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

Biological Functions and Prognostic Value of Ferroptosis-Related Genes in Bladder Cancer

Background: Every year, nearly 170,000 people die from bladder cancer worldwide. A major problem after transurethral resection of bladder tumor is that 40–80% of the tumors recur. Ferroptosis is a type of regulatory necrosis mediated by iron-catalyzed, excessive oxidation of polyunsaturated fatty acids. Increasing the sensitivity of tumor cells to ferroptosis is a potential treatment option for cancer. Establishing a diagnostic and prognostic model based on ferroptosis-related genes may provide guidance for the precise treatment of bladder cancer.

Methods: We downloaded mRNA data in Bladder Cancer from The Cancer Genome Atlas and analyzed differentially expressed genes based on and extract ferroptosis-related genes. We identified relevant pathways and annotate the functions of ferroptosis-related DEGs using Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and Gene Ontology functions. On the website of Search Tool for Retrieving Interacting Genes database (STRING), we downloaded the protein-protein interactions of DEGs, which were drawn by the Cytoscape software. Then the Cox regression analysis were performed so that the prognostic value of ferroptosis-related genes and survival time are combined to identify survival- and ferroptosis-related genes and establish a prognostic formula. Survival analysis and receiver operating characteristic curvevalidation were then performed. Risk curves and nomograms were generated for both groups to predict survival. Finally, RT-qPCR was applied to analyze gene expression.

Results: Eight ferroptosis-related genes with prognostic value (ISCU, NFE2L2, MAFG, ZEB1, VDAC2, TXNIP, SCD, and JDP2) were identified. With clinical data, we established a prognostic model to provide promising diagnostic and prognostic information of bladder cancer based on the eight ferroptosis-related genes. RT-qPCR revealed the genes that were differentially expressed between normal and cancer tissues.

Conclusion: This study found that the ferroptosis-related genes is associated with bladder cancer, which may serve as new target for the treatment of bladder cancer.

A Ferroptosis and Pyroptosis Molecular Subtype-Related Signature Applicable for Prognosis and Immune Microenvironment Estimation in Hepatocellular Carcinoma

Background: Due to the heterogeneity of tumors and the complexity of the immune microenvironment, the specific role of ferroptosis and pyroptosis in hepatocellular carcinoma (HCC) is not fully understood, especially its impact on prognosis.

Methods: The training set (n = 609, merged by TCGA and GSE14520) was clustered into three subtypes (C1, C2, and C3) based on the prognosis-related genes associated with ferroptosis and pyroptosis. The intersecting differentially expressed genes (DEGs) among C1, C2, and C3 were used in univariate Cox and LASSO penalized Cox regression analysis for the construction of the risk score. The median risk score served as the unified cutoff to divide patients into high- and low-risk groups.

Results: Internal (TCGA, n = 370; GSE14520, n = 239) and external validation (ICGC, n = 231) suggested that the 12-gene risk score had high accuracy in predicting the OS, DSS, DFS, PFS, and RFS of HCC. As an independent prognostic indicator, the risk score could be applicable for patients with different clinical features tested by subgroup (n = 26) survival analysis. In the high-risk patients with a lower infiltration abundance of activated B cells, activated CD8 T cells, eosinophils, and type I T helper cells and a higher infiltration abundance of immature dendritic cells, the cytolytic activity, HLA, inflammation promotion, and type I IFN response in the high-risk group were weaker. The TP53 mutation rate, TMB, and CSC characteristics in the high-risk group were significantly higher than those in the low-risk group. Low-risk patients have active metabolic activity and a more robust immune response. The high- and low-risk groups differed significantly in histology grade, vascular tumor cell type, AFP, new tumor event after initial treatment, main tumor size, cirrhosis, TNM stage, BCLC stage, and CLIP score.

Conclusion: The ferroptosis and pyroptosis molecular subtype-related signature identified and validated in this work is applicable for prognosis prediction, immune microenvironment estimation, stem cell characteristics, and clinical feature assessment in HCC.

A New Ferroptosis-Related lncRNA Signature Predicts the Prognosis of Bladder Cancer Patients

Background: Ferroptosis is closely related to the occurrence and development of cancer. An increasing number of studies have induced ferroptosis as a treatment strategy for cancer. However, the predictive value of ferroptosis-related lncRNAs in bladder cancer (BC) still need to be further elucidated. The purpose of this study was to construct a predictive signature based on ferroptosis-related long noncoding RNAs (lncRNAs) to predict the prognosis of BC patients.

Methods: We downloaded RNA-seq data and the corresponding clinical and prognostic data from The Cancer Genome Atlas (TCGA) database and performed univariate and multivariate Cox regression analyses to obtain ferroptosis-related lncRNAs to construct a predictive signature. The Kaplan-Meier method was used to analyze the overall survival (OS) rate of the high-risk and low-risk groups. Gene set enrichment analysis (GSEA) was performed to explore the functional differences between the high- and low-risk groups. Single-sample gene set enrichment analysis (ssGSEA) was used to explore the relationship between the predictive signature and immune status. Finally, the correlation between the predictive signature and the treatment response of BC patients was analyzed.

Results: We constructed a signature composed of nine ferroptosis-related lncRNAs (AL031775.1, AL162586.1, AC034236.2, LINC01004, OCIAD1-AS1, AL136084.3, AP003352.1, Z84484.1, AC022150.2). Compared with the low-risk group, the high-risk group had a worse prognosis. The ferroptosis-related lncRNA signature could independently predict the prognosis of patients with BC. Compared with clinicopathological variables, the ferroptosis-related lncRNA signature has a higher diagnostic efficiency, and the area under the receiver operating characteristic curve was 0.707. When patients were stratified according to different clinicopathological variables, the OS of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the high-risk group. ssGSEA showed that the predictive signature was significantly related to the immune status of BC patients. High-risk patients were more sensitive to anti-PD-1/L1 immunotherapy and the conventional chemotherapy drugs sunitinib, paclitaxel, cisplatin, and docetaxel.

Conclusion: The predictive signature can independently predict the prognosis of BC patients, provides a basis for the mechanism of ferroptosis-related lncRNAs in BC and provides clinical treatment guidance for patients with BC.

Identification of the ferroptosis-related long non-coding RNAs signature to improve the prognosis prediction and immunotherapy response in patients with NSCLC

BACKGROUND

Non-small cell lung cancer (NSCLC) is the most prevalent type of lung carcinoma with an unfavorable prognosis. Ferroptosis is involved in the development of multiple cancers. Whereas, the prognostic value of ferroptosis-related lncRNAs in NSCLC remains uncertain.

METHODS

Gene expression profiles and clinical information of NSCLC were retrieved from the TCGA database. Ferroptosis-related genes (FRGs) were explored in the FerrDb database and previous studies, ferroptosis-related lncRNAs (FRGs-lncRNAs) were identified by the correlation analysis and the LncTarD database. The differentially expressed FRGs-lncRNAs were screened and FRGs-lncRNAs associated with the prognosis were explored by univariate Cox regression analysis and Kaplan-Meier survival analysis. Then, an FRGs-lncRNAs signature was constructed and verified by the Lasso-penalized Cox analysis. Finally, the potential correlation between risk score, immune checkpoint genes, and chemotherapeutic sensitivity was further investigated.

RESULTS

129 lncRNAs with a potential regulatory relationship with 59 differentially expressed FRGs were found in NSCLC, of which 10 were related to the prognosis of NSCLC (P < 0.05). 9 prognostic-related FRGs-lncRNAs were used to construct the prognostic model and stratify NSCLC patients into high- and low-risk groups. A worse outcome was found in patients with high risk (P < 0.05). Moreover, a good predictive capacity of this signature in predicting NSCLC prognosis was confirmed. Additionally, 45 immune checkpoint genes and 4 chemotherapeutics drugs for NSCLC were identified to be correlated with the risk score.

CONCLUSION

A novel FRGs-lncRNAs signature was successfully constructed, which may contribute to improving the management strategies of NSCLC.

Role of ferroptosis-related genes in Stanford type a aortic dissection and identification of key genes: new insights from bioinformatic analysis

Stanford type A aortic dissection (TAAD) is one of the most dangerous vascular diseases worldwide, and the mechanisms of its development remain unclear. Further molecular pathology studies may contribute to a comprehensive understanding of TAAD and provide new insights into diagnostic markers and potential therapeutic targets. Recent studies have identified that ferroptosis, a form of cell death, may play a previously unrecognized role in influencing the development of TAAD. In this study, we explored the pathological role of ferroptosis in TAAD by performing bioinformatics analyses. Gene set enrichment analysis (GSEA) showed that the ferroptosis-related gene (FRG) set was significantly different between normal and TAAD aortic samples at an overall level (p < 0.001). Further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses explored the potential functions and pathways of FRG in TAAD. We further identified six key genes (CA9, HMOX1, IL6, CDKN1A, HIF1A, MYC) from differentially expressed FRGs in TAAD by constructing a protein-protein interaction (PPI) network, all key genes were upregulated in TAAD. Four of the key genes (CA9, IL6, CDKN1A, and HIF1A) were demonstrated to be correlated with cigarette smoke extract-induced ferroptosis in aortic vascular smooth muscle cells. These results suggest that ferroptosis is one of the essential pathological processes in the development of TAAD, and some FRGs affect TAAD development by mediating cellular ferroptosis, which provides deepening insights into the molecular mechanisms and potential therapeutic targets of TAAD.

