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

Identifying potential ferroptosis key genes for diagnosis and treatment of postmenopausal osteoporosis through competitive endogenous RNA network analysis

Objective

Postmenopausal osteoporosis (PMOP) is a common systemic metabolic bone disorder that is owing to the reduced estrogen secretion and imbalance of bone absorption and bone formation in postmenopausal women. Ferroptosis has been identified as a novel modulatory mechanism of osteoporosis. Nevertheless, the particular modulatory mechanism between ferroptosis and PMOP is still unclear. The objective of the current investigation was to detect potential biomarkers connected to ferroptosis in PMOP and discover its probable mechanism through bioinformatics.

Methods

We downloaded PMOP-related microarray datasets from the database of Gene Expression Omnibus (GEO) and obtained the differentially expressed genes (DEGs). Utilizing bioinformatics analysis, the DEGs were intersected with the ferroptosis dataset to obtain ferroptosis-connected mRNAs. Enrichment analysis employing KOBAS 3.0 was conducted to comprehend the biological functions and enrichment pathways of the DEGs. The generation of the protein-protein interaction (PPI) network was conducted with the aim of identifying central genes. Lastly, the coexpression and competitive endogenous RNA (ceRNA) networks were built using Cytoscape. With the help of external datasets GSE56815 to verify the reliability of the hub genes by plotting ROC curves.

Results

We identified 178 DE microRNAs (miRNAs), 138 DE circular RNAs (circRNAs), and 86 ferroptosis-related mRNAs. Enrichment analysis exhibited that mRNAs were primarily connected with the signaling pathways of PI3K/Akt, metabolism, mTOR, FoxO, HIF-1, AMPK, MAPK, ferroptosis, VEGF, and NOD-like receptors. Generation of the PPI network detected eight hub genes. The circRNA/miR-23b-3p/PTEN axis may relieve PMOP by inhibiting ferroptosis through targeting the pathway of PI3K/Akt signaling, which is a vital modulatory pathway for PMOP progression. Moreover, the ROC curves ultimately indicates that the four hub genes have greater diagnostic importance in PMOP samples in contrast to the normal group samples, which may be possible markers for PMOP diagnosis.

Conclusions

Bioinformatics analysis identified four hub genes, namely, PTEN, SIRT1, VEGFA, and KRAS, as potential biomarkers for PMOP diagnosis and management. Moreover, the circRNA/miR-23b-3p/PTEN axis may relieve PMOP by suppressing ferroptosis through targeting the pathway of PI3K/Akt signaling, providing a new avenue to explore the pathogenesis of PMOP.

Prediction of biomarkers associated with membranous nephropathy: Bioinformatic analysis and experimental validation

Membranous nephropathy (MN), the most prevalent form of nephrotic syndrome in non-diabetic adults globally, is currently the second most prevalent and fastest-increasing primary glomerular disease in China. Numerous renal disorders are developed partly due to ferroptosis. However, its relationship to the pathogenesis of MN has rarely been investigated in previous studies; actually, ferroptosis is closely linked to the immune microenvironment and inflammatory response, which might affect the entire process of MN development. In this study, we aimed to identify ferroptosis-related genes that are potentially related to immune cell infiltration, which can further contribute to MN pathogenesis. The microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Ferroptosis-related differentially expressed genes (FDEGs) were identified, which were further used for functional enrichment analysis. The common genes identified using the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithm and the support vector machine recursive feature elimination (SVM-RFE) algorithm were used to identify the characteristic genes related to ferroptosis. The feasibility of the 7 genes as a distinguishing factor was assessed using the receiver operating characteristic (ROC) curve, with the area under the curve (AUC) score serving as the evaluation metric. Gene set enrichment analysis (GSEA) and correlation analysis of these genes were further performed. The correlation between the expression of these genes and immune cell infiltration inferred by single sample gene set enrichment analysis (ssGSEA) algorithm was explored. As a result, 7 genes, including NR1D1, YTHDC2, EGR1, ZFP36, RRM2, RELA and PDK4, which were most relevant to immune cell infiltration, were identified to be potential diagnostic genes in MN patients. Next, the signature genes were validated with other GEO datasets. In the subsequent steps, we conducted quantitative real-time fluorescence PCR (qRT-PCR) analysis and immunohistochemistry (IHC) method on the cationic bovine serum albumin (C-BSA) induced membranous nephropathy (MN) rat model and the passive Heymann nephritis (pHN) rat model to examine characteristic genes. Finally, we analysed the mRNA expression patterns of hub genes in MN patients and normal controls using the Nephroseq V5 online platform. In concise terms, our study successfully identified biomarkers specific to MN patients and delved into the potential interplay between these markers and immune cell infiltration. This knowledge bears significance for the diagnosis and prospective treatment strategies for individuals affected by MN.

A risk model based on 10 ferroptosis regulators and markers established by LASSO-regularized linear Cox regression has a good prognostic value for ovarian cancer patients

Ovarian cancer is the deadliest gynecologic cancer due to its high rate of recurrence and limited early diagnosis. For certain patients, particularly those with recurring disorders, standard treatment alone is insufficient in the majority of cases. Ferroptosis, an iron- and ROS (reactive oxygen species)-reliant cell death, plays a vital role in the occurrence of ovarian cancer. Herein, subjects from TCGA-OV were calculated for immune scores using the ESTIMATE algorithm and assigned into high- (N = 185) or low-immune (N = 193) score groups; 259 ferroptosis regulators and markers were analyzed for expression, and 64 were significantly differentially expressed between two groups. These 64 differentially expressed genes were applied for LASSO-regularized linear Cox regression for establishing ferroptosis regulators and a markers-based risk model, and a 10-gene signature was established. The ROC curve indicated that the risk score-based curve showed satisfactory predictive efficiency. Univariate and multivariate Cox risk regression analyses showed that age and risk score were risk factors for ovarian cancer patients' overall survival; patients in the high-risk score group obtained lower immune scores. The Nomogram analysis indicated that the model has a good prognostic performance. GO functional enrichment annotation confirmed again the involvement of these 10 genes in ferroptosis and immune activities. TIMER online analysis showed that risk factors and immune cells were significantly correlated. In conclusion, the risk model based on 10 ferroptosis regulators and markers has a good prognostic value for ovarian cancer patients.

Leveraging technology-driven strategies to untangle omics big data: circumventing roadblocks in clinical facets of oral cancer

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and aggressive inclination. The early occurrences of this cancer can be clinically deceiving leading to a poor overall survival rate. The primary concerns from a clinical perspective include delayed diagnosis, rapid disease progression, resistance to various chemotherapeutic regimens, and aggressive metastasis, which collectively pose a substantial threat to prognosis. Conventional clinical practices observed since antiquity no longer offer the best possible options to circumvent these roadblocks. The world of current cancer research has been revolutionized with the advent of state-of-the-art technology-driven strategies that offer a ray of hope in confronting said challenges by highlighting the crucial underlying molecular mechanisms and drivers. In recent years, bioinformatics and Machine Learning (ML) techniques have enhanced the possibility of early detection, evaluation of prognosis, and individualization of therapy. This review elaborates on the application of the aforesaid techniques in unraveling potential hints from omics big data to address the complexities existing in various clinical facets of oral cancer. The first section demonstrates the utilization of omics data and ML to disentangle the impediments related to diagnosis. This includes the application of technology-based strategies to optimize early detection, classification, and staging via uncovering biomarkers and molecular signatures. Furthermore, breakthrough concepts such as salivaomics-driven non-invasive biomarker discovery and omics-complemented surgical interventions are articulated in detail. In the following part, the identification of novel disease-specific targets alongside potential therapeutic agents to confront oral cancer via omics-based methodologies is presented. Additionally, a special emphasis is placed on drug resistance, precision medicine, and drug repurposing. In the final section, we discuss the research approaches oriented toward unveiling the prognostic biomarkers and constructing prediction models to capture the metastatic potential of the tumors. Overall, we intend to provide a bird's eye view of the various omics, bioinformatics, and ML approaches currently being used in oral cancer research through relevant case studies.

Identification and validation of iron metabolism genes in osteoporosis

BACKGROUND

Osteoporosis is the most common metabolic bone disease in humans. Exploring the expression difference of iron metabolism-related genes in osteoporosis can provide a new target for diagnosis and treatment.

METHODS

First, we used online databases to identify differentially expressed genes (DEGs) related to iron metabolism in patients with osteoporosis. The differential genes were comprehensively analyzed by bioinformatics method (GO, KEGG, GSEA, immune infiltration analysis, PPI). The expression levels of hub genes and important signaling pathways were verified by qRT-PCR and Western blotting.

RESULTS

A total of 23 iron metabolism-related genes with significant differences were identified, which were enriched in "regulation of protein dephosphorylation" and "negative regulation of protein dephosphorylation". The GSEA results, heme metabolism and Myc targets v1 were among the top two pathways, both upregulated. The immune infiltration analysis revealed that the expressions of genes such as ABCA5, D2HGDH, GNAI2, and CTSW were correlated with the infiltration degree of significantly different cells. The PPI network contained 12 differentially expressed iron metabolism-related genes. Additionally, YWHAE, TGFB1, PPP1R15A, TOP2A, and CALR were mined as hub genes using the Cytoscape software. qRT PCR showed that the expression of TGF-β1, YWHAE, TOP2A and CALR increased. We also verified the expression of related proteins and genes in the oxidative stress signaling pathway by qRT PCR and Western blotting. The results showed that Mob1, YAP and TAZ molecules were highly expressed at the gene and protein levels.

CONCLUSIONS

These differentially expressed iron metabolism-related genes could provide new potential targets for the diagnosis and treatment of osteoporosis.

Identification of Drug Targets and Agents Associated with Ferroptosis-related Osteoporosis through Integrated Network Pharmacology and Molecular Docking Technology

BACKGROUND

Osteoporosis is a systemic bone disease characterized by progressive reduction of bone mineral density and degradation of trabecular bone microstructure. Iron metabolism plays an important role in bone; its imbalance leads to abnormal lipid oxidation in cells, hence ferroptosis. In osteoporosis, however, the exact mechanism of ferroptosis has not been fully elucidated.

OBJECTIVE

The main objective of this project was to identify potential drug target proteins and agents for the treatment of ferroptosis-related osteoporosis.

METHODS

In the current study, we investigated the differences in gene expression of bone marrow mesenchymal stem cells between osteoporosis patients and normal individuals using bioinformatics methods to obtain ferroptosis-related genes. We could predict their protein structure based on the artificial intelligence database of AlphaFold, and their target drugs and binding sites with the network pharmacology and molecular docking technology.

RESULTS

We identified five genes that were highly associated with osteoporosis, such as TP53, EGFR, TGFB1, SOX2 and MAPK14, which, we believe, can be taken as the potential markers and targets for the diagnosis and treatment of osteoporosis. Furthermore, we observed that these five genes were highly targeted by resveratrol to exert a therapeutic effect on ferroptosis-related osteoporosis.

