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

Construction of Ovarian Cancer Prognostic Model Based on the Investigation of Ferroptosis-Related lncRNA

(1) Background: Ovarian cancer (OV) has the high mortality rate among gynecological cancers worldwide. Inefficient early diagnosis and prognostic prediction of OV leads to poor survival in most patients. OV is associated with ferroptosis, an iron-dependent form of cell death. Ferroptosis, believed to be regulated by long non-coding RNAs (lncRNAs), may have potential applications in anti-cancer treatments. In this study, we aimed to identify ferroptosis-related lncRNA signatures and develop a novel model for predicting OV prognosis. (2) Methods: We downloaded data from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression, and Gene Expression Omnibus (GEO) databases. Prognostic lncRNAs were screened by least absolute shrinkage and selection operator (LASSO)-Cox regression analysis, and a prognostic model was constructed. The model's predictive ability was evaluated by Kaplan-Meier (KM) survival analysis and receiver operating characteristic (ROC) curves. The expression levels of these lncRNAs included in the model were examined in normal and OV cell lines using quantitative reverse transcriptase polymerase chain reaction. (3) Results: We constructed an 18 lncRNA prognostic prediction model for OV based on ferroptosis-related lncRNAs from TCGA patient samples. This model was validated using TCGA and GEO patient samples. KM analysis showed that the prognostic model was able to significantly distinguish between high- and low-risk groups, corresponding to worse and better prognoses. Based on the ROC curves, our model shows stronger prediction precision compared with other traditional clinical factors. Immune cell infiltration, immune checkpoint expression levels, and Tumor Immune Dysfunction and Exclusion analyses are also insightful for OV immunotherapy. (4) Conclusions: The prognostic model constructed in this study has potential for improving our understanding of ferroptosis-related lncRNAs and providing a new tool for prognosis and immune response prediction in patients with OV.

Evaluation of genetic variants in ferroptosis-related genes and house dust mite-induced allergic rhinitis risk

BACKGROUND

Ferroptosis-related genes disrupt iron homeostasis and enhance lipid peroxidation to initiate respiratory system diseases. However, the association between genetic variants in the ferroptosis-related genes with house dust mite (HDM)-induced allergic rhinitis (AR) susceptibility remains unclear.

METHODS

A case-control study, involving 222 cases and 237 healthy controls from a Chinese population, was conducted to evaluate the relationship between single nucleotide polymorphisms (SNPs) in ferroptosis-related genes and HDM-induced AR risk. A gene-based analysis was performed by multi-marker analysis of genomic annotation (MAGMA) to identify candidate associated ferroptosis-related genes. A logistic regression model and joint analysis were used to assess the effect of SNPs on HDM-induced AR susceptibility.

RESULTS

Two independent SNPs (rs2305128 in ENPP2 and rs1868088 in EPAS1) were significantly associated with HDM-induced AR risk (OR = 1.82, 95% CI = 1.19-2.79, P = 5.98 × 10-3, PFDR = 4.88 × 10-2; OR = 2.14, 95% CI = 1.23-3.72, P = 6.95 × 10-3, PFDR = 4.87 × 10-2, respectively). Moreover, combined analysis of these two SNPs revealed that an increased risk of HDM-induced AR was positively associated with an increasing number of risk genotypes (Ptrend = 8.48 × 10-5). The stratification analysis showed that the cumulative effect of two SNPs on HDM-induced AR risk was more pronounced among patients presenting more serious symptoms and harboring one or two risk genotypes.

CONCLUSIONS

These findings suggest that the genetic variants in ferroptosis-related genes ENPP2 and EPAS1 may increase HDM-induced AR risk and serve as potential predictors of HDM-induced AR susceptibility.

SPY1 inhibits neuronal ferroptosis in amyotrophic lateral sclerosis by reducing lipid peroxidation through regulation of GCH1 and TFR1

Ferroptosis is an iron-dependent cell death with the accumulation of lipid peroxidation and dysfunction of antioxidant systems. As the critical regulator, glutathione peroxidase 4 (GPX4) has been demonstrated to be down-regulated in amyotrophic lateral sclerosis (ALS). However, the mechanism of ferroptosis in ALS remains unclear. In this research, bioinformatics analysis revealed a high correlation between ALS, ferroptosis, and Speedy/RINGO cell cycle regulator family member A (SPY1). Lipid peroxidation of ferroptosis in hSOD1G93A cells and mice was generated by TFR1-imported excess free iron, decreased GSH, mitochondrial membrane dysfunction, upregulated ALOX15, and inactivation of GCH1, GPX4. SPY1 is a "cyclin-like" protein that has been proved to enhance the viability of hSOD1^G93A cells by inhibiting DNA damage. In our study, the decreased expression of SPY1 in ALS was resulted from unprecedented ubiquitination degradation mediated by MDM2 (a nuclear-localized E3 ubiquitin ligase). Further, SPY1 was identified as a novel ferroptosis suppressor via alleviating lipid peroxidation produced by dysregulated GCH1/BH4 axis (a resistance axis of ferroptosis) and transferrin receptor protein 1 (TFR1)-induced iron. Additionally, neuron-specific overexpression of SPY1 significantly delayed the occurrence and prolonged the survival in ALS transgenic mice through the above two pathways. These results suggest that SPY1 is a novel target for both ferroptosis and ALS.

The Emerging Role of Ferroptosis in Various Chronic Liver Diseases: Opportunity or Challenge

Ferroptosis is a recently identified iron-dependent form of intracellular lipid peroxide accumulation-mediated cell death. Different from other types of cell death mechanisms, it exhibits distinct biological and morphological features characterized by the loss of lipid peroxidase repair activity caused by glutathione peroxidase 4, the presence of redox-active iron, and the oxidation of phospholipids-containing polyunsaturated fatty acids. In recent years, studies have shown that ferroptosis plays a key role in various liver diseases such as alcoholic liver injury, non-alcoholic steatohepatitis, liver cirrhosis, and liver cancer. However, the mechanism of ferroptosis and its regulation on chronic liver disease are controversial among different types of cells in the liver. Herein, we summarize the current studies on mechanism of ferroptosis in chronic liver disease, aiming to outline the blueprint of ferroptosis as an effective option for chronic liver disease therapy.

Carbonic Anhydrase IX Controls Vulnerability to Ferroptosis in Gefitinib-Resistant Lung Cancer

Acquired resistance to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI, such as gefitinib) in lung cancer continues to be a major problem. Recent studies have shown the promise of ferroptosis-inducing therapy in EGFR-TKI resistant cancer, but have not been translated into clinical benefits. Here, we identified carbonic anhydrase IX (CA9) was upregulated in gefitinib-resistant lung cancer. Then we measured the cell viability, intracellular reactive oxygen species (ROS) levels, and labile iron levels after the treatment of ferroptosis inducer erastin. We found that CA9 confers resistance to ferroptosis-inducing drugs. Mechanistically, CA9 is involved in the inhibition of transferrin endocytosis and the stabilization of ferritin, leading to resistance to ferroptosis. Targeting CA9 promotes iron uptake and release, thus triggering gefitinib-resistant cell ferroptosis. Notably, CA9 inhibitor enhances the ferroptosis-inducing effect of cisplatin on gefitinib-resistant cells, thus eliminating resistant cells in heterogeneous tumor tissues. Taken together, CA9-targeting therapy is a promising approach to improve the therapeutic effect of gefitinib-resistant lung cancer by inducing ferroptosis.

Identification and Validation of Ferroptosis-Related Subtypes and a Predictive Signature in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world with an immunosuppressive Tumor microenvironment (TME). Ferroptosis plays an essential role in tumor proliferation, invasion, and metastasis. However, the relationship between ferroptosis and TME of HCC has remained elusive.

Methods

Differentially expressed ferroptosis-related genes (DE FRGs) between normal liver tissues and HCC tissues were obtained from The Cancer Genome Atlas (TCGA). On this basis, we identified the molecular subtypes mediated by DE FRGs and TME cell infiltration. Next, a predictive signature was established to quantity the ferroptosis-related characteristics by performing the least absolute shrinkage and selection operator Cox regression analyses. Univariate and multivariate COX analyses determined the independent prognostic factors. Finally, the expression stability of 3 ferroptosis-related signature genes was verified in cancer and paracancerous normal tissues of HCC.

Results

We identified three different molecular subtypes and found that the subtype with the better prognosis was associated with high enrichment of immune- and metabolic-related hallmark signaling pathways and high infiltration of immune cells in TME. The signature was considered to be an independent prognostic factor. We also found that the signature can reflect the infiltration characteristics of different immune cells in TME. Immunosuppressive cells such as myeloid-derived suppressor cells (MDSCs), regulatory T cells, and type 17 T helper cells were significantly enriched in the high-risk group. The analysis data of immune checkpoints and tumor mutation load indicated that the signature had great potential in predicting Immunotherapy response and chemotherapeutic sensitivity. In addition, the overexpression of 3 ferroptosis-related signature genes was confirmed in HCC tissues and HCC cell lines. Ferroptosis inducer RSL3 inhibited the proliferation of HCC cells and was a potential cancer immunotherapy agent.

Conclusion

These findings enhanced our understanding of the regulatory mechanism of ferroptosis in HCC and provided new insights into evaluating prognosis and developing more effective Immunotherapy and chemotherapy strategies.

Development and validation of a novel ferroptosis‑related lncRNA prognostic signature for pancreatic adenocarcinoma

Long non‑coding RNAs (lncRNAs) serve a pivotal role in the regulation of cancer cell ferroptosis. However, the prognostic value of ferroptosis‑related lncRNAs in pancreatic adenocarcinoma (PAAD) largely remains unclear. We aimed at constructing a lncRNA‑based signature to improve the prognosis prediction of PAAD. In the present study, the transcriptome profiling data and clinical information of patients with PAAD were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Gene Consortium (ICGC) databases. Univariate Cox regression analysis of the TCGA cohort demonstrated that 26 ferroptosis‑related lncRNAs had significant prognostic value for PAAD (all P<0.01). Least absolute shrinkage and selection operator regression and multivariate Cox proportional hazards regression analyses were performed to construct a prognostic ferroptosis‑related lncRNA signature (FRLS) comprising nine ferroptosis‑related lncRNAs. The efficacy of this FRLS was verified in the training (TCGA) and validation (ICGC) cohorts. Based on the risk model, high risk scores were significantly correlated with poor overall survival (OS) (hazard ratio, 1.314; 95% confidence interval, 1.218‑1.418; P<0.001). The receiver operating characteristic curves and principal component analysis further demonstrated the robust prognostic ability of the FRLS. Furthermore, a nomogram with favorable predictive efficacy for the prediction of OS was constructed based on the FRLS and clinical features. Gene set enrichment analysis demonstrated that the genes in the FRLS participated in a number of cancer‑associated immunoregulatory pathways. Importantly, it was demonstrated that immune infiltration and response to cancer immunotherapy differed significantly between the high and low‑risk groups according to the FRLS. In conclusion, the risk signature based on the FRLS has potential for the clinical prediction of prognosis and immunotherapy response in patients with PAAD.

