Jul 2026· Journal of Cancer· Vol 17, pp. 1295 - 1317· 0 citations· 71 references
Medicine
TL;DR
This study identified numerous key genes linked to ferroptosis and metabolic reprogramming in HCC and developed a robust prognostic risk model that demonstrated good predictive performance for 1- and 3-year overall survival, with moderate performance for 5-year survival.
Abstract
Background Hepatocellular carcinoma (HCC) continues to impose a heavy global health burden, with high incidence and mortality. The disease is highly heterogeneous and is commonly detected at late stages, which compromises treatment outcomes. Ferroptosis and metabolic reprogramming are increasingly recognized as key processes in HCC development; however, their roles in disease progression and therapeutic response remain incompletely understood. This research aimed to identify genes related to ferroptosis and metabolic reprogramming (FPMRRGs) that may serve as putative biomarkers and therapeutic targets in HCC. Methods The Cancer Genome Atlas (TCGA), including 369 HCC specimens and 50 normal controls, along with two Gene Expression Omnibus (GEO) datasets (GSE10143 and GSE76427), were analyzed using R (v4.3.3). From a curated list of 451 FPMRRGs, differentially expressed genes (DEGs) between tumor and normal tissues were identified. Univariate Cox regression analysis was then conducted to explore their prognostic relevance and to define molecular subtypes of HCC. Specimens were categorized into 2 subtypes using ConsensusClusterPlus, and overall survival differences were evaluated via survival analysis. Functional and pathway enrichment analyses were conducted to investigate the functional roles of these genes. Immune-related features were evaluated using the Mann-Whitney U test. A prognostic risk model was constructed using least absolute shrinkage and selection operator (LASSO) regression followed by multivariate Cox analysis. Model performance was assessed using receiver operating characteristic (ROC) curves and calibration plots. Immune cell infiltration was estimated by single-sample GSEA, and pathway activity differences were examined using gene set variation analysis (GSVA). Results HCC specimens were divided into 2 molecular subtypes, which demonstrated obvious differences in overall survival and immune-related features, including immune checkpoint gene expression and tumor immune dysfunction and exclusion (TIDE) scores. A prognostic model based on 12 key FPMRRGs demonstrated good predictive performance for 1- and 3-year overall survival, with moderate performance for 5-year survival. The prognostic value and expression patterns of these genes were further validated across independent datasets. In addition, these genes were mainly enriched in pathways linked to fatty acid metabolism and HIF-1 signaling, and were closely associated with patterns of immune cell infiltration. Conclusions This study identified numerous key genes linked to ferroptosis and metabolic reprogramming in HCC and developed a robust prognostic risk model. Our results offer new insight into the molecular basis of HCC and highlight potential biomarkers for more individualized treatment approaches. Further studies, particularly those combining clinical validation with functional experiments, are required to verify these findings and examine the therapeutic potential of targeting these pathways.
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
AIM
Hepatocellular carcinoma (HCC) is the most common primary liver cancer in adults, with increasing incidence. It is helpful to establish a prognostic risk prediction model related to macrophage polarization and mitochondrial dysfunction associated with HCC.
METHODS
Cox and Least Absolute Shrinkage and Selection Operator (LASSO) regression, Gene Set Variation Analysis (GSVA) and Gene Set Enrichment Analysis (GSEA), protein-protein interaction (PPI) network.
RESULTS
A total of 7 model genes (EZH2, G6PD, HMGA2, MAGEB2, PYCR1, SLC7A11, and SPP1) were identified. And the LASSO-Cox model showed preliminary prognostic predictive performance in the TCGA-LIHC cohort (0.9 > AUC > 0.7), with decision curve analysis (DCA) showing clinical potential, particularly in the third year. GSEA revealed that genes associated with Liver hepatocellular carcinoma (LIHC) exhibited enrichment in functions and pathways, notably including FCGR3A Mediated IL10 Synthesis, etc. GSVA indicated multiple pathways were significant in both Low-Risk and High-Risk groups, such as the biocatamcm pathway (p < 0.05). The PPI Network shows connections among G6PD, SLC7A11, HMGA2, and EZH2, with GeneMANIA predicting their interactions with similar function genes.
CONCLUSION
Our study screened candidate prognostic genes associated with macrophage polarization and mitochondrial dysfunction based on bioinformatics analysis and established a prognostic model.