Identification of a novel iron zinc finger protein 36 (ZFP36) for predicting the overall survival of osteosarcoma based on the Gene Expression Omnibus (GEO) database

Background

The purpose of this study is to explore the relationship between the ferroptosis-related gene zinc finger protein 36 (ZFP36) and the prognosis of osteosarcoma patients after surgery.

Methods

Differential expression genes (DEGs) between osteosarcoma and normal tissues were screened using osteosarcoma chip data in GEO database. Based on the median expression quantity, ferroptosis DEGs were divided into high and low expression groups. Combined with its corresponding clinical survival data, the survival analysis of ferroptosis DEGs was carried out using the Survival package, and ferroptosis-related genes related to prognosis were identified. Next, the clinical data of 60 osteosarcoma patients treated in Jiangyin Hospital Affiliated to Nanjing University of Chinese Medicine, Zhongda Hospital and Nanjing Drum Tower Hospital from January 2011 to January 2016 were retrospectively analyzed. Immunohistochemistry and reverse transcription quantitative polymerase chain reaction (qRT-PCR) were used to detect gene expression in osteosarcoma. The Kaplan-Meier method and log rank test were used for univariate survival analysis, the Cox regression method was used for multivariate analysis, and the nomogram was constructed for internal verification on this basis.

Results

Immunohistochemical and reverse transcription quantitative PCR results showed that the expression of ZFP36 was mainly higher in cancer-adjacent tissues than in tumor tissues. There were significant differences in age, tumor location, Enneking stage, and tumor specific growth factor (TSGF) between the high and low expression groups of ZFP36 (P<0.05). The final study included 60 patients, of whom 23 patients died (mortality rate: 38.33%), and 37 patients survived (survival rate: 61.67%), with a median progression-free survival (PFS) of 32.5 months and a median overall survival (OS) of 77 months. The Cox multivariate analysis showed that distant metastasis and ZFP36 were independent risk factors affecting tumor progression (P=0.021 and P=0.006, respectively). Elevated ZFP36 can significantly prolong the OS and PFS of osteosarcoma patients. In internal verification, the Concordance index (C-index) of the nomogram was 0.7211 [95% confidence interval (CI): 0.6308–0.8115], and the prediction model had certain accuracy.

Conclusions

Elevated ZFP36 can significantly prolong the OS and PFS in osteosarcoma patients. At the same time, ZFP36 could be used as a new predictive biomarker and novel therapeutic target for osteosarcoma patients.

DCcov: Repositioning of drugs and drug combinations for SARS-CoV-2 infected lung through constraint-based modeling

The 2019 coronavirus disease (COVID-19) became a worldwide pandemic with currently no approved effective antiviral drug. Flux balance analysis (FBA) is an efficient method to analyze metabolic networks. Here, FBA was applied on human lung cells infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to reposition metabolic drugs and drug combinations against the virus replication within the host tissue. Making use of expression datasets of infected lung tissue, genome-scale COVID-19-specific metabolic models were reconstructed. Then, host-specific essential genes and gene pairs were determined through in silico knockouts that permit reducing the viral biomass production without affecting the host biomass. Key pathways that are associated with COVID-19 severity in lung tissue are related to oxidative stress, ferroptosis, and pyrimidine metabolism. By in silico screening of Food and Drug Administration (FDA)-approved drugs on the putative disease-specific essential genes and gene pairs, 85 drugs and 52 drug combinations were predicted as promising candidates for COVID-19 (https://github.com/sysbiolux/DCcov).

Prognostic Value of a Ferroptosis-Related Gene Signature in Patients With Head and Neck Squamous Cell Carcinoma

Background: Ferroptosis is an iron-dependent programmed cell death (PCD) form that plays a crucial role in tumorigenesis and might affect the antitumor effect of radiotherapy and immunotherapy. This study aimed to investigate distinct ferroptosis-related genes, their prognostic value and their relationship with immunotherapy in patients with head and neck squamous cell carcinoma (HNSCC). Methods: The differentially expressed ferroptosis-related genes in HNSCC were filtered based on multiple public databases. To avoid overfitting and improve clinical practicability, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were performed to construct a prognostic risk model. Moreover, a nomogram was constructed to forecast individual prognosis. The differences in tumor mutational burden (TMB), immune infiltration and immune checkpoint genes in HNSCC patients with different prognoses were investigated. The correlation between drug sensitivity and the model was firstly analyzed by the Pearson method. Results: Ten genes related to ferroptosis were screened to construct the prognostic risk model. Kaplan-Meier (K-M) analysis showed that the prognosis of HNSCC patients in the high-risk group was significantly lower than that in the low-risk group (P < 0.001), and the area under the curve (AUC) of the 1-, 3- and 5-year receiver operating characteristic (ROC) curve increased year by year (0.665, 0.743, and 0.755). The internal and external validation further verified the accuracy of the model. Then, a nomogram was build based on the reliable model. The C-index of the nomogram was superior to a previous study (0.752 vs. 0.640), and the AUC (0.729 vs. 0.597 at 1 year, 0.828 vs. 0.706 at 3 years and 0.853 vs. 0.645 at 5 years), calibration plot and decision curve analysis (DCA) also shown the satisfactory predictive capacity. Furthermore, the TMB was revealed to be positively correlated with the risk score in HNSCC patients (R = 0.14; P < 0.01). The differences in immune infiltration and immune checkpoint genes were significant (P < 0.05). Pearson analysis showed that the relationship between the model and the sensitivity to antitumor drugs was significant (P < 0.05). Conclusion: Our findings identified potential novel therapeutic targets, providing further potential improvement in the individualized treatment of patients with HNSCC.

A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

Objective

To discover potential predictors and explore how to build better models by summarizing the existing prognostic prediction models of non-small cell lung cancer (NSCLC).

Background

Research on clinical prediction models of NSCLC has experienced explosive growth in recent years. As more predictors of prognosis are discovered, the choice of predictors to build models is particularly important, and in the background of more applications of next-generation sequencing technology, gene-related predictors are widely used. As it is more convenient to obtain samples and follow-up data, the prognostic model is preferred by researchers.

Methods

PubMed and the Cochrane Library were searched using the items “NSCLC”, “prognostic model”, “prognosis prediction”, and “survival prediction” from 1 January 1980 to 5 May 2021. Reference lists from articles were reviewed and relevant articles were identified.

Conclusions

The performance of gene-related models has not obviously improved. Relative to the innovation and diversity of predictors, it is more important to establish a highly stable model that is convenient for clinical application. Most of the prevalent models are highly biased and referring to PROBAST at the beginning of the study may be able to significantly control the bias. Existing models should be validated in a large external dataset to make a meaningful comparison.

Development and Validation of a Ferroptosis-Related Gene Signature and Nomogram for Predicting the Prognosis of Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common malignant tumor with high mortality and poor prognosis. Ferroptosis is a newly discovered form of cell death induced by iron-catalyzed excessive peroxidation of polyunsaturated fatty acids (PUFAs). However, the prognostic value of ferroptosis-related genes (FRGs) for ESCC remains unclear. Based on the ESCC dataset from the Gene Expression Omnibus (GEO) database, we identified 39 prognostic FRGs through univariate Cox regression analysis. After LASSO regression and multivariate Cox regression analyses, a multigene signature based on 10 prognostic FRGs was constructed and successfully divided ESCC patients into two risk groups. Patients in the low-risk group showed a significantly better prognosis than patients in the high-risk group. In addition, we combined the risk score with clinical predictors to construct a nomogram for ESCC. The predictive ability of the nomogram was further verified by ROC curves and calibration plots in both the training and validation sets. The predictive power of the nomogram was demonstrated to be better than that of either the risk score or clinical variable alone. Furthermore, functional analysis revealed that the 10-FRG signature was mainly associated with ferroptosis, differentiation and immune response. Connectivity map analysis identified potential compounds capable of targeting FRGs in ESCC. Finally, we demonstrated the prognostic value of SRC gene in ESCC using the clinical samples and found that SRC inhibition sensitized ESCC cells to ferroptosis inducers by in vitro experiments. In conclusion, we identified and verified a 10-FRG prognostic signature and a nomogram, which provide individualized prognosis prediction and provide insight into potential therapeutic targets for ESCC.