CONCLUSION

We examined the relationship between ferroptosis and osteoporosis based on bioinformatics and network pharmacology, presenting a promising direction to the pursuit of the exact molecular mechanism of osteoporosis so that a new target can be discovered for the treatment of osteoporosis.

New molecular insights into ferroptosis in lung adenocarcinoma progression and pharmacological compounds for targeted therapy

BACKGROUND

The involvement of ferroptosis has been found in many pathological conditions of the lung. The genetic engineering of ferroptosis-related genes may provide a potential target for the treatment of lung adenocarcinoma (LUAD).

METHODS

Nine ferroptosis regulators and markers were collected from FerrDb and their somatic mutations and expressions were analyzed based on The Cancer Genome Atlas (TCGA)-LUAD cohort data. Least absolute shrinkage and selection operator (LASSO) and Cox regression analysis were performed to screen genes significantly associated with ferroptosis. The ferroptosis-related gene signature was constructed using TCGA-LUAD cohort data and was verified using the GSE cohort with pooled data for GSE30219, GSE31210, GSE37745 and GSE50081. Immune microenvironment component and mutation analysis were performed for genes in the ferroptosis-related gene signature.

RESULTS

All nine ferroptosis regulators and markers were differentially expressed between normal LUAD tumor tissues and adjacent normal tissues and were related to copy number variation. The expression of 1329 genes were significantly associated with nine ferroptosis regulators and markers in the TCGA-LUAD dataset, five (ALDOA, PLK1, CD47, CENPC and TMOD3) of which were integrated into a ferroptosis-related gene signature to calculate the risk score of LUAD samples, showing a significant correlation with the abundance of immune cell infiltration and the immune score. Molecular docking showed the binding activity of natural active compound quercetin to target proteins ALDOA and CD47, as well as the binding activity of aristolochic acid to PLK1 protein and TMOD3 protein.

CONCLUSIONS

In the present study, a ferroptosis-related gene signature with predictive value for LUAD prognosis was constructed, in which the gene was a potential therapeutic target for LUAD. Quercetin and aristolochic acid were potential candidates for inhibiting these targets by directly binding to them and showing high affinity and strong stability.

Identification of novel biomarkers of ferroptosis involved in keloid based on bioinformatics analysis

Keloid is a fibroproliferative disease of unknown aetiology, which has a significant impact the quality of life of patients. Ferroptosis plays an important role in the occurrence and development of fibrosis, but there is still a lack of research related to keloids. The objective of this work was to identify the hub genes related to ferroptosis in keloid to better understand the keloid process. The microarray data (GSE7890 GSE145725, and GSE44270) (23 keloid and 22 normal fibroblast) were analysed via the gene expression comprehensive database (GEO). Only GSE7890 met the FerrDB database. Cell cycle and pathway analysis were performed with gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed to differentially expressed genes (DEG). The differential genes were confirmed in other GEO datasets (GSE145725 and GSE44270), and multi-fibrosis-gene correlation analysed. To validate these hub genes, quantitative real-time PCR (qRT-PCR) was conducted. A total of 581 DEGs were screened, with 417 genes down-regulated and 164 genes up-regulated, with 11 ferroptosis genes significantly up-regulated in both keloid and normal tissue, and 6 genes are consistent with our findings and are associated with multiple fibrosis genes. The qRT-PCR results and tissues of normal skin and keloid agreed with our predictions. Our findings provide new evidence for the ferroptosis-related molecular pathways and biomarker of keloid.

Fisetin ameliorates fibrotic kidney disease in mice via inhibiting ACSL4-mediated tubular ferroptosis

Kidney fibrosis is the hallmark of chronic kidney disease (CKD) progression, whereas no effective anti-fibrotic therapies exist. Recent evidence has shown that tubular ferroptosis contributes to the pathogenesis of CKD with persistent proinflammatory and profibrotic responses. We previously reported that natural flavonol fisetin alleviated septic acute kidney injury and protected against hyperuricemic nephropathy in mice. In this study, we investigated the therapeutic effects of fisetin against fibrotic kidney disease and the underlying mechanisms. We established adenine diet-induced and unilateral ureteral obstruction (UUO)-induced CKD models in adult male mice. The two types of mice were administered fisetin (50 or 100 mg·kg-1·d-1, i.g.) for 3 weeks or 7 days, respectively. At the end of the experiments, the mice were euthanized, and blood and kidneys were gathered for analyzes. We showed that fisetin administration significantly ameliorated tubular injury, inflammation, and tubulointerstitial fibrosis in the two types of CKD mice. In mouse renal tubular epithelial (TCMK-1) cells, treatment with fisetin (20 μM) significantly suppressed adenine- or TGF-β1-induced inflammatory responses and fibrogenesis, and improved cell viability. By quantitative real-time PCR analysis of ferroptosis-related genes, we demonstrated that fisetin treatment inhibited ferroptosis in the kidneys of CKD mice as well as in injured TCMK-1 cells, as evidenced by decreased ACSL4, COX2, and HMGB1, and increased GPX4. Fisetin treatment effectively restored ultrastructural abnormalities of mitochondrial morphology and restored the elevated iron, the reduced GSH and GSH/GSSG as well as the increased lipid peroxide MDA in the kidneys of CKD mice. Notably, abnormally high expression of the ferroptosis key marker ACSL4 was verified in the renal tubules of CKD patients (IgAN, MN, FSGS, LN, and DN) as well as adenine- or UUO-induced CKD mice, and in injured TCMK-1 cells. In adenine- and TGF-β1-treated TCMK-1 cells, ACSL4 knockdown inhibited tubular ferroptosis, while ACSL4 overexpression blocked the anti-ferroptotic effect of fisetin and reversed the cytoprotective, anti-inflammatory, and anti-fibrotic effects of fisetin. In summary, we reveal a novel aspect of the nephroprotective effect of fisetin, i.e. inhibiting ACSL4-mediated tubular ferroptosis against fibrotic kidney diseases.

Integrated Single-cell and Bulk RNA Sequencing Analysis Cross Talk between Ferroptosis-related Genes and Prognosis in Oral Cavity Squamous Cell Carcinoma

BACKGROUND

Ferroptosis is a new type of programmed apoptosis and plays an important role in tumour inhibition and immunotherapy.

OBJECTIVE

In this study, we aimed to explore the potential role of ferroptosis-related genes (FRGs) and the potential therapeutic targets in oral cavity squamous cell carcinoma (OCSCC).

METHODS

The transcription data of OCSCC samples were obtained from the Cancer Genome Atlas (TCGA) database as a training dataset. The prognostic FRGs were extracted by univariate Cox regression analysis. Then, we constructed a prognostic model using the least absolute shrinkage and selection operator (LASSO) and Cox analysis to determine the independent prognosis FRGs. Based on this model, risk scores were calculated for the OCSCC samples. The model's capability was further evaluated by the receiver operating characteristic curve (ROC). Then, we used the GSE41613 dataset as an external validation cohort to confirm the model's predictive capability. Next, the immune infiltration and somatic mutation analysis were applied. Lastly, single-cell transcriptomic analysis was used to identify the key cells.

RESULTS

A total of 12 prognostic FRGs were identified. Eventually, 6 FRGs were screened as independent predictors and a prognostic model was constructed in the training dataset, which significantly stratified OCSCC samples into high-risk and low-risk groups based on overall survival. The external validation of the model using the GSE41613 dataset demonstrated a satisfactory predictive capability for the prognosis of OCSCC. Further analysis revealed that patients in the highrisk group had distinct immune infiltration and somatic mutation patterns from low-risk patients. Mast cell infiltrations were identified as prognostic immune cells and played a role in OCSCC partly through ferroptosis.

CONCLUSION

We successfully constructed a novel 6 FRGs model and identified a prognostic immune cell, which can serve to predict clinical prognoses for OCSCC. Ferroptosis may be a new direction for immunotherapy of OCSCC.

A ferroptosis-related LncRNAs signature for predicting prognoses and screening potential therapeutic drugs in patients with lung adenocarcinoma: A retrospective study

BACKGROUND

Lung adenocarcinoma (LUAD) has a high mortality rate. Ferroptosis is linked to tumor initiation and progression.

AIMS

This study aims to develop prognostic models of ferroptosis-related lncRNAs, evaluate the correlation between differentially expressed genes and tumor microenvironment, and identify prospective drugs for managing LUAD.

METHODS AND RESULTS

In this study, transcriptomic and clinical data were downloaded from the TCGA database, and ferroptosis-related genes were obtained from the FerrDb database. Through correlation analysis, Cox analysis, and the LASSO algorithm for constructing a prognostic model, we found that ferroptosis-related lncRNA-based gene signatures (FLncSig) had a strong prognostic predicting ability in the LUAD patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichments reconfirmed that ferroptosis is related to receptor-ligand activity, enzyme inhibitor activity, and the IL-17 signaling pathway. Next, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE) algorithms, and pRRophetic were used to predict immunotherapy response and chemotherapy sensitivity. The IMvigor210 cohort was also used to validate the prognostic model. In the tumor microenvironment, Type_II_IFN_Response and HLA were found to be a group of low-risk pathways, while MHC_class_I was a group of high-risk pathways. Patients in the high-risk subgroup had lower TIDE scores. Exclusion, MDSC, CAF, and TAMM2 were significantly and positively correlated with risk scores. In addition, we found 15 potential therapeutic drugs for LUAD. Finally, differential analysis of stemness index based on mRNA expression (mRNAsi) indicated that mRNAsi was correlated with gender, primary tumor (T), distant metastasis (M), and the tumor, node, and metastasis (TNM) stage in LUAD patients.

CONCLUSIONS

In conclusion, the prognostic model based on FLncSig can alleviate the difficulty in predicting the prognosis and immunotherapy of LUAD patients. The identified FLncSig and the screened drugs exhibit potential for clinical application and provide references for the treatment of LUAD.

Casein-phosphatidylcholine emulsifier remodels LPS-induced intestinal barrier disfunction via regulating ferroptosis and lipid metabolism

Recently, the biosafety of synthetic emulsifier in intestinal barrier has raised significant concerns. Casein- phosphatidylcholine (CP), which is a natural emulsifier, has better emulsification and stability. However, the effect of CP on intestinal barrier remains unknow. Intestinal permeability and lipomics analysis showed that carboxymethyl cellulose (CMC) and CP have no significant effect on intestinal barrier in normal intestinal barrier model, whereas CP increased transmembrane resistance value and remodeled lipid homeostasis in LPS induced intestinal barrier dysfunction model, indicating its superior biosafety. To explore the underlying molecular mechanism of emulsifier on intestinal barrier dysfunction, the bioinformatics analysis of six original microarray datasets including 168 cases in NCBI-Gene Expression Omnibus database showed ferroptosis-related genes showed a significant differential expression. The quantitative polymerase chain reaction analysis demonstrated that CP can repair the imbalance of lipid homeostasis induced by LPS and restore normal intestinal permeability by regulating the expression of ferroptosis-related genes, while CMC could can enhance intestinal permeability by inducing ferroptosis of intestinal epithelial cells through lipid peroxidation. In conclusion, this study highlighted CP could remodel LPS-induced intestinal barrier disfunction via regulating ferroptosis and lipid metabolism. These findings can be used as a new insight for the design of new healthy emulsifier.