Identification and Validation of a Novel Prognostic Signature Based on Ferroptosis-Related Genes in Ovarian Cancer

BACKGROUND

Ovarian cancer is the most lethal gynecological tumor, with a poor prognosis due to the lack of early symptoms, resistance to chemotherapy, and recurrence. Ferroptosis belongs to the regulated cell death family, and is characterized by iron-dependent processes. Here, comprehensive bioinformatics analysis was applied to explore a valuable prognostic model based on ferroptosis-related genes, which was further validated in clinical OC samples.

METHODS

mRNA data of normal and ovarian tumor samples were obtained separately from the GTEx and TCGA databases. The least absolute shrinkage and selection operator (LASSO) cox regression was applied to construct the prognostic model based on ferroptosis-associated genes. Expression of ALOX12 in OC cell lines, as well as cell functions, including proliferation and migration, were examined. Finally, the prognostic efficiency of the model was assessed in the clinical tissues of OC patients.

RESULTS

A gene signature consisting of ALOX12, RB1, DNAJB6, STEAP3, and SELENOS was constructed. The signature divided TCGA, ICGC, and GEO cohorts into high-risk and low-risk groups separately. Receiver operating characteristic (ROC) curves and independent prognostic factor analysis were carried out, and the prognostic efficacy was validated. The expression levels of ALOX12 in cell lines were examined. Inhibition of ALOX12 attenuated cell proliferation and migration in HEY cells. Moreover, the prognostic value of ALOX12 expression was examined in clinical samples of OC patients.

CONCLUSION

This work constructed a novel ferroptosis-associated gene model. Furthermore, the clinical predictive role of ALOX12 was identified in OC patients, suggesting that ALOX12 might act as a potential prognostic tool and therapeutic target for OC patients.

Identification and validation of a novel ferroptosis-related gene signature for prognosis and potential therapeutic target prediction in cholangiocarcinoma

Cholangiocarcinoma (CCA) is a highly heterogeneous and aggressive malignancy of the bile ducts with a poor prognosis and high mortality rate. Effective targeted therapy and accurate prognostic biomarkers are still lacking. Ferroptosis is a form of regulated cell death implicated in cancer progression and has emerged as a potential therapeutic target in various cancers. However, a comprehensive analysis of ferroptosis-related genes (FRGs) for predicting CCA prognosis and therapeutic targets and determining the role of ferroptosis in CCA remain to be performed. Here, we developed a prognostic FRG signature using a least absolute shrinkage and selection operator Cox regression analysis in a training cohort. We then validated it using four independent public datasets. The six-FRG signature was developed to predict CCA patient survival, stratifying them into low-risk and high-risk groups based on survival time. Significantly, the high-risk CCA patients had shorter overall survival. A receiver operating characteristic curve analysis further confirmed the prognostic FRG signature's strong predictive ability, indicating that it was an independent prognostic indicator for CCA patients. Furthermore, the high-risk group was associated with fluke infection and high clinical stages. Cancer-associated fibroblast (CAF) score and CAF markers were significantly higher in the high-risk group than the low-risk group. Moreover, our FRG signature could predict immune checkpoint markers for immunotherapy and drug sensitivity. The mRNA expression levels of the six-FRG signature was validated in 10 CCA cell lines and dividing them into low-risk and high-risk groups using the FRG signature. We further showed that high-risk CCA cell lines were more resistant to ferroptosis inducers, including erastin and RSL3, than the low-risk CCA cell lines. Our study constructed a novel FRG signature model to predict CCA prognoses which might provide prognostic biomarkers and potential therapeutic targets for CCA patients. Ferroptosis sensitivity in high-risk and low-risk CCA cell lines suggests that ferroptosis resistance is associated with high-risk group CCA. Therefore, ferroptosis could be a promising therapeutic target for precision therapy in CCA patients.

ACSF2-mediated ferroptosis is involved in ulcerative colitis

AIMS

To investigate the role of ferroptosis-related genes in the induction into ulcerative colitis (UC) and provide new strategies for the prevention and treatment of UC.

MATERIALS AND METHODS

We screened the UC dataset from the GEO database and obtained ferroptosis-related genes from FerrDB and GeneCards. The R package "CancerSubtypes" was performed to identify the UC subtypes, followed by Short Time-series Expression Miner (STEM) analysis. The key genes were further screened by machine learning algorithms (LASSO and SVM-RFE). WB and IHC verified the changes in the expression content of ACSF2 in vivo and in vitro models. The changes in intracellular ROS and Fe2 + levels were detected.

KEY FINDINGS

Through bioinformatics analysis, we selected the ferroptosis-related gene ACSF2 (acyl CoA synthetase family member 2), which is significantly associated with immune-related pathways "Toll-like receptor signaling pathway", "NF-kappa B signaling pathway" and "NOD-like receptor signaling pathway". The expression of ACSF2 was significantly down-regulated in UC animals, Salmonella typhimurium colitis models and cell models, while the ferroptosis inhibitor Fer-1 reversed the expression of ACSF2 in LPS-induced cell models, indicating that the ferroptosis-related gene ACSF2 plays an important role in mediating ferroptosis and inflammation, and is expected to become a new target for further research.

SIGNIFICANCE

Ferroptosis is closely associated with the development of UC, and the ferroptosis-related gene ACSF2 can be used as a potential biomarker for the diagnosis and treatment of UC.

Study on differentially expressed genes between stage M and stage MS neuroblastoma

Objective

To search for the DEGs between stage MS NB and stage M NB and speculate the possible mechanism of spontaneous regression of stage MS NB.

Materials and methods

The NB datasets GSE49710 and GSE45547 in the GEO database were selected to screen the DEGs between children with NB stage MS vs. stage M, < 18 months. GO enrichment and KEGG pathway analysis of DEGs was performed using DAVID. The intersecting genes among DEGs and RCD-related genes were selected, and their survival roles and functions were assessed. We then used the collected clinical samples to validate the expression of these genes at the protein level using IHC methods and further analysis to explore their role.

Results

BIRC5, SLCO4A1, POPDC3, and HK2 were found to be downregulated in stage MS NB and related to apoptosis. BIRC5 and HK2 also participate in autophagy. The TF gene is upregulated in stage MS NB and related to ferroptosis. The above five genes are closely related to the survival of children with NB. And the expression levels of all five genes at the protein level were verified by IHC to be consistent with the results of the preliminary screening described above.

Conclusion

BIRC5, SLCO4A1, POPDC3, HK2 and TF are expected to become new important indicators to predict the prognosis of NB and can be used as the basis for further explored the benign prognosis and spontaneous regression mechanism of stage MS NB.

Cell death-related biomarker SLC2A1 has a significant role in prognosis prediction and immunotherapy efficacy evaluation in pan-cancer

Introduction: SLC2A1, a member of the SLC transporter family, is involved in a variety of cell death modalities and has been found to be associated with the prognosis and immune microenvironment of a variety of tumors. However, there is a lack of systematic and comprehensive studies on the role of SLC2A1 in pan-cancer. Methods: The mRNA, promoter methylation, and protein expression levels of SLC2A1 in pan-cancer were comprehensively evaluated using GEPIA2.0, TIMER2.0, and UALCAN databases. UCSCXenaShiny based on the cancer genomic atlas pan-cancer data and GEPIA2.0 database were used to assess the prognostic significance of SLC2A1 in pan-cancer. Genetic alterations in SLC2A1 were also evaluated using cBioPortal. The relevance of SLC2A1 to immune infiltrating cells in pan-cancer was evaluated using the XCELL algorithm in combination with the TIMER2.0 database. The correlation of SLC2A1 with the efficacy of immune checkpoint blocker (ICB) therapy was evaluated using the tumor immune dysfunction and exclusion (TIDE) score. The correlation of SLC2A1 with numerous immune-related markers was also evaluated using the TISIDB database. The correlation of SLC2A1 with tumor biological function was evaluated at the single-cell level using the CancerSEA database. Finally, the biological function of SLC2A1 was comprehensively evaluated using gene set enrichment analysis (GSEA) and protein interaction networks. Results: SLC2A1 expression is aberrant in a variety of tumors and is strongly associated with the prognosis of several cancers. SLC2A1 is significantly associated with a variety of immune infiltrating cells including CD8+ T cells, myeloid-derived suppressor cells and macrophages in a variety of tumors. Meanwhile, the expression of SLC2A1 significantly correlated with multiple immune-related markers. In addition, SLC2A1 can also predict the effect of immune checkpoint blocker therapy in some tumors. In a functional analysis, SLC2A1 was significantly associated with hypoxia, epithelial-mesenchymal transition, mTORC1 signaling, and multiple metabolic pathways in pan-cancer. Conclusion: Our study systematically and comprehensively summarizes the prognostic significance and immune-related role of SLC2A1 in pan-cancer and reveals the potential mechanism of SLC2A1 in regulating the tumor microenvironment and tumor behavior, providing a new effective pan-applicable biomarker for prognostic prediction and the evaluation of immunotherapeutic strategies for tumors.

Identification of a Novel Ferroptosis-Related Gene Signature for Predicting Prognosis and Responsiveness to Immunotherapy in Hepatocellular Carcinoma

Purpose

Ferroptosis has been reported to regulate multiple biological behaviors. However, the prognostic and oncologic values of ferroptosis-related genes (FRGs) have not been comprehensively elucidated in hepatocellular carcinoma (HCC). Here, we aimed to construct FRGs-associated signature for stratification of the prognosis of HCC patients.

Methods

A list of FRGs was generated from FerrDb. Public databases were used to extract expression matrices and clinical information. TCGA cohort was randomly divided into a training set and a validation set. Prognostic signature for Overall Survival (OS) was established in training set and validated in internal cohorts (TCGA validation set and entire set) and external cohort (ICGC cohort). Additionally, the role of signature in HCC was well investigated by analysis of mutations, gene set enrichment analysis (GSEA), analysis of immune infiltrates, and analysis of response to immune checkpoint blockade (ICB) treatment. The oncogenic effects of ZFP69B on HCC were also investigated in vitro.

