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Background Hypoxia, a typical hallmark of solid tumors, exhibits an essential role in the progression of colorectal cancer (CRC), in which the dysregulation of long non-coding RNAs (lncRNAs) is frequently observed. However, the underlying mechanisms are not clearly defined. Methods The TCGA database was analyzed to identify differential lncRNA expression involved in hypoxia-induced CRC progression. qRT-PCR was conducted to validate the upregulation of lncRNA STEAP3-AS1 in CRC cell lines and tumor-bearing mouse and zebrafish models under hypoxia. ChIP-qRT-PCR was used to detect the transcriptional activation of STEAP3-AS1 mediated by HIF-1α. RNA-seq, fluorescent in situ hybridization, RNA pulldown, RNA immunoprecipitation, co-immunoprecipitation, immunofluorescence and immunoblot experiments were used to ascertain the involved mechanisms. Functional assays were performed in both in vitro and in vivo models to investigate the regulatory role of STEAP3-AS1 /STEAP3/Wnt/β-catenin axis in CRC proliferation and metastasis. Results Here, we identified a hypoxia-induced antisense lncRNA STEAP3-AS1 that was highly expressed in clinical CRC tissues and positively correlated with poor prognosis of CRC patients. Upregulation of lncRNA STEAP3-AS1 , which was induced by HIF-1α-mediated transcriptional activation, facilitated the proliferation and metastasis of CRC cells both in vitro and in vivo. Mechanistically, STEAP3-AS1 interacted competitively with the YTH domain-containing family protein 2 (YTHDF2), a N 6 -methyladenosine (m 6 A) reader, leading to the disassociation of YTHDF2 with STEAP3 mRNA. This effect protected STEAP3 mRNA from m 6 A-mediated degradation, enabling the high expression of STEAP3 protein and subsequent production of cellular ferrous iron (Fe 2+ ). Increased Fe 2+ levels elevated Ser 9 phosphorylation of glycogen synthase kinase 3 beta (GSK3β) and inhibited its kinase activity, thus releasing β-catenin for nuclear translocation and subsequent activation of Wnt signaling to support CRC progression. Conclusions Taken together, our study highlights the mechanisms of lncRNA STEAP3-AS1 in facilitating CRC progression involving the STEAP3-AS1 /STEAP3/Wnt/β-catenin axis, which may provide novel diagnostic biomarkers or therapeutic targets to benefit CRC treatment. Graphical abstract Hypoxia-induced HIF-1α transcriptionally upregulates the expression of lncRNA STEAP3-AS1 , which interacts competitively with YTHDF2, thus upregulating mRNA stability of STEAP3 and consequent STEAP3 protein expression. The enhanced STEAP3 expression results in production of cellular ferrous iron (Fe 2+ ), which induces the Ser 9 phosphorylation and inactivation of GSK3β, releasing β-catenin for nuclear translocation and contributing to subsequent activation of Wnt signaling to promote CRC progression.

BackgroundHeart failure (HF) is a major health threat, with aging and programmed cell death (PCD) playing key roles. However, the link between aging-related PCD (aging-PCD) genes and HF remains unclear.MethodsWe used ssGSEA and random forest to analyze PCD types in HF, identified aging-related PCDs via correlation analysis, and applied eight machine learning algorithms to develop a diagnostic model. SHAP and LIME were used to explain key features, and the relationship between the aging-PCD index and immune microenvironment was explored. Gene expression was verified by qRT-PCR, and the function of STEAP3 was further investigated in an H2O2-induced AC16 cell model. Ferroptosis-related changes were assessed by measuring reactive oxygen species (ROS), malondialdehyde (MDA), glutathione peroxidase (GSH-Px), and ferrous ion (Fe2+) levels.ResultsFerroptosis, autophagy, and necroptosis were strongly correlated with aging in HF. Eighteen differentially expressed aging-related PCD genes were identified. The LASSO model showed the best diagnostic performance. Significant differences in the immune microenvironment were observed between the aging-PCD index-high and index-low groups. A regulatory network of 15 key genes and 19 transcription factors was constructed. The qRT-PCR results validated the bioinformatics analysis. Functional experiments further suggested that STEAP3 may participate in ferroptosis-related injury in cardiomyocytes, potentially through glutathione metabolism (GPX4/SLC7A11 axis) and iron homeostasis.ConclusionWe identified aging-related PCD signatures in HF that may provide candidate biomarkers for further clinical validation.