Comprehensive Analysis of Ferroptosis-Related Markers for the Clinical and Biological Value in Gastric Cancer

Gastric cancer is a highly malignant tumor with poor survival rate. Ferroptosis, a newly defined regulated cell death, is closely related to several tumors. Introduction of ferroptosis is promising for cancer treatments. However, the predictive role of ferroptosis in GC remains elusive. In this study, we screened the ferroptosis-related genes which were differentially expressed between normal and GC tissues. Then, based on these differentially expressed genes (DEGs), the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regressions were applied to construct the 10-gene prognostic signature (SP1, MYB, ALDH3A2, KEAP1, AIFM2, ITGB4, TGFBR1, MAP1LC3B, NOX4, and ZFP36) in TCGA training dataset. Based on the median risk score, all GC patients in TCGA training dataset and GSE84437 testing dataset were classified into a high- or low-risk group. GC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P < 0.001). Combined with the clinical characteristics, the risk score was proven as an independent factor for predicting the OS of GC patients. Besides, the GC patients in the high- or low-risk group showed significantly different GO and KEGG functional enrichments, somatic mutation, fractions of immune cells, and immunotherapy response. Then, the expression levels of these genes in signature were further verified in the GC cell lines and our own GC samples (30-paired tumor/normal tissues). Furthermore, the effects of ferroptosis inducer Erastin on these 10 ferroptosis-related genes in GC cell lines were also explored in our study. In conclusion, our study constructed a prognostic signature of 10 ferroptosis-related genes, which could well predict the prognosis and immunotherapy for GC patients.

Identification of a Ferroptosis-Related Long Noncoding RNA Prognostic Signature and Its Predictive Ability to Immunotherapy in Hepatocellular Carcinoma

Background: Immune checkpoint blockers (ICBs) are increasingly being used to treat patients with advanced hepatocellular carcinoma (HCC), but only a third of these patients are sensitive to ICBs. Emerging evidence suggests that ferroptosis could be a novel target for antitumor treatment, and combined treatment with ferroptosis inducers might enhance sensitivity to immunotherapy. However, there is a lack of information on the crosstalk between ferroptosis-related lncRNAs and anti-tumor immunity. Therefore, we aim to explore prognostic value of ferroptosis-related lncRNAs and clarify potential role in ICBs of HCC.

Methods: We obtained mRNA and lncRNA expression data from two independent cohorts (TCGA and GEO database). Univariate Cox, the least absolute shrinkage and selection operator (Lasso) algorithm and multivariate Cox analysis were used to construct a lncRNA signature, which was evaluated using the area under the receiver operating characteristic curve (AUC) and Kaplan–Meier curves. Tumor-infiltrating cell (TIC) profiling and the tumor immune dysfunction and exclusion (TIDE) algorithm were used to validate the signature model and immunotherapy. Finally, we adopted RT-PCR assay to evaluate the differential expression of lncRNAs in HCC tissues in our hospital.

Results: The ferroptosis-related lncRNA signature included five lncRNAs, most of which were positively correlated with clinical stage and grade. The signature could stratify patients into two risk groups, with the high-risk group associated with a shorter overall survival (OS, p < 0.05) in TCGA-LIHC and GSE76427. Besides, the AUCs of the 1-, 3-, and 5-years OS were 0.772, 0.707, and 0.666, respectively. Gene set enrichment analysis (GESA) of lncRNAs revealed enrichment of oncogenic and immune-related pathways. The TIC profiling indicated a close correlation between the signature and immune cells. Furthermore, the high-risk group had a better response to immunotherapy than low-risk group. RT-PCR demonstrated these five lncRNAs were upregulated in cancerous tissue than normal tissues.

Conclusions: The ferroptosis-related lncRNA signature could accurately predict the OS of HCC patients and may serve as an independent clinical factor for patients’ outcomes. Ferroptosis-related lncRNAs may remodel the tumor microenvironment (TME) and affect the anti-cancer ability of ICBs, and therefore, could potentially act as an indicator for the response to immunotherapy in HCC.

A Ferroptosis-Related Gene Signature for Predicting the Prognosis and Drug Sensitivity of Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancers worldwide and has a high mortality. Ferroptosis, an iron-dependent form of programmed cell death, plays a crucial role in tumor suppression and chemotherapy resistance in cancer. However, the prognostic and clinical values of ferroptosis-related genes (FRGs) in HNSCC remain to be further explored. In the current study, we constructed a ferroptosis-related prognostic model based on the Cancer Genome Atlas database and then explored its prognostic and clinical values in HNSCC via a series of bioinformatics analyses. As a result, we built a four-gene prognostic signature, including FTH1, BNIP3, TRIB3, and SLC2A3. Survival analysis showed that the high-risk group presented significantly poorer overall survival than the low-risk group. Moreover, the ferroptosis-related signature was found to be an independent prognostic predictor with high accuracy in survival prediction for HNSCC. According to immunity analyses, we found that the low-risk group had higher anti-tumor immune infiltration cells and higher expression of immune checkpoint molecules and meanwhile corelated more closely with some anti-tumor immune functions. Meanwhile, all the above results were validated in the independent HSNCC cohort GSE65858. Besides, the signature was found to be remarkably correlated with sensitivity of common chemotherapy drugs for HNSCC patients and the expression levels of signature genes were also significantly associated with drug sensitivity to cancer cells. Overall, we built an effective ferroptosis-related prognostic signature, which could predict the prognosis and help clinicians to perform individualized treatment strategy for HNSCC patients.

Ferroptosis Characterization in Lung Adenocarcinomas Reveals Prognostic Signature With Immunotherapeutic Implication

The iron-dependent cell death named ferroptosis has been implicated in the progression and therapeutic response of several tumors. However, potential role of ferroptosis in lung adenocarcinomas (LUAD) remained less well understood. In TCGA-LUAD cohort, unsupervised clustering was first conducted based on ferroptosis regulators extracted from FerrDb database. Comprehensive correlation analysis and comparisons were performed among ferroptosis subtypes. The ferroptosis-related prognostic (FRP) signature was identified based on filtered features and repeated LASSO and was validated in five independent cohorts. The clinical relevance between the risk score and therapeutic response was further explored by multiple algorithms. qPCR was implemented to verify gene expression. A total of 1,168 LUAD patients and 161 ferroptosis regulators were included in this study. Three ferroptosis subtypes were identified and patients in subtype B had the best prognosis among the three subtypes. Significant differences in immune microenvironment and biological function enrichment were illustrated in distinct subtypes. The Boruta algorithm was conducted on 308 common differentially expressed genes for dimensionality reduction. A total of 56 genes served as input for model construction and a six-gene signature with the highest frequencies of 881 was chosen as FRP. The prognostic significance of FRP was validated in five independent cohorts. High FRP risk score was also linked to increased tumor mutation burden, PD-L1 protein expression and number of neoantigens. Of the FRP genes, 83.3% was abnormally expressed in LUAD cell lines. In conclusion, ferroptosis plays a non-negligible role in LUAD. Exploration of the ferroptosis pattern will enhance the prognostic stratification of individual patients and move toward the purpose of personalized treatment.

Ferroptosis-Associated Classifier and Indicator for Prognostic Prediction in Cutaneous Melanoma

Ferroptosis plays a critical role in different types of cancers, but the prognostic impact of ferroptosis in cutaneous melanoma remains lacking. Therefore, ferroptosis-related genes (FRGs) were firstly obtained from the FerrDb database and the differentially expressed FRGs were identified by the “limma” algorithm. Next, the prognostic differentially expressed FRGs were screened out by univariate Cox regression, which were subsequently used to cluster melanomas into two subtypes (clusters A and B). Besides, the Boruta algorithm and principal component analysis (PCA) were performed to build a 15-FRGs indicator, which can robustly predict patients' overall survival (OS) and be considered as an independent prognostic factor in melanoma. The melanoma patients were further divided into high- and low-FRGs score groups. The high score group have a good prognosis, with higher T cell immune infiltrating and lower mutation frequencies in NRAS, KRAS, and NF1. Finally, we discovered that many immune processes and several chemotherapy drugs were closely associated with FRGs score. Thus, our study provides a novel ferroptosis-associated classifier and indicator to predict the prognosis of melanoma. Besides, we identified several potential chemotherapy drugs to induce ferroptosis and could supply additional effective treatments.