Results

We identified 12 FRGs-based signature for OS with LASSO regression. Patients were partitioned into different risk groups based on the signature. Overall, patients in different groups had different prognosis. The signature independently predicted OS in multivariate Cox regression analyses. Anti-tumor immune cells including activated CD8 T cells, cytolytic activity, and Th1 cells were negatively correlated with risk score in both TCGC and ICGC cohorts. Furthermore, low-risk patients responded better to ICB than high-risk patients. In addition, knockdown of ZFP69B reduced proliferation, migration, and invasion, and promoted erastin-induced ferroptosis of HCC cells.

Conclusion

We developed a prognostic signature based on FRGs to predict OS of HCC patients. And the signature may facilitate clinicians in identifying those who are likely to benefit from ICIs. The results also indicated that ZFP69B might regulate the process of ferroptosis and could be used as a novel potential target for HCC.

lncRNA-associated ceRNA network revealing the potential regulatory roles of ferroptosis and immune infiltration in Alzheimer's disease

Background

Alzheimer's disease (AD) is the most common form of dementia characterized by a prominent cognitive deterioration of sufficient magnitude to impair daily living. Increasing studies indicate that non-coding RNAs (ncRNAs) are involved in ferroptosis and AD progression. However, the role of ferroptosis-related ncRNAs in AD remains unexplored.

Methods

We obtained the intersection of differentially expressed genes in GSE5281 (brain tissue expression profile of patients with AD) from the GEO database and ferroptosis-related genes (FRGs) from the ferrDb database. Least absolute shrinkage and selection operator model along with weighted gene co-expression network analysis screened for FRGs highly associated with AD.

Results

A total of five FRGs were identified and further validated in GSE29378 (area under the curve = 0.877, 95% confidence interval = 0.794-0.960). A competing endogenous RNA (ceRNA) network of ferroptosis-related hub genes (EPT1, KLHL24, LRRFIP1, CXCL2 and CD44) was subsequently constructed to explore the regulatory mechanism between hub genes, lncRNAs and miRNAs. Finally, CIBERSORT algorithms were used to unravel the immune cell infiltration landscape in AD and normal samples. M1 macrophages and mast cells were more infiltrated whereas memory B cells were less infiltrated in AD samples than in normal samples. Spearman's correlation analysis revealed that LRRFIP1 was positively correlated with M1 macrophages (r = -0.340, P < 0.001) whereas ferroptosis-related lncRNAs were negatively correlated with immune cells, wherein miR7-3HG correlated with M1 macrophages and NIFK-AS1, EMX2OS and VAC14-AS1 correlated with memory B cells (|r| > 0.3, P < 0.001).

Conclusion

We constructed a novel ferroptosis-related signature model including mRNAs, miRNAs and lncRNAs, and characterized its association with immune infiltration in AD. The model provides novel ideas for the pathologic mechanism elucidation and targeted therapy development of AD.

Targeting critical pathways in ferroptosis and enhancing antitumor therapy of Platinum drugs for colorectal cancer

Colorectal cancer (CRC) can be resistant to platinum drugs, possibly through ferroptosis suppression, albeit the need for further work to completely understand this mechanism. This work aimed to sum up current findings pertaining to oxaliplatin resistance (OR) or resistance to ascertain the potential of ferroptosis to regulate oxaliplatin effects. In this review, tumor development relating to iron homeostasis, which includes levels of iron that ascertain cells' sensitivity to ferroptosis, oxidative stress, or lipid peroxidation in colorectal tumor cells that are connected with ferroptosis initiation, especially the role of c-Myc/NRF2 signaling in regulating iron homeostasis, coupled with NRF2/GPX4-mediated ferroptosis are discussed. Importantly, ferroptosis plays a key role in OR and ferroptotic induction may substantially reverse OR in CRC cells, which in turn could inhibit the imbalance of intracellular redox induced by oxaliplatin and ferroptosis, as well as cause chemotherapeutic resistance in CRC. Furthermore, fundamental research of small molecules, ferroptosis inducers, GPX4 inhibitors, or natural products for OR coupled with their clinical applications in CRC have also been summarized. Also, potential molecular targets and mechanisms of small molecules or drugs are discussed as well. Suggestively, OR of CRC cells could significantly be reversed by ferroptosis induction, wherein this result is discussed in the current review. Prospectively, the existing literature discussed in this review will provide a solid foundation for scientists to research the potential use of combined anticancer drugs which can overcome OR via targeting various mechanisms of ferroptosis. Especially, promising therapeutic strategies, challenges ,and opportunities for CRC therapy will be discussed.

A unique regulated cell death-related classification regarding prognosis and immune landscapes in non-small cell lung cancer

Regulated cell death (RCD) contributes to reshaping the tumor immune microenvironment and participating in the progression of non-small cell lung cancer (NSCLC); however, related mechanisms have not been fully disclosed. Here, we identified 5 subclusters of NSCLC based on consensus clustering of 3429 RCD-associated genes in the TCGA database and depicted the genomic features and immune landscape of these clusters. Importantly, the clusters provided insights into recognizing tumor microenvironment (TME) and tumor responses to immunotherapy and chemotherapy. Further, we established and validated an RCD-Risk model based on RCD-associated genes, which strongly predicted the prognosis, TME, and immunotherapy outcomes in NSCLC patients. Notably, tissue microarray staining confirmed that the expression of LDLRAD3, a core gene in RCD-Risk model, correlated with poor survival. In conclusion, we developed a novel RCD classification system and RCD-Risk model of NSCLC, serving as a robust and promising predictor for prognosis and immunotherapy benefit of individual NSCLC patients.

Identification and verification of ferroptosis-related genes in gastric intestinal metaplasia

Background: Gastric intestinal metaplasia (IM) is the key link of gastric precancerous lesions. Ferroptosis is a novel form of programmed cell death. However, its impact on IM is unclear. The focus of this study is to identify and verify ferroptosis-related genes (FRGs) that may be involved in IM by bioinformatics analysis. Materials and methods: Differentially expressed genes (DEGs) were obtained from microarray dataset GSE60427 and GSE78523 downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed ferroptosis-related genes (DEFRGs) were obtained from overlapping genes of DEGs and FRGs got from FerrDb. DAVID database was used for functional enrichment analysis. Protein-protein interaction (PPI) analysis and Cytoscape software were used to screen hub gene. In addition, we built a receiver operating characteristic (ROC) curve and verified the relative mRNA expression by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Finally, the CIBERSORT algorithm was used to analyze the immune infiltration in IM. Results: First, a total of 17 DEFRGs were identified. Second, a gene module identified by Cytoscape software was considered as hub gene: PTGS2, HMOX1, IFNG, and NOS2. Third, ROC analysis showed that HMOX1 and NOS2 had good diagnostic characteristics. qRT-PCR experiments confirmed the differential expression of HMOX1 in IM and normal gastric tissues. Finally, immunoassay showed that the proportion of T cells regulatory (Tregs) and macrophages M0 in IM was relatively higher, while the proportion of T cells CD4 memory activated and dendritic cells activated was lower. Conclusion: We found significant associations between FRGs and IM, and HMOX1 may be diagnostic biomarkers and therapeutic targets for IM. These results may enhance our understanding of IM and may contribute to its treatment.

BAG2 Is a Novel Prognostic Biomarker and Promising Immunotherapy Target in Uveal Melanoma

BACKGROUND

The importance of BAG2 in malignancy is gradually being recognized, however, information on its role in uveal melanoma (UVM) is limited. We aimed to elucidate its function and potential mechanism of action in UVM.

METHODS

Using the Cancer Genome Atlas (TCGA) and GEO-related datasets, we analyzed the differential expression of BAG2 in tumors, combined with clinical information and methylation data to analyze the prognostic value of BAG2, differential methylation and its association with UVM metastasis. In addition, correlation analysis explored the immunological characteristics of BAG2 in UVM and the response to immunotherapy. Finally, a prognostic model of ferroptosis- related genes was constructed and validated.

RESULTS

BAG2 is significantly downregulated in multiple cancers including UVM. Prognostic analysis showed that BAG2 was an independent prognostic factor for UVM. Abnormal methylation of BAG2 may affect the metastasis of UVM and be significantly associated with poor prognosis. Immune analysis clarified that BAG2 was significantly associated with UVM immune cell infiltration and multiple immune checkpoints, and low expression of BAG2 was more beneficial in immunotherapy. In addition, the prognostic model of ferroptosis we constructed has good performance in predicting overall survival and metastasis-free survival of UVM.

CONCLUSIONS

BAG2 is an independent prognostic factor for UVM and may be a potential immune checkpoint for UVM.

"From molecular to clinic": The pivotal role of CDC42 in pathophysiology of human papilloma virus related cancers and a correlated sensitivity of afatinib

Background

Human papilloma virus (HPV)-related cancers are global health challenge. Insufficient comprehension of these cancers has impeded the development of novel therapeutic interventions. Bioinformatics empowered us to investigate these cancers from new entry points.

Methods

DNA methylation data of cervical squamous cell carcinoma (CESC) and anal squamous cell carcinoma (ASCC) were analyzed to identify the significantly altered pathways. Through analyses integrated with RNA sequencing data of genes in these pathways, genes with strongest correlation to the TNM staging of CESC was identified and their correlations with overall survival in patients were assessed. To find a potential promising drug, correlation analysis of gene expression levels and compound sensitivity was performed. In vitro experiments were conducted to validate these findings. We further performed molecular docking experiments to explain our findings.

Results

Significantly altered pathways included immune, HPV infection, oxidative stress, ferroptosis and necroptosis. 10 hub genes in these pathways (PSMD11, RB1, SAE1, TAF15, TFDP1, CORO1C, JOSD1, CDC42, KPNA2 and NUP62) were identified, in which only CDC42 high expression was statistically significantly correlated with overall survival (Hazard Ratio: 1.6, P = 0.045). Afatinib was then screened out to be tested. In vitro experiments exhibited that the expression level of CDC42 was upregulated in HaCaT/A431 cells transfected with HPV E6 and E7, and the inhibitory effect of afatinib on proliferation was enhanced after transfection. CDC42-GTPase-effector interface-EGFR-afatinib was found to be a stable complex with a highest ZDOCK score of 1264.017.

Conclusion

We identified CDC42 as a pivotal gene in the pathophysiology of HPV-related cancers. The upregulation of CDC42 could be a signal for afatinib treatment and the mechanism in which may be an increased affinity of EGFR to afatinib, inferred from a high stability in the quaternary complex of CDC42-GTPase-effector interface-EGFR-afatinib.

