FerrDb: a manually curated resource for regulators and markers of ferroptosis and ferroptosis-disease associations

Cell Death and Senescence-Based Molecular Classification and an Individualized Prediction Model for Lung Adenocarcinoma

The exploration of cell death and cellular senescence (CDS) in cancer has been an area of interest, yet a systematic evaluation of CDS features and their interactions in lung adenocarcinoma (LUAD) to understand tumor heterogeneity, tumor microenvironment (TME) characteristics, and patient clinical outcomes is previously uncharted. Our study characterized the activities and interconnections of 21 CDS features in 1788 LUAD cases across 15 cohorts, employing unsupervised clustering to categorize patients into three CDS subtypes with distinct TME profiles. The CDS index (CDSI), derived from principal component analysis, was developed to assess individual tumor CDS regulation patterns. Twelve CDSI core genes, enriched in proliferating T cells within the TME as per single-cell analysis, were identified and their functional roles and prognostic significance were validated. High CDSI correlated with improved overall survival in discovery cohort, four independent validation cohorts, and subgroup analysis. CDSI-low patients exhibited a favorable clinical response to immunotherapy and potential sensitivity to mitosis pathway drugs, while CDSI-high patients might benefit from drugs targeting ERK/MAPK and MDM2-p53 pathways. The clinical utility of CDSI was further validated using 9185 pan-cancer samples, demonstrating the broad relevance of our prediction model across various cancer types and its potential clinical implications for cancer management.

Prognostic implication of six m6A-modulated genes signature in the ferroptosis for hepatocellular carcinoma patients

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.

Transcriptomic signatures of oxytosis/ferroptosis are enriched in Alzheimer's disease

BACKGROUND

Oxytosis/ferroptosis is a form of non-apoptotic regulated cell death characterized by specific changes in the redox balance that lead to lethal lipid peroxidation. It has been hypothesized recently that aging predisposes the brain to the activation of oxytosis/ferroptosis in Alzheimer's disease (AD), and consequently that inhibition of oxytosis/ferroptosis offers a path to develop a new class of therapeutics for the disease. The goal of the present study was to investigate the occurrence of oxytosis/ferroptosis in the AD brain by examining transcriptomic signatures of oxytosis/ferroptosis in cellular and animal models of AD as well as in human AD brain samples.

RESULTS

Since oxytosis/ferroptosis has been poorly defined at the RNA level, the publicly available datasets are limited. To address this limitation, we developed TrioSig, a gene signature generated from transcriptomic data of human microglia, astrocytes, and neurons treated with inducers of oxytosis/ferroptosis. It is shown that the different signatures of oxytosis/ferroptosis are enriched to varying extents in the brains of AD mice and human AD patients. The TrioSig signature was the most frequently found enriched, and bioinformatic analysis of its composition identified genes involved in the integrated stress response (ISR). It was confirmed in nerve cell culture that oxytosis/ferroptosis induces the ISR via phosphorylation of eukaryotic translation initiation factor 2 alpha (eIF2α) and activating transcription factor 4 (ATF4) signaling.

CONCLUSIONS

Our data support the involvement of oxytosis/ferroptosis in AD. The implications of the ISR for the progression and prevention of AD are discussed.

Molecular subtypes based on ferroptosis-related genes and tumor microenvironment infiltration characterization in small cell lung cancer

Background

Ferroptosis is an iron-dependent form of regulated cell death associated with cancer. However, the characteristics of ferroptosis in small cell lung cancer (SCLC) are still uncertain. This study aimed to explore the application value of ferroptosis-related genes (FRGs) classification in prognosis and characteristics prediction to provide clues for targeted SCLC therapy.

Method

We systematically characterized mRNA expression and genetic alterations of FRGs in SCLC, evaluating their expression pattern in 181 samples from 3 datasets. Unsupervised clustering analysis was performed to identify the molecular subtypes based on FRGs. We then conducted association analyses between FRG subtypes and various tumor microenvironment (TME) characteristics, traditional key transcript factor subtypes, clinical features, transcriptional and post-transcriptional regulation, drug response, and the efficacy of immunotherapy. Furthermore, the novel classification was validated in an independent cohort of 34 samples from Beijing.

Result

In this study, we identified three distinct ferroptosis subtypes in SCLC: S1, S2, and S3. We found that patients in S2 had the poorest prognosis. The FRG classification was correlated with the NOTCH pathway, MYC pathway, Neuroendocrine (NE), and epithelial-to-mesenchymal transition (EMT) process. Additionally, the FRG classification was strongly associated with TME 4 subtypes. To validate the classification, we employed an independent cohort. The FRG classification could also help to guide the prediction of chemical drugs. Finally, the heatmap showed the landscape of FRG subtypes, TME subtypes, NE subtypes, key transcription subtypes, age, gender, and stage.

Conclusion

Our identification of new SCLC subtypes provides novel insights into tumor biology and has potential clinical implications for the management of SCLC.

Bioinformatics and experimental validation of ferroptosis-related genes in steroid-induced osteonecrosis of the femoral head

Background

Steroid-induced osteonecrosis of the femoral head (SONFH) is a progressive condition that causes increasing disability. It is thought to result from reduced blood flow and oxygen levels in the femoral head, with reactive oxygen species (ROS) playing a key role in triggering ferroptosis. However, the role of ferroptosis in SONFH progression remains underexplored. This study aimed to identify and validate key genes associated with ferroptosis in SONFH using bioinformatics.

Methods

The study analyzed the SONFH dataset GSE123568, which includes data from 30 SONFH patients and 10 controls. Weighted gene co-expression network analysis (WGCNA) was used to identify differentially expressed genes (DEGs) between the SONFH and control groups. Core genes were identified by intersecting DEGs with ferroptosis-related genes retrieved from FerrDb V2. The diagnostic performance of the key genes was assessed using the receiver operating characteristic (ROC) curve, and a predictive nomogram model was developed. Interaction analysis of these genes was conducted to explore their link with immune infiltration. The expression of these genes in bone tissue from SONFH patients was validated. Finally, drug-protein interactions were predicted using the DSigDB database.

Results

Differential expression analysis identified 384 DEGs, which were significantly involved in inflammatory pathways. WGCNA revealed four key genes after intersecting DEGs with relevant module genes and ferroptosis-related genes. A nomogram model based on these genes demonstrated strong reliability and validity. Immune infiltration analysis showed significant differences between SONFH patients and controls, with notable associations between immune cell infiltration and the expression of the four core genes. Validation through quantitative real-time PCR (qRT-PCR) and Western blot confirmed that the expression of GCLC, GABARAPL2, CISD2, and NCOA4 was significantly lower in SONFH bone tissue compared to controls (P < 0.05). Additionally, potential therapeutic drugs targeting these genes, including Diethyl sulfate, Meloxicam, and NIMUSTINE, were predicted.

Conclusion

This study identifies GABARAPL2, CISD2, NCOA4, and GCLC as potential diagnostic biomarkers associated with immune cell infiltration in SONFH, offering new insights for future research and clinical applications.

Comprehensive analysis of ferroptosis-related long non-coding RNA and its association with tumor progression and ferroptosis in gastric cancer

Gastric cancer (GC) is one of the most common malignant tumors with a poor prognosis. Ferroptosis is an distinct type of non-apoptotic cell death that is closely associated with tumor prognosis. Thus, we aimed to develop an novel prognosis risk model based on ferroptosis-related lncRNAs and excavate novel diagnostic markers. In this study, eight ferroptosis-related lncRNAs were obtained for constructing the prognosis model in GC based on TCGA database. The patients in the high-risk group had worse survival than those in the low-risk group, and the risk-grouping could be used as an independent prognostic factor for OS. Receiver operating characteristic curve analysis demonstrated this risk model was superior to traditional clinicopathological features in predicting GC prognosis. GSEA revealed that these lncRNAs were mainly involved in cell adhesion, cancer pathways, and immune function regulation. The key gene HAGLR of this risk signature was up-regulated in GC tissues and cells. Function assays showed that knockdown of HAGLR could effectively inhibit the GC cells proliferation and migration, whereas silencing HAGLR accelerated apoptosis and ferroptosis cell death process. In conclusion, we established a novel ferroptosis-related prognostic risk signature including eight lncRNAs, which may improve prognostic predictive accuracy for patients with GC.

Synergistic bioinformatics and sophisticated machine learning unveil ferroptosis-driven regulatory pathways and immunotherapy potential in breast carcinoma

BACKGROUND

The intersection of aberrant iron metabolism and the rapidly advancing field of immunotherapy has emerged as a critical focus in breast cancer (BRCA) therapeutics. Ferroptosis, a distinct form of iron-dependent cell death driven by lipid peroxidation, has garnered increasing attention for its pivotal role in cancer progression.

METHODS

Utilizing extensive datasets from TCGA and GEO, this research extracted a wealth of biological data, including mRNA splicing indices, genomic aberrations, copy number variations (CNV), tumor mutational burden (TMB), and diverse clinical information. Through precise Lasso regression analysis, this research constructed a prognostic model that elucidates the molecular interactions of FRGs in BRCA. Concurrent co-expression network analyses were performed to explore the dynamic interplay between gene expression patterns and FRGs, revealing potential regulatory mechanisms.

RESULTS

This research analysis revealed significant overexpression of FRGs in high-risk BRCA samples, highlighting their prognostic relevance beyond traditional clinical parameters. GSVA identified immune response and cancer-related pathways as predominantly active in high-risk groups, suggesting ferroptosis as a central modulator within the tumor microenvironment. Notably, genes such as ACTL8, VGF, and CPLX2 emerged as markers of tumorigenesis, while IL33 and TP63 were identified as potential key regulators of cancer progression, each exhibiting distinct expression profiles across risk levels. Furthermore, this research incorporated gene correlations, CNV profiles, SNP arrays, and drug susceptibility analyses, contributing to the advancement of precision oncology.

CONCLUSIONS

The integration of bioinformatics and machine learning in this study underscores a strong correlation between FRG expression patterns and BRCA prognosis, affirming their potential as precise biomarkers for personalized immunotherapy.

