficacy.

Carcinoma, Hepatocellular↗

PubMed2026

Unlocking the potential of bacteriophage-based therapeutic gene delivery in hepatocellular carcinoma.

Liver cancer, mainly hepatocellular carcinoma (HCC), remains a global health burden marked by poor prognosis with limited therapeutic efficacy, and high recurrence rates. HCC remains one of the most lethal malignancies worldwide, with limited therapeutic options and high resistance to conventional treatments. Despite low therapeutic efficacy, molecular heterogeneity, treatment resistance and high recurrence rate, hepatocellular carcinoma (HCC) is still a significant health problem worldwide. These restrictions have stimulated the research of focused methods for delivering therapeutic genetic payload into cancer cells. Bacteriophages have been gaining growing attention as an emerging delivery platform due to their genetic versatility, ease of engineering, ability to be surface modified and payload targeted. In this narrative review, the therapeutic potential of engineered bacteriophages in the context of HCC therapy is critically analyzed focusing on phage display-mediated tumor targeting, phage-mediated intracellular gene delivery, TRAIL gene delivery, and CRISPR/Cas-based therapeutic strategies. It has been previously noted in the literature that phage display can be used to attach tumor-targeting ligands to the surface of a phage, which may aid in the recognition of receptors at the tumor site and promote targeted delivery to the receptor. Therapeutic application is stunted by inefficient trafficking to the cytosol, endosomal degradation, immune recognition and clearance, vector stability, manufacturing scalability and regulatory issues. In conclusion, engineered bacteriophages are a promising and versatile tool for targeted gene delivery in HCC but more mechanistic, preclinical and translational research is needed to prove their therapeutic effectiveness and clinical usefulness for this purpose.

Humans↗

PubMed2026

Integrated Bioinformatics Analysis Revealing that the NSDHL Gene Might Be Associated with the Progression of Western HFD/SW-Induced Hepatocellular Carcinoma.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC) remains a significant global health concern. However, the etiology and pathogenesis of HCC have yet to be fully elucidated. Previous studies have indicated a close association between obesity and the occurrence and progression of HCC. The objective of this study was to employ bioinformatics strategies in order to explore key genes associated with the clinical diagnosis and prognosis of HCC induced by a Western high-fat diet and sugar water (HFD/SW). MATERIALS AND METHODS: We obtained the expression profile chip data GSE197884 from the Gene Expression Omnibus (GEO) database. Subsequently, “DESeq” and “Limma” R packages were employed to identify differentially expressed genes (DEGs) while constructing a co-expressed gene network using weighted gene co-expression analysis (WGCNA). Functional enrichment analyses were then carried out, followed by the construction of a protein-protein interaction (PPI) network to uncover core genes. The core genes were confirmed through data retrieved from The Cancer Genome Atlas (TCGA) database in order to determine their status as hub genes. Finally, survival and tumor immune infiltration analyses were performed to unveil the prognostic significance of these hub genes. RESULTS: In total, 126 intersection targets were retrieved through the Venn diagram. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed that the DEGs were primarily related to the proliferation and apoptosis of HCC cells, the digestion and metabolism of liver cells, the HCC tumor microenvironment, and immune response. The PPI network analysis identified 11 core targets, among which seven hub genes, including NSDHL, MVK, SQLW, GCAT, ALAS2, GLDC, and AGXT, were obtained after TCGA database validation. Furthermore, it was found that NSDHL was closely associated with the clinical diagnosis and prognosis of HCC induced by HFD/SW and also affected the cellular immune infiltration in the HCC tumor microenvironment. CONCLUSION: The present study demonstrated a significantly elevated expression of NSDHL in HCC tissues, suggesting its potential as a specific biomarker for precise clinical diagnosis and prognosis assessment of HCC induced by HFD/SW.

Computational Biology↗

PubMed2026

Tumor Mutational Concordance and Recurrence Timing in Hepatocellular Carcinoma.

INTRODUCTION: In hepatocellular carcinoma (HCC), intrahepatic recurrence includes true recurrence from clonal relapse and multicentric recurrence from de novo tumorigenesis. Recurrence timing is used to distinguish these types; however, its accuracy remains unclear. This study aimed to classify recurrent tumors based on somatic mutational concordance and assess the validity of recurrence timing. METHODS: Whole-exome sequencing was performed on paired primary and recurrent HCC tumors from 49 patients enrolled in a prospective institutional omics project. Tumors with ≥ 10 shared somatic mutations were classified as true recurrence. Clinicopathological features, recurrence timing, driver mutation patterns, and survival outcomes were compared between recurrence types. Mutational concordance was quantified using shared variant counts and the Jaccard similarity index. RESULTS: Of the 49 patients, 22 (44.9%) showed true recurrence and 27 (55.1%) had multicentric recurrence. Multicentric recurrence tumors harbored no shared variants or only a single shared variant with the primary tumor. True recurrence was associated with significantly higher concordance in histological differentiation and Edmondson-Steiner grading and greater retention of CTNNB1, TP53, ARID1A, and KEAP1 mutations. The number of shared variants (median: 115 vs. 0, and p < 0.001) and the Jaccard index (median: 0.44 vs. 0.00 and p < 0.001) were significantly higher in the true recurrence group. Recurrence timing was inconsistently correlated with mutational concordance, although a 3-year cutoff yielded significant separation. CONCLUSION: Recurrence timing alone insufficiently reflects clonal relationships. Genomic profiling offers a reliable framework for distinguishing between recurrence types and guiding HCC management.