Background Steatotic livers tolerate ischemia–reperfusion injury (IRI) poorly, increasing the risk of organ dysfunction. Ferroptosis is considered the initiating factor of organ IRI. Heme oxygenase oxygen-1 (HO-1)-modified bone marrow mesenchymal stem cells (BMMSCs) (HO-1/BMMSCs) can reduce hepatic IRI; however, the role of ferroptosis in IRI of steatotic grafts and the effect of HO-1/BMMSCs-derived exosomes (HM-exos) on ferroptosis remain unknown. Methods A model of rat liver transplantation (LT) with a severe steatotic donor liver and a model of hypoxia and reoxygenation (H/R) of steatotic hepatocytes were established. Exosomes were obtained by differential centrifugation, and the differentially expressed genes (DEGs) in liver after HM-exo treatment were detected using RNA sequencing. The expression of ferroptosis markers was analyzed. microRNA (miRNA) sequencing was used to analyze the miRNA profiles in HM-exos. Results We verified the effect of a candidate miRNA on ferroptosis of H/R treated hepatocytes, and observed the effect of exosomes knockout of the candidate miRNA on hepatocytes ferroptosis. In vitro, HM-exo treatment reduced the IRI in steatotic grafts, and enrichment analysis of DEGs suggested that HM-exos were involved in the regulation of the ferroptosis pathway. In vitro, inhibition of ferroptosis by HM-exos reduced hepatocyte injury. HM-exos contained more abundant miR-124-3p, which reduced ferroptosis of H/R-treated cells by inhibiting prostate six transmembrane epithelial antigen 3 (STEAP3), while overexpression of Steap3 reversed the effect of mir-124-3p. In addition, HM-exos from cell knocked out for miR-124-3p showed a weakened inhibitory effect on ferroptosis. Similarly, HM-exo treatment increased the content of miR-124-3p in grafts, while decreasing the level of STEAP3 and reducing the degree of hepatic ferroptosis. Conclusion Ferroptosis is involved in the IRI during LT with a severe steatotic donor liver. miR-124-3p in HM-exos downregulates Steap3 expression to inhibit ferroptosis, thereby attenuating graft IRI, which might be a promising strategy to treat IRI in steatotic grafts. Graphical Abstract

Renal cell carcinoma is particularly sensitive to ferroptosis, an iron-dependent non-apoptotic form of cell death. This mechanism does not require activation of caspase or the participation of other apoptotic effector molecules (such as BAX or BAK), nor is it accompanied by the morphological characteristics or biochemical processes of apoptosis. The STEAP3 gene was found because it promotes tumor apoptosis in prostate cancer, but its role in renal cell carcinoma has not been studied in depth. Through real-time quantitative polymerase chain reaction, we found that the expression of the STEAP3 gene was upregulated in renal cell carcinoma tissue samples and cell lines, and it was found to be highly expressed in renal cell carcinoma tissue through immunohistochemistry. This upregulation is related to poor survival and prognosis of patients. We used erastin, a ferroptosis inducer, found that renal cell carcinoma became more susceptible to ferroptosis after knocking down STEAP3. The results indicate that renal cell carcinoma cell lines with knocked down STEAP3 expression are more sensitive to ferroptosis, and this effect occurs through the p53/xCT pathway. In summary, our research helps to identify new biomarkers and provides new targets for the treatment of renal cell carcinoma.

Ferroptosis, a distinct type of regulated cell death, has been reported to be involved in the tumorigenesis of liver hepatocellular carcinoma (LIHC). However, the precise functions and potential mechanisms of ferroptosis in LIHC were still poorly understood. Herein, we investigated the biological roles of ferroptosis-related gene STEAP3 in LIHC. STEAP3 was previously proved to serve a key regulator in ferroptosis via mediating the iron metabolism. Comprehensive bioinformatics from several databases revealed that STEAP3 was significantly downregulated in LIHC tissues and exhibited the favorable prognostic significance in LIHC patients. The downregulated STEAP3 was further confirmed in two LIHC cells Huh7 and MHCC97H using real-time PCR and western blot. And STEAP3 overexpression significantly inhibited the cell proliferation in Huh7 and MHCC97H cells. In addition, clinical data identified the relationship between STEAP3 expression and several clinicopathological parameters of LIHC patients, including histologic grade, alpha fetal protein (AFP) concentration, etc. Receiver operation characteristic (ROC) curve revealed STEAP3 as a potential diagnostic biomarker for LIHC patients. Moreover, the co-expression network of STEAP3 was explored to gain a better insight into its underlying signaling pathways. Finally, aberrant STEAP3 might participate in varieties of immune-associated signatures in LIHC pathogenesis, including immunostimulators, immunoinhibitors, chemokines, and chemokine receptors. Taken together, these findings could enhance our knowledge regarding the inhibitory roles and underlying biological significance of STEAP3 in LIHC tumorigenesis.