Identification and validation of ferroptosis-related hub genes in obstructive sleep apnea syndrome

Background

By 2020, the prevalence of Obstructive Sleep Apnea Syndrome (OSAS) in the US has reached 26. 6-43.2% in men and 8.7-27.8% in women. OSAS promotes hypertension, diabetes, and tumor growth through unknown means. Chronic intermittent hypoxia (CIH), sleep fragmentation, and increased pleural pressure are central mechanisms of OSAS complications. CIH exacerbates ferroptosis, which is closely related to malignancies. The mechanism of ferroptosis in OSAS disease progression remains unknown.

Methods

OSAS-related datasets (GSE135917 and GSE38792) were obtained from the GEO. Differentially expressed genes (DEGs) were screened using the R software and intersected with the ferroptosis database (FerrDb V2) to get ferroptosis-related DEGs (f-DEGs). GO, DO, KEGG, and GSEA enrichment were performed, a PPI network was constructed and hub genes were screened. The TCGA database was used to obtain the thyroid cancer (THCA) gene expression profile, and hub genes were analyzed for differential and survival analysis. The mechanism was investigated using GSEA and immune infiltration. The hub genes were validated with RT-qPCR, IHC, and other datasets. Sprague-Dawley rats were randomly separated into normoxia and CIH groups. ROS, MDA, and GSH methods were used to detect CIH-induced ferroptosis and oxidative stress.

Results

GSEA revealed a statistically significant difference in ferroptosis in OSAS (FDR < 0.05). HIF1A, ATM, HSPA5, MAPK8, MAPK14, TLR4, and CREB1 were identified as hub genes among 3,144 DEGs and 74 f-DEGs. HIF1A and ATM were the only two validated genes. F-DEGs were mainly enriched in THCA. HIF1A overexpression in THCA promotes its development. HIF1A is associated with CD8 T cells and macrophages, which may affect the immunological milieu. The result found CIH increased ROS and MDA while lowering GSH indicating that it could cause ferroptosis. In OSAS patients, non-invasive ventilation did not affect HIF1A and ATM expression. Carvedilol, hydralazine, and caffeine may be important in the treatment of OSAS since they suppress HIF1A and ATM.

Conclusions

Our findings revealed that the genes HIF1A and ATM are highly expressed in OSAS, and can serve as biomarkers and targets for OSAS.

Fibroblast ferroptosis is involved in periodontitis-induced tissue damage and bone loss

Periodontitis causes inflammatory destructions of tooth-supporting tissue and constitutes a significant burden on public health. Failing to reserve the tissue damage and bone loss by any of the currently available therapies has left periodontitis uncurable thus far. Understanding the molecular mechanism in the inflammatory process is crucial to elucidating the pathogenesis and enlightening new therapeutic strategies for periodontitis. This study was to investigate whether and how ferroptosis, a newly-discovered form of cell death, was involved in the pathogenesis of periodontitis. Healthy and periodontitis human gingiva samples were collected and ligature-induced periodontitis murine models were constructed to investigate the role of ferroptosis in periodontitis. Single-cell RNA sequencing data was analyzed to identify the cell type that underwent ferroptosis. The susceptibility of human gingival fibroblasts to ferroptosis was investigated by in vitro cell cultures. We found that gingival fibroblasts undergo ferroptosis in periodontitis, and that periodontitis-induced tissue damage and bone loss were alleviated by inhibition of ferroptosis. Periodontitis-induced pro-inflammatory immune responses was featured by profound elevation of fibroblast-derived Interleukin-6, which was attenuated by ferroptosis inhibition. These results indicated fibroblast ferroptosis as a new clue to unveiling the cellular and molecular basis for periodontitis-induced tissue damage. Involvement of ferroptosis/Interleukin-6 signaling in the pathogenic process suggested a potential target for immunopharmacological approaches to curing periodontitis.

A conjoint analysis of bulk RNA-seq and single-nucleus RNA-seq for revealing the role of ferroptosis and iron metabolism in ALS

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive and selective degeneration of motor neurons in the motor cortex of brain and spinal cord. Ferroptosis is a newly discovered form of cell death and reported to mediate selective motor neuron death in the mouse model of ALS. The growing awareness of ferroptosis and iron metabolism dysfunction in ALS prompted us to investigate the expression pattern of ferroptosis and iron metabolism-related genes (FIRGs) in ALS. Here, we performed a conjoint analysis of bulk-RNA sequence and single-nucleus RNA sequence data using the datasets from Gene Expression Omnibus (GEO) to reveal the role of FIRGs in ALS, especially in selective motor neuron death of ALS. We first investigated the differentially expressed genes (DEGs) between ALS and non-neurological controls. Weighted gene co-expression network analysis constructed the gene co-expression network and identified three modules closely associated with ALS. Fifteen FIRGs was identified as target genes based on least absolute shrinkage and selection operator regression analysis as follows: ACSL4, ANO6, ATP6V0E1, B2M, CD44, CHMP5, CYBB, CYBRD1, HIF1A, MOSPD1, NCF2, SDCBP, STEAP2, TMEM14C, ULK1. These genes could differentiate ALS patients from non-neurological controls (p < 2.2e-16) and had a valid value in predicting and diagnosing ALS (AUC = 0.881 in primary dataset and AUC = 0.768 in validation dataset). Then we performed the functional enrichment analysis of DEGs between ALS cases, the most significantly influenced by target genes, and non-neurological controls. The result indicated that the most significantly influenced functions in ALS pathogenesis by these identified FIRGs are synapse pathways, calcium signaling pathway, cAMP signaling pathway, and phagosome and several immune pathways. At last, the analysis of single- nuclear seq found that CHMP5, one of the 15 FIRGs identified by bulk single-nucleus RNA-seq data, was expressed significantly higher in ALS than pathologically normal (PN), specifically in excitatory neuron populations with layer 2 and layer 3 markers (Ex L2_L3), layer 3 and layer 5 markers (Ex L3_L5). Taken together, our study indicates the positive correlation between FIRGs and ALS, presents potential markers for ALS diagnosis and provides new research directions of CHMP5 function in selective motor neuron death in ALS.

Identification and validation of ferroptosis-related genes and immune infiltration in ischemic cardiomyopathy

Background

Cardiomyocyte death is an important pathophysiological basis for ischemic cardiomyopathy (ICM). Many studies have suggested that ferroptosis is a key link in the development of ICM. We performed bioinformatics analysis and experiment validation to explore the potential ferroptosis-related genes and immune infiltration of ICM.

Methods

We downloaded the datasets of ICM from the Gene Expression Omnibus database and analyzed the ferroptosis-related differentially expressed genes (DEGs). Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and protein-protein interaction network were performed to analyze ferroptosis-related DEGs. Gene Set Enrichment Analysis was used to evaluate the gene enrichment signaling pathway of ferroptosis-related genes in ICM. Then, we explored the immune landscape of patients with ICM. Finally, the RNA expression of the top five ferroptosis-related DEGs was validated in blood samples from patients with ICM and healthy controls using qRT-PCR.

Results

Overall, 42 ferroptosis-related DEGs (17 upregulated and 25 downregulated genes) were identified. Functional enrichment analysis indicated several enriched terms related to ferroptosis and the immune pathway. Immunological analysis suggested that the immune microenvironment in patients with ICM is altered. The immune checkpoint-related genes (PDCD1LG2, LAG3, and TIGIT) were overexpressed in ICM. The qRT-PCR results showed that the expression levels of IL6, JUN, STAT3, and ATM in patients with ICM and healthy controls were consistent with the bioinformatics analysis results from the mRNA microarray.

Conclusion

Our study showed significant differences in ferroptosis-related genes and functional pathway between ICM patients and healthy controls. We also provided insight into the landscape of immune cells and the expression of immune checkpoints in patients with ICM. This study provides a new road for future investigation of the pathogenesis and treatment of ICM.

A novel 25-ferroptosis-related gene signature for the prognosis of gliomas

Background

Ferroptosis is closely associated with cancer and is of great importance in the immune evasion of cancer. However, the relationship between ferroptosis and glioma is unclear.

Methods

We downloaded the expression profiles and clinical data of glioma from the GlioVis database and obtained the expression profiles of ferroptosis genes. A ferroptosis-related gene signature was developed for the prognosis of gliomas.

Results

We screened out prognostic ferroptosis genes, named ferroptosis-related genes, by the Cox regression method. Based on these genes, we used unsupervised clustering to obtain two different clusters; the principal component analysis algorithm was applied to determine the gene score of each patient, and then all the patients were classified into two subgroups. Results showed that there exist obvious differences in survival between different clusters and different gene score subgroups. The prognostic model constructed by the 25 ferroptosis-related genes was then evaluated to predict the clinicopathological features of immune activity in gliomas.

Conclusion

The ferroptosis-related genes play an important role in the malignant process of gliomas, potentially contributing to the development of prognostic stratification and treatment strategies.

Identification of Ferroptosis-Related Biomarkers for Diagnosis and Molecular Classification of Staphylococcus aureus-Induced Osteomyelitis

Objective

Staphylococcus aureus (SA)-induced osteomyelitis (OM) is one of the most common refractory diseases in orthopedics. Early diagnosis is beneficial to improve the prognosis of patients. Ferroptosis plays a key role in inflammation and immune response, while the mechanism of ferroptosis-related genes (FRGs) in SA-induced OM is still unclear. The purpose of this study was to determine the role of ferroptosis-related genes in the diagnosis, molecular classification and immune infiltration of SA-induced OM by bioinformatics.

Methods

Datasets related to SA-induced OM and ferroptosis were collected from the Gene Expression Omnibus (GEO) and ferroptosis databases, respectively. The least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms were combined to screen out differentially expressed-FRGs (DE-FRGs) with diagnostic characteristics, and gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to explore specific biological functions and pathways. Based on these key DE-FRGs, a diagnostic model was established, and molecular subtypes were divided to explore the changes in the immune microenvironment between molecular subtypes.

Results

A total of 41 DE-FRGs were identified. After screening and intersecting with LASSO and SVM-RFE algorithms, 8 key DE-FRGs with diagnostic characteristics were obtained, which may regulate the pathogenesis of OM through the immune response and amino acid metabolism. The ROC curve indicated that the 8 DE-FRGs had excellent diagnostic ability for SA-induced OM (AUC=0.993). Two different molecular subtypes (subtype 1 and subtype 2) were identified by unsupervised cluster analysis. The CIBERSORT analysis revealed that the subtype 1 OM had higher immune cell infiltration rates, mainly in T cells CD4 memory resting, macrophages M0, macrophages M2, dendritic cells resting, and dendritic cells activated.

Conclusion

We developed a diagnostic model related to ferroptosis and molecular subtypes significantly related to immune infiltration, which may provide a novel insight for exploring the pathogenesis and immunotherapy of SA-induced OM.