Detecting ferroptosis and immune infiltration profiles in multiple system atrophy using postmortem brain tissue

Background

The importance of ferroptosis and the immune system has been mentioned in the pathogenesis of α-synucleinopathy. The α-synuclein-immunoreactive inclusions that primarily affect oligodendrocytes are the hallmark of multiple system atrophy (MSA). Limited evidence implicates that iron and immune responses are involved in the pathogenesis of MSA, which is associated with neurodegeneration and α-synuclein aggregation.

Methods

The RNA sequencing data were collected from the Gene Expression Omnibus database. MSA-C-related module genes were identified through weighted gene co-expression network analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to predict the potential molecular functions. The candidate ferroptosis-related genes associated with MSA-C were obtained using a machine-learning algorithm. CIBERSORT was used to estimate the compositional patterns of the 22 types of immune cells.

Results

The tissues for sequencing were extracted from postmortem cerebellar white matter tissues of 11 MSA-C patients and 47 healthy controls. The diagnostic ability of the six MSA-C-related ferroptosis-related genes in discriminating MSA-C from the healthy controls demonstrated a favorable diagnostic value, with the AUC ranging from 0.662 to 0.791. The proportion of CD8+ T cells in MSA-C was significantly higher than in the controls (P = 0.02). The proportion of NK cells resting in MSA-C was significantly higher than in the controls (P = 0.011).

Conclusion

Ferroptosis and T-cell infiltration may be important pathways of disease development in MSA-C, and targeting therapies for these pathways may be disease-modifying.

Bioinformatics analysis of ferroptosis-related genes and immune cell infiltration in non-alcoholic fatty liver disease

BACKGROUND

The morbidity and mortality rates of patients with non-alcoholic fatty liver disease (NAFLD) have been steadily increasing in recent years. Previous studies have confirmed the important role of ferroptosis in NAFLD development; however, the precise mechanism through which ferroptosis influences NAFLD occurrence remains unclear. The present study aimed to identify and validate ferroptosis-related genes involved in NAFLD pathogenesis and to investigate the underlying molecular mechanisms of NAFLD.

METHODS

We downloaded microarray datasets GSE72756 and GSE24807 to identify differentially expressed genes (DEGs) between samples from healthy individuals and patients with NAFLD. From these DEGs, we extracted ferroptosis-related DEGs. GSE89632, another microarray dataset, was used to validate the expression of ferroptosis-related genes. A protein-protein interaction (PPI) network of ferroptosis-related genes was then constructed. The target genes were also subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Finally, competing endogenous RNA networks were constructed. We used the CIBERSORT package to evaluate the infiltration of immune cells infiltration in NAFLD.

RESULTS

Five ferroptosis-related genes (SCP2, MUC1, DPP4, SLC1A4, and TF) were identified as promising diagnostic biomarkers for NAFLD. Enrichment analyses revealed that these genes are mainly involved in metabolic processes. NEAT1-miR-1224-5p-SCP2, NEAT1-miR-485-5p-MUC1, MALAT1-miR-485-5p-MUC1, and CNOT6-miR-145-5p-SLC1A4 are likely to be the potential RNA regulatory pathways that affect NAFLD development. Principal component analysis indicated significant differences in immune cell infiltration between the two groups.

CONCLUSIONS

This study identified five ferroptosis-related genes as potential biomarkers for diagnosing NAFLD. The correlations between the expression of ferroptosis-related genes and immune cell infiltration might shed light on the study of the molecular mechanism underlying NAFLD development.

Construction of a ferroptosis-based prognostic model for breast cancer helps to discriminate high/low risk groups and treatment priority

Introduction

Breast cancer is a common malignant tumor associated with high morbidity and mortality. The role of ferroptosis, a regulated form of cell death, in breast cancer development and prognosis remains unclear. This study aims to investigate the relationship between ferroptosis-related genes and breast cancer and develop a prognostic model.

Methods

RNA-seq expression datasets and clinical samples of breast cancer patients were obtained from public databases. Immunity- and drug resistance-related data were integrated. A preliminary screening was performed, resulting in the identification of 73 candidate ferroptosis factors. Univariate Cox regression analysis was conducted to select 12 genes, followed by LASSO Cox regression analysis to construct a prognostic risk prediction model consisting of 10 ferroptosis-related genes. The model was further characterized by immune cell infiltration. The expression levels of ferroptosis-related genes were validated in human breast cancer cell lines, and immunohistochemical (IHC) analysis was conducted on cancer specimens to assess ferroptosis-related protein expression.

Results

The study identified 10 ferroptosis-related genes that were significantly associated with breast cancer prognosis. The constructed prognostic risk prediction model showed potential for predicting the prognostic value of these genes. In addition, the infiltration of immune cells was observed to be a characteristic of the model. The expression levels of ferroptosis-related genes were confirmed in human breast cancer cell lines, and IHC analysis provided evidence of ferroptosis-related protein expression in cancer specimens.

Discussion

This study provides a novel prognostic model for breast cancer, incorporating 10 ferroptosis-related genes. The model demonstrates the potential for predicting breast cancer prognosis and highlights the involvement of immune cell infiltration. The expression levels of ferroptosis-related genes and proteins further support the association between ferroptosis and breast cancer development.

Development and validation of stable ferroptosis- and pyroptosis-related signatures in predicting prognosis and immune status in breast cancer

To develop and validate the predictive effects of stable ferroptosis- and pyroptosis-related features on the prognosis and immune status of breast cancer (BC). We retrieved as well as downloaded ferroptosis- and pyroptosis-related genes from the FerrDb and GeneCards databases. The minimum absolute contraction and selection operator (LASSO) algorithm in The Cancer Genome Atlas (TCGA) was used to construct a prognostic classifier combining the above two types of prognostic genes with differential expression, and the Integrated Gene Expression (GEO) dataset was used for validation. Seventeen genes presented a close association with BC prognosis. Thirteen key prognostic genes with prognostic value were considered to construct a new expression signature for classifying patients with BC into high- and low-risk groups. Kaplan-Meier analysis revealed a worse prognosis in the high-risk group. The receiver operating characteristic (ROC) curve and multivariate Cox regression analysis identified its predictive and independent features. Immune profile analysis showed that immunosuppressive cells were upregulated in the high-risk group, and this risk model was related to immunosuppressive molecules. We successfully constructed combined features of ferroptosis and pyroptosis in BC that are closely related to prognosis, clinicopathological and immune features, chemotherapy efficacy and immunosuppressive molecules. However, further experimental studies are required to verify these findings.

The Evaluation of Prognostic Value and Immune Characteristics of Ferroptosis-Related Genes in Lung Squamous Cell Carcinoma

Background  The purpose of our study was to construct a prognostic model based on ferroptosis-related gene signature to improve the prognosis prediction of lung squamous carcinoma (LUSC). Methods  The mRNA expression profiles and clinical data of LUSC patients were downloaded. LUSC-related essential differentially expressed genes were integrated for further analysis. Prognostic gene signatures were identified through random forest regression and univariate Cox regression analyses for constructing a prognostic model. Finally, in a preliminary experiment, we used the reverse transcription-quantitative polymerase chain reaction assay to verify the relationship between the expression of three prognostic gene features and ferroptosis. Results  Fifty-six ferroptosis-related essential genes were identified by using integrated analysis. Among these, three prognostic gene signatures (HELLS, POLR2H, and POLE2) were identified, which were positively affected by LUSC prognosis but negatively affected by immune cell infiltration. Significant overexpression of immune checkpoint genes occurred in the high-risk group. In preliminary experiments, we confirmed that the occurrence of ferroptosis can reduce three prognostic gene signature expression. Conclusions  The three ferroptosis-related genes could predict the LUSC prognostic risk of antitumor immunity.

Ferroptosis-related genes prognostic signature for pancreatic cancer and immune infiltration: potential biomarkers for predicting overall survival

BACKGROUND

Pancreatic adenocarcinoma (PAAD) constitutes a lethal malignancy, notorious for its elevated mortality rates due to the difficulties in early diagnosis and rapid metastasis. The emerging paradigm of ferroptosis-an iron-catalyzed, regulated cell death distinguished by the accrual of lipid peroxides-has recently garnered scholarly focus. However, the expression landscape of ferroptosis-related genes (FRGs) in PAAD and their prognostic implications remain enigmatic.

METHODS

We undertook a rigorous quantification of FRGs in PAAD samples, sourcing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. These repositories also provided extensive metadata, encompassing mesenchymal stemness index (mRNAsi), genomic mutations, copy number variations (CNV), tumor mutational burden (TMB), and other clinical attributes. A predictive model was constructed utilizing Lasso regression analysis, and a co-expression study was executed to elucidate the complex interconnections between FRGs and other gene sets.

RESULTS

Intriguingly, FRGs were substantially upregulated in the high-risk cohort, even in the absence of clinically manifest symptoms, emphasizing their utility as prognostic biomarkers. Gene set enrichment analysis (GSEA) revealed significant enrichment of immune and tumor-related pathways in this high-risk demographic. Striking heterogeneities in immune function and N6-methyladenosine (m6A) RNA modification were observed between the low- and high-risk groups. Our analysis further implicated a cohort of genes-including LINC01559, C11orf86, SERPINB5, DSG3, MSLN, EREG, FAM83A, CXCL5, LY6D, and PSCA-as cardinal mediators in PAAD pathogenesis. A convergence of our predictive model with an analysis of CNVs, single nucleotide polymorphisms (SNPs), and drug sensitivities, revealed an intricate relationship with the FRGs.

CONCLUSIONS

Our findings accentuate the salient role of FRGs as critical modulators in the pathogenesis and progression of PAAD. Importantly, our composite prognostic framework offers invaluable insights into PAAD clinical trajectory. Moreover, the complex crosstalk between FRGs and immune cell landscapes in the tumor microenvironment (TME) may elucidate prospective therapeutic strategies. The clinical translational utility of these insights, however, requires further in-depth empirical exploration. Accordingly, the FRG signature introduces a compelling new avenue for risk stratification and targeted therapeutic interventions in this devastating malignancy.

