Jul 2026· Journal of experimental & clinical cancer research : CR· 0 citations
Medicine
TL;DR
The findings establish the NSUN6-SAV1-YAP axis as a key epitranscriptomic tumor-suppressive mechanism and support circulating NSUN6 as a potential biomarker for early risk stratification in HCC.
Abstract
Background
Portal vein tumor thrombus is a lethal complication of HCC for which effective biomarkers are urgently needed.
Methods
Through proteomic profiling, functional and mechanistic assays, and machine learning-based evaluation of serum NSUN6 in 472 HCC patients with external validation (n = 98), we characterized an epitranscriptomic regulator of HCC metastasis.
Results
NSUN6 was downregulated in PVTT and suppressed metastasis by catalyzing m⁵C modification of SAV1 mRNA, stabilizing its transcript and activating Hippo signaling. Furthermore, NSUN6 was released from HCC cells via extracellular vesicle-associated and non-canonical pathways. Circulating NSUN6 levels were inversely associated with metastasis in both discovery and validation cohorts, and lower levels predicted shorter metastasis-free survival.
Conclusion
Our findings establish the NSUN6-SAV1-YAP axis as a key epitranscriptomic tumor-suppressive mechanism and support circulating NSUN6 as a potential biomarker for early risk stratification in HCC.
Hepatocellular carcinoma (HCC) is widely recognized as one of the leading causes of cancer‐related deaths worldwide. Although advances in screening, diagnosis, and treatment have been made, reliable biomarkers are urgently needed to monitor the disease. This study aims to investigate the association between spermidine synthase (SRM) and clinicopathological characteristics, inflammatory responses, and immune infiltration in HCC. RNA‐seq data and clinical information for liver HCC (LIHC) were obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases to assess SRM expression. The correlation between SRM expression and immune infiltration was analyzed using the TIMER algorithm. Comprehensive analyses of immune checkpoints (ICPs), microsatellite instability (MSI), and tumor mutational burden (TMB) were performed using R‐based packages. KEGG analysis indicated SRM is involved in the IL‐17 signaling pathway. This association was further supported by experimental validation of key markers via qPCR and western blot. Functional studies, including in vivo experiments, are needed to establish a causal relationship. Our results show that SRM expression is significantly elevated in HCC tissues compared to adjacent nontumor tissues and associated with adverse clinicopathological features and poor prognosis. SRM expression was significantly correlated with immune infiltration levels in LIHC, involving 22 immune cell subtypes, particularly tumor‐associated macrophages (TAMs; CD86 and IL10). Moreover, SRM expression was closely associated with ICPs, TMB, and MSI. Based on transcriptomic data, KEGG pathway analysis of SRM‐associated differentially expressed genes revealed significant enrichment in the IL‐17 signaling pathway. These in vitro findings suggest a potential association among SRM, IL‐8 expression, and pathways related to tumor progression and immune modulation, although further in vivo studies are required to confirm these observations. However, in vivo studies using animal models are required to evaluate whether targeting SRM has therapeutic effects on HCC and to further validate these mechanistic findings.
Bo-Wen Wu, Feng-Hong Wang, Lei Zhang et al.· Mediators of Inflammation· 0 citations
Objective: Hepatocellular carcinoma (HCC) has poor prognosis and variable immunotherapy response. Resveratrol exhibits anti-HCC activity, but its direct targets and association with immunotherapy response are unclear. This study identifies core resveratrol targets in HCC and evaluates their prognostic and predictive value. Methods: Resveratrol targets were intersected with TCGA-LIHC differentially expressed genes. A prognostic risk model was built using LASSO-Cox regression. Drug-target binding was assessed by molecular dynamics simulations and qRT-PCR. Single-cell and spatial transcriptomics, cell-cell communication, and a pan-immunotherapy cohort were used to investigate KIF11. An HCC mouse model validated immunomodulatory effects via flow cytometry. Results: Thirty-four resveratrol-associated targets were identified, enriched in metabolism pathways. A nine-gene risk model showed robust prognostic performance. Resveratrol stably binds to KIF11’s ATP-binding pocket. KIF11 is overexpressed in malignant hepatocytes and proliferating T cells; KIF11 + cells orchestrate VEGF-mediated microenvironment remodeling. High KIF11 expression correlated with poor prognosis but predicted superior survival in the immunotherapy cohort, a phenomenon attributed to the observation that KIF11-high tumors exhibit both enhanced immunogenicity and active immunosuppression. In vivo, resveratrol enhanced CD8 + T cell infiltration, proliferation, effector function, and central memory T cells, while reducing Tregs. Conclusion: KIF11 drives HCC progression and predicts immunotherapy response. It is a candidate direct resveratrol target and a potential biomarker for patient stratification in immune checkpoint therapy, although further experimental validation is warranted.