Prognosis and personalized treatment prediction in lung adenocarcinoma: An in silico and in vitro strategy adopting cuproptosis related lncRNA towards precision oncology

Background: There is a rapid increase in lung adenocarcinomas (LUAD), and studies suggest associations between cuproptosis and the occurrence of various types of tumors. However, it remains unclear whether cuproptosis plays a role in LUAD prognosis. Methods: Dataset of the TCGA-LUAD was treated as training cohort, while validation cohort consisted of the merged datasets of the GSE29013, GSE30219, GSE31210, GSE37745, and GSE50081. Ten studied cuproptosis-related genes (CRG) were used to generated CRG clusters and CRG cluster-related differential expressed gene (CRG-DEG) clusters. The differently expressed lncRNA that with prognosis ability between the CRG-DEG clusters were put into a LASSO regression for cuproptosis-related lncRNA signature (CRLncSig). Kaplan-Meier estimator, Cox model, receiver operating characteristic (ROC), time-dependent AUC (tAUC), principal component analysis (PCA), and nomogram predictor were further deployed to confirm the model's accuracy. We examined the model's connections with other forms of regulated cell death, including apoptosis, necroptosis, pyroptosis, and ferroptosis. The immunotherapy ability of the signature was demonstrated by applying eight mainstream immunoinformatic algorithms, TMB, TIDE, and immune checkpoints. We evaluated the potential drugs for high risk CRLncSig LUADs. Real-time PCR in human LUAD tissues were performed to verify the CRLncSig expression pattern, and the signature's pan-cancer's ability was also assessed. Results: A nine-lncRNA signature, CRLncSig, was built and demonstrated owning prognostic power by applied to the validation cohort. Each of the signature genes was confirmed differentially expressed in the real world by real-time PCR. The CRLncSig correlated with 2,469/3,681 (67.07%) apoptosis-related genes, 13/20 (65.00%) necroptosis-related genes, 35/50 (70.00%) pyroptosis-related genes, and 238/380 (62.63%) ferroptosis-related genes. Immunotherapy analysis suggested that CRLncSig correlated with immune status, and checkpoints, KIR2DL3, IL10, IL2, CD40LG, SELP, BTLA, and CD28, were linked closely to our signature and were potentially suitable for LUAD immunotherapy targets. For those high-risk patients, we found three agents, gemcitabine, daunorubicin, and nobiletin. Finally, we found some of the CRLncSig lncRNAs potentially play a vital role in some types of cancer and need more attention in further studies. Conclusion: The results of this study suggest our cuproptosis-related CRLncSig can help to determine the outcome of LUAD and the effectiveness of immunotherapy, as well as help to better select targets and therapeutic agents.

Identification of ferroptosis-related genes and pathways in diabetic kidney disease using bioinformatics analysis

Diabetic kidney disease (DKD) is a major public health issue because of its refractory nature. Ferroptosis is a newly coined programmed cell death characterized by the accumulation of lipid reactive oxygen species (ROS). However, the prognostic and diagnostic value of ferroptosis-related genes (FRGs) and their biological mechanisms in DKD remain elusive. The gene expression profiles GSE96804, GSE30566, GSE99339 and GSE30528 were obtained and analyzed. We constructed a reliable prognostic model for DKD consisting of eight FRGs (SKIL, RASA1, YTHDC2, SON, MRPL11, HSD17B14, DUSP1 and FOS). The receiver operating characteristic (ROC) curves showed that the ferroptosis-related model had predictive power with an area under the curve (AUC) of 0.818. Gene functional enrichment analysis showed significant differences between the DKD and normal groups, and ferroptosis played an important role in DKD. Consensus clustering analysis showed four different ferroptosis types, and the risk score of type four was significantly higher than that of other groups. Immune infiltration analysis indicated that the expression of macrophages M2 increased significantly, while that of neutrophils and mast cells activated decreased significantly in the high-risk group. Our study identified and validated the molecular mechanisms of ferroptosis in DKD. FRGs could serve as credible diagnostic biomarkers and therapeutic targets for DKD.

Insights on Ferroptosis and Colorectal Cancer: Progress and Updates

Patients with advanced-stage or treatment-resistant colorectal cancer (CRC) benefit less from traditional therapies; hence, new therapeutic strategies may help improve the treatment response and prognosis of these patients. Ferroptosis is an iron-dependent type of regulated cell death characterized by the accumulation of lipid reactive oxygen species (ROS), distinct from other types of regulated cell death. CRC cells, especially those with drug-resistant properties, are characterized by high iron levels and ROS. This indicates that the induction of ferroptosis in these cells may become a new therapeutic approach for CRC, particularly for eradicating CRC resistant to traditional therapies. Recent studies have demonstrated the mechanisms and pathways that trigger or inhibit ferroptosis in CRC, and many regulatory molecules and pathways have been identified. Here, we review the current research progress on the mechanism of ferroptosis, new molecules that mediate ferroptosis, including coding and non-coding RNA; novel inducers and inhibitors of ferroptosis, which are mainly small-molecule compounds; and newly designed nanoparticles that increase the sensitivity of cells to ferroptosis. Finally, the gene signatures and clusters that have predictive value on CRC are summarized.

Multiparametric magnetic resonance imaging-derived deep learning network to determine ferroptosis-related gene signatures in gliomas

Introduction

Ferroptosis-related gene (FRG) signature is important for assessing novel therapeutic approaches and prognosis in glioma. We trained a deep learning network for determining FRG signatures using multiparametric magnetic resonance imaging (MRI).

Methods

FRGs of patients with glioma were acquired from public databases. FRG-related risk score stratifying prognosis was developed from The Cancer Genome Atlas (TCGA) and validated using the Chinese Glioma Genome Atlas. Multiparametric MRI-derived glioma images and the corresponding genomic information were obtained for 122 cases from TCGA and The Cancer Imaging Archive. The deep learning network was trained using 3D-Resnet, and threefold cross-validation was performed to evaluate the predictive performance.

Results

The FRG-related risk score was associated with poor clinicopathological features and had a high predictive value for glioma prognosis. Based on the FRG-related risk score, patients with glioma were successfully classified into two subgroups (28 and 94 in the high- and low-risk groups, respectively). The deep learning networks TC (enhancing tumor and non-enhancing portion of the tumor core) mask achieved an average cross-validation accuracy of 0.842 and an average AUC of 0.781, while the deep learning networks WT (whole tumor and peritumoral edema) mask achieved an average cross-validation accuracy of 0.825 and an average AUC of 0.781.

Discussion

Our findings indicate that FRG signature is a prognostic indicator of glioma. In addition, we developed a deep learning network that has high classification accuracy in automatically determining FRG signatures, which may be an important step toward the clinical translation of novel therapeutic approaches and prognosis of glioma.

Identification and validation of a ferroptosis-related lncRNA signature to robustly predict the prognosis, immune microenvironment, and immunotherapy efficiency in patients with clear cell renal cell carcinoma

Background

Ferroptosis is a new type of iron- and reactive oxygen species-dependent cell death, studies on ferroptosis-related long noncoding RNAs (FerLncRNAs) in clear cell renal cell carcinoma (ccRCC) are limited. The purpose of this study was to investigate the potential prognostic value of FerLncRNAs and their relationship with the immune microenvironment and immunotherapy response of ccRCC.

Methods

RNA sequencing data of 526 patients with ccRCC were downloaded from The Cancer Genome Atlas (TCGA) database. The patients with ccRCC in TCGA were randomly divided (1:1) into a training and testing cohort. ICGC and GEO databases were used for validation. Screening for FerLncRNAs was performed using Pearson's correlation analysis with the reported ferroptosis-related genes. A FerLncRNA signature was constructed using univariate, LASSO, and multivariate Cox regression analyses in the training cohort. Internal and external datasets were performed to verify the FRlncRNA signature. Four major FRlncRNAs were verified through in vitro experiment.

Results

We identified seven FerLncRNAs (LINC00894, DUXAP8, LINC01426, PVT1, PELATON, LINC02609, and MYG1-AS1), and established a risk signature and nomogram for predicting the prognosis of ccRCC. Four major FRlncRNAs were verified with the prognosis of ccRCC in the GEPIA and K-M Plotter databases, and their expressions were validated by realtime PCR. The risk signature can also effectively reflect the immune environment, immunotherapy response and drug sensitivity of ccRCC. These FRlncRNAs have great significance to the implementation of individualized treatment and disease monitoring of ccRCC patients.

Construction of a ferroptosis-related signature based on seven lncRNAs for prognosis and immune landscape in clear cell renal cell carcinoma

BACKGROUND

Recent studies have demonstrated that long non-coding RNAs (lncRNAs) are involved in regulating tumor cell ferroptosis. However, prognostic signatures based on ferroptosis-related lncRNAs (FRLs) and their relationship to the immune microenvironment have not been comprehensively explored in clear cell renal cell carcinoma (ccRCC).

METHODS

In the present study, the expression profiles of ccRCC were acquired from The Cancer Genome Atlas (TCGA) database; 459 patient specimens and 69 adjacent normal tissues were randomly separated into training or validation cohorts at a 7:3 ratio. We identified 7 FRLs that constitute a prognostic signature according to the differential analysis, correlation analysis, univariate regression, and least absolute shrinkage and selection operator (LASSO) Cox analysis. To identify the independence of risk score as a prognostic factor, univariate and multivariate regression analyses were also performed. Furthermore, CIBERSORT was conducted to analyze the immune infiltration of patients in the high-risk and low-risk groups. Subsequently, the differential expression of immune checkpoint and m6A genes was analyzed in the two risk groups.

RESULTS

A 7-FRLs prognostic signature of ccRCC was developed to distinguish patients into high-risk and low-risk groups with significant survival differences. This signature has great prognostic performance, with the area under the curve (AUC) for 1, 3, and 5 years of 0.713, 0.700, 0.726 in the training set and 0.727, 0.667, and 0.736 in the testing set, respectively. Moreover, this signature was significantly associated with immune infiltration. Correlation analysis showed that risk score was positively correlated with regulatory T cells (Tregs), activated CD4 memory T cells, CD8 T cells and follicular helper T cells, whereas it was inversely correlated with monocytes and M2 macrophages. In addition, the expression of fourteen immune checkpoint genes and nine m6A-related genes varied significantly between the two risk groups.

CONCLUSION

We established a novel FRLs-based prognostic signature for patients with ccRCC, containing seven lncRNAs with precise predictive performance. The FRLs prognostic signature may play a significant role in antitumor immunity and provide a promising idea for individualized targeted therapy for patients with ccRCC.