LncRNA RP11-89 facilitates tumorigenesis and ferroptosis resistance through PROM2-activated iron export by sponging miR-129-5p in bladder cancer

Long non-coding RNAs (lncRNAs) act as important regulators of tumorigenesis and development in bladder cancer. However, the underlying molecular mechanisms remain elusive. We previously identified a novel lncRNA signature related to immunity and progression in bladder cancer. Here we further explored the function of RP11-89, a lncRNA discovered in the previous signature. Loss- and gain-of function experiments were performed using CCK-8 assay, flow cytometry, Transwell assays, scratch tests and subcutaneous nude mouse models. High-throughput RNA sequencing was conducted to identify dysregulated genes in bladder cancer cells with RP11-89 knockdown or overexpression. Regulation of RP11-89 on miR-129-5p and PROM2 was explored through luciferase reporter assay, RIP assay and RNA pull-down assay. RP11-89 promoted cell proliferation, migration and tumorigenesis and inhibited cell cycle arrest via the miR-129-5p/PROM2 axis. We found that RP11-89 "sponges" miR-129-5p and upregulates PROM2. Elevated PROM2 in cells was associated with attenuated ferroptosis through iron export, formation of multivesicular bodies and less mitochondrial abnormalities. We demonstrated that RP11-89 is a novel tumorigenic regulator that inhibits ferroptosis via PROM2-activated iron export. RP11-89 may serve as a potential biomarker for targeted therapy in bladder cancer.

Ferroptosis regulators, especially SQLE, play an important role in prognosis, progression and immune environment of breast cancer

BACKGROUND

Ferroptosis, a new form of programmed cell death, has great potential for cancer treatment. However, the roles of ferroptosis-related (FR) genes in breast cancer (BC) remain elusive.

MATERIALS AND METHODS

Using TCGA database, a novel FR risk signature was constructed through the Lasso regression analysis. Meanwhile, its prognostic value was assessed by a series of survival analyses. Besides, a nomogram was constructed to predict the overall survival rate (OSR) of individual at 1,3,5 year. Four validation cohorts (n = 2248), including METABRIC, GSE58812, GSE20685 and ICGC-KR datasets, were employed to test the prognostic value of FR risk signature. The effects of FR risk signature on BC immune microenvironment were explored by CIBERSORT algorithm and ssGSEA method. The histological expressions of FR risk genes were presented by HPA database. The biofunctions of SQLE were determined by qPCR, MTT, wound-healing and Transwell assays.

RESULTS

We constructed a novel FR risk signature consisting of eight genes. High FR risk led a poor prognosis and was identified as an independent prognostic factor. Besides, A higher proportion of patients with luminal A type was observed in low-risk group (53%), while a higher proportion of patients with basal type in high-risk group (24%). FR risk score could discriminate the prognostic difference of most clinical subgroups, except for M1 stage, HER2 and basal types. Moreover, its prognostic value was successfully validated in other four cohorts. Through immune analyses, we found that the reduced infiltration levels of CD8+ and NK cells, whereas the enhanced activity of antigen presentation process appeared in high FR risk. Then, FR risk score was found to weakly correlate with the expressions of six immune checkpoints. Through the experiments in vitro, we confirmed that overexpression of SQLE could promote, whereas blocking SQLE could inhibit the proliferative, migrative and invasive abilities of BC cells.

CONCLUSIONS

FR risk signature was conducive to BC prognostic assessment. High FR risk level was closely associated with BC immunosuppression, but may not predict ICIs efficacy. Moreover, SQLE was identified as a crucial cancer-promoting gene in BC. Our findings provide new insights into prognostic assessment and molecular mechanism of BC.

Cigarettes, a skin killer! Cigarette smoke may cause ferroptosis in female skin

INTRODUCTION

Skin exposure to tobacco smoke is closely related to skin aging. Ferroptosis is an iron-dependent form of regulated cell death driven by the accumulation of lipid peroxides to levels sufficient to trigger cell death. However, few studies have examined ferroptosis in skin-related diseases.

METHODS

This study searched for differentially expressed genes by analyzing gene expression data downloaded from the Gene Expression Omnibus. Ferroptosis-related genes were obtained by analyzing the FerrDb database. We also investigated the regulatory mechanism of ferroptosis-related genes by enrichment analysis and constructing gene-miRNA and gene-transcription factor networks.

RESULTS

Based on these analyses, exposure to cigarette smoke can cause ferroptosis in female skin. Ferroptosis-associated genes might be regulated by 17 miRNAs and 20 TFs.

CONCLUSION

Finally, we found ferroptosis in the skin of women exposed to cigarette smoke, and the results provide an important theoretical basis for future research and anti-aging treatment of skin.

Ferroptosis-related gene AKR1C1 predicts the prognosis of non-small cell lung cancer

BACKGROUND

Ferroptosis is a newly discovered mode of cell death distinct from apoptosis and necrosis, and its activation contributes to anticancer therapy in a variety of cancers. However, the prognostic value of ferroptosis-related genes in non-small cell lung cancer (NSCLC) remains to be further investigated.

METHODS

NSCLC transcriptome mRNA-seq data set and corresponding clinical data set were downloaded from the Cancer Genome Atlas (TCGA). Then, bioinformatics approaches were subsequently employed to identify potential prognostic markers. Finally, the effects of candidate markers on NSCLC cell proliferation, migration, and ferroptosis were assessed by CCK8, colony formation, wound-healing assay, and functional assays related to ferroptosis.

RESULTS

A total of 37 common differentially expressed genes were screened based TCGA database. Six overall survival associated genes (ENPP2, ULK1, CP, LURAP1L, HIC1, AKR1C1) were selected to build survival model, of which hub gene AKR1C1 was with high expression and low ferroptosis level in NSCLC tumor. Further research showed that AKR1C1 was related with many pathways involved in the process of ferroptosis and associated with diverse cancer-infiltrating immune cells. Moreover, the results of in vitro experiments indicated that the expression of AKR1C1 was upregulated in NSCLC cell lines, and silencing AKR1C1 can inhibit the proliferation and migration of NSCLC cells and promote the occurrence of ferroptosis.

CONCLUSIONS

Our study revealed the potential role of ferroptosis-related gene AKR1C1 in NSCLC, which can be used for prognostic prediction in NSCLC.

Ferroptosis Patterns Correlate with Immune Microenvironment Characterization in Gastric Cancer

Objective

We aimed to build a ferroptosis-based classifier to characterize the molecular features of gastric cancers (GC) and investigate the relationship between different ferroptosis patterns and GC tumor microenvironment (TME).

Methods

Based on the genomic and clinical information from TCGA portal and GEO database, non-negative matrix factorization (NMF) was used to identify ferroptosis subtypes in GC patients. In order to estimate the ferroptosis levels, we established ferroptosis subtype score (FSS) to quantify ferroptosis patterns and ferroptosis potential index (FPI) by principal component analysis (PCA). The correlations of different ferroptosis patterns with TME cell-infiltrating characteristics (including immune cell infiltration, immune checkpoints expression levels, tumor mutational burden (TMB) and immunotherapy response) were systematically analyzed.

Results

Two ferroptosis subtypes, C1 (with lower FSS) and C2 (with higher FSS), were determined. C2 displayed a significantly lower FPI than C1. Besides, C2 was associated with diffuse subtype while C1 with intestinal subtype. As for TME characteristics, C2 was in accordance with the immune-excluded phenotype as it showed more active immune and stromal activities but lower TMB, less probability of immunotherapy response and poorer prognosis. C1 was linked to immune-inflamed phenotype as it had lower stromal activities but increased neoantigen load, enhanced response to immunotherapy and relatively better prognosis.

Conclusion

The systematic assessment of ferroptosis patterns and ferroptosis levels presented in our study implied that ferroptosis serves as an important factor in the formation of TME, which may expand the understanding of TME and provide a novel perspective for the development of targeted immunotherapeutic strategies for GC patients.

Ferroptosis-Related Genes in Bronchoalveolar Lavage Fluid Serves as Prognostic Biomarkers for Idiopathic Pulmonary Fibrosis

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive disease with unknown etiology and unfavorable prognosis. Ferroptosis is a form of regulated cell death with an iron-dependent way that is involved in the development of various diseases. Whereas the prognostic value of ferroptosis-related genes (FRGs) in IPF remains uncertain and needs to be further elucidated.

Methods: The FerrDb database and the previous studies were screened to explore the FRGs. The data of patients with IPF were obtained from the GSE70866 dataset. Wilcoxon's test and univariate Cox regression analysis were applied to identify the FRGs that are differentially expressed between normal and patients with IPF and associated with prognosis. Next, a multigene signature was constructed by the least absolute shrinkage and selection operator (LASSO)-penalized Cox model in the training cohort and evaluated by using calibration and receiver operating characteristic (ROC) curves. Then, 30% of the dataset samples were randomly selected for internal validation. Finally, the potential function and pathways that might be affected by the risk score-related differently expressed genes (DEGs) were further explored.