Identification of a novel signature derived from ferroptosis-related genes to predict prognosis, immune landscape and chemotherapeutic sensitivity in head and neck squamous cell carcinoma

BACKGROUND

Ferroptosis resistance is increasingly appreciated as an indispensable factor for tumor initiation, progression, and therapeutic resistance in various human malignancies including head and neck squamous cell carcinoma (HNSCC). Herein, we sought to develop a novel signature utilizing ferroptosis-related genes (FRGs) for prognosis and therapeutic prediction in HNSCC.

METHODS

A prognostic signature specific to HNSCC was developed using univariate Cox regression and LASSO-penalized multivariate Cox regression analyses. A nomogram incorporating this signature and selected clinicopathological factors was created through multivariate Cox regression. The effectiveness of the FRG signature in predicting tumor mutation burden (TMB), immune status, and responses to chemotherapy was also evaluated.

RESULTS

The FRG signature based on eight genes (AURKA, LPIN1, MIOX, CDKN2A, PRKAA2, CISD2, TRIB3, and ASNS) successfully classified patients into subgroups with distinct outcomes across multiple cohorts. A FRG nomogram was constructed with good-prognostic performance. Additionally, higher FRG signature scores were positively associated with TMB and negatively correlated with tumor-infiltrating immune cells, which were linked to sensitivity to several chemotherapeutic drugs.

CONCLUSIONS

Our findings provide strong evidence that the FRG-derived signature/nomogram can effectively predict both prognosis and therapeutic response in HNSCC.

Experimental validation and identification of ferroptosis-associated biomarkers for diagnostic and therapeutic targeting in hearing loss

Objectives

Ferroptosis, a regulated form of cell death, has attracted significant attention in hearing loss research; however, the role of ferroptosis-related genes remains unclear. This study aimed to clarify diagnostic and therapeutic targeting of ferroptosis-related genes in hearing loss.

Methods

Differentially expressed genes related to hearing loss from the GEO database were intersected with ferroptosis-related genes. The Lasso and SVM-RFE models were applied to reduce the gene set, identifying model genes. Biological functions, pathways, and gene-drug associations related to these model genes were analyzed. Age-related hearing loss (ARHL) genes within the model genes were obtained from a genome-wide association study (GWAS) dataset. Further validation was conducted in HEI-OC1 cells and the cochleae of C57BL/6J mice, including auditory brainstem response (ABR) testing, qRT-PCR, Western blotting, Fe2+ detection, and immunofluorescence analysis.

Results

The study identified 20 ferroptosis-related genes associated with hearing loss. Using Lasso and SVM-RFE models, a novel model was constructed, consisting of nine genes (SCD, ENPP2, PANX2, NEDD4, MEF2C, ABCC5, KLHDC3, CYP4F8 and IFNA2). Among these, MEF2C and NEDD4 were found to be associated with ARHL.

Conclusion

Ferroptosis is a potential pathological mechanism in hearing loss research, and the nine ferroptosis-related genes identified provide promising targets for exploring new diagnostics and treatments for hearing loss. Notably, MEF2C and NEDD4 are associated with ARHL.

PDP1 related ferroptosis risk signature indicates distinct immune microenvironment and prognosis of breast cancer patients

Objective

We aim to construct a RiskScore model to aid in the early prognosis of breast cancer (BC).

Methods

BC mRNA expression profiles were obtained from TCGA and GEO databases. Differential gene expression analysis identifies PDP1-ferroptosis-related genes. LASSO Cox regression was utilized to screen genes to build a RiskScore model, and survival analysis were performed to investigate the reliability in BC prognosis. Immune cell infiltration proportions were calculated using CIBERSORT and xCell algorithms. Single-cell data processing and analysis were conducted using "Seurat", "monocle", and "iTALK" packages. PDP1 was silenced to validate its influence on the target genes.

Results

Data from public databases revealed significant upregulation of PDP1 in BC samples compared to normal tissues. A RiskScore model based on PDP1-related differential ferroptosis-related genes (FRGs) ACSL1, BNIP3, and EMC2 was developed, which effectively predicted BC patient prognosis. High-risk BC samples exhibited poorer overall survival and were associated with immune microenvironment. The model remained significant in multivariate Cox regression analysis, indicating that it could independently predict the survival of BC patients. ACSL1, BNIP3, and EMC2 were downregulated after knockdown of PDP1.

Conclusion

RiskScore model constructed by PDP1-ferroptosis-related genes ACSL1, BNIP3, and EMC2 is able to help predict the prognosis of BC patients.

Identification of shared important genes associated with ferroptosis across different etiologies of acute lung injury

Acute lung injury (ALI) of different etiologies has shared pathophysiologic process, from which we speculated that ALI of different etiologies may share common molecular features. While the shared genetic characteristics of ALI remain unclear. In this paper, we aimed to identify shared ferroptosis-associated and bottleneck genes from acute lung injury of different etiologies. Firstly, we extracted five groups of gene sets related to three distinct models of ALI from the Gene Expression Omnibus (GEO) database. Then, through the utilization of weighted gene co-expression network analysis (WGCNA), we identified 3 significant gene modules and ascertained 7 shared co-expressed genes affected by these models. Subsequently, through the utilization of differential gene expression analysis and protein-protein interaction network analysis for the 3 gene modules, the shared bottleneck gene Slc7a11 was identified. Moreover, the 7 shared co-expressed genes subjected to these three ALI models were used to identify shared ferroptosis-associated genes via the FerrDb database. Finally, the key gene Slc7a11 was confirmed and validated. In addition, we observed that Slc7a11 is both a driver and a suppressor gene in the FerrDb database. Interestingly, we found the expression level of Slc7a11 was significantly upregulated in the three ALI models. Experimentally, we confirmed the expression of Slc7a11 in rat ALI tissues by using immunofluorescence staining and real-time polymerase chain reaction (qRT-PCR) assays. Collectively, our findings complement the exploration of the shared pathogenesis of ALI. There are genetic features shared by ALI of different etiology and the increased expression of Slc7a11 was identified in the three different etiologies of ALI, which can improve our understanding of the shared molecular mechanisms underlying ALI.

Exploration potential sepsis-ferroptosis mechanisms through the use of CETSA technology and network pharmacology

As an important self-protection response mechanism of the body, inflammation can not only remove the necrotic or even malignant cells in the body, but also take a series of targeted measures to eliminate the pathogen of foreign invasion and block the foreign substances that may affect the life and health of the body. Flavonoids have known anti-inflammatory, anti-oxidation, anti-cancer and other effects, including glycyrrhizin molecules is one of the representatives. Licochalcone D has known anti-inflammatory and antioxidant properties and is effective in the treatment of a variety of inflammatory diseases. However, the underlying mechanism for the treatment of sepsis remains unclear. In this study, the therapeutic potential of Licochalcone D for sepsis was studied by analyzing network pharmacology and molecular dynamics simulation methods. Sepsis-related genes were collected from the database to construct PPI network maps and drug-targeting network profiles. The potential mechanism of Licochalcone D in sepsis was predicted by gene ontology, KEGG and molecular dynamics simulation. Sixty drug-disease genes were subsequently validated. Go analysis showed that monomeric small molecule Licochalcone D could regulate the process of intracellular enzyme system. The KEGG pathway analysis showed that the signal pathway of the main effect was related to the calcium pathway. The results of intersections with iron death-related target genes showed that ALOX5, ALOX15B and other nine targets all had the effect of possibly improving sepsis, while GSE 54,514, GSE 95,233 and GSE 69,528 were used to analyze the survival rate and ROC curve. Five genes were screened, including ALOX5, ALOX15B, NFE2L2 and NR4A1, HIF1A. The results of molecular docking showed that ALOX5 and Licochalcone D had strong binding activity. Finally, the results of molecular dynamics simulation showed that there was good binding power between drug and target. In the present study, we utilized molecular dynamics simulation techniques to assess the binding affinity between the small-molecule ligand and the protein receptor. The simulation outcomes demonstrate that the binding interface between the ligand and receptor remains stable, with a calculated binding free energy (ΔG) of -32.47 kJ/mol. This signifies a high-affinity interaction between the ligand and receptor, suggesting the long-term stability of the small molecule under physiological conditions. These findings provide critical insights for drug development efforts. This study elucidates the therapeutic potential of Licochalcone D, a traditional Chinese medicine monomer, in improving sepsis through the regulation of ferroptosis, thereby providing a new direction and option for subsequent clinical drug development in the treatment of sepsis.

Ferroptosis regulation by traditional chinese medicine for ischemic stroke intervention based on network pharmacology and data mining

OBJECTIVE

The aim of this study is to use network pharmacology and data mining to explore the role of traditional Chinese medicine (TCM) in ischemic stroke (IS) intervention by ferroptosis regulation. The results will provide reference for related research on ferroptosis in IS.

METHODS

The ferroptosis-related targets were obtained from the GeneCards, GeneCLiP3, and FerrDdb databases, while the IS targets were sourced from the GeneCards and DisGeNET databases. Venny was used to identify IS targets associated with ferroptosis. A protein-protein interaction (PPI) analysis was then conducted, and machine learning screening was used to validate these potential targets. The potential targets that met specific criteria and their related compounds allowed us to select TCMs. A mechanistic analysis of the potential targets was conducted using the DAVID database. PPI network diagrams, target-compound network diagrams, and target-compound-TCM network diagrams were then constructed. Finally, molecular docking technology was used to verify the binding activities of the TCM compounds and core components with the identified targets. In addition, the properties, flavors, meridian tropism, and therapeutic effects of the candidate TCMs were analyzed and statistically evaluated.

RESULTS

A total of 706 targets associated with ferroptosis in IS were obtained, and 14 potential ferroptosis targets in IS were obtained using machine learning. Furthermore, 413 compounds and 301 TCMs were screened, and the binding activities of the targets to the TCM compounds and the core prescriptions were stable. The candidate TCMs primarily exhibited cold, warm, bitter taste, pungent taste, liver meridian, heat-cleaning medicinal, and tonify deficiency properties.