Traditional investigations of viral infection mechanisms have predominantly relied on two-dimensional (2D) cell culture models, which lack the structural organization and physiological relevance of native tissues. These systems often fail to capture key features such as spatial cell–cell interactions, tissue-specific heterogeneity, and microenvironmental complexity that govern virus–host dynamics in vivo . To address these limitations, we established an integrative platform that combines the strengths of both 2D and three-dimensional (3D) models to investigate the role of six-transmembrane epithelial antigen of prostate 3 (STEAP3), a membrane ferrireductase, in regulating viral infection in human intestinal epithelium. The 2D system enabled high-resolution mechanistic interrogation of STEAP3-dependent viral entry processes, while the patient-derived 3D colon organoid model recapitulated the architectural and cellular complexity of intestinal tissue, allowing spatially resolved assessment of infection patterns. Using this integrated approach, we found that STEAP3 knockdown significantly increased viral entry and infection, particularly in enterocytes and enteroendocrine cells. To further mimic physiological conditions in human body, we developed a vascularized organoid-on-chip model, in which increased viral signals were observed within vascular lumens upon STEAP3 depletion, suggesting a protective role of STEAP3 in limiting viral dissemination. For efficient and multiplexed screening of antiviral mechanisms, we also fabricated a 3D-printed 27-well chip tailored for organoid culture. By leveraging the complementary advantages of both 2D and 3D systems, this study demonstrates the power of integrated biomimetic modeling platforms to investigate antiviral defense mechanisms and underscores their value for engineering physiologically relevant infection models.

Alzheimer's disease (AD) is a neurodegenerative disease whose origins have not been universally accepted. Numerous studies have demonstrated the relationship between AD and alcohol dependence; however, few studies have combined the origins of AD, alcohol dependence, and programmed cell death (PCD) to analyze the mechanistic relationship between the development of this pair of diseases. We demonstrated in previous studies the relationship between psychiatric disorders and PCD, and in the same concerning neurodegeneration-related AD, we found an interesting link with the Ferroptosis pathway. In the present study, we explored the bioinformatic interactions between AD, alcohol dependence, and Ferroptosis and tried to elucidate and predict the development of AD from this aspect. We selected the Alzheimer's disease dataset GSE118553 and alcohol dependence dataset GSE44456 from the Gene Expression Omnibus (GEO) database. Ferroptosis-related genes were gathered through Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes (KEGG), and relevant literature, resulting in a total of 88 related genes. For the AD and alcohol dependence datasets, we conducted Limma analysis to identify differentially expressed genes (DEGs) and performed functional enrichment analysis on the intersection set. Furthermore, we used ferroptosis-related genes and the DEGs to perform machine learning crossover analysis, employing Least Absolute Shrinkage and Selection Operator (LASSO) regression to identify candidate immune-related central genes. This analysis was also used to construct protein-protein interaction networks (PPI) and artificial neural networks (ANN), as well as to plot receiver operating characteristic (ROC) curves for diagnosing AD and alcohol dependence. We analyzed immune cell infiltration to explore the role of immune cell dysregulation in AD. Subsequently, we conducted consensus clustering analysis of AD using three relevant candidate gene models and examined the immune microenvironment and functional pathways between different subgroups. Finally, we generated a network of gene-gene interactions and miRNA-gene interactions using Networkanalyst. The crossover of AD and alcohol dependence DEG contains 278 genes, and functional enrichment analysis showed that both AD and alcohol dependence were strongly correlated with Ferroptosis, and then crossed them with Ferroptosis-related genes to obtain seven genes. Three candidate genes were finally identified by machine learning to build a diagnostic prediction model. After validation by ANN and PPI analysis, ROC curves were plotted to assess the diagnostic value of AD and alcohol dependence. The results showed a high diagnostic value of the predictive model. In the immune infiltration analysis, functional metabolism and immune microenvironment of AD patients were significantly associated with Ferroptosis. Finally, analysis of target genes and miRNA-gene interaction networks showed that hsa-mir-34a-5p and has-mir-106b-5p could simultaneously regulate the expression of both CYBB and ACSL4. We obtained a diagnostic prediction model with good effect by comprehensive analysis, and validation of ROC in AD and alcohol dependence data sets showed good diagnostic, predictive value for both AD (AUC 0. 75, CI 0.91-0.60), and alcohol dependence (AUC 0.81, CI 0.95-0.68). In the consensus clustering grouping, we identified variability in the metabolic and immune microenvironment between subgroups as a likely cause of the different prognosis, which was all related to Ferroptosis function. Finally, we discovered that hsa-mir-34a-5p and has-mir-106b-5p could simultaneously regulate the expression of both CYBB and ACSL4.