Results: A total of 183 FRGs were identified by the FerrDb database and the previous studies, and 19 of them were differentially expressed in bronchoalveolar lavage fluid (BALF) between IPF and healthy controls and associated with prognosis (p < 0.05). There were five FRGs (aconitase 1 [ACO1], neuroblastoma RAS viral (v-ras) oncogene homolog [NRAS], Ectonucleotide pyrophosphatase/phosphodiesterase 2 [ENPP2], Mucin 1 [MUC1], and ZFP36 ring finger protein [ZFP36]) identified as risk signatures and stratified patients with IPF into the two risk groups. The overall survival rate in patients with high risk was significantly lower than that in patients with low risk (p < 0.001). The calibration and ROC curve analysis confirmed the predictive capacity of this signature, and the results were further verified in the validation group. Risk score-related DEGs were found enriched in ECM-receptor interaction and focal adhesion pathways.

Conclusion: The five FRGs in BALF can be used for prognostic prediction in IPF, which may contribute to improving the management strategies of IPF.

Iron Metabolism and Idiopathic Pulmonary Arterial Hypertension: New Insights from Bioinformatic Analysis

Idiopathic pulmonary arterial hypertension (IPAH) is a rare vascular disease with a poor prognosis, and the mechanism of its development remains unclear. Further molecular pathology studies may contribute to a comprehensive understanding of IPAH and provide new insights into diagnostic markers and potential therapeutic targets. Iron deficiency has been reported in 43-63% of patients with IPAH and is associated with reduced exercise capacity and higher mortality, suggesting that dysregulated iron metabolism may play an unrecognized role in influencing the development of IPAH. In this study, we explored the regulatory mechanisms of iron metabolism in IPAH by bioinformatic analysis. The molecular function of iron metabolism-related genes (IMRGs) is mainly enriched in active transmembrane transporter activity, and they mainly affect the biological process of response to oxidative stress. Ferroptosis and fluid shear stress and atherosclerosis pathways may be the critical pathways regulating iron metabolism in IPAH. We further identified 7 key genes (BCL2, GCLM, MSMO1, SLC7A11, SRXN1, TSPAN5, and TXNRD1) and 5 of the key genes (BCL2, MSMO1, SLC7A11, TSPAN5, and TXNRD1) as target genes may be regulated by 6 dysregulated miRNAs (miR-483-5p, miR-27a-3p, miR-27b-3p, miR-26b-5p, miR-199a-5p, and miR-23b-3p) in IPAH. In addition, we predicted potential IPAH drugs-celastrol and cinnamaldehyde-that target iron metabolism based on our results. These results provide insights for further definition of the role of dysregulated iron metabolism in IPAH and contribute to a deeper understanding of the molecular mechanisms and potential therapeutic targets of IPAH.

Expression of Ferroptosis-Related Genes Shapes Tumor Microenvironment and Pharmacological Profile in Gastric Cancer

Background: Ferroptosis is a form of regulated cell death that occurs as a consequence of lethal lipid peroxidation. A wealth of studies has demonstrated that ferroptosis profoundly modulated numerous biological behaviors of tumor. However, its natural functions in gastric cancer (GC) remain to be explored.

Methods: Firstly, a total of over 1,000 GC patients from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database were included in our study. Secondly, 32 ferroptosis-related genes were extracted from the ferrDb website. Then, unsupervised clustering was performed to classify patients into three distinct ferroptosis-related clusters. Subsequently, we systematically and comprehensively explored the biological characteristics of each cluster. Finally, we constructed a scoring system, named ferroptosis score, to quantify each cluster and also investigated the predictive therapeutic value of the ferroptosis score for chemotherapy and immunotherapy.

Results: Based on the expressions of 32 ferroptosis-related genes, three distinct ferroptosis-related subtypes with various biological characteristics were determined. Integrated analysis showed that cluster 1 is a microsatellite instability (MSI)-like subtype, cluster 2 is an epithelial–mesenchymal transition (EMT)-like subtype, while cluster 3 tends to be a metabolic-like subtype. Prognostic analysis revealed that patients in cluster 2 had a worse overall survival and relapse-free survival. The distribution of the ferroptosis score was significantly different in clusters and gene clusters. The ferroptosis score could predict the biological characteristics of each cluster, the stromal activity, and progression of tumor. The low ferroptosis score group was characterized by the activation of antigen processing and presentation, DNA damage repair pathways, and metabolic pathways, while the high ferroptosis score group was characterized by stromal activation. In response to anticancer drugs, the ferroptosis score was highly negatively associated with drugs targeting MAPK signaling and PI3K/mTOR signaling, while it was positively correlated with drugs targeting the cell cycle, mitosis, and metabolism. Finally, we also proved that the ferroptosis score could serve as a reliable biomarker to predict response to immunotherapy.

Conclusion: This work revealed that tumor cells and their surrounding microenvironment could be shaped by varying the activation degrees of ferroptosis. Establishing ferroptosis-related subtypes would guide in predicting the biological features of individual tumors and selecting appropriate treatment protocols for patients.

A Novel Ferroptosis-Related Gene Signature Predicts Recurrence in Patients With Pancreatic Ductal Adenocarcinoma

Background: Recurrence after surgery is largely responsible for the extremely poor outcomes for patients with pancreatic ductal adenocarcinoma (PDAC). Ferroptosis is implicated in chemotherapy sensitivity and tumor recurrence, we aimed to find out survival-associated ferroptosis-related genes and use them to build a practical risk model with the purpose to predict PDAC recurrence. Methods: Univariate Cox regression analysis was conducted to obtain prognostic ferroptosis-related genes in The Cancer Genome Atlas (TCGA, N = 140) cohort. Multivariate Cox regression analysis was employed to construct a reliable and credible gene signature. The prognostic performance was verified in a MTAB-6134 (N = 286) validation cohort and a PACA-CA (N = 181) validation cohort. The stability of the signature was tested in TCGA and MTAB-6134 cohorts by ROC analyses. Pathway enrichment analysis was adopted to preliminary illuminate the biological relevance of the gene signature. Results: Univariate and multivariate Cox regression analyses identified a 5-gene signature that contained CAV1, DDIT4, SLC40A1, SRXN1 and TFAP2C. The signature could efficaciously stratify PDAC patients with different recurrence-free survival (RFS), both in the training and validation cohorts. Results of subgroup receiver operating characteristic curve (ROC) analyses confirmed the stability and the independence of this signature. Our signature outperformed clinical indicators and previous reported models in predicting RFS. Moreover, the signature was found to be closely associated with several cancer-related and drug response pathways. Conclusion: This study developed a precise and concise prognostic model with the clinical implication in predicting PDAC recurrence. These findings may facilitate individual management of postoperative recurrence in patients with PDAC.

Development and validation of a ferroptosis-related prognostic model for the prediction of progression-free survival and immune microenvironment in patients with papillary thyroid carcinoma

BACKGROUND

Ferroptosis is an iron-dependent and regulated cell death that has been widely reported in a variety of malignancies. The overall survival of papillary thyroid cancer (PTC) is excellent, but the identification of patients with poor prognosis still faces challenges. Nevertheless, whether ferroptosis-related genes (FRGs) can be used to screen high-risk patients is not clear.

METHODS

We obtained the clinical data of patients with PTC and FRGs from the UCSC Xena platform and the FerrDb respectively. Differentially expressed genes (DEGs) of FRGs were obtained from the entire The Cancer Genome Atlas (TCGA). Subsequently, the entire TCGA dataset was randomly split into two subsets: training and test datasets. Based on DEGs, we constructed a predictive model which was tested in the test dataset and the entire TCGA dataset to predict progression-free survival (PFS). Patients were categorized into high- or low-risk groups based on their median risk score. We analyzed differences in some aspects, including pathway enrichment analysis, single-sample Gene Set Enrichment Analysis (ssGSEA), tumor microenvironment (TME), human leukocyte antigen (HLA) genes, and tumor mutation burden (TMB) analyses, between high-risk and low-risk groups.

RESULTS

A predictive model with three FRGs (HSPA5, AURKA, and TSC22D3) was constructed. Patients in the high-risk group had worse PFS compared with patients in the low-risk group. Functional analysis results revealed that ssGSEA, immune cell infiltration, TME, HLA, and TMB were closely associated with ferroptosis.

CONCLUSION

The prognostic model constructed in this study can effectively predict PFS for patients with PTC.