Exploring the Role of Obesity in Dilated Cardiomyopathy Based on Bio-informatics Analysis

(1) Background: Obesity is a major risk factor for cardiovascular disease (CVD), contributing to increasing global disease burdens. Apart from heart failure, coronary artery disease, and arrhythmia, recent research has found that obesity also elevates the risk of dilated cardiomyopathy (DCM). The main purpose of this study was to investigate the underlying biological role of obesity in increasing the risk of DCM. (2) Methods: The datasets GSE120895, GSE19303, and GSE2508 were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were analyzed using GSE120895 for DCM and GSE2508 for obesity, and the findings were compiled to discover the common genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted for the common genes in RStudio. In addition, CIBERSORT was used to obtain the immune cellular composition from DEGs. The key genes were identified in the set of common genes by the least absolute shrinkage and selection operator (LASSO) algorithm, the prognostic risk models of which were verified by receiver operator characteristic (ROC) curves in GSE19303. Finally, Spearman's correlation was used to explore the connections between key genes and immune cells. (3) Results: GO and KEGG pathway enrichment analyses showed that the main enriched terms of the common genes were transforming growth factor-beta (TGF-β), fibrillar collagen, NADPH oxidase activity, and multiple hormone-related signaling pathways. Both obesity and DCM had a disordered immune environment, especially obesity. The key genes NOX4, CCDC80, COL1A2, HTRA1, and KLHL29 may be primarily responsible for the changes. Spearman's correlation analysis performed for key genes and immune cells indicated that KLHL29 closely correlated to T cells and M2 macrophages, and HTRA1 very tightly correlated to plasma cells. (4) Conclusions: Bio-informatics analyses performed for DCM and obesity in our study suggested that obesity disturbed the immune micro-environment, promoted oxidative stress, and increased myocardial fibrosis, resulting in ventricular remodeling and an increased risk of DCM. The key genes KLHL29 and HTRA1 may play critical roles in obesity-related DCM.

Identification and Validation of Ferroptosis-Related DNA Methylation Signature for Predicting the Prognosis and Guiding the Treatment in Cutaneous Melanoma

Cutaneous melanoma (CM) is one of the most aggressive skin tumors with a poor prognosis. Ferroptosis is a newly discovered form of regulated cell death that is closely associated with cancer development and immunotherapy. The aim of this study was to establish and validate a ferroptosis-related gene (FRG) DNA methylation signature to predict the prognosis of CM patients using data from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. A reliable four-FRG DNA methylation prognostic signature was constructed via Cox regression analysis based on TCGA database. Kaplan-Meier analysis showed that patients in the high-risk group tended to have a shorter overall survival (OS) than the low-risk group in both training TCGA and validation GEO cohorts. Time-dependent receiver operating characteristic (ROC) analysis showed the areas under the curve (AUC) at 1, 3, and 5 years were 0.738, 0.730, and 0.770 in TCGA cohort and 0.773, 0.775, and 0.905 in the validation cohort, respectively. Univariate and multivariate Cox regression analyses indicated that the signature was an independent prognostic indicator of OS in patients with CM. Immunogenomic profiling showed the low-risk group of patients had a higher immunophenoscore, and most immune checkpoints were negatively associated with the risk signature. Functional enrichment analysis revealed that immune response and immune-related pathways were enriched in the low-risk group. In conclusion, we established and validated a four-FRG DNA methylation signature that independently predicts prognosis in CM patients. This signature was strongly correlated with the immune landscape, and may serve as a biomarker to guide clinicians in making more precise and personalized treatment decisions for CM patients.

Identification of a signature based on non‐apoptotic regulatory cell death to improve prognosis prediction in acute myeloid leukaemia

Although anti-apoptotic cell death is a common feature of cancer and non-apoptotic regulatory cell death (RCD) is highly correlated with cancer progression and response to therapy, its prognostic role in patients with acute myeloid leukaemia (AML) is unknown. The RNA sequence and clinical data from AML patients were downloaded from the TCGA and GEO databases. The prognostic characteristics of non-apoptotic RCD-related genes (NRGs) were determined by Cox and LASSO regression analysis. Thirteen NRG signatures were identified as independent prognostic parameters in patients with AML that outperformed other prognostic models. Higher NRG scores were associated with shorter survival and less retention of tumour mutations. Although patients with high NRG risk have abundant signalling pathways for cell adhesion, cytokine upregulation, and cellular defence responses, patients with low NRG risk may benefit the most from immunotherapy. Specifically, patients with high NRG score may benefit from treatment with anti-EGFR and CDK2 inhibitors, including erlotinib and roscovitine. The NPM1 and FLT3 mutant cell lines undergo alterations after multiple drug treatments. Our established NRG signature and scoring highlight its vital clinical significance, emphasize the inevitability of stratifying treatment for different mutation subtypes and provide new ideas to guide personalized immunotherapy strategies for AML patients.

Identification of ferroptosis‑associated genes in chronic kidney disease

Ferroptosis serves a pivotal role in developing chronic kidney disease (CKD). The present study aimed to detect and confirm the relevance of potential ferroptosis-related genes in CKD using bioinformatics and experimentation strategies. The original GSE15072 mRNA expression dataset was retrieved from the Gene Expression Omnibus database. Subsequently, the potential differentially expressed genes associated with ferroptosis of CKD were screened using R software. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses, correlation analysis and protein-protein interactions (PPI) were performed for differentially expressed ferroptosis-associated genes (DFGs). Lastly, the expression levels of the top nine DFGs were measured in the kidney tissue of Adriamycin-induced CKD rats and healthy controls via reverse transcription-quantitative (RT-q)PCR analysis. Overall, 49 DFGs among 21 patients with CKD and nine healthy controls were identified. GO and KEGG enrichment analyses demonstrated that these DFGs were primarily involved in 'ferroptosis' and 'mitophagy'. PPI findings indicated that these ferroptosis-associated genes interacted with one another. RT-qPCR of CKD tissue from the rat model revealed that STAT3, MAPK14, heat shock protein (HSP)A5, MTOR and solute carrier family 2 member 1 (SLC2A1) mRNA levels in CKD were upregulated. Overall, 49 potential ferroptosis-associated genes of CKD were identified via bioinformatics analyses. STAT3, MAPK14, HSPA5, MTOR and SLC2A1 may influence CKD onset by regulating ferroptosis. The present results add to the existing body of knowledge about CKD and may be useful in the treatment of CKD.

Atorvastatin attenuates ferroptosis-dependent myocardial injury and inflammation following coronary microembolization via the Hif1a/Ptgs2 pathway

Objectives: Coronary microembolization (CME) represents a serious periprocedural complication after percutaneous coronary intervention. Ferroptosis has been identified in multiple cardiovascular diseases. In this study, we aimed to investigate the effects of atorvastatin (ATV) on ferroptosis and inflammation following CME and elucidate the underlying mechanism. Methods: We established a rat model of CME by injecting microspheres into the left ventricle. Deferoxamine (DFO), a selective ferroptosis inhibitor, or ATV was pretreated before modeling. Cardiac function and cardiac troponin T (cTnT) levels were detected. Levels of ferroptosis-associated genes, malondialdehyde (MDA), glutathione (GSH), and ferrous iron (Fe²⁺) were measured to validate ferroptosis. Levels of tumor necrosis factor alpha (TNF-α) and interleukin 1 beta (IL-1β) were assayed to determine the inflammation. Chromatin immunoprecipitation was performed to determine the binding of hypoxia-inducible factor 1 subunit alpha (Hif1a) to the promoter of prostaglandin-endoperoxide synthase-2 (Ptgs2). Results: Ferroptosis and inflammation were induced following CME with increased levels of MDA (∼2.5 fold, p < 0.01), Fe²⁺ (∼1.5 fold, p < 0.01), TNF-α, and IL-1β and decreased GSH levels (∼42%, p < 0.01). Meanwhile, the level of Ptgs2 was significantly increased, while those of glutathione peroxidase 4 (Gpx4) and solute carrier family 7 member 11 (Slc7a11) were decreased. The level of cTnT was increased by 7-fold (p < 0.01). Left ventricular ejection fraction (LVEF) was significantly reduced (∼85% in the sham group versus ∼45% in the CME group, p < 0.01). DFO or Ptgs2 silencing inhibited the increase of MDA, Ptgs2, TNF-α, and IL-1β, and induced the levels of GSH and Gpx4, followed by reduction in cTnT levels by approximately 50% (p < 0.01). LVEF was improved by approximately 2 fold (p < 0.01). Mechanistically, the transcription factor Hif1a bound to the promoter of Ptgs2 and upregulated its expression. In addition, ATV inhibited the activation of the Hif1a/Ptgs2 axis and attenuated cardiac ferroptosis and inflammation, thus ameliorating CME-induced myocardial injury (LVEF, ∼34% elevation; cTnT, ∼1.8 fold decrease, p < 0.01). Conclusion: Atorvastatin ameliorates ferroptosis-mediated myocardial injury and inflammation following CME via the Hif1a/Ptgs2 pathway.

Bioinformatics analysis of genes related to ferroptosis in hepatic ischemia-reperfusion injury

Background: Primary liver cancer is the sixth most commonly diagnosed cancer and the third leading cause of cancer death worldwide in 2020, and it ranks fifth in global incidence. Liver resection or liver transplantation are the two most prominent surgical procedures for treating primary liver cancer. Both inevitably result in HIRI, causing severe complications for patients and affecting their prognosis and quality of survival. Ferroptosis, a newly discovered mode of cell death, is closely related to HIRI. We used bioinformatics analysis to explore the relationship between the two further. Methods: The GEO database dataset GSE112713 and the FerrDB database data were selected to use bioinformatic analysis methods (difference analysis, FRGs identification, GO analysis, KEGG analysis, PPI network construction and analysis, Hub gene screening with GO analysis and KEGG analysis, intergenic interaction prediction, drug-gene interaction prediction, miRNA prediction) for both for correlation analysis. The GEO database dataset GSE15480 was selected for preliminary validation of the screened Hub genes. Results: We analysed the dataset GSE112713 for differential gene expression before and after hepatic ischemia-reperfusion and identified by FRGs, yielding 11 genes. These 11 genes were subjected to GO, and KEGG analyses, and PPI networks were constructed and analysed. We also screened these 11 genes again to obtain 5 Hub genes and performed GO analysis, KEGG analysis, intergenic interaction prediction, drug-gene interaction prediction, and miRNA prediction on these 5 Hub genes. Finally, we obtained preliminary validation of all these 5 Hub genes by dataset GSE15480. Conclusion: There is a close relationship between HIRI and ferroptosis, and inhibition of ferroptosis can potentially be a new approach to mitigate HIRI treatment in the future.

Diabetic Ferroptosis and Pancreatic Cancer: Foe or Friend?