clonal relapse↗

PubMed1975

A rare case of megaloblastic anaemia caused by disturbances in the plasma cobalamin binding proteins in a patient with hepatocellular carcinoma.

A patient with hepatocellular carcinoma, megaloblastic anaemia and increased concentration of serum cobalamin is described. Plasma TC I was increased to 10,000 times the normal concentration, thus explaining the increased concentration of serum cobalamin and a false Schilling test. The increase in plasma TC I in concurrence with undetectable amounts of plasma TC II was a likely explanation for the anaemia. The electron microscopic picture of the hepatocellular carcinoma was in accordance with TC I being produced by the tumour cells.

Anemia, Macrocytic↗

PubMed2026

Circulating Methylated SEPT9 for Detection of Hepatocellular Carcinoma in Cirrhosis.

IMPORTANCE: Hepatocellular carcinoma (HCC) surveillance in patients with cirrhosis remains suboptimal, with inadequate early-stage detection. α-Fetoprotein (AFP) demonstrates insufficient sensitivity. Circulating methylated septin 9 (SEPT9) has shown diagnostic promise. OBJECTIVE: To determine whether methylated SEPT9 improves detection of HCC when combined with AFP in patients with cirrhosis undergoing surveillance. DESIGN, SETTING, AND PARTICIPANTS: In this prospective, cross-sectional, diagnostic accuracy study, patients with cirrhosis undergoing routine HCC surveillance with ultrasonography and AFP were enrolled at 2 French academic centers from February 2018 through October 2024. HCC was diagnosed per international guidelines with centralized radiologic review, blinded to methylated SEPT9 results. Data were analyzed from October 2025 to January 2026. EXPOSURES: Plasma methylated SEPT9 was analyzed from 3 independent plasma aliquots and classified by number of positive replicates (single-positive, double-positive, or triple-positive). Serum AFP was evaluated at a threshold of 20 ng/mL. Biomarkers were evaluated individually and in combination using disjunction logic (tier 1; maximizing sensitivity) or conjunction logic (tier 2; maximizing specificity). MAIN OUTCOMES AND MEASURES: The primary outcome was the presence of HCC at enrollment. The primary end point was comparison of the area under the receiver operating characteristic curve (AUROC) between methylated SEPT9 and AFP. Secondary end points included diagnostic performance stratified by Barcelona Clinic Liver Cancer (BCLC) stage. RESULTS: Among 574 participants, 414 (72.1%) were male, and the median (IQR) age was 63 (57-70) years. A total of 118 had HCC, including 51 (43.2%) with BCLC stage 0-A. Methylated SEPT9 outperformed AFP (AUROC: 0.79 [95% CI, 0.74-0.84] vs 0.71 [95% CI, 0.66-0.76], respectively; P = .002; posterior probability of superiority >99.8%). Tier 1a (at least single-positive methylated SEPT9 or AFP >20 ng/mL) achieved 87.8% (95% CI, 81.6-93.5) sensitivity and a negative likelihood ratio of 0.2 (95% CI, 0.1-0.3). Among 64 HCC cases missed by AFP, tier 1a recovered 50 (78%). For BCLC 0-A disease, tier 1a sensitivity was 74.5% (95% CI, 62.2-86.5) vs 23.5% (95% CI, 12.5-35.8) for AFP, 3.2-fold increase. Tier 2 (triple-positive methylated SEPT9 and AFP >20 ng/mL) achieved 99.6% (95% CI, 98.9-100) specificity, a positive likelihood ratio of 76.0 (95% CI, 26.9-181.0), and a diagnostic odds ratio of 112.1 (95% CI, 37.8-294.7). CONCLUSIONS AND RELEVANCE: In this diagnostic study, combining methylated SEPT9 with AFP substantially improved HCC detection in patients with cirrhosis, particularly for early-stage disease amenable to curative treatment. Prospective studies are needed to determine whether improved detection translates into survival benefit.

Humans↗