Establishment of a novel ferroptosis-related lncRNA pair prognostic model in colon adenocarcinoma

Long non-coding RNAs (lncRNAs) have been reported to be prognostic factors for cancer. Ferroptosis is an iron-dependent process of programmed cell death. Here, we established a ferroptosis-related lncRNA (frlncRNA) pair signature and revealed its prognostic value in colon adenocarcinoma (COAD) by analyzing the data from The Cancer Genome Atlas (TCGA). FrlncRNAs were identified based on co-expression analysis using the Pearson correlation. Differentially expressed frlncRNAs (DEfrlncRNAs) were recognized and paired, followed by prognostic assessment using univariate Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) penalized Cox analysis was used to determine and construct a risk score prognostic model, by which the receiver operating characteristic (ROC) curves for predicting the overall survival (OS) were conducted. Following the evaluation of whether it was an independent prognostic factor, correlations between the risk score model and clinicopathological characteristics, hypoxia- and immune-related factors, and somatic variants were investigated. In total, 148 DEfrlncRNA pairs were identified, 25 of which were involved in a risk score prognostic signature. The area under ROC curves (AUCs) representing the predictive effect for 1-, 3-, and 5-year survival rates were 0.860, 0.885, and 0.934, respectively. The risk score model was confirmed as an independent prognostic factor and was significantly superior to the clinicopathological characteristics. Correlation analyses showed disparities in clinicopathological characteristics, hypoxia- and immune-related factors, and somatic variants, as well as specific signaling pathways between high- and low-risk groups. The novel risk score prognostic model constructed by pairing DEfrlncRNAs showed promising clinical prediction value in COAD.

Identification of a ferroptosis-related lncRNA signature with prognosis for Wilms tumor

BACKGROUND

Wilms tumor (WT) is a widespread urologic tumor in children. Ferroptosis, on the other hand, is a novel form of cell death associated with tumor development. In this study, we aim to explore the predictability of ferroptosis-related biomarkers in estimating prognosis in WT patients.

METHODS

To determine a link between ferroptosis-related gene expression and WT prognosis, we first collected RNA sequencing data and clinical information, involving 124 WT and 6 healthy tissue samples, from the TARGET database. Next, we screened the collected information for ferroptosis-related long non-coding RNA using Cox regression analysis, and constructed a signature model, as well as a nomogram, related to prognosis. Finally, we explored a potential link between ferroptosis-related lncRNA and tumor immunity and screened for possible immune checkpoints.

RESULTS

We constructed a WT prognosis prediction signature containing 12 ferroptosis-related lncRNAs. The area under the curves values, from the ROC curves, predicting overall survival rates at the 1, 3-, and 5-year timepoints were 0.775, 0.867, and 0.891 respectively. Moreover, we generated a nomogram, using clinical features and risk scores, carrying a C-index value of 0.836, which suggested a high predictive value. We also demonstrated significant differences in tumor immunity between low- and high-risk WT patients, particularly in the presence of B cells, NK cells, Th1 cells, Treg cells, inflammation promoting, and type I and II IFN responses. In addition, we showed that immune checkpoints like SIRPA, ICOSLG, LAG3, PVRIG, NECTIN1, and SIRPB2 can serve as potential therapeutic targets for WT.

CONCLUSIONS

Based on our analyses, we generated a ferroptosis-related lncRNA signature that can both estimate prognosis of WT patients and may provide basis for future WT therapy.

Development and validation of a ferroptosis-related lncRNAs prognosis signature in colon cancer

Ferroptosis is a form of iron-dependent programmed cell death. Regulation of ferroptosis in tumor cells is a novel treatment modality. The present study aimed to investigate ferroptosis-related long non-coding RNAs (lncRNAs) and construct a prognostic model for colon adenocarcinoma (COAD). RNA- sequencing data and ferroptosis-related genes were obtained from The Cancer Genome Atlas database and FerrDb database. COAD patients were randomly assigned to training- and validation groups. The Least Absolute Shrinkage and Selection Operator regression and Cox regression model were used to determine and develop a predictive model. The model was corroborated using the validation group and the entire group. In total, 259 ferroptosis-related genes and 905 ferroptosis-related LncRNAs were obtained. Cox model revealed and constructed seven ferroptosis-related LncRNAs signature (LINC01503, AC004687.1, AC010973.2, AP001189.3, ARRDC1-AS1, OIP5-AS1, and NCK1-DT). Patients were assigned into two groups according to the median risk score. Kaplan-Meier survival curves showed that overall survival between high- and low-risk groups was statistically significant (P<0.01). Cox multivariate analysis seven ferroptosis-related LncRNAs signature was an independent risk factor for COAD outcomes (P<0.05). The relationship between seven ferroptosis-related LncRNAs and clinicopathological features was also examined. The principal component analysis showed a difference between high- and low-risk groups intuitively. With the aid of gene set enrichment analysis, the underlying mechanisms of seven ferroptosis-related LncRNAs were uncovered, including the MAPK signaling pathway, mTOR signaling pathway, and glutathione metabolism pathway. Finally, we established and validated seven ferroptosis-related lncRNAs signature for COAD patients to predict survival. These results may provide meaningful targets for future study.

A Promising Esophageal Cancer Prognostic Signature of Ferroptosis-Related LncRNA to Predict Immune Scenery and Immunotherapy Response

Purpose

Ferroptosis and long non-coding RNA (lncRNA) expression signatures have been associated with the clinical progression and immune-contexture of different solid tumors. The study aimed to identify a prognostic signature of ferroptosis-related lncRNAs (falncRNAs) to forecast the immune scenery and immunotherapy response in esophageal cancer (EC).

Patients and Methods

Gene expression profiles of EC were extracted from The Cancer Genome Atlas (TCGA) database, and ferroptosis-related genes were downloaded from the FerrDb database, which identified differentially expressed falncRNAs (DEfalncRNAs) via differential analysis. DEfalncRNA pairs associated with prognosis were identified by constructing a matrix, univariate and least absolute shrinkage and selection operator (LASSO) analysis. The prognostic signature was constructed by multivariate analysis. We appraised the forecasting capability of prognostic signature in survival, clinicopathological features, immune landscape, efficacy of immunotherapy, and drug sensitivity. The potential molecular mechanism of signature was investigated by gene set enrichment analysis (GSEA).

Results

We obtained 18 DEfalncRNA pairs to define a novel prognostic signature that was determined on a discovery cohort of 158 tumor samples and 11 adjacent normal tissues from TCGA and internally validated, with the definition of high- vs low-risk groups based on 3 years overall survival. We demonstrated that the high- vs low-risk groups differed for clinical parameters and computationally predicted drug sensitivity and tumor immune contexture, with the high-risk group having worse survival, more aggressive disease (node involvement, metastasis), reduced drug sensitivity, higher tumor mutation load, and gene signatures of infiltration of pro-tumoral immune cell subsets. The GSEA results revealed that ferroptosis and immunoregulatory pathways were significantly enriched in the high-risk group.

Conclusion

The prognostic signature based on falncRNAs has the potential to forecast the survival, immune scenery, efficacy of immunotherapy, and drug sensitivity of EC, which is helpful for clinical prediction and individualized treatment.

Identification of seven novel ferroptosis-related long non-coding RNA signatures as a diagnostic biomarker for acute myeloid leukemia

Background

Ferroptosis is a newly discovered type of programmed cell death that participates in the biological processes of various cancers. However, the mechanism by which ferroptosis modulates acute myeloid leukemia (AML) remains unclear. This study aimed to investigate the role of ferroptosis-related long non-coding RNAs (lncRNAs) in AML and establish a corresponding prognostic model.

Methods

RNA-sequencing data and clinicopathological characteristics were obtained from The Cancer Genome Atlas database, and ferroptosis-related genes were obtained from the FerrDb database. The “limma” R package, Cox regression, and the least absolute shrinkage and selection operator were used to determine the ferroptosis-related lncRNA signature with the lowest Akaike information criteria (AIC). The risk score of ferroptosis-related lncRNAs was calculated and patients with AML were divided into high- and low-risk groups based on the median risk score. The Kaplan–Meier curve and Cox regression were used to evaluate the prognostic value of the risk score. Finally, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to explore the biological functions of the ferroptosis-related lncRNAs.

Results

Seven ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan–Meier and Cox regression analyses confirmed that risk scores were independent prognostic predictors of AML in both the training and validation groups (All P < 0.05). In addition, the area under the curve (AUC) analysis confirmed that the signatures had a good predictive ability for the prognosis of AML. GSEA and ssGSEA showed that the seven ferroptosis-related lncRNAs were related to glutathione metabolism and tumor immunity.

Conclusions

In this study, seven novel ferroptosis-related lncRNA signatures (AP001266.2, AC133961.1, AF064858.3, AC007383.2, AC008906.1, AC026771.1, and KIF26B-AS1) were established. These signatures were shown to accurately predict the prognosis of AML, which would provide new insights into strategies for the development of new AML therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01085-9.

Identification of a Novel Ferroptosis-Related Gene Prognostic Signature in Bladder Cancer

Background

Ferroptosis is a newly found non-apoptotic forms of cell death that plays an important role in tumors. However, the prognostic value of ferroptosis-related genes (FRG) in bladder cancer (BLCA) have not been well examined.