Quercetin is a Potential Therapy for Rheumatoid Arthritis via Targeting Caspase-8 Through Ferroptosis and Pyroptosis

Background

Rheumatoid arthritis (RA) is one of the most common chronic inflammatory autoimmune diseases. However, the underlying molecular mechanisms of its pathogenesis are unknown. This study aimed to identify the common biomarkers of ferroptosis and pyroptosis in RA and screen potential drugs.

Methods

The RA-related differentially expressed genes (DEGs) in GSE55235 were screened by R software and intersected with ferroptosis and pyroptosis gene libraries to obtain differentially expressed ferroptosis-related genes (DEFRGs) and differentially expressed pyroptosis-related genes (DEPRGs). We performed Gene Ontology (GO), Kyoto Encyclopedia of the Genome (KEGG), ClueGO, and Protein-Protein Interaction (PPI) analysis for DEFRGs and DEPRGs and validated them by machine learning. The microRNA/transcription factor (TF)-hub genes regulatory network was further constructed. The key gene was validated using the GSE77298 validation set, cellular validation was performed in in vitro experiments, and immune infiltration analysis was performed using CIBERSORT. Network pharmacology was used to find key gene-targeting drugs, followed by molecular docking and molecular dynamics simulations to analyze the binding stability between small-molecule drugs and large-molecule proteins.

Results

Three hub genes (CASP8, PTGS2, and JUN) were screened via bioinformatics, and the key gene (CASP8) was validated and obtained through the validation set, and the diagnostic efficacy was verified to be excellent through the receiver operating characteristic (ROC) curves. The ferroptosis and pyroptosis phenotypes were constructed by fibroblast-like synoviocytes (FLS), and caspase-8 was detected and validated as a common biomarker for ferroptosis and pyroptosis in RA, and quercetin can reduce caspase-8 levels. Quercetin was found to be a potential target drug for caspase-8 by network pharmacology, and the stability of their binding was further verified using molecular docking and molecular dynamics simulations.

Conclusion

Caspase-8 is an important biomarker for ferroptosis and pyroptosis in RA, and quercetin is a potential therapy for RA via targeting caspase-8 through ferroptosis and pyroptosis.

Screening of potential key ferroptosis-related genes in Chronic Obstructive Pulmonary Disease

PURPOSE

Ferroptosis plays essential roles in the development of COPD. We aim to identify the potential ferroptosis-related genes of COPD through bioinformatics analysis.

METHODS

The RNA expression profile dataset GSE148004 was obtained from the GEO database. The ferroptosis-related genes were obtained from the FerrDb database. The potential differentially expressed ferroptosis-related genes of COPD were screened by R software. Then, protein-protein interactions (PPI), correlation analysis, gene-ontology (GO) enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were applied for the differentially expressed ferroptosis-related genes. Finally, hub gene-microRNA(miRNA), hug gene-transcription factor interaction networks were constructed by miRTarBase v8.0 and JASPAR respectively, and hub gene drugs were predicted by the Enrichr database.

RESULTS

A total of 41 differentially expressed ferroptosis-related genes (22 up-regulated genes and 19 down-regulated genes) were identified between 7 COPD patients and 9 healthy controls. The PPI results demonstrated that these ferroptosis-related genes interacted with each other. The GO and KEGG enrichment analyses of differentially expressed ferroptosis-related genes indicated several enriched terms related to ferroptosis, central carbon metabolism in cancer, and the HIF-1 signaling pathway. The crucial miRNAs and drugs associated with the top genes were identified.

CONCLUSION

We identified 41 potential ferroptosis-related genes in COPD through bioinformatics analysis. HIF1A, PPARG, and KRAS may affect the development of COPD by regulating ferroptosis. These results may expand our understanding of COPD and might be useful in the treatment of COPD.

Identification of ferroptotic genes and phenotypes in idiopathic nonobstructive azoospermia

Effective treatments for nonobstructive azoospermia (NOA), which affects 1% of all men globally, are limited by undefined pathogenic mechanisms, especially in idiopathic NOA (iNOA). Here, we tried to identify the functional ferroptosis-related genes and phenotypes involved in iNOA. Differentially expressed ferroptotic genes were identified from iNOA mRNA microarray datasets by bioinformatic analyses, and these ferroptotic genes were subsequently filtered by various algorithms. Then, receiver operating characteristic (ROC) curves were generated to evaluate the diagnostic ability of the abovementioned genes for iNOA. Generally, 11 differentially expressed ferroptotic genes were downregulated, and five genes were upregulated in iNOA samples. Four genes, including DUSP1, GPX4, HSD17B11, and SLC2A8, were technically selected and determined to be potential biomarkers for iNOA. Subsequently, similar expression levels were validated at both the RNA and protein levels in the iNOA specimens. Finally, morphologic and biochemical assays were applied to define the ferroptotic phenotypes in testes. The ferroptotic features, like shrunken mitochondria with electron-dense membranes and a reduction in cristae were observed across various cell types within iNOA patients, accompanied by the overload of ferrous ions and increased lipid peroxidation production. Our findings demonstrated that these ferroptosis genes could be involved in the underlying pathogenesis mechanisms of iNOA by regulating ferroptosis and serve as potential diagnostic biomarkers. Also, the ferroptotic phenotypes were identified in iNOA patients.

LncPCD: a manually curated database of experimentally supported associations between lncRNA-mediated programmed cell death and diseases

Programmed cell death (PCD) refers to controlled cell death that is conducted to keep the internal environment stable. Long noncoding RNAs (lncRNAs) participate in the progression of PCD in a variety of diseases. However, no specialized online repository is available to collect and store the associations between lncRNA-mediated PCD and diseases. Here, we developed LncPCD, a comprehensive database that provides information on experimentally supported associations of lncRNA-mediated PCD with diseases. The current version of LncPCD documents 6666 associations between five common types of PCD (apoptosis, autophagy, ferroptosis, necroptosis and pyroptosis) and 1222 lncRNAs in 331 diseases. We also manually curated a wealth of information: (1) 7 important lncRNA regulatory mechanisms, (2) 310 PCD-associated cell types in three species, (3) detailed information on lncRNA subcellular locations and (4) clinical applications for lncRNA-mediated PCD in diseases. Additionally, 10 single-cell sequencing datasets were integrated into LncPCD to characterize the dynamics of lncRNAs in diseases. Overall, LncPCD is an extremely useful resource for understanding the functions and mechanisms of lncRNA-mediated PCD in diseases. Database URL:  http://spare4.hospital.studio:9000/lncPCD/Home.jsp.

Astaxanthin alleviates PM2.5-induced cardiomyocyte injury via inhibiting ferroptosis

BACKGROUND

Long-term exposure of humans to air pollution is associated with an increasing risk of cardiovascular diseases (CVDs). Astaxanthin (AST), a naturally occurring red carotenoid pigment, was proved to have multiple health benefits. However, whether or not AST also exerts a protective effect on fine particulate matter (PM2.5)-induced cardiomyocyte damage and its underlying mechanisms remain unclear.

METHODS

In vitro experiments, the H9C2 cells were subjected to pretreatment with varying concentrations of AST, and then cardiomyocyte injury model induced by PM2.5 was established. The cell viability and the ferroptosis-related proteins expression were measured in different groups. In vivo experiments, the rats were pretreated with different concentrations of AST for 21 days. Subsequently, a rat model of myocardial PM2.5 injury was established by intratracheal instillation every other day for 1 week. The effects of AST on myocardial tissue injury caused by PM2.5 indicating by histological, serum, and protein analyses were examined.

RESULTS

AST significantly ameliorated PM2.5-induced myocardial tissue injury, inflammatory cell infiltration, the release of inflammatory factors, and cardiomyocyte H9C2 cell damage. Mechanistically, AST pretreatment increased the expression of SLC7A11, GPX4 and down-regulated the expression of TfR1, FTL and FTH1 in vitro and in vivo.

CONCLUSIONS

Our study suggest that ferroptosis plays a significant role in the pathogenesis of cardiomyocyte injury induced by PM2.5. AST may serve as a potential therapeutic agent for mitigating cardiomyocyte injury caused by PM2.5 through the inhibition of ferroptosis.

Integrated Analysis of Ferroptosis and Immunity-Related Genes Associated with Diabetic Kidney Disease

Purpose

Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease (CKD) worldwide. Elucidation of the molecular mechanisms underlying ferroptosis and immunity in DKD could aid the development of potentially effective therapeutics. This study aimed to perform an integrated analysis of ferroptosis and immune-related differentially expressed mRNAs (DEGs) in DKD.

Materials and Methods

Gene expression profiles of samples obtained from patients with DKD and controls were downloaded from the Gene Expression Omnibus (GEO) database. The potential differentially expressed genes (DEGs) were screened using R software, and ferroptosis immune-related differentially expressed genes (FIRDEGs) were extracted from the DEGs. We performed functional enrichment analyses, and constructed protein-protein interaction (PPI) networks, transcription factor (TFs)-gene networks, and gene-drug networks to explore their potential biological functions. Correlation analysis and receiver operating characteristic curves were used for evaluating the FIRDEGs. We used the CIBERSORT algorithm to examine the composition of immune cells and determine the relationship between FIRDEG signatures and immune cells. Finally, the RNA expression of six FIRDEGs was validated in animal kidney samples using RT-PCR.

Results

We identified 80 FIRDEGs and performed their functional analyses. We identified six hub genes (Ccl5, Il18, Cybb, Fcgr2b, Myd88, and Ccr2) using PPI networks and predicted potential TF gene networks and gene-drug pairs. Immune cells, including M2 macrophages, resting mast cells, and gamma-delta T cells, were altered in DKD; the FIRDEGs (Fcgr2b, Cybb, Ccr2, and Ccl5) were closely correlated with the infiltration abundance of M2 macrophages and gamma-delta T cells. Finally, the hub genes were verified in mouse kidney samples.

Conclusion

We identified six hub FIRDEGs (Ccl5, Il18, Cybb, Fcgr2b, Myd88, and Ccr2) in DKD, and predicted the potential transcription factor gene networks and possible treatment targets for future research.

Integrated network pharmacology and experimental validation to explore the potential pharmacological mechanism of Qihuang Granule and its main ingredients in regulating ferroptosis in AMD

BACKGROUND

Qihuang Granule (QHG) is a traditional prescription  that has exhibited potential in safeguarding against age-related maculopathy (AMD). Salvia miltiorrhiza (SM) and Fructus lycii (FL) are the main components of QHG. Ferroptosis, a newly discovered, iron-dependent, regulated cell death pathway, have been implicated in the pathogenesis of AMD. This study delves into the intricate mechanism by which SM/FL and QHG confer protection against AMD by modulating the ferroptosis pathway, employing a combination of network pharmacology and experimental validation.

