Objective: Significant advancements have been made in hepatocellular carcinoma (HCC) therapeutics, such as immunotherapy for treating patients with HCC. However, there is a lack of reliable biomarkers for predicting the response of patients to therapy, which continues to be challenging. Cancer stem cells (CSCs) are involved in the oncogenesis, drug resistance, and invasion, as well as metastasis of HCC cells. Therefore, in this study, we aimed to create an mRNA expression-based stemness index (mRNAsi) model to predict the response of patients with HCC to immunotherapy.Methods: We retrieved gene expression and clinical data of patients with HCC from the GSE14520 dataset and the Cancer Genome Atlas (TCGA) database. Next, we used the “one-class logistic regression (OCLR)” algorithm to obtain the mRNAsi of patients with HCC. We performed “unsupervised consensus clustering” to classify patients with HCC based on the mRNAsi scores and stemness subtypes. The relationships between the mRNAsi model, clinicopathological features, and genetic profiles of patients were compared using various bioinformatic methods. We screened for differentially expressed genes to establish a stemness-based classifier for predicting the patient’s prognosis. Next, we determined the effect of risk scores on the tumor immune microenvironment (TIME) and the response of patients to immune checkpoint blockade (ICB). Finally, we used qRT-PCR to investigate gene expression in patients with HCC.Results: We screened CSC-related genes using various bioinformatics tools in patients from the TCGA-LIHC cohort. We constructed a stemness classifier based on a nine-gene (PPARGC1A, FTCD, CFHR3, MAGEA6, CXCL8, CABYR, EPO, HMMR, and UCK2) signature for predicting the patient’s prognosis and response to ICBs. Further, the model was validated in an independent GSE14520 dataset and performed well. Our model could predict the status of TIME, immunogenomic expressions, congenic pathway, and response to chemotherapy drugs. Furthermore, a significant increase in the proportion of infiltrating macrophages, Treg cells, and immune checkpoints was observed in patients in the high-risk group. In addition, tumor cells in patients with high mRNAsi scores could escape immune surveillance. Finally, we observed that the constructed model had a good expression in the clinical samples. The HCC tumor size and UCK2 genes expression were significantly alleviated and decreased, respectively, by treatments of anti-PD1 antibody. We also found knockdown UCK2 changed expressions of immune genes in HCC cell lines.Conclusion: The novel stemness-related model could predict the prognosis of patients and aid in creating personalized immuno- and targeted therapy for patients in HCC.

Ferroptosis is a form of regulated cell death, which is dependent on iron metabolism imbalance and characterized by lipid peroxidation; it plays a crucial role in various pathological processes. Studies have shown that the occurrence of ferroptosis is closely associated with the progression of hepatocellular carcinoma (HCC). Ferroptosis is involved in regulating the lipid metabolism, iron homeostasis, mitochondrial metabolism, and redox processes in HCC. Additionally, ferroptosis plays a key role in HCC tumor immunity by modulating the phenotype and function of various immune cells in the tumor microenvironment, affecting tumor immune escape and progression. Ferroptosis-induced lipid peroxidation and oxidative stress can promote the polarization of M1 macrophages and enhance the pro-inflammatory response in tumors, inhibiting immune suppressive cells such as myeloid-derived suppressor cells and Treg cells to disrupt their immune suppression function. The expression regulation of ferroptosis-related molecules such as GPX4 and SLC7A11 not only affects the sensitivity of tumor cells to immunotherapy but also directly influences the activity and survival of effector cells such as T cells and dendritic cells, further enhancing or weakening host anti-tumor immune response. Targeting ferroptosis has demonstrated significant clinical potential in HCC treatment. Induction of ferroptosis by nanomedicine and molecular targeting strategies can directly kills tumor cells or enhances antitumor immune responses. The integration of multimodal therapies with immunotherapy further expands the application of targeting ferroptosis as a cancer therapy. This article reviews the relationship between ferroptosis and anti-tumor immune responses and the role of ferroptosis in HCC progression from the perspective of tumor immune microenvironment, to provide insights for the development of anti-tumor immune therapies based on targeting ferroptosis.

Hepatocellular carcinoma (HCC) remains one of the most prevalent and lethal malignancies worldwide, with survival rates still falling short of expectations. Emerging evidence highlights the pivotal roles of both m6A methylation and ferroptosis-related genes (FRGs) in HCC progression. However, the prognostic significance of m6A-modulated FRGs remains largely unexplored. In this study, we developed a novel prognostic signature based on m6A-regulated FRGs, identifying six key genes (VEGFA, FANCD2, ZFP69B, EIF2S1, SLC7A11, and SRXN1) through multivariate and LASSO Cox regression analyses. A high m6A-FRGs score was strongly associated with poor prognosis, and multivariate analysis confirmed it as an independent prognostic factor. Notably, the high-risk group exhibited increased expression of immune checkpoint genes and a higher frequency of gene mutations. Functional assays further demonstrated that silencing ZFP69B significantly suppressed liver cancer cell proliferation, migration, and invasion. Clinical validation in 144 HCC samples revealed that elevated ZFP69B expression correlated with worse patient outcomes. Moreover, qPCR analysis confirmed CLSPN and HNRNPR as downstream targets of ZFP69B. Collectively, our findings establish the m6A-FRGs signature as a powerful prognostic tool for HCC and identify ZFP69B as a promising therapeutic target, warranting further investigation.

Background: Lon protease 1 (LONP1), an adenosine triphosphate (ATP)-dependent protease encoded by nuclear DNA that is highly conserved, maintains the mitochondrial protein balance and regulates adaptive responses to cellular stress. LONP1 dysfunction ultimately results in various forms of cellular and tissue damage. The function of LONP1 in hepatocellular carcinoma (HCC) and how it affects HCC growth were investigated in this work. Methods: The RNA and protein expression levels of LONP1 were determined in paired HCC and adjacent tissue samples through real-time quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) staining. The correlation between LONP1 expression and clinical features was evaluated via statistical analysis. Overexpression (OE) and knockdown (KD) experiments, small RNA interference, Cell Counting Kit-8 (CCK8) and wound-healing assays, and animal experiments were employed to assess the potential mechanism by which LONP1 promotes the proliferation and migration of HCC cells both in vitro and in vivo. Results: In HCC samples, LONP1 expression was higher than in the equivalent surrounding tissues. Compared to patients with low LONP1 expression, individuals with high LONP1 expression had shorter disease-free survival and overall survival periods. Functionally, LONP1 facilitated the proliferation and migration of HCC cells, whereas LONP1 knockdown mitigated the growth of HCC subcutaneous tumors. Mechanistically, LONP1 affects the processes of ferroptosis and cuproptosis processes by regulating the stability of aconitase 2 (ACO2). Histological analysis showed that the expression of LONP1 in liver cancer tissues was significantly upregulated, accompanied by a decrease in the level of ACO2 protein (Hematoxylin-Eosin (HE) staining and IHC verification). Mitochondrial function experiments indicated that overexpression of LONP1 led to a significant decrease in mitochondrial membrane potential suggesting mitochondrial dysfunction and reduced susceptibility to ferroptosis. Conclusions: Our results suggest that LONP1 promotes HCC proliferation and migration by inhibiting ferroptosis and cuproptosis through the degradation of ACO2. Therefore, targeting LONP1 might be an effective therapeutic strategy to inhibit HCC growth.