Methods

FRG data and clinical information were collected from The Cancer Genome Atlas (TCGA). Then, significantly different FRGs were investigated by functional enrichment analyses. The prognostic FRG signature was identified by univariate cox regression and least absolute shrinkage and selection operator (LASSO) analysis, which was validated in TCGA cohort and Gene Expression Omnibus (GEO) cohort. Subsequently, the nomogram integrating risk scores and clinical parameters were established and evaluated. Additionally, Gene Set Enrichment Analyses (GSEA) was performed to explore the potential molecular mechanisms underlying our prognostic FRG signature. Finally, the expression of three key FRGs was verified in clinical specimens.

Results

Thirty-two significantly different FRGs were identified from TCGA–BLCA cohort. Enrichment analyses showed that these genes were mainly related to the ferroptosis. Seven genes (TFRC, G6PD, SLC38A1, ZEB1, SCD, SRC, and PRDX6) were then identified to develop a prognostic signature. The Kaplan–Meier analysis confirmed the predictive value of the signature for overall survival (OS) in both TCGA and GEO cohort. A nomogram integrating age and risk scores was established and demonstrated high predictive accuracy, which was validated through calibration curves and receiver operating characteristic (ROC) curve [area under the curve (AUC) = 0.690]. GSEA showed that molecular alteration in the high- or low-risk group was closely associated with ferroptosis. Finally, experimental results confirmed the expression of SCD, SRC, and PRDX6 in BLCA.

Conclusion

Herein, we identified a novel FRG prognostic signature that maybe involved in BLCA. It showed high values in predicting OS, and targeting these FRGs may be an alternative for BLCA treatment. Further experimental studies are warranted to uncover the mechanisms that these FRGs mediate BLCA progression.

Comprehensive analyses of glycolysis-related lncRNAs for ovarian cancer patients

Background

Not only glycolysis but also lncRNAs play a significant role in the growth, proliferation, invasion and metastasis of of ovarian cancer (OC). However, researches about glycolysis -related lncRNAs (GRLs) remain unclear in OC. Herein, we first constructed a GRL-based risk model for patients with OC.

Methods

The processed RNA sequencing (RNA-seq) profiles with clinicopathological data were downloaded from TCGA and glycolysis-related genes (GRGs) were obtained from MSigDB. Pearson correlation coefficient between glycolysis-related genes (GRGs) and annotated lncRNAs (|r| > 0.4 and p < 0.05) were calculated to identify GRLs. After screening prognostic GRLs, a risk model based on five GRLs was constructed using Univariate and Cox regression. The identified risk model was validated by two validation sets. Further, the differences in clinicopathology, biological function, hypoxia score, immune microenvironment, immune checkpoint, immune checkpoint blockade, chemotherapy drug sensitivity, N6-methyladenosine (m6A) regulators, and ferroptosis-related genes between risk groups were explored by abundant algorithms. Finally, we established networks based on co-expression, ceRNA, cis and trans interaction.

Results

A total of 535 GRLs were gained and 35 GRLs with significant prognostic value were identified. The prognostic signature containing five GRLs was constructed and validated and can predict prognosis. The nomogram proved the accuracy of the model for predicting prognosis. After computing hypoxia score of each sample by ssGSEA, we found patients with higher risk scores exhibited higher hypoxia score and high hypoxia score was a risk factor. It was revealed that a total of 21 microenvironment cells (such as Central memory CD4 T cell, Neutrophil, Regulatory T cell and so on) and Stromal score had significant differences between the two groups. Four immune checkpoint genes (CD274, LAG3, VTCN1, and CD47) showed disparate expression levels in the two groups. Besides, 16 m6A regulators and 126 ferroptosis-related genes were expressed higher in the low-risk group. GSEA revealed that the risk groups were associated with tumor-related pathways. The two risk groups were confirmed to be sensitive to several chemotherapeutic agents and patients in the low-risk group were more sensitive to ICB therapy. The networks based on co-expression, ceRNA, cis and trans interaction provided insights into the regulatory mechanisms of GRLs.

Conclusions

Our identified and validated risk model based on five GRLs is an independent prognostic factor for OC patients. Through comprehensive analyses, findings of our study uncovered potential biomarker and therapeutic target for the risk model based on the GRLs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00881-2.

Ferroptosis Driver SOCS1 and Suppressor FTH1 Independently Correlate With M1 and M2 Macrophage Infiltration in Head and Neck Squamous Cell Carcinoma

Objective

To investigate the role of ferroptosis, an iron-dependent form of non-apoptotic cell death, in the head and neck squamous cell carcinoma (HNSCC) immune microenvironment.

Materials and Methods

A list of ferroptosis-related genes was obtained from the FerrDb database. Gene expression data were acquired from the cancer genome atlas (TCGA) and analyzed using the R language. Protein–protein interaction analysis was conducted using STRING and GeneMANIA. The correlations between gene expression levels and a patient’s survival were analyzed using GEPIA, the Kaplan–Meier estimate, and a multivariate Cox proportional hazards model. The expression results were verified using Oncomine and Human Protein Atlas data. We used the TIMER, GEPIA2, GEPIA2021, and TIMER2 databases to investigate the relationships between gene expression and infiltrating immune cells.

Results

Analysis of differentially expressed genes (DEGs) identified nine each ferroptosis drivers and ferroptosis suppressors, among which four genes correlated with survival as follows: two drivers (SOCS1, CDKN2A) associated with better survival and two suppressors (FTH1, CAV1) associated with poorer survival. Multivariate Cox survival analysis identified SOCS1 and FTH1 as independent prognostic factors for HNSCC, and their higher expression levels were verified using Oncomine and HPA data. The results acquired using TIMER, GEPIA2, GEPIA2021, and TIMER2 data revealed that the driver SOCS1 and the suppressor FTH1 independently correlated with M1 and M2 macrophage infiltration.

Conclusions

The ferroptosis driver SOCS1 and suppressor FTH1 are independent prognostic factors and that correlate with M1 and M2 macrophage infiltration in HNSCC. Targeting ferroptosis-immunomodulation may serve as a strategy to enhance the activity of immunotherapy.

Construction and analysis of a novel ferroptosis-related gene signature predicting prognosis in lung adenocarcinoma

Ferroptosis is a newly discovered, iron‐dependent, nonapoptotic form of programmed cell death that plays an important role in the development of lung adenocarcinoma (LUAD). In this study, ferroptosis‐related genes (FRGs) were identified from the FerrDb dataset, and the mRNA expression profiles and corresponding clinical data of LUAD patients were downloaded from the University of California, Santa Cruz (UCSC) databases. Data from LUAD patients from the Gene Expression Omnibus (GEO) dataset were used as the verification set. Cox and Lasso regression analyses were used to screen the FRGs with prognostic value, and six prognostic‐related FRGs were selected to construct prognostic risk score signatures. Immunohistochemistry was utilized to manifest the differential expression of six FRGs in tumor and normal tissues at the protein level. Functional enrichment analysis indicated that FRGs were mainly enriched in ferroptosis‐related pathways. Patients were divided into high‐ and low‐risk groups based on the median risk score. The Kaplan–Meier survival curves confirmed that patients with a high score had significantly worse overall survival. Receiver operating characteristic (ROC) curves proved that the prognostic signature has good sensitivity and specificity for predicting the prognosis of LUAD patients. Nomogram analysis showed that the prognostic signature has potential independent prognostic value. Moreover, the prognostic signature has been shown to be significantly associated with some clinical features (T stage, N stage, tumor stage, and survival status) as well as many immune‐activity‐related genes and immune‐checkpoint‐related genes. In conclusion, we constructed a prognostic signature consisting of six FGRs, which can provide a reference for predicting the prognosis of LUAD patients.

Construction on of a Ferroptosis-Related lncRNA-Based Model to Improve the Prognostic Evaluation of Gastric Cancer Patients Based on Bioinformatics

Background

Gastric cancer is one of the most serious gastrointestinal malignancies with bad prognosis. Ferroptosis is an iron-dependent form of programmed cell death, which may affect the prognosis of gastric cancer patients. Long non-coding RNAs (lncRNAs) can affect the prognosis of cancer through regulating the ferroptosis process, which could be potential overall survival (OS) prediction factors for gastric cancer.

Methods

Ferroptosis-related lncRNA expression profiles and the clinicopathological and OS information were collected from The Cancer Genome Atlas (TCGA) and the FerrDb database. The differentially expressed ferroptosis-related lncRNAs were screened with the DESeq2 method. Through co-expression analysis and functional annotation, we then identified the associations between ferroptosis-related lncRNAs and the OS rates for gastric cancer patients. Using Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) algorithm, we constructed a prognostic model based on 17 ferroptosis-related lncRNAs. We also evaluated the prognostic power of this model using Kaplan–Meier (K-M) survival curve analysis, receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA).