METHODS

Bioactive compounds and potential targets of SM and FL were gathered from databases such as TCMSP, GeneCard, OMIM, and FerrDb, along with AMD-related genes and key genes responsible for ferroptosis regulation. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network were performed to discover the potential mechanism. The construction of an interaction network involving AMD, ferroptosis, SM/FL potential target genes was facilitated by the STRING database and realized using Cytoscape software. Subsequent validation was accomplished through molecular docking and in vitro cell experiments.

RESULTS

Noteworthy active compounds including quercetin, tanshinone IIA, luteolin, cryptotanshinone, and hub targets such as HIF-1α, EGFR, IL6, and VEGFA were identified. KEGG enrichment unveiled the HIF-1 signalling pathway as profoundly enriched, and IL6 and VEGF were involved. The molecular docking revealed the significant active compounds with hub genes and quercetin showed good binding to HIF-1α, which is involved in inflammation and angiogenesis. Experimental results verified that both herbs and QHG could regulate key ferroptosis-related targets in the retinal pigment epithelium and inhibit the expression of HIF-1α, VEGFA, and IL-6, subsequently increase cell viability and decrease the ROS content induced by H2O2.

CONCLUSION

This study demonstrates the molecular mechanism through which SM/FL and QHG protect against AMD and emerges as a plausible mechanism underlying this protection.

Investigating EGF and PAG1 as necroptosis-related biomarkers for diabetic nephropathy: an in silico and in vitro validation study

The current study aims to understand the mechanisms behind regulated cell death (RCD) in diabetic nephropathy and identify related biomarkers through bioinformatics and experimental validation. Datasets of bulk and single-cell RNA sequencing were obtained from public databases and analyzed using gene set variation analysis (GSVA) with gene sets related to RCD, including autophagy, necroptosis, pyroptosis, apoptosis, and ferroptosis. RCD-related gene biomarkers were identified using weighted gene correlation network analysis (WGCNA). The results were verified through experiments with an independent cohort and in vitro experiments. The GSVA revealed higher necroptosis scores in diabetic nephropathy. Three necroptosis-related biomarkers, EGF, PAG1, and ZFP36, were identified and showed strong diagnostic ability for diabetic kidney disease. In vitro experiments showed high levels of necroptotic markers in HK-2 cells treated with high glucose. Bioinformatics and experimental validation have thus identified EGF and PAG1 as necroptosis-related biomarkers for diabetic nephropathy.

Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis

BACKGROUND

Epilepsy is a prevalent neurological disorder, and while its precise mechanism remains elusive, a connection to ferroptosis has been established. This study investigates the potential clinical diagnostic significance of ferroptosis-related genes (FRGs) during the acute phase of temporal lobe epilepsy.

METHODS

To identify differentially expressed genes (DEGs), we accessed data from the GEO database and performed an intersection analysis with the FerrDB database to pinpoint FRGs. A protein-protein interaction (PPI) network was constructed. To assess the diagnostic utility of the discovered feature genes for the disease, ROC curve analysis was conducted. Subsequently, qRT-PCR was employed to validate the expression levels of these feature genes.

RESULTS

This study identified a total of 25 FRGs. PPI network analysis revealed six feature genes: IL6, PTGS2, HMOX1, NFE2L2, TLR4, and JUN. ROC curve analysis demonstrated that the combination of these six feature genes exhibited the highest diagnostic potential. qRT-PCR validation confirmed the expression of these feature genes.

CONCLUSION

We have identified six feature genes (IL6, PTGS2, HMOX1, NFE2L2, TLR4, and JUN) strongly associated with ferroptosis in epilepsy, suggesting their potential as biomarkers for the diagnosis of temporal lobe epilepsy.

Uncovering the prominent role of satellite cells in paravertebral muscle development and aging by single-nucleus RNA sequencing

To uncover the role of satellite cells (SCs) in paravertebral muscle development and aging, we constructed a single-nucleus transcriptomic atlas of mouse paravertebral muscle across seven timepoints spanning the embryo (day 16.5) to old (month 24) stages. Eight cell types, including SCs, fast muscle cells, and slow muscle cells, were identified. An energy metabolism-related gene set, TCA CYCLE IN SENESCENCE, was enriched in SCs. Forty-two skeletal muscle disease-related genes were highly expressed in SCs and exhibited similar expression patterns. Among them, Pdha1 was the core gene in the TCA CYCLE IN SENESCENCE; Pgam2, Sod1, and Suclg1 are transcription factors closely associated with skeletal muscle energy metabolism. Transcription factor enrichment analysis of the 42 genes revealed that Myod1 and Mef2a were also highly expressed in SCs, which regulated Pdha1 expression and were associated with skeletal muscle development. These findings hint that energy metabolism may be pivotal in SCs development and aging. Three ligand-receptor pairs of extracellular matrix (ECM)-receptor interactions, Lamc1-Dag1, Lama2-Dag1, and Hspg2-Dag1, may play a vital role in SCs interactions with slow/fast muscle cells and SCs self-renewal. Finally, we built the first database of a skeletal muscle single-cell transcriptome, the Musculoskeletal Cell Atlas (http://www.mskca.tech), which lists 630,040 skeletal muscle cells and provides interactive visualization, a useful resource for revealing skeletal muscle cellular heterogeneity during development and aging. Our study could provide new targets and ideas for developing drugs to inhibit skeletal muscle aging and treat skeletal muscle diseases.

The putative role of ferroptosis in gastric cancer: a review

Ferroptosis is a unique cell death modality triggered by iron-dependent lipid peroxidation, with cysteine metabolism and glutathione-dependent antioxidant defence responses as the primary triggering mechanisms. Ferroptosis is an independent tumour suppression mechanism and has been implicated in various disorders. In tumourigenesis, ferroptosis plays a dual role in promoting and inhibiting tumours. P53, NFE2L2, BAP1, HIF, and other tumour suppressor genes regulate ferroptosis, releasing damage-associated molecular patterns or lipid metabolites to influence cellular immune responses. Ferroptosis is also involved in tumour suppression and metabolism. The combination of amino acid, lipid, and iron metabolism is involved in the initiation and execution of ferroptosis, and metabolic regulatory mechanisms also play roles in malignancies. Most investigations into ferroptosis in gastric cancer are concentrated on predictive models, not the underlying processes. This review investigates the underlying mechanisms of ferroptosis, tumour suppressor genes, and the tumour microenvironment.

Identification of potential ferroptosis key genes and immune infiltration in rheumatoid arthritis by integrated bioinformatics analysis

Objective

Ferroptosis is of vital importance in the development of Rheumatoid arthritis (RA). The purpose of this project is to clarify the potential ferroptosis-related genes, pathways, and immune infiltration in RA by bioinformatics analysis.

Methods

We acquired ferroptosis-related genes (FRGs) from Ferroptosis database (FerrDb). We obtained the Gene dataset of RA (GSE55235) from the Gene Expression Omnibus (GEO) Database, screened the differentially expressed genes (DEGs) in RA and control samples, and then took the intersection of it and FRGs. Aiming to construct the protein-protein interaction (PPI) networks of the FRGs-DEGs, STRING database and Cytoscape software 3.7.0 would be used. Furthermore, hub genes were identified by CytoNCA, a Cytoscape plug-in. The gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of FRGs-DEGs were performed.

Results

We identified 34 FRGs-DEGs, including 7 upregulated and 27 downregulated genes by taking the intersection of the FRGs and DEGs. PPI analysis identified a total of 3 hub genes(VEGFA, PTGS2, and JUN). GO enrichment analyses and KEGG Pathway enrichment displayed that the FRGs-DEGs are involved in the response to oxidative stress and corticosteroid, heme binding, FoxO-signal pathway. Results of immune infiltration displayed that increased infiltration of T cells, while Macrophages M2 less may be related to the occurrence of RA.

Conclusion

The hub genes involved in ferroptosis in RA may be VEGFA, PTGS2, and JUN, which are mainly involved in FoxO-signal pathway. T cell, Mac, and plasma cells may be involved in the regulation of RA-joints-synovial-inflammation.

Role of dysregulated ferroptosis‑related genes in cardiomyocyte ischemia‑reperfusion injury: Experimental verification and bioinformatics analysis

Acute myocardial infarction is a life-threatening condition with high mortality and complication rates. Although myocardial reperfusion can preserve ischemic myocardial tissue, it frequently exacerbates tissue injury, a phenomenon known as ischemia-reperfusion injury (IRI). However, the underlying pathological mechanisms of IRI remain to be completely understood. Ferroptosis is a novel type of regulated cell death that is associated with various pathological conditions, including angiocardiopathy. The purpose of this article was to elucidate the possible mechanistic role of ferroptosis in IRI through bioinformatics analysis and experimental validation. Healthy and IRI heart samples were screened for differentially expressed ferroptosis-related genes and functional enrichment analysis was performed to determine the potential crosstalk and pathways involved. A protein-protein interaction network was established for IRI, and 10 hub genes that regulate ferroptosis, including HIF1A, EGFR, HMOX1, and ATF3 were identified. In vitro, an anoxia/reoxygenation (A/R) injury model was established using H9c2 cardiomyoblasts to validate the bioinformatics analysis results, and extensive ferroptosis was detected. A total of 4 key hub genes and 3 key miRNAs were also validated. It was found that IRI was related to the aberrant infiltration of immune cells and the small-molecule drugs that may protect against IRI by preventing ferroptosis were identified. These results provide novel insights into the role of ferroptosis in IRI, which can help identify novel therapeutic targets.

Identification and validation of ferroptosis-related biomarkers in steroid-induced osteonecrosis of the femoral head

OBJECTIVES

Treatment of steroid-induced osteonecrosis of the femoral head (SIONFH) is challenging. Due to the limited understanding of its molecular mechanisms, investigating the potential mechanisms of ferroptosis will shed light on SIONFH and provide directions for treating this disease.

METHODS

The GSE123568 dataset was utilized to apply various bioinformatics methodologies to identify ferroptosis-related hub genes (FRHGs). Subsequently, the importance of these genes and the reliability of the results were confirmed using protein data-independent acquisition (DIA) and cell experiments. Finally, we assessed the correlation between FRHG expression and immune cell infiltration.

RESULTS

Thirty-one hub genes were identified and validated by constructing a protein-protein interaction network and subsequent screening using experimentally determined interactions. These 31 hub genes were enriched in immunity, the AMPK signaling pathway, and the Toll-like receptor signaling pathway. Next, we identified a diagnostic marker comprising two ferroptosis-related genes, NCF2 and SLC2A1. The differential expression of these two genes in healthy and necrotic regions was confirmed by protein DIA analysis. Cell experiments verified the link between FRHGs and ferroptosis and preliminarily explored the potential mechanism of the antioxidant vitexin in promoting osteogenic differentiation in cells. The diagnostic efficiency of these two markers was confirmed by receiver operating characteristic curve (ROC) curves, yielding an area under the curve of 1.0. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated enrichment of FRHGs in the superoxide anion and HIF-1 signaling pathways. A significant correlation was observed between FRHGs and various immune cell populations.