CONCLUSIONS

This study investigated ferroptosis regulation for IS intervention using TCM. We began by investigating the targets of IS and ferroptosis, and we also analyzed the relevant mechanism of ferroptosis in IS. The results of this study provide reference for related research on ferroptosis in IS.

Exploring Immune-Related Ferroptosis Genes in Thyroid Cancer: A Comprehensive Analysis

Background: The increasing incidence and poor outcomes of recurrent thyroid cancer highlight the need for innovative therapies. Ferroptosis, a regulated cell death process linked to the tumour microenvironment (TME), offers a promising antitumour strategy. This study explored immune-related ferroptosis genes (IRFGs) in thyroid cancer to uncover novel therapeutic targets. Methods: CIBERSORTx and WGCNA were applied to data from TCGA-THCA to identify hub genes. A prognostic model composed of IRFGs was constructed using LASSO Cox regression. Pearson correlation was employed to analyse the relationships between IRFGs and immune features. Single-cell RNA sequencing (scRNA-seq) revealed gene expression in cell subsets, and qRT-PCR was used for validation. Results: Twelve IRFGs were identified through WGCNA, leading to the classification of thyroid cancer samples into three distinct subtypes. There were significant differences in patient outcomes among these subtypes. A prognostic risk score model was developed based on six key IRFGs (ACSL5, HSD17B11, CCL5, NCF2, PSME1, and ACTB), which were found to be closely associated with immune cell infiltration and immune responses within the TME. The prognostic risk score was identified as a risk factor for thyroid cancer outcomes (HR = 14.737, 95% CI = 1.95-111.65; p = 0.009). ScRNA-seq revealed the predominant expression of these genes in myeloid cells, with differential expression validated using qRT-PCR in thyroid tumour and normal tissues. Conclusions: This study integrates bulk and single-cell RNA sequencing data to identify IRFGs and construct a robust prognostic model, offering new therapeutic targets and improving prognostic evaluation for thyroid cancer patients.

Integrative insights into the role of CAV1 in ketogenic diet and ferroptosis in pancreatic cancer

Pancreatic cancer exhibits high mortality rates with limited therapeutic options. Emerging evidence suggests that the ketogenic diet may act as adjuvant therapy by triggering ferroptosis in cancer cells, though the underlying molecular mechanisms remain unclear. This study aims to investigate the molecular mechanisms linking ketogenic metabolism and ferroptosis, with an emphasis on key regulatory proteins. We demonstrated that pancreatic adenocarcinoma (PAAD) tissues significantly enhanced ketogenic and ferroptosis phenotypes compared to normal tissues, both correlating with poorer patient prognosis. These phenotypes showed strong interdependence mediated by CAV1. In the pancreatic tumor microenvironment, CAV1 was predominantly expressed in tumor cells. Through in vitro cell experiments, we clarified that Na-OHB downregulated CAV1 expression in pancreatic cancer cells, inhibiting the transcription of the CAV1/AMPK/NRF2 downstream ferroptosis-protective genes SLC7A11 and SLC40A1. Additionally, we demonstrated the interaction between CAV1 and SLC7A11 molecules; when CAV1 was downregulated, it affected the stability of SLC7A11, leading to the ubiquitination and degradation of the translated SLC7A11 protein. Through these dual mechanisms, Na-OHB caused Fe2+ overload, lipid peroxidation accumulation, and oxidative stress in pancreatic cancer cells, ultimately triggering ferroptosis. In ketogenic diet-fed tumor-bearing mouse models, we also observed a significant increase in lipid peroxidation and other related biomarkers, while CAV1 and SLC7A11 levels were markedly decreased compared to the normal diet group. Our findings identify CAV1 as a pivotal molecular link between ketogenic metabolism and ferroptosis in pancreatic cancer. The multi-level regulatory axis involving CAV1-mediated transcriptional regulation and post-translational modifications provides mechanistic insights into ketogenic diet-induced ferroptosis, suggesting potential therapeutic targets for pancreatic cancer adjuvant treatment.

Regulatory factor X1 promotes sorafenib-induced ferroptosis in hepatocellular carcinoma by transcriptional regulation of BECN1

BACKGROUND

Sorafenib is a commonly used first-line kinase-targeted drug for advanced hepatocellular carcinoma (HCC) patients suffering from limited efficacy. Emerging evidence indicates that sorafenib exerts anti-cancer activity through the induction of ferroptosis in HCC cells, but the underlying mechanism is still unclear.

METHODS

The whole transcriptome sequencing and bioinformatics analysis were used to screen for target genes. The expression and subcellular localization of regulatory factor X1 (RFX1) were determined through immunohistochemistry, immunofluorescence, PCR and western blot analyses. The impact of RFX1 on HCC cell growth was assessed using CCK8, colony formation assays, cell death assays, and animal experiments. Glutathione measurement, iron assay and lipid peroxidation detection assays were performed to investigate ferroptosis of HCC cells. The regulatory mechanism of RFX1 in HCC was investigated by sgRFX1, co-IP, ChIP and luciferase experiments. Immunohistochemical and survival analyses were performed to examine the prognostic significance of RFX1 in HCC.

RESULTS

In this study, we found that RFX1 promote ferroptosis in HCC cells. Further, we showed that sorafenib induces cell death through RFX1-mediated ferroptosis in HCC cells. The enhancing effect of RFX1 on HCC cell ferroptosis is largely dependent on inhibition of cystine/glutamate antiporter (system Xc-) activity through the BECN-SLC7A11 axis, where RFX1 directly binds to the promoter region of BECN1 and upregulates BECN1 expression. In addition, a STAT3-RFX1-BECN1 signalling loop was found to promote RFX1 expression in HCC cells.

CONCLUSIONS

Our study reveals a novel mechanism underlying sorafenib-induced HCC cell death.

NUPR1 Promotes Radioresistance in Colorectal Cancer Cells by Inhibiting Ferroptosis

Radioresistance is a major clinical challenge and the underlying mechanism has not been thoroughly elucidated. In this study, a radioresistant (RR) cell line is established to explore the transcriptomic signatures of radioresistance in colorectal cancer (CRC). KEGG enriched pathway analysis demonstrated that ferroptosis is inactivated in RR cells. Further detection confirmed that radiotherapy can promote ferroptosis, and ferroptosis inactivation is one of the hallmarks of radioresistance in CRC. What's more, induction of ferroptosis can restore the radiosensitivity of CRC cells. Then, we performed RNA sequencing to compare gene expression between parental and RR cells, and cells pretreated with or without RSL3. Via high-throughput screening, NUPR1 was identified as a potential candidate for ferroptosis-mediated radioresistance in CRC. CRC cells can acquire radiation resistance by NUPR1-mediated ferroptosis suppression in the NUPR1-overexpressing cell line. More importantly, ZZW-115, an NUPR1 inhibitor, can sensitise RR cells to radiotherapy. Overall, our findings identify ferroptosis inactivation linked with resistance to radiotherapy. Besides, NUPR1 can promote radiation resistance by inhibiting ferroptosis, and targeting NUPR1 may be a potential strategy to relieve radioresistance associated with ferroptosis in CRC.

Ferroptosis: CD8+T cells' blade to destroy tumor cells or poison for self-destruction

Ferroptosis represents an emerging, iron-dependent form of cell death driven by lipid peroxidation. In recent years, it has garnered significant attention in the realm of cancer immunotherapy, particularly in studies involving immune checkpoint inhibitors. This form of cell death not only enhances our comprehension of the tumor microenvironment but is also considered a promising therapeutic strategy to address tumor resistance, investigate immune activation mechanisms, and facilitate the development of cancer vaccines. The combination of immunotherapy with ferroptosis provides innovative targets and fresh perspectives for advancing cancer treatment. Nevertheless, tumor cells appear to possess a wider array of ferroptosis evasion strategies compared to CD8+T cells, which have been conclusively shown to be more vulnerable to ferroptosis. Furthermore, ferroptosis in the TME can create a favorable environment for tumor survival and invasion. Under this premise, both inducing tumor cell ferroptosis and inhibiting T cell ferroptosis will impact antitumor immunity to some extent, and even make the final result run counter to our therapeutic purpose. This paper systematically elucidates the dual-edged sword role of ferroptosis in the antitumor process of T cells, briefly outlining the complexity of ferroptosis within the TME. It explores potential side effects associated with ferroptosis-inducing therapies and critically considers the combined application of ferroptosis-based therapies with ICIs. Furthermore, it highlights the current challenges faced by this combined therapeutic approach and points out future directions for development.

Analysis and assessment of ferroptosis-related gene signatures and prognostic risk models in skin cutaneous melanoma

Background

The occurrence and development of skin cutaneous melanoma (SKCM) are significantly influenced by ferroptosis, a sort of regulated cell death characterized by iron deposition and lipid peroxidation. Although positive strides have been achieved in the present management of SKCM, it is still unknown exactly how ferroptosis occurs in this condition. We aimed to determine the role of prognostically relevant ferroptosis-related genes (PR-FRGs) in SKCM development and prognosis.

Methods

The training group was created using combined transcriptomic RNA data acquired from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The dataset GSE19234 was acquired from the Gene Expression Omnibus (GEO) database as a validation group. Differentially expressed ferroptosis-related genes (DE-FRGs) were obtained from the training group, of which 103 showed up-regulation and 77 showed down-regulation. Then, 12 PR-FRGs were identified by the protein-protein interaction (PPI) network and Cox regression analysis, and prognostic risk models and nomograms were constructed. The risk model was validated using a validation group, and the prognostic value of the risk model was analyzed. Finally, immunohistochemical data were obtained from the Human Protein Atlas (HPA) website to validate the PR-FRGs.