Yeying Wang, Shun Wan, Wan-Jia Qiao et al.· Journal of Hepatocellular Ca...· 0 citations
Hepatocellular carcinoma (HCC) poses a significant global health burden with limited therapeutic options, particularly for non-viral etiologies. The mitochondrial solute carrier SLC25A43 is implicated in cellular redox homeostasis, yet its role in HCC remains unclear. This study aimed to comprehensively investigate the expression pattern, clinical significance, biological function, and potential mechanisms of SLC25A43 in HCC. Utilizing multi-omics data from public databases (TCGA-LIHC, GEO, and HPA), we performed integrated bioinformatic analyses. SLC25A43 was consistently upregulated in HCC tissues compared with non-tumorous liver tissues and demonstrated strong diagnostic value (AUC = 0.861). High SLC25A43 expression was significantly associated with advanced tumor stage, metastasis, and adverse clinicopathological features. Survival analyses identified SLC25A43 as an independent prognostic risk factor for overall survival, progression-free interval, and disease-specific survival. Functional enrichment analyses suggested that SLC25A43 is involved in mitochondrial oxidative phosphorylation, energy metabolism, and immune-related pathways. Immune infiltration analyses using ssGSEA, xCell, and TIMER consistently revealed negative correlations between SLC25A43 expression and multiple antitumor immune cell populations, particularly CD8 + T cells. Experimental validation confirmed that SLC25A43 was significantly upregulated in HCC tissues at both mRNA and protein levels. Functional assays in Huh-7, Hep-LM3, MHCC97H, and LO2 cells demonstrated that SLC25A43 knockdown inhibited, whereas overexpression promoted, cell proliferation and migration. Rescue experiments further verified the specificity of these effects. Mechanistically, SLC25A43 regulated intracellular ATP production, ROS accumulation, and glutathione metabolism, indicating a role in redox homeostasis and energy metabolism. In addition, PBMC co-culture experiments showed that SLC25A43 suppressed CD8 + T-cell cytotoxic activity by reducing Granzyme B expression. A prognostic nomogram incorporating SLC25A43 exhibited favorable predictive performance and was successfully validated in two independent GEO cohorts. SLC25A43 is a novel diagnostic and prognostic biomarker for HCC. Its upregulation promotes tumor progression through metabolic reprogramming, redox homeostasis remodeling, and suppression of antitumor immune responses. These findings highlight SLC25A43 as a promising therapeutic target and provide new insights into the metabolic-immune regulatory network in hepatocellular carcinoma.
Dunzhen Chen, Li Yu, Xichang Zhou et al.· Scientific Reports· 0 citations
BACKGROUND & AIM
Microvascular invasion (MVI) is a critical prognostic risk factor in hepatocellular carcinoma (HCC). This study evaluated the performance of 5-hydroxymethylcytosine (5hmC) modifications in circulating cell-free DNA (cfDNA) in preoperative assessment of MVI.
METHODS
A total of 907 patients with HCC were enrolled from two centers, including 671 in the training cohort, 152 in the internal validation cohort, and 84 in the external validation cohort. Preoperative clinical data, laboratory parameters, and cfDNA-derived 5hmC profiles were collected. Feature selection was performed using XGBoost, and modeling was conducted using a multilayer perceptron (MLP) neural network. Survival analyses were performed to evaluate the prognostic significance of the MVI prediction model. RNA sequencing analysis was performed to explore the potential mechanism underlying the proposed model.