CONCLUSION

NCF2 and SLC2A1 are promising ferroptosis-related diagnostic biomarkers of SIONFH. Concurrently, we embarked on a preliminary investigation to elucidate the potential mechanism underlying the promotion of osteogenic differentiation by the antioxidant vitexin. Moreover, these biomarkers are associated with distinct immune cell populations.

Ferroptosis-Related Immune Genes in Hematological Diagnosis of Parkinson's Diseases

Emerging evidence suggested that ferroptosis and immune activation, as well as their interactions, played a crucial role in the occurrence and progression of Parkinson's disease (PD). However, whether this interaction could serve as the basis for a hematological diagnosis of PD remained poorly understood. This study aimed to construct a novel hematological model for PD diagnosis based on the ferroptosis-related immune genes. The brain imaging of PD patients was obtained from the Affiliated Hospital of Nantong University. We used least absolute shrinkage and selection operator (LASSO) to identify the optimal signature ferroptosis-related immune genes based on six gene expression profile datasets of substantia nigra (SN) and peripheral blood of PD patients. Then we used the support vector machine (SVM) classifier to construct the hematological diagnostic model named Ferr.Sig for PD. Gene set enrichment analysis was utilized to execute gene functional annotation. The brain imaging and functional annotation analysis revealed prominent iron deposition and immune activation in the SN region of PD patients. We identified a total of 17 signature ferroptosis-related immune genes using LASSO method and imported them to SVM classifier. The Ferr.Sig model exhibited a high diagnostic accuracy, and its area under the curve (AUC) for distinguishing PD patients from healthy controls in the training and internal validation cohort reached 0.856 and 0.704, respectively. We also used the Ferr.Sig into other external validation cohorts, and a comparable AUC with the internal cohort was obtained, with the AUC of 0.727 in Scherzer's cohort, 0.745 in Roncagli's cohort, and 0.778 in Meiklejohn's cohort. Furthermore, the diagnostic performance of Ferr.Sig was not interfered by the other neurodegenerative diseases. This study revealed the value of ferroptosis-related immune genes in PD diagnosis, which may provide a novel direction and strategy for the development of novel biomarkers with less invasiveness, low cost, and high accuracy for PD screening and diagnosis.

Ferroptosis-related genes as diagnostic markers for major depressive disorder and their correlations with immune infiltration

Background

Major depression disorder (MDD) is a devastating neuropsychiatric disease, and one of the leading causes of suicide. Ferroptosis, an iron-dependent form of regulated cell death, plays a pivotal role in numerous diseases. The study aimed to construct and validate a gene signature for diagnosing MDD based on ferroptosis-related genes (FRGs) and further explore the biological functions of these genes in MDD.

Methods

The datasets were downloaded from the Gene Expression Omnibus (GEO) database and FRGs were obtained from the FerrDb database and other literatures. Least absolute shrinkage and selection operator (LASSO) regression and stepwise logistic regression were performed to develop a gene signature. Receiver operating characteristic (ROC) curves were utilized to assess the diagnostic power of the signature. Gene ontology (GO) enrichment analysis was used to explore the biological roles of these diagnostic genes, and single sample gene set enrichment analysis (ssGSEA) algorithm was used to evaluate immune infiltration in MDD. Animal model of depression was constructed to validate the expression of the key genes.

Results

Eleven differentially expressed FRGs were identified in MDD patients compared with healthy controls. A signature of three FRGs (ALOX15B, RPLP0, and HP) was constructed for diagnosis of MDD. Afterwards, ROC analysis confirmed the signature's discriminative capacity (AUC = 0.783, 95% CI = 0.719-0.848). GO enrichment analysis revealed that the differentially expressed genes (DEGs) related to these three FRGs were mainly involved in immune response. Furthermore, spearman correlation analysis demonstrated that these three FRGs were associated with infiltrating immune cells. ALOX15B and HP were significantly upregulated and RPLP0 was significantly downregulated in peripheral blood of the lipopolysaccharide (LPS)-induced depressive model.

Conclusion

Our results suggest that the novel FRG signature had a good diagnostic performance for MDD, and these three FRGs correlated with immune infiltration in MDD.

Use of a ferroptosis-related gene signature to construct diagnostic and prognostic models for assessing immune infiltration in metabolic dysfunction-associated fatty liver disease

Introduction: Metabolic dysfunction-associated fatty liver disease (MAFLD), a serious health problem worldwide, can involve ferroptosis. This study aimed to comprehensively analyze the ferroptosis-related genes associated with MAFLD. Methods: Ferroptosis-related differentially expressed genes (FRDEGs) were identified in patients with MAFLD and healthy individuals. Gene ontology functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and gene set enrichment analysis (GSEA) were used to analyze the relevant action pathways of the FRDEGs. The Encyclopedia of RNA Interactomes, CHIPBase, and comparative toxicogenomics databases were used to build mRNA-miRNA, mRNA-transcription factor (TF), and mRNA-drug interaction networks, respectively. A diagnostic model was constructed and bioinformatics analysis methods, such as least absolute shrinkage and selection operator regression analysis, Cox regression analysis, nomogram-based analysis, consensus clustering analysis, and single-sample GSEA, were used to systematically investigate the prognostic values and immunologic characteristics. Results: A total of 13 FRDEGs were obtained and eight were used to construct a diagnostic model and perform a prognostic analysis. Hub genes were also used to construct mRNA-miRNA and mRNA-TF interaction networks and potential drug or molecular compounds. Two MAFLD subtypes were identified: cluster2, which represents an "immunoactive" type, and cluster1, which represents an "immunosuppressive" type; a significant correlation was observed between the immune cell contents and the expression of three FRDEGs (NR4A1, FADS2, and SCD). Conclusion: A ferroptosis-related gene signature was constructed to diagnose MAFLD-associated steatohepatitis, predict the prognosis of MAFLD patients, and analyze the immunologic characteristics of MAFLD. Our findings may provide insights into developing innovative MAFLD treatment techniques.

Bioinformatics-led discovery of ferroptosis-associated diagnostic biomarkers and molecule subtypes for tuberculosis patients

BACKGROUND

Ferroptosis is closely associated with the pathophysiological processes of many diseases, such as infection, and is characterized by the accumulation of excess lipid peroxides on the cell membranes. However, studies on the ferroptosis-related diagnostic markers in tuberculosis (TB) is still lacking. Our study aimed to explore the role of ferroptosis-related biomarkers and molecular subtypes in TB.

METHODS

GSE83456 dataset was applied to identify ferroptosis-related genes (FRGs) associated with TB, and GSE42826, GSE28623, and GSE34608 datasets for external validation of core biomarkers. Core FRGs were identified using weighted gene co-expression network analysis (WGCNA). Subsequently, two ferroptosis-related subtypes were constructed based on ferroptosis score, and differently expressed analysis, GSEA, GSEA, immune cell infiltration analysis between the two subtypes were performed.Affiliations: Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.correctly RESULTS: A total of 22 FRGs were identified, of which three genes (CHMP5, SAT1, ZFP36) were identified as diagnostic biomarkers that were enriched in pathways related to immune-inflammatory response. In addition, TB patients were divided into high- and low-ferroptosis subtypes (HF and LF) based on ferroptosis score. HF patients had activated immune- and inflammation-related pathways and higher immune cell infiltration levels than LF patients.

CONCLUSION

Three potential diagnostic biomarkers and two ferroptosis-related subtypes were identified in TB patients, which would help to understand the pathogenesis of TB.Author names: Kindly check and confirm the process of the author names [2,4]correctly.

Heme-deficient primitive red blood cells induce HSPC ferroptosis by altering iron homeostasis during zebrafish embryogenesis

The crosstalk between hematopoietic lineages is important for developmental hematopoiesis. However, the role of primitive red blood cells (RBCs) in the formation of definitive hematopoietic stem and progenitor cells (HSPCs) is largely unknown. Primitive RBC deficiencies in mammals always lead to early embryonic lethality, but zebrafish lines with RBC deficiencies can survive to larval stage. By taking advantage of a zebrafish model, we find that the survival of nascent HSPCs is impaired in alas2- or alad-deficient embryos with aberrant heme biosynthesis in RBCs. Heme-deficient primitive RBCs induce ferroptosis of HSPCs through the disruption of iron homeostasis. Mechanistically, heme-deficient primitive RBCs cause blood iron-overload via Slc40a1, and an HSPC iron sensor, Tfr1b, mediates excessive iron absorption. Thus, iron-induced oxidative stress stimulates the lipid peroxidation, which directly leads to HSPC ferroptosis. Anti-ferroptotic treatments efficiently reverse HSPC defects in alas2 or alad mutants. HSPC transplantation assay reveals that the attenuated erythroid reconstitution efficiency may result from the ferroptosis of erythrocyte-biased HSPCs. Together, these results illustrate that heme-deficient primitive RBCs are detrimental to HSPC production and may provide potential implications for iron dysregulation-induced hematological malignancies.

Comparison with gastric cancer-associated genes reveals the role of ferroptosis-related genes in eosinophils of asthma patients: A bioinformatic study

Ferroptosis-inducing agents (FIAs) induced lipid-peroxidation-independent ferroptosis in eosinophils, thus ameliorating airway inflammation in asthmatic mice. Differences in ferroptosis-related genes (FerrGs) between eosinophils and cells in which FIAs induce canonical ferroptosis are supposed to contribute to this noncanonical ferroptosis but remain unclear. This study aims to explore these differences. This study used gastric cancer cells (GCCs) in stomach adenocarcinoma as the representative of cells in which FIAs induce canonical ferroptosis. FerrGs in Ferroptosis Database V2 respectively intersected with differentially expressed genes (DEGs) of eosinophils (E-MTAB-4660 dataset) and GCCs (GEPIA2 Stomach adenocarcinoma dataset) to obtain original ferroptosis DEGs (FerrDEGs). Then, they were subjected to Venn analysis to identify FerrDEGs shared by them and FerrDEGs exclusively expressed in eosinophils or GCCs. Identified genes were subjected to functional enrichment analysis, protein-protein interactions analysis, Hub genes analysis, and construction of the LncRNA-mediated ceRNA network. Sixty-six original FerrDEGs in eosinophils and 110 original FerrDEGs in GCCs were obtained. Venn analysis identified that eosinophils and GCCs shared 19 FerrDEGs that presented opposite expression directions and were involved in the ferroptosis pathway. Four upregulated and 20 downregulated FerrDEGs were exclusively expressed in eosinophils and GCCs, respectively. The former were enriched only in glycerolipid metabolism, while the latter were not enriched in pathways. Forty downregulated and 68 upregulated FerrDEGs were solely expressed in eosinophils and GCCs, respectively. The former was associated with the FoxO signaling pathway; the latter was related to glutathione metabolism and they were all implicated in autophagy. PPI analysis shows that the top 10 Hub genes of 66 original FerrDEGs and 44 exclusive FerrDEGs in eosinophils shared 9 genes (STAT3, NFE2L2, MAPK8, PTEN, MAPK3, TLR4, SIRT1, BECN1, and PTGS2) and they were also involved in the FoxO signaling pathway and autophagy pathway. Among them, PTEN is involved in forming a ceRNA network containing 3 LncRNAs, 3 miRNAs and 3 mRNAs. In contrast to FerrGs in cells in which FIAs induce canonical ferroptosis, the FerrGs in eosinophils differ in expression and in the regulation of ferroptosis, FoxO signaling pathway, and autophagy. It lays the groundwork for targeted induction of eosinophils lipid-peroxidation-independent ferroptosis in asthma.