Results

Twelve PR-FRGs were identified. A prognostic risk model was built using PR-FRGs, and patients in the training and validation groups were classified as high or low risk based on the risk model. The outcomes demonstrated that the prognosis was better for the low-risk group. Prognostic value analysis showed that the prognostic risk model could accurately predict the patients' overall survival (OS), was superior to clinical traits such as age, gender, and tumor stage in predicting ability, and could be used as an independent predictor. Meanwhile, the nomogram constructed based on PR-FRGs can effectively predict the prognosis of SKCM patients. Finally, PR-FRGs were validated in the HPA database.

Conclusions

Ferroptosis affects the prognosis of SKCM patients. Prognostic risk model and nomogram constructed based on 12 PR-FRGs demonstrated significant advantages in predicting the prognosis of SKCM patients. This will help in the identification and prognostic prediction of SKCM and in the discovery of new individualized treatment modalities.

The Expression of Ferroptosis-Related Genes in Hepatocellular Carcinoma and Their Relationships With Prognosis

Background

Ferroptosis, a form of cell death discovered in recent years, is expected to provide new targets for the diagnosis and treatment of hepatocellular carcinoma (HCC) through further research.

Methods

Based on data from The Cancer Genome Atlas (TCGA), we screened HCC-associated genes from 259 candidate genes in the FerrDb database. The screened genes were subjected to differential expression analysis, survival analysis, correlation analysis with clinical data, and univariate and multivariate Cox regression analysis. The results were validated with the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) database and the Human Protein Atlas (HPA) database, and signaling pathways were analyzed with the Gene Set Enrichment Analysis (GSEA) enrichment analysis. Human normal hepatocytes and different liver cancer cell lines were used to verify the expression levels of genes, using quantitative reverse transcription PCR (RT-qPCR).

Results

Eight ferroptosis-related genes were finally selected, including ACSL3, ASNS, CHMP5, MYB, PCK2, PGD, SLC38A1, and YY1AP1. The expression of eight genes except PCK2 was significantly correlated with a lower survival rate of HCC, and the expression of PCK2 showed a correlation with a higher survival rate of HCC. The expression of all eight genes was also correlated with clinical traits. GSEA enrichment analysis obtained many pathways such as apoptosis, endocytosis, pathways in cancer, Wnt signaling pathway, primary bile acid biosynthesis, and fatty acid metabolism pathway.

Conclusion

The ACSL3, ASNS, CHMP5, MYB, PCK2, PGD, SLC38A1, and YY1AP1 genes may become markers and new targets for early diagnosis and prognostic assessment of HCC.

Exploring mitochondrial and ferroptotic mechanisms for systemic lupus erythematosus biomarker identification and therapy

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with heterogeneous clinical manifestations. Understanding the molecular mechanisms of SLE is crucial for developing effective therapeutic strategies. This study downloaded microarray datasets from the Gene Expression Omnibus (GEO) database. Single-cell RNA sequencing (scRNA-seq) data was processed to identify 19 clusters and annotated five major cell types. Then we calculated mitochondrial-related genes (MRGs) and ferroptosis-related genes (FRGs) scores. FRGs scored the highest in Megakaryocytes, while MRGs scored the highest in B cells. By employing pseudotime analysis, cell-cell communication analysis, and Single-Cell Regulatory Network Inference and Clustering (SCENIC) analysis, we explored the heterogeneity of cells in SLE. Hub genes were identified using high-dimensional weighted correlation network analysis (hdWGNCA) and machine learning algorithms, leading to the development of a predictive diagnostic model with high predictive accuracy. Immune infiltration analysis revealed significant correlations between diagnostic biomarkers and various immune cells. Lastly, molecular docking studies suggested Doxorubicin may exert therapeutic effects by affecting these diagnostic biomarkers. This study offers new insights into the pathogenesis of SLE and provide valuable directions for future therapeutic research.

Analysis of expression characteristics of ferroptosis-related lncRNAs in gastrointestinal cancer patients in Asia

BACKGROUND

Asian cancer patients have become the highest morbidity and mortality group, and gastrointestinal tumors account for the majority of them, so it is urgent to find effective targets. Therefore, ferroptosis-related lncRNAs models were established to predict the prognosis and clinical immune characteristics of GI cancer.

METHODS

RNA sequencing and clinical data were collected from the TCGA database (LIHC, STAD, ESCA, PAAD, COAD, CHOL, and READ) of patients with gastrointestinal cancer in Asia. Download ferrodroptosis genes from FerrDb. Through R language, differential genes were identified, prognostic related LncRNAs were screened, and risk scores were obtained by risk formula to build models. Survival analysis, risk heat map, COX regression and ROC were used to evaluate the risk model. Establish Nomogram and clinically relevant heat maps. GSEA software was used to analyze gene enrichment and immune-related characteristics in high and low risk groups. LncRNA expression was validated through paired sample differential analysis and qRT-PCR, and the drug sensitivity of genes was also analyzed.

RESULTS

The transcriptome data of 297 cases and clinical data of 322 cases were downloaded from TCGA, and the intersection of ferroptosis-related genes were obtaine. Cox analysis revealed 48 ferroptosis-related LncRNAs associated with prognosis. Through survival analysis, risk heatmap, COX regression and ROC, it was found that the risk model was highly accurate and efficient in predicting prognosis. KEGG-related GSEA enrichment analysis showed that 12 related pathways were significantly expressed in the low-risk group. Four immune-related functions were significantly higher in the high-risk group than in the low-risk group, and the expression of all immune checkpoints were significantly higher in the high-risk group than in the low-risk group. The three LncRNAs in the model exhibited varying expression levels across different tumors and obtained drug sensitivity data.

CONCLUSIONS

Our results reveal innovative and strong evidence that ferroptosis-related lncRNAs can be used as biomarkers for the treatment and prognosis of Asian GI cancer.

Integrated Analysis of Ferroptosis and Immune Infiltration in Ulcerative Colitis Based on Bioinformatics

Introduction

Ulcerative colitis (UC) is an inflammatory bowel disease influenced by genetic, immune, and environmental factors. This study investigates the link between ferroptosis, a cell death process related to oxidative stress and iron metabolism, and immune infiltration in UC.

Materials and Methods

We analyzed UC patient transcription data from the Gene Expression Omnibus (GEO) and identified ferroptosis-related genes using FerrDB. Using STRING and Cytoscape, we analyzed protein-protein interactions to identify hub UC Differentially Expressed Genes (UCDEGs) and performed functional enrichment with GO and KEGG pathways. Machine learning helped further identify key UC Differentially Expressed Ferroptosis-related genes (UCDE-FRGs), which were validated using additional GEO datasets and immunohistochemical staining.

Results

A total of 11 hub UCDEGs (CCL2, ICAM1, TLR2, CXCL9, MMP9, CXCL10, IL1B, CXCL8, PTPRC, FCGR3A, and IL1A) and 3 key UCDE-FRGs (DUOX2, LCN2 and IDO1) were identified. GO and KEGG functional enrichment indicates that these genes play a role in immunity and ferroptosis. Analysis of immune cell infiltration showed that there were a large number of Plasma cells, Monocytes, M0/M1 Macrophages and Neutrophils in the UC. Correlation analysis revealed 3 key UCDE-FRGs associated with immune-infiltrated cells in UC. IHC results showed that the expression levels of 3 key UCDE-FRGs in UC were all higher than that in the healthy controls.

Conclusion

In summary, this study identified three key genes related to UC ferroptosis and immunity, namely DUOX2, IDO1 and LCN2. These findings suggest that immune infiltration plays an important role in UC caused by ferroptosis, and that there is mutual regulation between UC and immune-infiltrated cells. Our research revealed the potential application of immune and ferroptosis in the diagnosis, treatment and prognosis of UC, providing new strategies for clinical management.

Exploration of ferroptosis-related biomarkers with prognostic capability in RIF based on WGCNA

PURPOSE

To explore the association of ferroptosis with repeated implantation failure (RIF) and prognostic capability of ferroptosis-related genes.

METHODS

Data in GSE106602 from the GEO database were used for gene co-expression network construction to confirm ferroptosis-related genes compared to gene sets that were downloaded from FerrDB. Then these genes were analyzed for functional enrichment and validated using endometrium samples from our center. ImplantScore and ROC curve were constructed for prognostic correlation analysis.

RESULTS

We observed that ferroptosis probably participated in RIF according to bioinformatics analysis on a gene set which exhibited a strong association with RIF from WGCNA. Fifty-four ferroptosis-related genes in the gene set were subsequently verified, and the PPI network was established for underlying interactions among them. There were 23 hub genes with differential expression in RIF and six of them (PML, LCN2, PRKAA1, BACH1, SLC7A11, and CAMKK2) showed significant correlation with implantation outcomes using samples collected from our center. Therefore, we combined the six genes and constructed an ImplantScore whose AUC reached 0.891, higher than the AUC of each single gene, respectively. ImplantScore of six genes with down-regulated expression in the group with failed implantation were much lower than that with successful outcome.

CONCLUSION

Our results demonstrated the potential prognostic functions of ferroptosis-related biomarkers in RIF, which will provide novel perspectives for further research and clinical applications.

Ferroptosis-related genes as prognostic markers for survival and immunotherapy in triple-negative breast cancer: analysis of public databases and a single institution

Background

Ferroptosis plays a vital role in cancer development and treatment. The relationship between ferroptosis-related genes and breast cancer prognosis, as well as immunotherapy outcomes, remains unknown.

Objectives

To evaluate the prognostic value of ferroptosis-related genes in breast cancer.

Methods

We conducted differential expressions and prognostic analysis for ferroptosis-related genes on public databases and breast cancer patients in our center and analyzed their predictive value for immunotherapy of breast cancer patients.

Results

We identified prognostic ferroptosis-related genes, constructed a nomogram, and validated key genes using patient data from our center. We also investigated ferroptosis-related genes significantly associated with immune infiltration and identified FTH1 as a promising biomarker for triple-negative breast cancer immunotherapy.

Conclusion

Ferroptosis-related genes had potential prognostic value and predictive value for breast cancer immunotherapy.