Bin-Bin Cheng, Wei-Ping Tu, Xiao-Yu Tu et al.· Discover Oncology· 0 citations
Identifying diagnostic and prognostic biomarkers and therapeutic targets for hepatocellular carcinoma (HCC) is essential to improve risk stratification, guide individualized treatment, and enhance therapeutic efficacy.The expression of SAMM50 (Sorting and Assembly Machinery Component 50) was initially analyzed in publicly accessible curated genomic and proteomic databases, such as the Cancer Cell Line Encyclopedia, the Human Protein Atlas, and other HCC-specific repositories. This analysis revealed differential expression patterns between HCC and non-neoplastic liver tissue. Subsequently, clinicopathological data and tissue specimens were collected from 200 HCC patients who underwent treatment at our institution. The protein and transcript levels of SAMM50 were experimentally measured in paired HCC and adjacent non-tumorous tissues using immunohistochemistry (IHC) and quantitative reverse transcription polymerase chain reaction (qRT-PCR). The association between SAMM50 expression and key clinicopathological features was further evaluated. Univariate and multivariate Cox proportional hazards analyses were performed to determine the independent prognostic value of SAMM50 expression in HCC. Based on these results, a reproducible and clinically applicable nomogram, supported by a forest plot, was constructed to facilitate prognostic prediction and support individualized therapeutic decision-making. Finally, in vitro and in vivo experiments were conducted to characterize the phenotypic alterations in HCC cells after SAMM50 knockdown, thereby confirming its involvement in critical oncogenic behaviors.This research demonstrated that the mRNA and protein levels of SAMM50 in HCC tissues were elevated compared to those in normal liver and adjacent tissues. Immunohistochemistry findings confirmed that SAMM50 protein levels were persistently higher in HCC tissues than in paired adjacent tissues. High expression of SAMM50 was correlated with unfavorable clinicopathological factors, encompassing pretreatment alpha-fetoprotein (AFP) levels, tumor size, T stage, American Joint Committee on Cancer (AJCC) stage, histological grade, and worse overall survival.Specifically, high expression of SAMM50 was linked to shorter overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS). Moreover, univariate and multivariate Cox analyses were conducted to investigate the association between SAMM50 expression and clinicopathological features in HCC patients and to identify independent prognostic factors. The area under the receiver operating characteristic (ROC) curve (AUC) for SAMM50 was 0.863, suggesting its potential as a diagnostic marker for HCC, though further validation in independent cohorts is needed. Silencing of SAMM50 inhibited HCC cell proliferation, migration, and invasion, promoted apoptosis in vitro, and suppressed HCC growth in vivo.This research demonstrates that SAMM50 shows potential diagnostic value for HCC, though this observation requires further validation in larger, independent, and prospective cohorts. The results of this study not only contribute to the evaluation of baseline data and risk stratification in HCC but also offer novel approaches for the development of precise treatment strategies and targeted therapies.
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.
Bo-Wen Wu, Feng-Hong Wang, Lei Zhang et al.· Mediators of Inflammation· 0 citations
LINC01607 contributes to HCC progression and ferroptosis-associated therapy resistance, at least in part through the p62–Keap1–Nrf2 pathway, supporting further investigation of LINC01607 as a potential therapeutic target.
Yuxin Zhang, Weiqi Xu, Fangling Cheng et al.· Cancer Drug Resistance· 0 citations
This study aimed to develop and validate a hypoxia-related gene signature for prognostic assessment in hepatocellular carcinoma (HCC) and to explore its associated biological characteristics and immune features. In addition, a self-established human tissue cohort was used to verify the expression stability of the identified signature genes. The TCGA-LIHC cohort was used as the training set to identify differentially expressed hypoxia-related genes associated with overall survival. Least absolute shrinkage and selection operator (LASSO) regression and Cox regression analyses were subsequently applied to construct a prognostic model. The predictive performance of the model was externally validated using the GSE14520 and GSE116174 cohorts. Functional enrichment and immune microenvironment analyses were performed to characterize the biological differences between risk groups. Furthermore, quantitative real-time PCR (qRT-PCR) was conducted in a human tissue cohort, including normal liver tissues, adjacent non-tumorous tissues, and HCC tissues, to validate the expression patterns of the four signature genes (TMEM45A, PPARGC1A, EFNA3, and STC2). A four-gene hypoxia-related prognostic signature was established and successfully stratified patients into high- and low-risk groups. Patients in the high-risk group exhibited significantly poorer overall survival in both the training and validation cohorts. Functional enrichment analyses revealed that high-risk tumors were associated with activation of pathways related to cell-cycle progression, MYC targets, epithelial–mesenchymal transition, and metabolic reprogramming. Immune analyses demonstrated increased M0 macrophage infiltration and elevated expression of multiple immune checkpoint genes in the high-risk group. qRT-PCR validation further confirmed the differential expression patterns of the four signature genes in human HCC tissues. This four-gene hypoxia-related signature demonstrated robust prognostic performance across multiple independent cohorts and was associated with distinct metabolic and immune characteristics in HCC. qRT-PCR validation further supported the expression stability of the identified genes in human tissues. These findings provide a useful framework for prognostic stratification and future investigation of hypoxia-related biological mechanisms and therapeutic strategies in HCC.
Chengting Wu, Yuanqin Du, Juhong Jia et al.· Discover Oncology· 0 citations