Integrated bioinformatic analysis reveals NOS2 as a novel ferroptosis-related biomarker for pre-eclampsia

BACKGROUND

Pre-eclampsia (PE) is a common condition in pregnancy; however, methods for early diagnosis and effective treatment options are lacking. Ferroptosis is a newly identified iron-dependent cell death pathway. The aim of this study was to investigate the role of ferroptosis-related genes in PE, the underlying mechanism, and their potential diagnostic value using a bioinformatics approach.

METHODS

We downloaded the GSE48424 and GSE98224 datasets from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between PE and healthy pregnancy samples were identified in the GSE48424 dataset and subjected to weighted gene co-expression network analysis; the most relevant modules were intersected with known ferroptosis-related genes to distinctly identify the role of ferroptosis in PE. We further searched transcription factors and microRNAs that are predicted to regulate these ferroptosis-related genes, and patients in the GSE48424 dataset were divided into two groups according to high or low expression of the key ferroptosis-related genes associated with PE. To obtain robust key ferroptosis-related genes in PE, we validated their expression levels in the external dataset GSE98224. Finally, the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) assay was utilized to access the expression of these genes in the PE and normal blood samples.

RESULTS

Six ferroptosis-related genes involved in PE were obtained by overlapping 3661 genes most associated with PE, 565 DEGs between PE and normal samples, and 259 known ferroptosis-related genes. Among these genes, patients with PE displaying lower expression levels of NOS2 and higher expression levels of PTGS2 had a higher ferroptosis potential index. The expression pattern of NOS2 was consistent in the GSE48424 and GSE98224 datasets. RT-qPCR data confirmed that NOS2 expression was more significantly elevated in patients with PE than in those with a normal pregnancy.

CONCLUSIONS

Our study explored the diagnostic value of ferroptosis-related genes in PE, and identified NOS2 as the key gene linking ferroptosis and PE, suggesting a new candidate biomarker for early PE diagnosis.

Screening of miR-15a-5p as a potential biomarker for intervertebral disc degeneration through RNA-sequencing

Low back pain (LBP) is a prevalent clinical condition that imposes substantial economic burdens on society. Intervertebral disc degeneration (IVDD) is recognized as a major contributing factor to LBP. Recent studies have highlighted the pivotal role of microRNAs (miRNAs) in regulating the onset and progression of IVDD. Understanding the involvement of miRNAs in IVDD will expand our knowledge of the underlying mechanisms and potentially identify novel therapeutic targets for managing LBP. However, the pathological process of IVDD and the miRNA-mediated pathomechanism in IVDD remain unclear. Herein, we comprehensively analyzed and divided the pathological process of IVDD into three stages based on the analysis by Risbud and colleagues. Results showed that IVDD was especially associated with cell death, oxidative stress, inflammatory and immune response, and extracellular matrix (ECM) metabolism. Subsequently, we obtained human normal and degenerative nucleus pulposus tissues, which were visually confirmed through histological staining techniques such as HE and TUNEL staining. RNA sequencing was then performed on these tissue samples. Additionally, miRNA (GSE116726) and mRNA (GSE56081/GSE70362/GSE23130/GSE34095) datasets were collected from the GEO database. Our analysis revealed that miR-15a-5p was significantly upregulated IVDD, as validated by both RNA sequencing and qRT-PCR experiments. To further refine our findings, bioinformatics analysis was conducted, merging the targets of miR-15a-5p and multiple mRNA datasets, ultimately identifying the overlapping IVDD-associated mRNAs. Notably, many cuproptosis-related genes (CRGs), ferroptosis-related genes, oxidative stress-related genes, and immunity-related genes were potential targets of miR-15a-5p. The miR-15a-5p-mRNA network was constructed using Cytoscape software. Additionally, PPI, functional, and pathway enrichment analyses of the CRGs were also performed. We found that MTF1, one of the CRGs, was highly expressed in IVDD and primarily localized in the nucleus of nucleus pulposus cells. These findings suggest that miR-15a-5p is a potential biomarker in IVDD, and targeting the miR-15a-5p-mRNA signaling pathway may be a promising strategy for treating IVDD diseases.

Identification and verification of ferroptosis-related genes in diabetic foot using bioinformatics analysis

Ferroptosis is a novel form of cell death that plays a key role in several diseases, including inflammation and tumours; however, the role of ferroptosis-related genes in diabetic foot remains unclear. Herein, diabetic foot-related genes were downloaded from the Gene Expression Omnibus and the ferroptosis database (FerrDb). The least absolute shrinkage and selection operator regression algorithm was used to construct a related risk model, and differentially expressed genes were analysed through immune infiltration. Finally, we identified relevant core genes through a protein-protein interaction network, subsequently verified using immunohistochemistry. Comprehensive analysis showed 198 genes that were differentially expressed during ferroptosis. Based on functional enrichment analysis, these genes were primarily involved in cell response, chemical stimulation, and autophagy. Using the CIBERSORT algorithm, we calculated the immune infiltration of 22 different types of immune cells in diabetic foot and normal tissues. The protein-protein interaction network identified the hub gene TP53, and according to immunohistochemistry, the expression of TP53 was high in diabetic foot tissues but low in normal tissues. Accordingly, we identified the ferroptosis-related gene TP53 in the diabetic foot, which may play a key role in the pathogenesis of diabetic foot and could be used as a potential biomarker.

Paraquat-induced ferroptosis suppression via NRF2 expression regulation

Paraquat (PQ) is an environmentally friendly and efficient herbicide, but PQ misuse or intentional self-use can cause death through multiple organ damage and can cause acute lung injury. Existing clinical treatments alleviate symptoms but do not significantly improve the mortality rate. Ferroptosis is a type of necrosis that presents in a manner very similar to the cell damage induced by high doses of PQ, but the role of ferroptosis in paraquat-induced lung injury remains unclear. In this study, we aimed to explore the role of ferroptosis in PQ-induced A549 cell injury and identify the potential mechanisms and critical sites of protection against PQ-induced A549 injury by ferroptosis inhibitors. We found that the ferroptosis inhibitors Ferr-1 and Lip-1 inhibit ferroptosis by attenuating oxidative stress through the upregulation of NRF2 gene expression. The protective role of the ferroptosis inhibitor Dfo was most evident in paraquat-induced cell injury. Dfo inhibited ferroptosis by iron chelation and promoted NRF2 protein level reduction. NRF2 attenuated PQ-induced ferroptosis in A549 cells, mainly through the upregulation of SLC40A1 to encourage the movement of iron to the extracellular side to alleviate iron overload, and the upregulation of SLC7A11 to promote the expression of GPX4 to inhibit lipid peroxidation.

PIAS3 promotes ferroptosis by regulating TXNIP via TGF-β signaling pathway in hepatocellular carcinoma

Ferroptosis has been suggested to play a potential role in cancer therapy as an iron-dependent programmed cell death mechanism distinct from other forms. Hepatocellular carcinoma (HCC) remains a great threat, with high mortality and limited therapeutic options. The induction of ferroptosis has emerged as a novel and promising therapeutic strategy for HCC. In the present study, we identified protein inhibitor of activated STAT3 (PIAS3) as a driver of ferroptosis in HCC using TMT-based quantitative proteomics and ferroptosis-related functional assays. Mechanistically, thioredoxin-interacting protein (TXNIP) was confirmed to be PIAS3 in promoting ferroptotic cell death, based on RNA-seq analysis. Knockdown of TXNIP degrades ferroptotic susceptibility caused by PIAS3-overexpression, whereas transfection-forced reexpression of TXNIP restores sensitivity to ferroptosis in PIAS3-downregulated cells. PIAS3 interacts with SMAD2/3 to activate transforming growth factor (TGF)-β signaling, leading to increased TXNIP expression. Our study revealed the critical role of PIAS3 in ferroptosis and a novel actionable axis-PIAS3/TGF-β/TXNIP that could govern ferroptotic sensitivity, paving the path for using ferroptosis as an efficient approach in HCC therapies.

Bioinformatics identification and integrative analysis of ferroptosis-related key lncRNAs in patients with osteoarthritis

BACKGROUND

Ferroptosis and dysregulation of long non-coding RNA (lncRNA) have been described to be strictly relevant to the pathogenesis of osteoarthritis (OA). However, the connection between ferroptosis and lncRNA in OA is poorly appreciated. Herein, we investigated the functional contribution of lncRNA markers correlated with the progression of human OA by comprehensive bioinformatics analysis of a panoramic network of competing endogenous RNA (ceRNA) based on ferroptosis-related genes (FRGs).

METHODS

FRGs-related competing endogenous RNA (ceRNA) networks were generated using differentially expressed genes based on OA-related whole transcriptome data from the Gene Expression Omnibus (GEO) database via starBase, miRTarBase, and miRWalk databases. The pivotal lncRNAs were ascertained by topological features (degree, betweenness, and closeness) and subceRNA networks were re-visualized. The expression difference of pivotal lncRNAs was verified by quantitative real-time polymerase chain reaction (qRT-PCR). The latent molecular mechanisms of the global ceRNA and subceRNA networks were uncovered by the R package clusterProfiler-based enrichment analysis.

RESULTS

A total of 98 dysregulated lncRNA-miRNA-mRNA regulatory relationships were attained in the FRGs-related panoramic ceRNA network of OA, covering 26 mRNAs, 20 miRNAs, and 20 lncRNAs. Three lncRNAs (AC011511.5, AL358072.1, and C9orf139) were ascertained as the central lncRNAs in the panoramic ceRNA network. Functional ensemble analysis illustrated that both the panoramic ceRNA network and the subceRNA network were integrally affiliated with the immune-inflammatory response, oxygen homeostasis, and cell death (apoptosis, autophagy, and ferroptosis).

CONCLUSION

Comprehensive bioinformatics analysis of the FRGs-related ceRNA network determined three molecular biomarkers of lncRNAs that might be affiliated with OA progression.