Harnessing ferroptosis for precision oncology: challenges and prospects

The discovery of diverse molecular mechanisms of regulated cell death has opened new avenues for cancer therapy. Ferroptosis, a unique form of cell death driven by iron-catalyzed peroxidation of membrane phospholipids, holds particular promise for targeting resistant cancer types. This review critically examines current literature on ferroptosis, focusing on its defining features and therapeutic potential. We discuss how molecular profiling of tumors and liquid biopsies can generate extensive multi-omics datasets, which can be leveraged through machine learning-based analytical approaches for patient stratification. Addressing these challenges is essential for advancing the clinical integration of ferroptosis-driven treatments in cancer care.

Identification of ferroptosis-related key genes in tuberculosis by bioinformatics methods

Tuberculosis, induced by Mycobacterium tuberculosis (Mtb), continues to pose a significant global public health challenge. Ferroptosis has emerged as a pivotal factor in tuberculosis pathogenesis, however, the mechanism has not yet been fully clarified. Therefore, the aim of this study was to hypothesize and validate potential ferroptosis-related genes in Mtb infection through bioinformatics analysis, thereby offering insights for further investigation. The mRNA microarray expression profile datasets were sourced from the Gene Expression Omnibus. The differentially expressed genes (DEGs) were derived using GEO2R. Subsequently, the shared DEGs between the GSE174566 and GSE227851 datasets were intersected with the genes in the ferroptosis database. The ferroptosis-associated shared DEGs (Ferr-sDEGs) were validated in the GSE20050 dataset. They were subjected to PPI, Cytoscape and Friends analysis, the infiltration correlation of immune cells and qRT-PCR. A total of 11 Ferr-sDEGs were identified, and 9 genes were validated. These analyses revealed that the key Ferr-sDEGs contributed to ferroptosis during Mtb infection and these key Ferr-sDEGs were relatively independent, implying that ferroptosis may be triggered by various mechanisms. Concurrently, the infiltration and correlation analysis demonstrated that multiple types of immune cells could be activated by the key Ferr-sDEGs. Ultimately, qRT-PCR validated that the expression levels of key Ferr-sDEGs. In conclusion, ferroptosis serves a pivotal function in the pathogenesis of tuberculosis. IL1B, PTGS2, TNFAIP3, HMOX1, SOCS1, CD82, and NUPR1 may be vital genes associated with the ferroptosis induced by Mtb infection.

Study of an N6-methyladenosine- and ferroptosis-related prognostic model and the mechanisms underlying the molecular network in neuroblastoma based on multiple datasets

Recent research highlights the pivotal role of N6-methyladenosine (m6A) modification and ferroptosis in the evolution of various cancers. This study aimed to establish a prognostic framework centered on genes associated with m6A and ferroptosis to enhance the accuracy of prognosis predictions for neuroblastoma (NB) patients, thereby improving targeted therapeutic strategies. Patient data, including expression profiles and clinical information from NB cases, were acquired from The Cancer Genome Atlas. Genes related to m6A modification and ferroptosis were identified, and those significant for prognosis were pinpointed using a combination of Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression. For further validation, the study utilized external datasets GSE62564 and GSE85047. A prognostic index was computed for each NB patient, followed by analyses of immune cell infiltration and potential drug responsiveness based on the prognostic model. Additionally, enrichment analysis was conducted on the prognostic scores. These scores showed a strong association with the tumor immune environment and the efficacy of prevalent cancer therapies. Moreover, the model's prognostic score emerged as an independent predictive marker for NB. This research succeeded in creating and confirming a prognostic model rooted in m6A and ferroptosis-linked genes, promising to enrich the prognostic understanding and treatment approaches for NB.

Deciphering the role of cuproptosis in the development of intimal hyperplasia in rat carotid arteries using single cell analysis and machine learning techniques

This study aims to explore the regulatory role of cuproptosis in carotid intimal hyperplasia (IH), providing new insights into its pathophysiological mechanisms and potential diagnostic and therapeutic strategies.

METHODS

We downloaded single-cell sequencing and bulk transcriptome data from the GEO database to screen for copper-growth-associated genes (CAGs) using machine-learning algorithms, including Random Forest and Support Vector Machine. After identifying relevant genes, we verified CAGs expression in IH and control groups using a rat model of carotid balloon strain. We analyzed the immune infiltration characteristics of carotid intimal hyperplasia and used electron microscopy to observe mitochondrial structural changes in cuproptosis. Additionally, we performed subgroup analyses of carotid balloon strains. The cuproptosis activity of VSMCs was explored in a single-cell dataset. Immunohistochemistry was applied to validate the expression of CAGs.

RESULTS

By means of machine learning algorithms, we identified several genes, including Pdhx and Fdx1, as novel therapeutic targets for carotid intimal hyperplasia. Meanwhile, immunohistochemistry results observed decreased expression of Pdhx and Fdx1 in the Neointimal hyperplasia(Neo) group. Immunohistochemical results showed a difference in cellular infiltration between Dendritic cells resting and Mast cells resting. By calculating cuproptosis activity in vascular smooth muscle cells (VSMCs), we found increased cuproptosis activity in normal vascular smooth muscle cells which was also observed in the electron microscopy. Microscopy revealed less mitochondrial swelling characteristic of cuproptosis in Neo group.

CONCLUSION

The CAGs identified may regulate intimal hyperplasia in rat carotid arteries by modulating cuproptosis and represent potential targets for treatment.

A novel defined risk signature of ferroptosis-related lncRNAs for predicting prognosis, immune infiltration, and chemotherapy response in multiple myeloma

BACKGROUND

Ferroptosis, an iron-dependent form of programmed cell death, has been implicated in various types of cancer. However, the association between ferroptosis-related long noncoding RNAs (FRLs) and multiple myeloma (MM) remains unclear. This study aimed to develop an FRL-based predictive model to assess its potential role in predicting overall survival prognosis and evaluating immune cell infiltration and chemotherapy response in MM patients.

METHODS

We identified FRLs using the GEO and FerrDb databases and employed univariate Cox regression and least absolute shrinkage and selection operator (LASSO) to establish a prognostic FRLs signature in the training cohort. The reliability of the risk model was evaluated using Kaplan-Meier (K-M) and time-dependent receiver operating characteristic (ROC) curve analyses. Gene set enrichment analysis (GSEA) was conducted to explore the biological functions associated with the FRLs signature. We also assessed immune cell infiltration and estimated the IC50 of drugs using the R package 'pRRophetic'. The expression of FRLs was validated by qRT-PCR.

RESULTS

We established a novel 8 FRLs signature, comprising AC005592.1, AC093714.1, AC104041.1, AL122058.1, DIRC1, ERVH-1, FAM223B, and TDRKH-AS1. The risk model was identified as an independent risk factor for overall survival (OS) in MM patients. Bioinformatics analysis indicated that the high-risk group exhibited activation of carcinogenic signaling pathways and immune cell infiltration. The qRT-PCR confirmed the significant upregulation in the expression of ERVH-1, TDRKH-AS1, and AC104041.1, and the downregulation of DIRC1, AC005592.1, AC093714.1, and AL122058.1 in MM samples. Furthermore, the ferroptosis inducer erastin triggered ferroptosis, inhibited cell viability, and upregulated TDRKH-AS1.

CONCLUSION

Our study highlights the potential of the FRLs signature as a prognostic tool and its implications for therapeutic strategies in MM.

Hedyotis diffusa injection modulates the ferroptosis in bladder cancer via CAV1/JUN/VEGFA

Hedyotis diffusa Willd. (HDW), a traditional Chinese medicinal plant, exhibits a variety of pharmacological effects and has anticancer potential for a wide range of cancer types; Ferroptosis is a non-apoptosis-regulated cell death induced by iron accumulation and subsequent lipid peroxidation; and there is currently an increasing interest in the therapeutic role of ferroptosis in cancer. However, the effects of HDW on bladder cancer and its underlying molecular mechanisms remain largely unknown. In this study, a combination of in vivo and in vitro experiments, network pharmacology and data mining methods were used to investigate the effects of HDW on BLCA. The results showed that HDW exerted its anticancer activity by inducing ferroptosis in bladder cancer cells. Subsequently, we demonstrated for the first time that HDW induced ferroptosis in vitro and in vivo. To further explore the possible targets of HDW-induced ferroptosis in bladder cancer, we performed network pharmacological analyses, transcriptomic analyses, and single-cell analyses; through integrative analyses, we identified three key pivotal genes associated with iron death, CAV1, VEGFA, and JUN.Mechanistically, we showed that CAV1, VEGFA and JUN are key determinants of HDW-induced ferroptosis in BLCA. Knockdown of target genes altered the anticancer effects of HDW in 5637 and T24 cells. In conclusion, our data show for the first time that HDW exerts its anticancer effects on BLCA through CAV1, VEGFA and JUN gene-induced ferroptosis. This is expected to provide a promising compound for bladder cancer therapy.

Targeting ferroptosis for improved radiotherapy outcomes in HPV-negative head and neck squamous cell carcinoma

To enhance the efficacy of radiotherapy (RT) in human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC), we explored targeting ferroptosis, a regulated cell death process. We developed a gene signature associated with ferroptosis using Cox proportional hazard modeling in HPV-negative HNSCC patients who underwent RT. This ferroptosis-related gene signature (FRGS) was a significant predictor of overall survival and recurrence-free survival in HPV-negative HNSCC patients who received RT. Subtype B of the FRGS, characterized by decreased expression of ferroptosis inducers [nuclear receptor coactivator 4 (NCOA4) and natural resistance-associated macrophage protein 2 homolog/divalent metal transporter 1 (NRAMP2/DMT1)] and increased expression of suppressors [phospholipid hydroperoxide glutathione peroxidase (GPX4) and ferritin heavy chain (FTH1)], was associated with poorer prognosis, potentially indicating the inhibition of ferroptosis. Furthermore, our in vitro and in vivo studies demonstrated that treatment with statins, such as atorvastatin and simvastatin, induced ferroptosis and sensitized radioresistant HNSCC cells to irradiation, improving radiosensitivity and potentially enhancing the response to RT. Additionally, in xenograft models, the combination of statins and RT led to a significant reduction in tumor initiation. These findings provide valuable insights for enhancing treatment and improving prognosis in HPV-negative HNSCC by targeting ferroptosis and utilizing statins to sensitize tumors to RT-induced cell death.