RESULTS
The 181-5hmC-modification signature demonstrated strong discriminatory performance, achieving an area under curve (AUC) of 0.852 in the training cohort, 0.862 in the internal validation cohort, and 0.864 in the external validation cohort, respectively. Univariate and multivariate analyses identified the α-fetoprotein (AFP) level (odds ratio [OR] 1.576, P = 0.039), Barcelona Clinical Liver Cancer (BCLC) stage (OR 3.051, P < 0.001), and the 5hmC signature (OR 46.891, P < 0.001) as independent predictors of MVI. The 5hmC signature demonstrated significantly higher predictive accuracy than AFP levels or BCLC stage alone. Survival analysis showed that the 5hmC signature significantly stratified both recurrence-free and overall survival in resectable HCC patients. Additionally, interpretability analysis based on RNA sequencing revealed that lower MVI prediction scores were associated with immune-related pathways and immune infiltration levels.
CONCLUSIONS
We developed and validated a circulating cfDNA-derived 5hmC signature that non-invasively predicts preoperative MVI status, with potential clinical utility in the management of resectable HCC.
IMPACT AND IMPLICATIONS
This study presents the first integration of cfDNA-derived 5hmC profiling with machine learning for preoperative MVI prediction in resectable HCC. The proposed 5hmC signature demonstrates potential for predicting MVI status and prognosis before surgery. Integration of RNA sequencing analysis provides biological support for the model's predictions, strengthening its clinical relevance. As a blood-based assay, this approach offers practical advantages for potential routine clinical implementation.
Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide and exhibits considerable biological heterogeneity in both molecular and clinical characteristics. The diverse molecular alterations and clinical manifestations of HCC indicate substantial heterogeneity across patient subgroups. This study aimed to identify novel therapeutic targets and predictive biomarkers associated with HCC using an integrative bioinformatics approach. High-throughput genomic datasets were obtained from the UCSC Xena browser to retrieve mRNA HTSeq-count data from the TCGA-HCC cohort. Gene co-expression network (GCN), protein–protein interaction network (PPIN), and enrichment analyses were performed to identify key dysregulated genes and their biological significance. Integrated network analyses identified three dysregulated hub genes, namely CXCR2, TLR2, and TLR4. Genomic alterations in these genes were further evaluated across tumor samples in the TCGA-HCC cohort. Kaplan–Meier (KM) survival analysis demonstrated that lower CXCR2 mRNA expression was significantly associated with poorer overall survival (OS) and recurrence-free survival (RFS). Furthermore, TIMER and UALCAN analyses revealed significant associations between CXCR2 expression and tumor purity, as well as immune cell infiltration levels, including T cells, macrophages, dendritic cells (DCs), and neutrophils. These findings suggest that CXCR2 is significantly associated with the immune microenvironment of HCC and represents a potential prognostic biomarker whose biological role warrants further mechanistic investigation.
S. Almatroodi, Tarique Sarwar, A. Rahmani· International Journal of Mol...· 0 citations
Summary The heterogeneity within the same AJCC TNM stage of gastric cancer necessitates robust prognostic biomarkers beyond conventional staging. By integrating transcriptomic data from 1,613 patients across eight cohorts, we developed an 11-gene lymph node metastasis gene signature (LMGS) using an ensemble learning strategy to overcome the instability of traditional models. LMGS robustly predicted survival (mean C-index = 0.619), providing incremental prognostic value beyond conventional AJCC staging. Single-cell and spatial transcriptomic analyses revealed LMGS enrichment in epithelial/immune cells at the tumor-normal interface. Integrative analysis nominated the transcription factor SPIB as a candidate regulator, which was specifically overexpressed in metastatic lesions. Our study provides a clinically relevant prognostic tool and identifies SPIB as a molecular marker associated with lymphatic dissemination.