Ferroptosis regulator NOS2 is closely associated with the prognosis and cell malignant behaviors of hepatoblastoma: a bioinformatic and in vitro study

Background

Hepatoblastoma (HB) is the most common liver tumor in children with easy metastasis. The emergence of ferroptosis as a novel form of cell death has gained increased attention in various human cancers. However, the roles of ferroptosis-related (FR) genes in HB remain elusive.

Methods

The GSE133039, GSE131329, and GSE81928 datasets were utilized for screening core FR genes in HB. Through Lasso regression analysis and using the support vector machine recursive feature elimination (SVM-RFE) algorithm, three candidate FR genes were obtained for characterizing HB. Their expression patterns and their clinical associations were explored through the 'Limma' R package, and their diagnostic potential was evaluated using ROC curves. Nitric oxide synthase 2 (NOS2) emerged as a candidate for further analyses. The CIBERSORT algorithm and GSEA dataset were used to respectively investigate the immune and metabolism effects of NOS2; the former was validated through immunofluorescence. The GSDC database was employed to analyze the correlation between NOS2 expression and the therapeutic efficacy of multiple drugs. PCR, Western blotting, colony formation assays, and Transwell experiments, were used to determine biological functions of NOS2 in HB cells. Potential upstream transcription factors of NOS2 were predicted through the TRRUST, hTFtarget, GeneCards, and JASPAR databases.

Results

NQO1, SLC1A4, and NOS2 were identified as potential genes in HB and found to be significantly upregulated in tumor samples. Nevertheless, only NOS2 was closely associated with HB clinicopathological characteristics; high NOS2 expression indicated poor prognosis, metastatic tendency, and late clinical stage. Immune analyses indicated that high NOS2 expression was concomitant with decreased infiltration levels of CD8+ T cells but increased infiltration levels of macrophages. GSEA revealed that NOS2 failed to affect the enrichments of glycolysis, fatty acid metabolism, and cholesterol biosynthesis in HB. Moreover, NOS2 was positively correlated with the IC50 values of trametinib, lapatinib, and cisplatin. NOS2 overexpression promoted the proliferation, migration and invasion of HepG2 and HuH-6 cells. JUND was identified as a potential transcriptional regulator of NOS2 by binding to its promoter (5'-TTCTGACTCTTTT-3').

Conclusion

NOS2 plays a significant role in HB clinical assessments and holds promise as a novel therapeutic target.

Identification of a novel competing endogenous RNA network and candidate drugs associated with ferroptosis in aldosterone-producing adenomas

Aldosterone-producing adenoma (APA), characterized by unilaterally excessive aldosterone production, is a common cause of primary aldosteronism. Ferroptosis, a recently raised iron-dependent mode of programmed cell death, has been involved in the development and therapy of various diseases. This study obtained datasets of the mRNA and lncRNA expression profiles for APA and adjacent adrenal gland (AAG) from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and lncRNAs (DE lncRNAs) associated with ferroptosis were identified. Enrichment analyses indicated 89 ferroptosis-related DEGs were primarily enriched in ROS related processes and ferroptosis. Two physical cores, and one combined core were identified in the protein-protein interaction (PPI). DEGs and clinical traits were used in conjunction to screen eight hub genes from two hub modules and 89 DEGs. A competitive endogenous RNA (ceRNA) network was constructed via co-express analysis. Thereafter, molecular docking was used to identify potential targets. Two active compounds, QL-X-138 and MK-1775, bound to AURKA and DUOX1, respectively, with the lowest binding energies. Molecular dynamics simulation verified the stability of the two complexes. In summary, our studies identified eight hub genes and a novel ceRNA regulatory network associated with ferroptosis, wherein QL-X-138 and MK-1775 were considered to be potential drugs for treating APA.

Identification and Validation of Ferroptosis-Related Genes in Patients with Acute Spinal Cord Injury

Ferroptosis plays crucial roles in the pathology of spinal cord injury (SCI). The purpose of this study was to identify differentially expressed ferroptosis-related genes (DE-FRGs) in human acute SCI by bioinformatics analysis and validate the hub DE-FRGs in non-SCI and SCI patients. The GSE151371 dataset was downloaded from the Gene Expression Omnibus and difference analysis was performed. The differentially expressed genes (DEGs) in GSE151371 overlapped with the ferroptosis-related genes (FRGs) obtained from the Ferroptosis Database. A total of 41 DE-FRGs were detected in 38 SCI samples and 10 healthy samples in GSE151371. Then, enrichment analyses of these DE-FRGs were performed for functional annotation. The GO enrichment results showed that upregulated DE-FRGs were mainly associated with reactive oxygen species and redox reactions, and the KEGG enrichment analysis indicated involvement in some diseases and ferroptosis pathways. Protein-protein interaction (PPI) analysis and lncRNA-miRNA-mRNA regulatory network were performed to explore the correlations between genes and regulatory mechanisms. The relationship between DE-FRGs and differentially expressed mitochondria-related genes (DE-MRGs) was also analyzed. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the hub DE-FRGs in clinical blood samples from acute SCI patients and healthy controls. Consistent with the bioinformatics results, qRT-PCR of the clinical samples indicated similar expression levels of TLR4, STAT3, and HMOX1. This study identified DE-FRGs in blood samples from SCI patients, and the results could improve our understanding of the molecular mechanisms of ferroptosis in SCI. These candidate genes and pathways could be therapeutic targets for SCI.

Anti-ferroptotic PRKAA2 serves as a potential diagnostic and prognostic marker for hepatoblastoma

Background

The incidence rate of hepatoblastoma (HB), which is the most prevalent malignant tumour among children, rises each year. According to recent studies, a number of neoplastic disorders and ferroptosis are intimately connected. This study aims to identify key ferroptosis-related genes in HB and explore new directions for the diagnosis and treatment of HB.

Methods

Differentially expressed ferroptosis-related genes were identified using the Gene Expression Omnibus datasets. The functional annotation of candidate genes was evaluated through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Machine learning and receiver operating characteristic (ROC) curves revealed protein kinase AMP-activated catalytic subunit alpha 2 (PRKAA2), tribbles homolog 2 (TRIB2), and liver-type glutaminase (GLS2) as potential diagnostic genes of HB. By using quantitative reverse transcription polymerase chain reaction (qRT-PCR) and immunohistochemistry, relative expression of PRKAA2 was examined. The effect of PRKAA2 on proliferation, apoptosis, and ferroptosis of HB cells was verified in vitro and in vivo. Fisher's exact test was used to evaluate the clinical significance of PRKAA2 in HB.

Results

The prognostic indicators had a substantial correlation with PRKAA2 expression, which rose dramatically in HB tissues. PRKAA2 promotes proliferation and inhibits ferroptosis in HB cells. PRKAA2 plays a role in ferroptosis by regulating hypoxia-inducible factor 1α (HIF-1α) and transferrin receptor 1 (TFR1).

Conclusions

PRKAA2 functions as a tumor-promoting factor in HB by promoting cell proliferation and prohibiting ferroptosis. Ferroptosis-related genes PRKAA2 is a potential diagnostic and prognostic marker for HB as well as a novel therapeutic target in the future.

Construction and validation of a novel ferroptosis-related prognostic signature for lung adenocarcinoma

Background

Lung cancer has the highest prevalence and mortality of all cancers, and lung adenocarcinoma (LUAD) occupies the largest proportion of lung cancers. Herein, this study is aimed at constructing a ferroptosis-related prognostic signature for LUAD and conducting functional analysis based on the signature, highlighting the importance of ferroptosis in LUAD.

Methods

We employed RNA-sequencing (RNA-seq) and clinical data from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis were conducted to build the ferroptosis-related genes (FRGs) prognostic signature. The efficacy of this FRG signature was further analyzed with Kaplan-Meier (KM) plot, multivariate Cox regression, and the receiver operating characteristic (ROC) curves. Enrichment analysis was used to evaluate key pathways. The expression of immunomodulators, immune infiltration status, and drug sensitivity correlation were explored to predict the response to various therapies. The expression of FRGs was validated in LUAD samples with western blot (WB) and immunohistochemistry (IHC) staining. Cell viability assay and lipid peroxidation detection were measured after small interfering RNA (siRNA) knockdown of two FRGs in lung cancer cell lines.

Results

A seven-gene signature was constructed and used to divide LUAD patients into high- and low-risk groups. High-risk patients were notably related to shorter overall survival (OS), and multivariate Cox regression demonstrated that our signature was an independent predictor of OS. ROC curve analysis presented a maximum area under the curve (AUC) value of 0.740 for the experimental cohort and 0.705 for the validation cohort. The low-risk group showed higher levels of plasma cell infiltration and higher expression of programmed cell death protein 1 (PDCD1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA4). Ferroptosis inducers such as talazoparib or cisplatin had lower IC50 values in the high-risk group, while navitoclax (BCL-2 gene family inhibition and apoptosis inducer) had higher IC50 values in the high-risk group. Additionally, peroxiredoxin-6 (PRDX6) and acyl-CoA synthetase long chain family member 3 (ACSL3) were upregulated in LUAD tissues. Lipid peroxide assay showed that silencing PRDX6 or ACSL3 promoted lipid peroxidation and ferroptosis in lung cancer cells.

Conclusions

Our novel ferroptosis-related signature shows potential clinical and functional importance in LUAD patients, and further research on ferroptosis as a therapeutic target in LUAD is warranted.

The Emerging Role of Ferroptosis in Sepsis, Opportunity or Challenge?

Sepsis is a syndrome in multi-organ dysfunction triggered by a deleterious immunological reaction of the body to a condition caused by infection, surgery, or trauma. Currently, sepsis is thought to be primarily associated with abnormal immune responses resulting in organ microcirculatory disturbances, cellular mitochondrial dysfunction, and induced cell death, although the exact pathogenesis of sepsis is still inconclusive. In recent years, the role of abnormal metabolism of trace nutrients in the pathogenesis of sepsis has been investigated. Ferroptosis is a type of cell death that relies on iron and is characterized by unique morphological, biochemical, and genetic features. Unlike other forms of cell death, such as autophagy, apoptosis, necrosis, and pyroptosis, ferroptosis is primarily driven by lipid peroxidation. Ferroptosis cells may be immunogenic, amplify inflammatory responses, cause more cell death, and ultimately induce multi-organ failure. An increasing number of studies have indicated the significance of ferroptosis in sepsis and its role in reducing inflammation. The effectiveness of sepsis treatment has been demonstrated by the use of drugs that specifically target molecules associated with the ferroptosis pathway, including ferroptosis inhibitors. Nevertheless, there is a scarcity of studies investigating the multi-organ dysfunction caused by ferroptosis in sepsis. This article presents a summary and evaluation of recent progress in the role of ferroptosis through molecularly regulated mechanisms and its potential mechanisms of action in the multi-organ dysfunction associated with sepsis. It also discusses the current challenges and prospects in understanding the connection between sepsis and ferroptosis, and proposes innovative ideas and strategies for the treatment of sepsis.