Development and validation of a prognostic model based on disulfidptosis-related ferroptosis genes: DRD4 and SLC2A3 as biomarkers for predicting prognosis in colon cancer

Background

Disulfidptosis and ferroptosis are emerging cell death modalities crucial to cancer progression, yet their prognostic potential in colon cancer (CC) remains underexplored. This study develops and validates a prognostic model based on DRD4 and SLC2A3, two genes involved in key biological processes in CC. DRD4 regulates cell proliferation, migration, and apoptosis, while SLC2A3 enhances glucose uptake via the Warburg effect, promoting tumor growth. High expression of both genes is linked to poor prognosis, advanced stages, and increased aggressiveness, enabling precise stratification of patients and accurate prognostic predictions.

Methods

Transcriptomic and clinical data from 476 CC samples and 41 normal colon samples were obtained from The Cancer Genome Atlas (TCGA) database, with 452 patient samples utilized for survival analysis. A training cohort and a validation cohort were generated through random allocation. Disulfidptosis-related ferroptosis genes (DRFGs) were identified using Pearson correlation analysis, and a prognostic model was built using the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. External validation was performed using the Gene Expression Omnibus (GEO) datasets (GSE17538 and GSE38832), and clinical samples were further analyzed through immunohistochemistry. Predictors in the nomogram included age, gender, tumor stage, and risk score. The C-index of the final model was used to assess its prognostic accuracy.

Results

The results were validated using external cohorts from the GEO database and immunohistochemistry experiments. A prognostic model incorporating DRD4 and SLC2A3 effectively stratified CC patients into high- and low-risk groups, revealing distinct differences in survival times, immune landscapes, and biological characteristics. High expression levels of DRD4 and SLC2A3 correlated with advanced clinicopathological stages and poor prognosis, with a C-index of 0.75 indicating strong predictive accuracy. Immunohistochemistry confirmed the upregulation of both genes in CC tissues, further validating the model's clinical relevance.

Conclusions

This DRFG-based prognostic model offers an effective tool for predicting clinical outcomes in CC and can guide personalized treatment strategies. The upregulation of DRD4 and SLC2A3 suggests their potential as therapeutic targets. Future studies should focus on elucidating the underlying mechanisms of these biomarkers to enhance their clinical application.

Luciferase-Based Reporter System for Investigating GPx4-Mediated Ferroptosis and Its Therapeutic Implications in Diabetes

Ferroptosis, a distinct form of regulated cell death, is characterized by iron-dependent lipid peroxide accumulation in cell membranes from dysregulated cellular iron homeostasis and compromised antioxidant defense mechanisms. Glutathione peroxidase 4 (GPx4) is crucial in the regulation of ferroptosis by controlling lipid peroxide accumulation. Recent research established the association of ferroptosis with several diseases, prompting investigation toward ferroptosis-targeted therapeutic approaches. However, there is a lack of sensor systems designed to evaluate ferroptosis modulation in intact cells. In this study, we developed a highly sensitive luciferase-based reporter system to study GPx4-mediated ferroptosis in cells. We constructed a novel vector flanking the GPx4 promoter driving luciferase gene expression, demonstrating ferroptosis-specific luciferase activity in transfected HEK293T cells. We established stable cells expressing the construct and optimized its suitability for high-throughput screening using well-established ferroptosis modulators. We identified eugenol, a phenolic compound, as a potent ferroptosis inhibitor using the developed reporter system. Eugenol demonstrated dose-dependent protection against ferroptosis-induced damage in pancreatic beta cells, as assessed by the expression of the key markers such as GPx4, SLC7A11, NRF2, and HO1. Further, we showed the regulation of iron levels and total iron-binding capacity of beta cells by eugenol in streptozotocin (STZ) -induced diabetic mice. Additionally, the diabetes-induced downregulation of GPx4 and antioxidant Nrf2 in pancreatic tissue was significantly mitigated by eugenol, as evidenced by both immunohistochemistry and gene expression analysis. This research validates the functionality of the ferroptosis sensor and offers an approach to develop antidiabetic therapy by targeting ferroptosis to protect beta-cell viability and function.

Selenomethionine alleviates T-2 toxin-induced articular chondrocyte ferroptosis via the system Xc-/GSH/GPX4 axis

T-2 toxin can induce bone and cartilage development disorder, and oxidative stress plays an important role in it. It is well known that selenomethionine (Se-Met) has antioxidative stress properties and promotes the repair of cartilage lesion, but it remains unclear whether Se-Met can relieve damaged cartilage exposure to T-2 toxin. Here, the oxidative stress and ferroptosis of chondrocytes exposure to T-2 toxin were observed. Mechanistically, T-2 toxin increased ROS, lipid ROS, MDA and Fe2+ contents in chondrocytes, decreased GSH and GPX4 activity, and inhibited the system Xc-/GSH/GPX4 antioxidant axis. In addition, the mitochondria of chondrocytes shrunk and the mitochondrial crest decreased or disappeared. However, Fer-1 (Ferrostatin-1) inhibited ferroptosis induced by T-2 toxin in chondrocytes. The Se-Met alleviated lipid peroxidation, oxidative stress, and damaged mitochondrial in T-2 toxin-infected chondrocytes, enhanced antioxidant enzyme activity, and activated the system Xc-/GSH/GPX4 axis, thereby antagonizing ferroptosis of chondrocytes and alleviating articular cartilage damage. In conclusion, our findings highlight the essentiality of ferroptosis in chondrocyte caused by T-2 toxin, elucidate how Se-Met offers protection against this injury and provide research evidence for the drug treatment target of Kashin-Beck disease.

Identification of biomarkers associated with ferroptosis in macrophages infected with Mycobacterium abscessus using bioinformatic tools

Mycobacterium abscessus is a rapidly growing nontuberculous mycobacterium that causes severe pulmonary infections. Recent studies indicate that ferroptosis may play a critical role in the pathogenesis of M. abscessus pulmonary disease. We obtained gene expression microarray data from the Gene Expression Omnibus database, focusing on THP-1-derived macrophages infected with M. abscessus and uninfected controls. Differentially expressed genes related to ferroptosis were identified through weighted gene co-expression network analysis and the "limma" package, followed by gene set variation analysis and gene set enrichment analysis for enrichment assessment. To explore regulatory network relationships among hub genes, we constructed RBP-mRNA, ceRNA, and TF-mRNA networks. Additionally, a protein-protein interaction network was built, and functional enrichment analyses were conducted for the hub genes. The diagnostic value of these genes was assessed using receiver operating characteristic curves. Six differentially expressed genes associated with ferroptosis were identified in M. abscessus infection. The receiver operating characteristic curves demonstrated that these genes had excellent predictive value for the infection. Functional enrichment analysis showed that these genes were involved in immune responses, inflammation, cellular metabolism, cell death, and apoptosis. Pathway enrichment analysis revealed significant enrichment in pathways related to apoptosis, inflammation, and hypoxia. The RBP-mRNA network highlighted significant interactions between hub genes and key RNA-binding proteins, while the ceRNA network predicted that miRNAs and lncRNAs regulate ferroptosis-related genes NACC2 and ITPKB. Furthermore, interactions between the hub gene HSD3B7 and transcription factors LMNB1 and ASCL1 may promote ferroptosis in macrophages by influencing iron metabolism and reactive oxygen species production, contributing to the M. abscessus infection process. Our findings identified biomarkers linked to ferroptosis in M. abscessus infection, providing new insights into its pathogenic mechanisms and potential therapeutic strategies.

Identification of ferroptosis-related signature predicting prognosis and therapeutic responses in pancreatic cancer

Ferroptosis plays a role in tumorigenesis by affecting lipid peroxidation and metabolic pathways; however, its prognostic or therapeutic relevance in pancreatic adenocarcinoma (PAAD) remains poorly understood. In this study, we developed a prognostic ferroptosis-related gene (FRG)-based risk model using cohorts of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), proposing plausible therapeutics. Differentially expressed FRGs between tumors from TCGA-PAAD and normal pancreatic tissues from Genotype-Tissue Expression were analyzed to construct a prognostic risk model using univariate and multivariate Cox regression and LASSO analyses. A model incorporating AURKA, CAV1, and PML gene expression effectively distinguished survival differences between high- and low-risk groups among TCGA-PAAD patients, with validation in two ICGC cohorts. The high-risk group was enriched in gene sets involving mTOR, MAPK, and E2F signaling. The immune and stromal cells infiltration score did not differ between the groups. Analysis of PRISM datasets using our risk model to classify pancreatic cell lines suggested the dasatinib's efficacy in the high-risk group, which was experimentally confirmed in four cell lines with a high- or low-risk signature. In conclusion, this study proposed a robust FRG-based prognostic model that may help stratify PAAD patients with poor prognoses and select potential therapeutic avenues.

Molecular mechanisms of ferroptosis in renal ischemia-reperfusion injury Investigated via bioinformatics analysis and animal experiments

Kidney transplantation is a pivotal treatment for end-stage renal disease. However, renal ischemia-reperfusion injury (IRI) during surgery significantly impacts graft function. Despite unclear molecular mechanisms, no specific therapies or preventative measures are available. Gene expression profiles from renal biopsies before and after IRI were downloaded from public databases. Differentially expressed genes were identified using the Wilcoxon rank-sum test and weighted gene co-expression network analysis. Ferroptosis-associated genes were screened using the FerrDb database. The genes with the highest connectivity were identified via the protein-protein interaction (PPI) network and upstream regulatory miRNAs were found through the gene-miRNA network. A mouse renal IRI model was constructed for transcriptome sequencing and quantitative real-time polymerase chain reaction (qRT-PCR) validation to elucidate the relationship between key ferroptosis genes and regulatory miRNAs in renal IRI. Differential analysis identified 15 ferroptosis-associated genes (TNFAIP3, IL6, KLF2, EGR1, JUN, ZFP36, GDF15, CDKN1A, HSPB1, BRD2, PDK4, DUSP1, SLC2A3, DDIT3, and CXCL2) involved in renal IRI regulation. In animal experiments, ferroptosis-related genes were also upregulated in the model group. Enrichment analysis and hematoxylin-eosin pathological staining suggested these genes are primarily involved in renal inflammatory responses. PPI network analysis revealed IL6 as the gene with the highest connectivity, and the gene-miRNA network indicated IL6 might be regulated by miR-let-7a. Animal experiments revealed decreased miR-let-7a and increased IL6 levels in the model group, identifying potential therapeutic targets. MiR-let-7a regulates ferroptosis in renal IRI by targeting IL6, highlighting IL6 as a crucial gene in the ferroptosis process of renal IRI.