Six-transmembrane epithelial antigen of prostate 3 ( STEAP3 ), a member of the iron regulation protein family, is characterized by a high recurrence rate and a short survival time. Nevertheless, studies investigating the role of STEAP3 in glioblastoma (GB) are scarce. In this study, the prognostic value of STEAP3 was evaluated utilizing mRNA expression profiles from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases as the validation and training cohorts, respectively. Moreover, differentially expressed genes were subjected to a functional enrichment analysis. The relationship between STEAP3 and the tumor microenvironment (TME) was examined. The immunophenoscore (IPS) and tumor immune dysfunction and exclusion (TIDE) score were used to investigate response to immunotherapy. In all cohorts, GB patients with higher STEAP3 expression levels exhibited shorter overall survival (OS). Additionally, STEAP3 -associated genes were primarily implicated in leukocyte migration, the JAK-STAT signaling pathway, and the cytokine-mediated signaling pathway. In the STEAP3 high-expression group, the ESTIMATEScore, ImmuneScore, StromalScore, and IPS were significantly higher. Overall, our results highlighted that STEAP3 might serve as a candidate prognostic biomarker for GB. Additionally, it might regulate the TME and influence GB metastasis.

Background Accurate prediction of the prognosis of RCC using a single biomarker is challenging due to the genetic heterogeneity of the disease. However, it is essential to develop an accurate system to allow better patient selection for optimal treatment strategies. ARL4C, ECT2, SOD2, and STEAP3 are novel molecular biomarkers identified in earlier studies as survival-related genes by comprehensive analyses of 43 primary RCC tissues and RCC cell lines. Methods To develop a prognostic model based on these multiple biomarkers, the expression of four biomarkers ARL4C, ECT2, SOD2, and STEAP3 in primary RCC tissue were semi-quantitatively investigated by immunohistochemical analysis in an independent cohort of 97 patients who underwent nephrectomy, and the clinical significance of these biomarkers were analyzed by survival analysis using Kaplan-Meier curves. The prognostic model was constructed by calculation of the contribution score to prognosis of each biomarker on Cox regression analysis, and its prognostic performance was validated. Results Patients whose tumors had high expression of the individual biomarkers had shorter cancer-specific survival (CSS) from the time of primary nephrectomy. The prognostic model based on four biomarkers segregated the patients into a high- and low-risk scored group according to defined cut-off value. This approach was more robust in predicting CSS compared to each single biomarker alone in the total of 97 patients with RCC. Especially in the 36 metastatic RCC patients, our prognostic model could more accurately predict early events within 2 years of diagnosis of metastasis. In addition, high risk-scored patients with particular strong SOD2 expression had a much worse prognosis in 25 patients with metastatic RCC who were treated with molecular targeting agents. Conclusions Our findings indicate that a prognostic model based on four novel biomarkers provides valuable data for prediction of clinical prognosis and useful information for considering the follow-up conditions and therapeutic strategies for patients with primary and metastatic RCC.

Clear cell renal cell carcinoma (ccRCC) is a common malignant tumor of the urinary system characterized by poor prognosis and difficult treatment. It has been reported that iron metabolism dysregulation is a common phenomenon in ccRCC and is closely related to the process of ccRCC. But still now, the exact function and underlying mechanisms of iron metabolism dysregulation in ccRCC have not been fully elucidated. In this study, we comprehensively investigated the prognostic value and potential role of STEAP3 (an iron metabolism-related gene) in ccRCC. STEAP3 is significantly up-regulated in ccRCC. High STEAP3 expression is associated with gender, hemoglobin level, pathological grade, tumor stage and significantly predicts an unfavorable prognosis of ccRCC patients. Functional enrichment analysis and evaluation of the tumor microenvironment indicated that STEAP3 was involved in the remodeling of tumor extracellular matrix and the shaping of an immune-suppressive tumor microenvironment to promote tumor metastasis and evade immune killing. Besides, the expression of STEAP3 is also associated with the expression of various immune checkpoint molecules and the IC50 of targeted drugs. Finally, we verified STEAP3 by RT-qPCR and IHC staining. In conclusion, we found that STEAP3 can serve as a candidate prognostic biomarker for ccRCC, and targeting STEAP3 and its biological processes may provide new references for the individualized treatment of ccRCC.