Significance: Pancreatic cancer and diabetes have a reciprocal causation relationship. As a potential risk factor, diabetes increases morbidity and promotes pancreatic cancer progression. The main mechanisms include islet dysfunction-induced systemic metabolic disorder, pancreatic stellate cell activation, and immunosuppression. Ferroptosis is regarded as regulated cell death, which participates in chemotherapy resistance and is refractory to radiation therapy and immunotherapy. Diabetes-induced ferroptosis causes many complications, but the underlying mechanism of diabetes-related ferroptosis in pancreatic cancer has not been discussed. Recent Advances: Ferroptosis alleviates pancreatic intraepithelial neoplasia (PanIN) progression by activating chronic inflammation. The specific drugs that cause ferroptosis achieve tumor suppression by inducing lipid peroxidation. Ferroptosis plays pro and con roles in cancer. Both the ferroptosis inhibitor and inducer exhibit antitumor effects through killing cancer cells or directly affecting tumor growth. Diabetes-induced ferroptosis contributes to tumor cell death by different components, including tumor cells, fibroblasts, immune cells, and adipocytes. A better understanding of its role in modulating the tumor microenvironment will reveal diabetes-associated ferroptotic features in cancer development, which can be used to figure out possible treatment strategies for cancer patients with hyperglycemia. Critical Issues: We demonstrate the potential roles of diabetes-related ferroptosis in pancreatic cancer progression and discuss ferroptosis-related antitumor effects and therapeutics for pancreatic cancer treatment. Future Directions: Further studies are required to highlight mechanisms of diabetes-mediated ferroptosis in pancreatic cancer tumorigenesis and progression. The antitumor effects of ferroptosis regulators combined with chemotherapy, targeted therapy, or immunotherapy in diabetic patients should be investigated. We hope that pancreatic cancer patients with diabetes will benefit from ferroptosis-related therapies. Antioxid. Redox Signal. 37, 1206-1221.

New Insights into Mechanisms of Ferroptosis Associated with Immune Infiltration in Neonatal Hypoxic-Ischemic Brain Damage

BACKGROUND

The mechanisms underlying ferroptosis in neonatal hypoxic-ischemic brain damage (HIBD) remain unclear.

METHOD

Four microarray datasets were collected from the GEO database (three mRNA datasets GSE23317, GSE144456, and GSE112137, and one miRNA microarray dataset GSE184939). Weighted gene co-expression network analysis (WGCNA) was used to identify modules of HIBD-related genes. The ferroptosis-related genes were extracted from FerrDb, of which closely correlated to HIBD were obtained after the intersection with existing HIBD's DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, as well as protein-protein interaction (PPI) network analysis were subsequently conducted. Cytoscape was used to identify central genes. Immune cell infiltration analysis was performed by the CIBERSORT algorithm.

RESULT

Fifty-six ferroptosis-related differentially expressed genes (FRDEGs) were screened, mainly related to ferroptosis, autophagy, hypoxia response, metabolic pathways, and immune inflammation. The seven optimal hub FRDEGs were obtained by intersecting with key modules of WGCNA. Then, the expression levels of the seven optimal hub FRDEGs were validated in the GSE144456 and GSE112137 datasets, and the ferroptosis-related mRNA-miRNA network was established. In addition, this study revealed immune cell infiltration in the HIBD cerebral cortex and the interaction between immune cells. Moreover, notably, specific FRDEGs were strongly positively correlated with immune function.

CONCLUSIONS

The mechanism of ferroptosis is intricate and closely related to neonatal HIBD. Therefore, targeting ferroptosis-related gene therapy and immunotherapy may have therapeutic prospects for neonatal HIBD.

Fuzheng Nizeng Decoction regulated ferroptosis and endoplasmic reticulum stress in the treatment of gastric precancerous lesions: A mechanistic study based on metabolomics coupled with transcriptomics

Background: Fuzheng Nizeng Decoction (FZNZ) has a history of decades in gastric precancerous lesions (GPL) treatment, which has shown clear clinical efficacy. Blocking GPL is a key measure to reduce the incidence of gastric cancer (GC). Therefore, we aim to investigate the mechanism of FZNZ-induced ferroptosis and endoplasmic reticulum (ER) in MNNG-induced gastric precancerous lesion (MC) cells, which has been rarely studied in Traditional Chinese Medicine (TCM). Methods: First, CCK8 and lactate dehydrogenase assays were conducted to study the potential effect of FZNZ on MC cells. Second, combined transcriptomic and metabolomic analysis were used to explore the effect and mechanism of FZNZ. Functionally, the occurrence of ferroptosis was assessed by transmission electron microscopy morphological observation and measurement of ferrous iron levels, lipid peroxidation, and glutathione levels. Finally, the expression levels of mRNAs or proteins related to ferroptosis and ER stress were determined by qPCR or western blot assays, respectively. Results: FZNZ inhibited MC cells viability and induced cell death. By metabolomics coupled with transcriptomics analysis, we found that the mechanism of FZNZ treatment induced ferroptosis and was related to glutathione metabolism and ER stress. We then, for the first time, found that FZNZ induced ferroptosis, which contributed to an increase in intracellular ferrous iron, reactive oxygen species, and malondialdehyde and a decrease in glutathione. Meanwhile, the protein level of glutathione peroxidase 4 (GPX4) was decreased. The mRNA levels of ATF3/CHOP/CHAC1, which are related to ferroptosis and ER stress, were also upregulated. Conclusion: Our results elaborate that FZNZ could induce ferroptosis and ER stress in MC cells, and reduce GPX4/GSH. ATF3/CHOP/CHAC1 may play a crosstalk role, which provides a new molecular mechanism for the treatment of GPL.

Discovery and validation of Ferroptosis-related molecular patterns and immune characteristics in Alzheimer's disease

Background

To date, the pathogenesis of Alzheimer's disease is still not fully elucidated. Much evidence suggests that Ferroptosis plays a crucial role in the pathogenesis of AD, but little is known about its molecular immunological mechanisms. Therefore, this study aims to comprehensively analyse and explore the molecular mechanisms and immunological features of Ferroptosis-related genes in the pathogenesis of AD.

Materials and methods

We obtained the brain tissue dataset for AD from the GEO database and downloaded the Ferroptosis-related gene set from FerrDb for analysis. The most relevant Hub genes for AD were obtained using two machine learning algorithms (Least absolute shrinkage and selection operator (LASSO) and multiple support vector machine recursive feature elimination (mSVM-RFE)). The study of the Hub gene was divided into two parts. In the first part, AD patients were genotyped by unsupervised cluster analysis, and the different clusters' immune characteristics were analysed. A PCA approach was used to quantify the FRGscore. In the second part: we elucidate the biological functions involved in the Hub genes and their role in the immune microenvironment by integrating algorithms (GSEA, GSVA and CIBERSORT). Analysis of Hub gene-based drug regulatory networks and mRNA-miRNA-lncRNA regulatory networks using Cytoscape. Hub genes were further analysed using logistic regression models.

Results

Based on two machine learning algorithms, we obtained a total of 10 Hub genes. Unsupervised clustering successfully identified two different clusters, and immune infiltration analysis showed a significantly higher degree of immune infiltration in type A than in type B, indicating that type A may be at the peak of AD neuroinflammation. Secondly, a Hub gene-based Gene-Drug regulatory network and a ceRNA regulatory network were successfully constructed. Finally, a logistic regression algorithm-based AD diagnosis model and Nomogram diagram were developed.

Conclusion

Our study provides new insights into the role of Ferroptosis-related molecular patterns and immune mechanisms in AD, as well as providing a theoretical basis for the addition of diagnostic markers for AD.

Construction and validation of a novel Ferroptosis-related gene signature predictive model in rectal Cancer

Background

Rectal cancer (RC) is one of the most common malignant tumors. Ferroptosis is an iron-dependent form of cell death, which plays an important role in various cancers. However, the correlation between ferroptosis-related genes (FRGs) and prognosis in RC remains unclear.

Methods

Gene expression data from The Cancer Genome Atlas Rectum adenocarcinoma (TCGA-READ) and GSE87211 were downloaded. Clustering and functional enrichment were evaluated. A FRGs risk score was established based on the univariate Cox analysis and the Least absolute shrinkage and selection operator (LASSO) analysis. K-M analysis and ROC analysis were conducted to determine prognostic values. qRT-PCR was performed to validate levels of mRNA expression. Multivariate Cox analysis was used to build a prognostic prediction model based on the risk score.

Results

Based on FRGs, RC patients were grouped into two clusters. In the functional enrichment of differentially expressed genes between the two clusters, immune-related pathways dominated. A novel FRGs signature with 14 genes related to the overall survival (OS) of RC was established. qRT-PCR of the 14 genes identified TP63, ISCU, PLIN4, MAP3K5, OXSR, FANCD2 and ATM were overexpressed in RC tissue; HSPB1, MAPK1, ABCC1, PANX1, MAPK9 and ATG7 were underexpressed; TUBE1 had no difference. The high-risk group had a significantly lower OS than the low-risk group (P < 0.001), and ROC curve analysis confirmed the signature’s predictive capacity. Multivariate analysis demonstrated that the risk score and age were independent prognostic factors.

Conclusion

A novel FRGs model can be used to predict the prognosis in RC, as well as to guide individual treatment.

Identification of a key ceRNA network associated with ferroptosis in gastric cancer

Ferroptosis, a newly discovered irondependent form of regulated cell death caused by excessive accumulation of lipid peroxides, is linked to the development and treatment response of various types of cancer, including gastric cancer (GC). Noncoding RNAs (ncRNAs), as key regulators in cancer, have both oncogenic and tumor suppressive roles. However, studies on ferroptosis-related ncRNA networks in GC are still lacking. Here, we first identified 61 differentially expressed genes associated with ferroptosis in GC by computing and analyzing gene expression profile of tumor and normal tissues for GC. Then, upstream lncRNAs and miRNAs interacting with them were found through miRNet and miRBase databases, and hub lncRNAs and miRNAs were obtained through topological analysis. Finally, the ceRNA regulatory network linked to ferroptosis in GC was established, which includes two ferroptosis marker genes (TXNIP and TSC22D3), one driver gene (GABARAPL1), and one suppressor gene (CAV1). Kaplan-Meier survival analysis showed that changes in the expression of these genes were associated with the survival of GC patients. Furthermore, our study revealed that this ceRNA network may influence the progression of GC by regulating ferroptosis process. These results will help experimental researchers to design an experiment study to further explore the roles of this regulatory network in GC ferroptosis.