Aristolochic acids-hijacked p53 promotes liver cancer cell growth by inhibiting ferroptosis

Aristolochic acids (AAs) have been identified as a significant risk factor for hepatocellular carcinoma (HCC). Ferroptosis is a type of regulated cell death involved in the tumor development. In this study, we investigated the molecular mechanisms by which AAs enhanced the growth of HCC. By conducting bioinformatics and RNA-Seq analyses, we found that AAs were closely correlated with ferroptosis. The physical interaction between p53 and AAs in HepG2 cells was validated by bioinformatics analysis and SPR assays with the binding pocket sites containing Pro92, Arg174, Asp207, Phe212, and His214 of p53. Based on the binding pocket that interacts with AAs, we designed a mutant and performed RNA-Seq profiling. Interestingly, we found that the binding pocket was responsible for ferroptosis, GADD45A, NRF2, and SLC7A11. Functionally, the interaction disturbed the binding of p53 to the promoter of GADD45A or NRF2, attenuating the role of p53 in enhancing GADD45A and suppressing NRF2; the mutant did not exhibit the same effects. Consequently, this event down-regulated GADD45A and up-regulated NRF2, ultimately inhibiting ferroptosis, suggesting that AAs hijacked p53 to down-regulate GADD45A and up-regulate NRF2 in HepG2 cells. Thus, AAs treatment resulted in the inhibition of ferroptosis via the p53/GADD45A/NRF2/SLC7A11 axis, which led to the enhancement of tumor growth. In conclusion, AAs-hijacked p53 restrains ferroptosis through the GADD45A/NRF2/SLC7A11 axis to enhance tumor growth. Our findings provide an underlying mechanism by which AAs enhance HCC and new insights into p53 in liver cancer. Therapeutically, the oncogene NRF2 is a promising target for liver cancer.

IDENTIFYING POTENTIAL KEY FERROPTOSIS-RELATED GENES AND THERAPEUTIC DRUGS IN SEPSIS-INDUCED ARDS BY BIOINFORMATICS AND EXPERIMENTAL VERIFICATION

ABSTRACT

Background: Acute respiratory distress syndrome (ARDS) is a serious pathological process with high mortality. Ferroptosis is pivotal in sepsis, whose regulatory mechanisms in sepsis-induced ARDS remains unknown. We aimed to determine key ferroptosis-related genes in septic ARDS and investigate therapeutic traditional Chinese medicine. Method: Sepsis-induced ARDS dataset obtained from Gene Expression Omnibus was analyzed to identify ferroptosis-related differentially expressed genes. Enrichment analysis and protein-protein interaction network construction were performed to identify hub genes. Immune cells infiltration was analyzed and competitive endogenous RNA network was constructed. The diagnostic value of hub genes in septic ARDS was analyzed and the occurrence of ferroptosis and the expression of hub genes were detected. Traditional Chinese medicine targeting hub genes was predicted via SymMap database and was verified. Results: Sixteen ferroptosis-related differentially expressed genes were obtained, among which the top four genes ( IL1B , TXN , MAPK3 , HSPB1 ) were selected as hub genes, which may be potential diagnostic markers of septic ARDS. Immunoassay showed that sepsis-induced ARDS and hub genes were closely related to immune cells. The competitive endogenous RNA network showed 26 microRNAs and 38 long noncoding RNA. Ferroptosis occurred and the expressions of IL1B , MAPK3 , and TXN were increased in septic ARDS mice and LPS-challenged human pulmonary alveolar epithelial cells. Sea buckthorn alleviated septic lung injury and affected hub genes expression. Conclusions: Ferroptosis-related genes of IL1B , MAPK 3, and TXN serve as potential diagnostic genes for sepsis-induced ARDS. Sea buckthorn may be therapeutic medication for ARDS. This study provides a new direction for septic ARDS treatment.

Synergistic machine learning models utilizing ferroptosis-related genes for improved neuroblastoma outcome prediction

Background

Neuroblastoma (NB) is a highly heterogeneous and common pediatric malignancy with a poor prognosis. Ferroptosis, an iron-dependent cell death pathway, may play a crucial role in NB tumor progression and immune response. This study aimed to investigate ferroptosis in NB to identify potential therapeutic targets and develop predictive models for prognosis and recurrence.

Methods

Six datasets were accessed from the ArrayExpress database and Gene Expression Omnibus. Ferroptosis-related genes (FRGs) were selected from the FerrDb website. Unsupervised clustering, differential expression analysis, weighted correlation network analysis (WGCNA), and gene set enrichment analysis (GSEA) were adopted to investigate potential pathways associated with ferroptosis in NB and identify the key genes involved. We used the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression to develop the ferroptosis-related prognostic signatures (FRPS) while using machine learning (ML) algorithms to construct the recurrence model.

Results

Ribosome and cell cycle may be the potential pathways for ferroptosis involved in NB, with MYCN and RRM2 identified as key genes in this regulatory process. Five FRGs-ATG7 (-1.009), ELAVL1 (1.739), PPARA (0.493), RDX6 (1.457), and TERT (0.247)-were screed out for the FRPS, which showed excellent predictive performance in comparison with other published NB signatures. Eight FRGs-ALDH3A2 (48.597), TERT (23.398), ULK2 (21.034), AKR1C1 (20.699), MFN2 (12.575), SLC16A1 (12.342), TF (10.240), and DDR2 (7.598)-were selected based on the importance scores to construct the recurrence model. Among the models, utilizing random forest (RF), XGboost, support vector machine (SVM), K-nearest neighbors (KNN), and linear discriminant analysis (LDA), the RF model exhibited the highest performance.

Conclusions

We investigated the potential ferroptosis-related pathways and hub- FRGs in NB and developed prognosis and recurrence models, providing new potential targets for prognostic evaluation and treatment in NB patients.

Chuanxiong Rhizoma regulates ferroptosis and the immune microenvironment in ischemic stroke through the JAK-STAT3 pathway

Ferroptosis is linked to various pathological conditions; however, the specific targets and mechanisms through which traditional Chinese medicine influences ischemic stroke (IS)-induced ferroptosis remain poorly understood. In this study, data from the Gene Expression Omnibus and disease target databases (OMIM, GeneCards, DisGeNet, TTD, and DrugBank) were integrated with ferroptosis-related gene datasets. To identify key molecular targets of Chuanxiong Rhizoma (CX), drug ingredient databases, including PubChem and TCMBank, were employed to map CX-related targets (CX-DEGs-FRG and CX-IS-FRG). Gene targets and relevant signaling pathways were analyzed using weighted gene co-expression network analysis, protein-protein interaction networks, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment. The least absolute shrinkage and selection operator regression and support vector machine methods were utilized to identify intersecting genes, and the predictive accuracy of core targets was evaluated through receiver operating characteristic curve analysis. Immune cell infiltration in the IS microenvironment was assessed using CIBERSORT, followed by molecular docking of CX's active components with key targets. The JAK-STAT3 pathway was identified as a critical regulatory mechanism, and five key targets (ALOX5, PTGS2, STAT3, G6PD, and HIF1A) emerged as central to the IS-induced ferroptosis. Elevated infiltration of CD8 + T cells and neutrophils was significantly correlated with IS. Notably, the active components mandenol and myricanone demonstrated strong binding affinities with these five targets, which validated the results from network-based analysis. In conclusion, the JAK-STAT3 pathway, through its regulation of ALOX5, PTGS2, STAT3, G6PD, and HIF1A, could play a crucial role in modulating ferroptosis and immune responses in IS. These findings suggest that CX could serve as a potential therapeutic approach for IS, targeting the regulation of IS-induced ferroptosis and the immune microenvironment.

Elevation of ANXA1 associated with potential protective mechanism against ferroptosis and immune cell infiltration in age-related macular degeneration

BACKGROUND

Age-related macular degeneration (AMD), is a neurodegenerative ocular disease. This study investigated the role of ferroptosis-related genes and their interaction with immune cell infiltration in AMD.

METHODS

We screened differential expression genes (DEGs) of AMD from data sets in Gene Expression Omnibus. We identified ferroptosis-related differentially expressed genes (ferroDEGs) by intersecting DEGs with ferroptosis-related genes. Protein-protein interactions network and Cytoscape were used for screening hub genes. Next, we analyzed immune cell infiltration using CIBERSORT and examined the crosstalk between hub ferroDEGs and immune cell infiltration. Hub genes expression in each cell cluster and the proportions of different cell clusters between AMD and normal samples were examined using single-cell data. The hub ferroDEG expressions were verified in cell and mouse models using RT-qPCR, western blot, and immunofluorescence assay. The roles of ANXA1 in ferroptosis and its crosstalk with microglia were investigated.

RESULTS

We identified hub ferroDEGs that include six genes (ANXA1, DKK1, CD44, VIM, TGFB2, DUSP1). Functional analysis of those hub ferroDEGs was found to be correlated with leukocyte migration and chemotaxis, macrophage migration, and gliogenesis. The high-risk ferroptosis group exhibited elevated levels of CD8+ T cells, activated NK cells, and M2 macrophages. Single-cell sequencing data revealed a high degree of cell heterogeneity in macular degeneration and the monocytes proportion in the macular area was higher in AMD samples. Moreover, we observed elevated mRNA and protein levels of CD44, ANXA1 (P < 0.01), while ANXA1 knockdown reduced GPX4 expression in the cell model. Finally, we validated increased ANXA1 expression and observed its colocalization with microglia in mouse models using immunofluorescence assays.