Development of a ferroptosis-based model to predict prognosis, tumor microenvironment, and drug response for lung adenocarcinoma with weighted genes co-expression network analysis

Objective: The goal of this study was to create a risk model based on the ferroptosis gene set that affects lung adenocarcinoma (LUAD) patients' prognosis and to investigate the potential underlying mechanisms. Material and Methods: A cohort of 482 LUAD patients from the TCGA database was used to develop the prognostic model. We picked the module genes from the ferroptosis gene set using weighted genes co-expression network analysis (WGCNA). The least absolute shrinkage and selection operator (LASSO) and univariate cox regression were used to screen the hub genes. Finally, the multivariate Cox analysis constructed a risk prediction score model. Three other cohorts of LUAD patients from the GEO database were included to validate the prediction ability of our model. Furthermore, the differentially expressed genes (DEG), immune infiltration, and drug sensitivity were analyzed. Results: An eight-gene-based prognostic model, including PIR, PEBP1, PPP1R13L, CA9, GLS2, DECR1, OTUB1, and YWHAE, was built. The patients from the TCGA database were classified into the high-RS and low-RS groups. The high-RS group was characterized by poor overall survival (OS) and less immune infiltration. Based on clinical traits, we separated the patients into various subgroups, and RS had remarkable prediction performance in each subgroup. The RS distribution analysis demonstrated that the RS was significantly associated with the stage of the LUAD patients. According to the study of immune cell infiltration in both groups, patients in the high-RS group had a lower abundance of immune cells, and less infiltration was associated with worse survival. Besides, we discovered that the high-RS group might not respond well to immune checkpoint inhibitors when we analyzed the gene expression of immune checkpoints. However, drug sensitivity analysis suggested that high-RS groups were more sensitive to common LUAD agents such as Afatinib, Erlotinib, Gefitinib, and Osimertinib. Conclusion: We constructed a novel and reliable ferroptosis-related model for LUAD patients, which was associated with prognosis, immune cell infiltration, and drug sensitivity, aiming to shed new light on the cancer biology and precision medicine.

Ferroptosis-related biomarkers for Alzheimer's disease: Identification by bioinformatic analysis in hippocampus

BACKGROUND

Globally, Alzheimer's Disease (AD) accounts for the majority of dementia, making it a public health concern. AD treatment is limited due to the limited understanding of its pathogenesis. Recently, more and more evidence shows that ferroptosis lead to cell death in the brain, especially in the regions of the brain related to dementia.

MATERIALS AND METHODS

Three microarray datasets (GSE5281, GSE9770, GSE28146) related to AD were downloaded from Gene Expression Omnibus (GEO) datasets. Ferroptosis-related genes were extracted from FerrDb database. Data sets were separated into two groups. GSE5281 and GSE9770 were used to identify ferroptosis-related genes, and GSE28146 was used to verify results. During these processes, protein-protein interaction (PPI), the Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. Finally, the differentiated values of ferroptosis-related genes were determined by receiver operator characteristic (ROC) monofactor analysis to judge their potential quality as biomarkers.

RESULTS

Twenty-four ferroptosis-related genes were obtained. Using STRING (https://cn.string-db.org/) and Cytoscape with CytoHubba, the top 10 genes (RB1, AGPAT3, SESN2, KLHL24, ALOX15B, CA9, GDF15, DPP4, PRDX1, UBC, FTH1, ASNS, GOT1, PGD, ATG16L1, SLC3A2, DDIT3, RPL8, VDAC2, GLS2, MTOR, HSF1, AKR1C3, NCF2) were identified as target genes. GO analysis revealed that response to carboxylic acid catabolic process, organic acid catabolic process, alpha-amino acid biosynthetic process and cellular amino acid biosynthetic process were the most highly enriched terms. KEGG analysis showed that these overlapped genes were enriched in p53 signaling pathways, longevity regulating pathway, mTOR signaling pathway, type 2 diabetes mellitus and ferroptosis. Box plots and violine plots were created and verified to confirm the significance of identified target genes. Moreover, ROC monofactor analysis was performed to determine the diagnostic value of identified genes. Two genes (ASNS, SESN2) were subsequently obtained. For the tow genes, STRING was used to obtain the five related genes and determined enriched GO terms and KEGG pathways for those genes.

CONCLUSION

Our results suggest that ASNS and SENS2 may serve as potential diagnostic biomarkers for AD and provide additional evidence regarding the essential role of ferroptosis in AD.

Development and validation of a ferroptosis-related lncRNAs signature to predict prognosis and microenvironment for melanoma

Ferroptosis plays an important role in cancer. However, studies about ferroptosis-related lncRNAs (FRLs) in skin cutaneous melanoma (SKCM) are scarce. Moreover, the relationship between prognostic FRLs and tumor microenvironment (TME) in melanoma remains unclear. This study investigates the potential prognostic value of FRLs and their association with TME in SKCM. The RNA-sequencing data of SKCM were downloaded from The Cancer Genome Atlas (TCGA) database. Melanoma patients were randomly divided into training and testing groups in a 1:1 ratio. A signature composed of 19 FRLs was developed by the least absolute shrinkage and selection operator (LASSO) regression analysis to divide patients into a low-risk group with a better prognosis and a high-risk group with a poor prognosis. Multivariate Cox regression analysis suggested that the risk score was an independent prognostic factor. The Area Under Curve (AUC) value of the risk score reached 0.768 in the training group and 0.770 in the testing group. Subsequent analysis proved that immune-related signaling pathways were significantly enriched in the low-risk group. The tumor immune cell infiltration analysis demonstrated that melanoma in the high-risk group tended to be immunologically "cold". We identified a novel FRLs signature which could accurately predict the prognosis of patients with melanoma.

A ferroptosis-related gene signature associated with immune landscape and therapeutic response in osteosarcoma

BACKGROUND

The role of ferroptosis in tumor progression and immune microenvironment is extensively investigated. However, the potential value of ferroptosis regulators in predicting prognosis and therapeutic strategies for osteosarcoma (OS) patients remains to be elucidated.

METHODS

Here, we extracted transcriptomic and survival data from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) to investigate the expression and prognostic value of ferroptosis regulators in OS patients. After comprehensive analyses, including Gene set variation analysis (GSVA), single-sample gene-set enrichment analysis (ssGSEA), Estimated Stromal and Immune cells in Malignant Tumor tissues using Expression (ESTIMATE), single-cell RNA sequencing, and biological experiments, our constructed 8-ferroptosis-regulators prognostic signature effectively predicted the immune landscape, prognosis, and chemoradiotherapy strategies for OS patients.

RESULTS

We constructed an 8-ferroptosis-regulators signature that could predict the survival outcome of OS. The signature algorithm scored samples, and high-scoring patients were more prone to worse prognoses. The tumor immune landscape suggested the positive relevance between risk score and immunosuppression. Interfering HILPDA and MUC1 expression would inhibit tumor cell proliferation and migration, and MUC1 might improve the ferroptosis resistance of OS cells. Moreover, we predicted chemoradiotherapy strategies of cancer patients following ferroptosis-risk-score groups.

CONCLUSION

Dysregulated ferroptosis gene expression can affect OS progression by affecting the tumor immune landscape and ferroptosis resistance. Our risk model can predict OS survival outcomes, and we propose that HILPDA and MUC1 are potential targets for cancer therapy.

Role of ferroptosis-associated genes in ankylosing spondylitis and immune cell infiltration

Ankylosing spondylitis (AS) is a chronic progressive autoimmune disease with insidious onset, high rates of disability among patients, unknown pathogenesis, and no effective treatment. Ferroptosis is a novel type of regulated cell death that is associated with various cancers and diseases. However, its relation to AS is not clear. In the present study, we identified two potential therapeutic targets for AS based on genes associated with ferroptosis and explored their association with immune cells and immune cell infiltration (ICI). We studied gene expression profiles of two cohorts of patients with AS (GSE25101 and GSE41038) derived from the gene expression omnibus database, and ferroptosis-associated genes (FRGs) were obtained from the FerrDb database. LASSO regression analysis was performed to build predictive models for AS based on FRGs, and the ferroptosis level in each sample was assessed via single-sample gene set enrichment analysis. Weighted gene co-expression network and protein-protein interaction network analyses were performed for screening; two key genes, DDIT3 and HSPB1, were identified in patients with AS. The relationship between key genes and ICI levels was assessed using the CIBERSORT algorithm, followed by gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Finally, DDIT3 and HSPB1 were identified as diagnostic markers and potential therapeutic targets for AS. DDIT3 was highly positively correlated with the infiltration levels of various immune cells, while HSPB1 was negatively correlated with the infiltration levels of several different types of immune cells. In conclusion, DDIT3 and HSPB1 may induce ferroptosis in the cells of patients with AS via changes in the inflammatory response in the immune microenvironment, and these genes could serve as molecular targets for AS therapy.

Ferroptosis-related differentially expressed genes serve as new biomarkers in ischemic stroke and identification of therapeutic drugs

BACKGROUND

Iron is an essential nutrient element, and iron metabolism is related to many diseases. Ferroptosis is an iron-dependent form of regulated cell death associated with ischemic stroke (IS). Hence, this study intended to discover and validate the possible ferroptosis-related genes involved in IS.

MATERIALS AND METHODS

GSE16561, GSE37587, and GSE58294 were retrieved from the GEO database. Using R software, we identified ferroptosis-related differentially expressed genes (DEGs) in IS. Protein-protein interactions (PPIs) and enrichment analyses were conducted. The ROC curve was plotted to explore the diagnostic significance of those identified genes. The consistent clustering method was used to classify the IS samples. The level of immune cell infiltration of different subtypes was evaluated by ssGSEA and CIBERSORT algorithm. Validation was conducted in the test sets GSE37587 and GSE58294.

RESULTS

Twenty-one ferroptosis-related DEGs were detected in IS vs. the normal controls. Enrichment analysis shows that the 21 DEGs are involved in monocarboxylic acid metabolism, iron ion response, and ferroptosis. Moreover, their expression levels were pertinent to the age and gender of IS patients. The ROC analysis demonstrated remarkable diagnostic values of LAMP2, TSC22D3, SLC38A1, and RPL8 for IS. Transcription factors and targeting miRNAs of the 21 DEGs were determined. Vandetanib, FERRIC CITRATE, etc., were confirmed as potential therapeutic drugs for IS. Using 11 hub genes, IS patients were categorized into C1 and C2 subtypes. The two subtypes significantly differed between immune cell infiltration, checkpoints, and HLA genes. The 272 DEGs were identified from two subtypes and their biological functions were explored. Verification was performed in the GSE37587 and GSE58294 datasets.

CONCLUSION

Our findings indicate that ferroptosis plays a critical role in the diversity and complexity of the IS immune microenvironment.