CONCLUSIONS

This study offers insights into the AMD pathogenesis and identifies ANXA1 as a potential target related to protecting from ferroptosis and immune response for future research.

Exploring the potential role of ENPP2 in polycystic ovary syndrome and endometrial cancer through bioinformatic analysis

Background

Growing evidence indicates a significant correlation between polycystic ovary syndrome (PCOS) and endometrial carcinoma (EC); nevertheless, the fundamental molecular mechanisms involved continue to be unclear.

Methods

Initially, differential analysis, the least absolute shrinkage and selection operator (LASSO) regression, and support vector machine-recursive feature elimination (SVM-RFE) algorithms were employed to identify candidate genes associated with ferroptosis in PCOS. Subsequently, the TCGA-UCEC data were utilized to pinpoint the core gene. Then, the expression of ENPP2 in granulosa cells and endometrium of PCOS was validated using real-time PCR (RT-qPCR). Additionally, we investigated the role of ENPP2 in the progression from PCOS to EC through western blotting (WB), colony formation assay, cell scratch assay, transwell assay, and immunofluorescence (IF). Subsequently, ENPP2 gene set enrichment analysis (GSEA) analyses were conducted to identify common pathways involved in PCOS and EC, which were then verified by RT-qPCR. Finally, immune infiltration and the tumor microenvironment (TME) were explored to examine the involvement of ENPP2 in EC progression.

Results

The datasets TCGA-UCEC (pertaining to EC), GSE34526, GSE137684, and GSE6798 (related to PCOS) were procured and subjected to analysis. The gene ENPP2 has been recognized as the shared element connecting PCOS and EC. Next, we observed a significant downregulation of ENPP2 expression in the granulosa cells in PCOS compared to the normal patients, while an upregulation of ENPP2 expression was observed in the endometrium of hyperandrogenic PCOS patients relative to the normal. In vitro, the WB revealed that 5-dihydrotestosterone (DHT) upregulated ENPP2 expression in Ishikawa and HEC-1-A cells. Additionally, we found that ENPP2 promoted the proliferation, migration, and invasion of Ishikawa and HEC-1-A cells. Subsequently, we discovered that overexpressed ENPP2 may lead to an increase in CYP19A1 (aromatase) and AR mRNA level. IF demonstrated that ENPP2 increased the expression of AR, suggesting a regulatory role for ENPP2 in hormonal response within PCOS and EC. Our findings indicated a significant correlation between ENPP2 expression and the modulation of immune responses.

Decoding the Ferroptosis-Related Gene Signatures and Immune Infiltration Patterns in Ovarian Cancer: Bioinformatic Prediction Integrated with Experimental Validation

Background

Ovarian cancer is a type of gynecological cancer with extremely high fatality rate. Ferroptosis, an iron-dependent regulated cell death, inhibits the immune infiltration of tumor cells. Therefore, it is worthwhile to explore the effects of ferroptosis-related gene signatures and immune infiltration patterns on the clinical prognosis of ovarian cancer.

Methods

In this study, we used the mRNA expression matrix and related medical information of those who suffer from ovarian cancer in the TCGA database. After that, we established a ferroptosis-related gene signature based on LASSO Cox regression model, and employed several specific enrichment analyses to explore the bioinformatics functions of differentially expressed genes (DEGs). Additionally, we analyzed the link between ferroptosis and immune cells by single-sample gene set enrichment analysis (ssGSEA) to create a heatmap of gene-immune cell correlation. We then examined the expression of immune checkpoints and verified the gene expression in ovarian cancer tissues by qPCR assays. Finally, we induced ferroptosis in ovarian cancer cells using drugs and analyzed their migration, invasion and gene expression.

Results

According to LASSO Cox regression analysis, 9 prognostic DEGs were in association with overall survival (OS), which was utilized to construct a 9-gene signature for patients. Patients were divided into two groups, in which high-risk group's OS was markedly shorter than that of low-risk group (Log-rank p<0.001). KEGG enrichment analysis showed that these DEGs were linked to human cytomegalovirus (HCMV) infection. The ssGSEA analysis revealed significant differences in immune cell type and expression between ALOX12 and GLRX5 groups (p<0.05). Heatmap showed high correlation of prognostic genes with various immune cells. qPCR assay confirmed the 9 gene expression signature in ovarian cancer tissues. The ovarian cancer cell invasion and migration were significantly inhibited after induction of ferroptosis.

Conclusion

We decoded the ferroptosis-related gene signatures and immune infiltration patterns that can be used to predict the prognosis of ovarian cancer patients.

Identification of new hub- ferroptosis-related genes in Lupus Nephritis

Background: Lupus Nephritis (LN) is the primary causation of kidney injury in systemic lupus erythematosus (SLE). Ferroptosis is a programmed cell death. Therefore, understanding the crosstalk between LN and ferroptosis is still a significant challenge. Methods: We obtained the expression profile of LN kidney biopsy samples from the Gene Expression Omnibus database and utilised the R-project software to identify differentially expressed genes (DEGs). Then, we conducted a functional correlation analysis. Ferroptosis-related genes (FRGs) and differentially expressed genes (DEGs) crossover to select FRGs with LN. Afterwards, we used CIBERSORT to assess the infiltration of immune cells in both LN tissues and healthy control samples. Finally, we performed immunohistochemistry on LN human renal tissue. Results: 10619 DEGs screened from the LN biopsy tissue were identified. 22 hub-ferroptosis-related genes with LN (FRGs-LN) were screened out. The CIBERSORT findings revealed that there were significant statistical differences in immune cells between healthy control samples and LN tissues. Immunohistochemistry further demonstrated a significant difference in HRAS, TFRC, ATM, and SRC expression in renal tissue between normal and control groups. Conclusion: We developed a signature that allowed us to identify 22 new biomarkers associated with FRGs-LN. These findings suggest new insights into the pathology and therapeutic potential of LN ferroptosis inhibitors and iron chelators.

TGFβ2-Driven Ferritin Degradation and Subsequent Ferroptosis Underlie Salivary Gland Dysfunction in Postmenopausal Conditions

Despite the high incidence of dry mouth in postmenopausal women, its underlying mechanisms and therapeutic interventions remain underexplored. Using ovariectomized (OVX) mouse models, here this study identifies ferroptosis, an iron-dependent regulated cell death, as a central mechanism driving postmenopausal salivary gland (SG) dysfunction. In the OVX-SGs, TGFβ signaling pathway is enhanced with the aberrant TGFβ2 expression in SG mesenchymal cells. Intriguingly, TGFβ2 treatment reduces iron-storing ferritin levels, leading to lipid peroxidation and ferroptotic death in SG epithelial organoids (SGOs). Mechanistically, TGFβ2 promotes the autophagy-mediated ferritin degradation, so-called ferritinophagy. A notable overexpression of the type III TGFβ receptor (TβRIII) is found in the OVX-SGs and TGFβ2-treated SGOs, while the silencing of TβRIII mitigates the ferroptosis-mediated deleterious effects of TGFβ2 on SGOs. Finally, administration of ferroptosis inhibitor, Liproxstatin-1 (Lip-1), improves saliva secretion in OVX mice. Present findings collectively suggest a link between TGFβ signaling, ferroptosis, and SG injury, offering new therapeutic avenues for postmenopausal xerostomia.

Ferroptosis and the tumor microenvironment

Ferroptosis is a type of regulated cell death characterized by its non-apoptotic, iron-dependent and oxidative nature. Since its discovery in 2012, extensive research has demonstrated its pivotal roles in tumorigenesis, metastasis and cancer therapy. The tumor microenvironment (TME) is a complex ecosystem comprising cancer cells, non-cancer cells, extracellular matrix, metabolites and cytokines. Recent studies have underscored a new paradigm in which non-cancer cells in the TME, such as immune and stromal cells, also play significant roles in regulating tumor progression and therapeutic resistance typically through complicated crosstalk with cancer cells. Notably, this crosstalk in the TME were partially mediated through ferrotopsis-related mechanisms. This review provides a comprehensive and systematic summary of the current findings concerning the roles of ferroptosis in the TME and how ferroptosis-mediated TME reprogramming impacts cancer therapeutic resistance and progression. Additionally, this review outlines various ferroptosis-related therapeutic strategies aimed at targeting the TME.

Novel signature of ferroptosis-related long non-coding RNA to predict lower-grade glioma overall survival

BACKGROUND

Ferroptosis is a novel type of programmed cell death in various tumors; however, underlying mechanisms remain unclear. We aimed to develop ferroptosis-related long non-coding RNA (FRlncRNA) risk scores to predict lower-grade glioma (LGG) prognosis and to conduct functional analyses to explore potential mechanisms.

METHODS

LGG-related RNA sequencing data were extracted from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases. Pearson correlation analysis was used to identify the FRlncRNAs, univariate Cox regression analysis was for identify the prognostic FRlncRNAs, and then intersection FRlncRNAs were screened between TCGA and CGGA. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to develop a risk score to predict LGG prognosis.

RESULTS

A total of nine FRlncRNAs were screened to construct the novel prognostic risk score of LGG, and high-risk score patients had a worse overall survival than low-risk score patients both in TCGA and CGGA datasets. The risk score was quite correlated with clinicopathological characteristics (age, WHO grade, status of MGMT Methtlation, IDH mutation, 1p/19q codeletion, and TMB), and could promote current molecular subtyping systems. Comprehensive analyses revealed that signaling pathways of B-cell receptor and T-cell receptor, immune cells of macrophage cell and CD4+ T cell, tumor microenvironment of stroma score and immune score, and immune checkpoints of PD-1, PD-L1, and CTLA4 were all enriched in the high-risk score group.

CONCLUSION

The nine FRlncRNAs risk scores was a promising biomarker to predict the LGG's prognosis and distinguish the characteristics of molecular and immune.