Results

A ferroptosis-related “lncRNA–mRNA” co-expression network was constructed. Functional annotation revealed that the FOXO and HIF-1 signaling pathways were dysregulated, which might control the prognosis of gastric cancer patients. Then, a ferroptosis-related gastric cancer prognostic signature model including 17 lncRNAs was constructed. Based on the RiskScore calculated using this model, the patients were divided into a High-Risk group and a low-risk group. The K-M survival curve analysis revealed that the higher the RiskScore, the worse is the obtained prognosis. The ROC curve analysis showed that the area under the ROC curve (AUC) of our model is 0.751, which was better than those of other published models. The multivariate Cox regression analysis results showed that the lncRNA signature is an independent risk factor for the OS rates. Finally, using nomogram and DCA, we also observed a preferable clinical practicality potential for prognosis prediction of gastric cancer patients.

Conclusion

Our prognostic signature model based on 17 ferroptosis-related lncRNAs may improve the overall survival prediction in gastric cancer.

Identification of ferroptosis-associated genes exhibiting altered expression in pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a life-threatening illness and ferroptosis is an iron-dependent form of regulated cell death, driven by the accumulation of lipid peroxides to levels that are sufficient to trigger cell death. However, only few studies have examined PAH-associated ferroptosis. In the present study, lung samples mRNA expression profiles (derived from 15 patients with PAH and 11 normal controls) were downloaded from a public database, and 514 differentially expressed genes (DEGs) were identified using the Wilcoxon rank-sum test and weighted gene correlation network analyses. These DEGs were screened for ferroptosis-associated genes using the FerrDb database: eight ferroptosis-associated genes were identified. Finally, the construction of gene-microRNA (miRNA) and gene-transcription factor (TF) networks, in conjunction with gene ontology and biological pathway enrichment analysis, were used to inform hypotheses regarding the molecular mechanisms underlying PAH-associated ferroptosis. Ferroptosis-associated genes were largely involved in oxidative stress responses and could be regulated by several identified miRNAs and TFs. This suggests the existence of modulatable pathways that are potentially involved in PAH-associated ferroptosis. Our findings provide novel directions for targeted therapy of PAH in regard to ferroptosis. These findings may ultimately help improve the therapeutic outcomes of PAH.

Integrative analysis of ferroptosis-related genes in ulcerative colitis

OBJECTIVE

The aim of this study was to identify and validate ferroptosis-related markers in ulcerative colitis (UC) to explore new directions for UC diagnosis and treatment.

METHODS

We screened UC chips and ferroptosis-related genes from the Gene Expression Omnibus (GEO), FerrDb, and GeneCards databases. The differentially expressed genes (DEGs) and ferroptosis-related DEGs between the UC group and normal controls were analyzed using bioinformatics methods. Enrichment analysis, protein-protein interaction analysis, and hub genes were screened. Peripheral blood chip and animal experiments were used to validate the ferroptosis-related hub genes. Finally, hub gene-transcription factor, hub gene-microRNA (miRNA), and hub gene-drug interaction networks were constructed.

RESULTS

Overall, 26 ferroptosis-related DEGs were identified that were significantly enriched in energy pathways and metabolism. We identified ten ferroptosis-related hub genes from the protein-protein interaction network: IL6, PTGS2, HIF1A, CD44, MUC1, CAV1, NOS2, CXCL2, SCD, and ACSL4. In the peripheral blood chip GSE94648, CD44 and MUC1 were upregulated, which was consistent with the expression trend in GSE75214. Animal experiments showed that CD44 expression was significantly increased in the colon.

CONCLUSIONS

Our findings indicate that CD44 and MUC1 may be ferroptosis-related markers in UC.

A Ferroptosis-Related Gene Model Predicts Prognosis and Immune Microenvironment for Cutaneous Melanoma

Background

Cutaneous melanoma is a common but aggressive tumor. Ferroptosis is a recently discovered cell death with important roles in tumor biology. Nevertheless, the prognostic power of ferroptosis-linked genes remained unclear in cutaneous melanoma.

Methods

Cutaneous melanoma patients of TCGA (The Cancer Genome Atlas) were taken as the training cohort while GSE65904 and GSE22153 as the validation cohorts. Multifactor Cox regression model was used to build a prognostic model, and the performance of the model was assessed. Functional enrichment and immune infiltration analysis were used to clarify the mechanisms.

Results

A five ferroptosis-linked gene predictive model was developed. ALOX5 and GCH1 were illustrated as independent predictive factors. Functional assessment showed enriched immune-linked cascades. Immune infiltrating analysis exhibited the distinct immune microenvironment.

Conclusion

Herein, a novel ferroptosis-related gene prognostic model was built in cutaneous melanoma. This model could be used for prognostic prediction, and maybe helpful for the targeted and immunotherapies.

Establishment of a ferroptosis-related gene signature for prognosis in lung adenocarcinoma patients

Objective

Lung cancer is the most common malignancy worldwide and exhibits both high morbidity and mortality. In recent years, scientists have made substantial breakthroughs in the early diagnosis and treatment of lung adenocarcinoma (LUAD), however, patient prognosis still shows vast individual differences. In this study, bioinformatics methods were used to identify and analyze ferroptosis-related genes to establish an effective signature for predicting prognosis in LUAD patients.

Methods

The gene expression profiles of LUAD patients with complete clinical and follow-up information were downloaded from two public databases, univariate Cox regression and multivariate Cox regression analysis were used to obtain ferroptosis-related genes for constructing the prognos tic risk model, AUC and calibration plot were used to evaluate the predictive accuracy of the FRGS and nomogram.

Results

A total of 74 ferroptosis-related differentially expressed genes (DEGs) were identi fied between LUAD and normal tissues from The Cancer Genome Atlas (TCGA) database. A five-gene panel for prediction of LUAD prognosis was established by multivariate regression and was verified using the GSE68465 cohort from the Gene Expression Omnibus (GEO) database. Patients were divided into two different risk groups according to the median risk score of the five genes. Based on Kaplan-Meier (KM) analysi, the OS rate of the high-risk group was markedly worse than that of the low-risk group. We also found that risk score was an independent prognostic indicator. The receiver operating characteristic ROC curve showed that the proposed model had good prediction ability. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses indicated that risk score was prominently enriched in ferroptosis processes. Moreover, at the score of immune-associated gene sets, significant differences were found between the two risk groups.

Conclusions

This study demonstrated that ferroptosis-related gene signatures can be used as a potential predictor for the prognosis of LUAD, thus providing a novel strategy for individualized treatment in LUAD patients.

Ferroptosis-Related Genes in Lung Adenocarcinoma: Prognostic Signature and Immune, Drug Resistance, Mutation Analysis

It is reported that ferroptosis has close relation with tumorigenesis and drug resistance. However, the clinical significance of ferroptosis in lung adenocarcinoma (LUAD) remains elusive, and the potential targets for ferroptosis-based treatment are limited. In this study, we constructed a 15-gene prognostic signature predicting overall survival based on ferroptosis-related genes (ferroptosis driver genes VDAC2, GLS2, FLT3, TLR4, PHKG2, phosphogluconate dehydrogenase (PGD), PANX1, KRAS, PEBP1, ALOX15, and ALOX12B, and suppressor genes ACSL3, CISD1, FANCD2, and SLC3A2) in The Cancer Genome Atlas (TCGA)-LUAD cohort. The signature’s predictive ability was validated in the GSE68465 and GSE72094 cohorts by survival analysis and independent prognostic analysis with clinical features. Nomograms were provided for clinical reference. Functional analysis revealed that ferroptosis was closely related to cell cycle, cell metabolism, and immune pathways. Pan-cancer analysis comprehensively analyzed these 15 genes in 33 cancer types, indicating that the heterogeneity of 15 genes was evident across different cancer types. Besides, these genes were critical regulators modulating drug resistance, tumor microenvironment infiltration, and cancer stemness. Then, we screened 10 genes (TLR4, PHKG2, PEBP1, GLS2, FLT3, ALOX15, ACSL3, CISD1, FANCD2, and SLC3A2) as potential targets for further research because their biological functions in ferroptosis were consistent with their prognostic significance. Somatic mutation and copy number variation analysis revealed that the alteration rates of KRAS, PGD, and ALOX15 were more than 1% and significantly associated with overall survival in LUAD. Moreover, the expression of KRAS and PGD was positively related to tumor mutation burden, indicating that KRAS and PGD could serve as novel biomarkers for predicting immunotherapy response rate. Our study identified and validated a ferroptosis-related gene signature for LUAD, provided a 10-gene set for future research, and screened KRAS and PGD as potential novel immunotherapy biomarkers.

Research Progress of Ferroptosis: A Bibliometrics and Visual Analysis Study

Background

Ferroptosis is a type of cell death with major topic of debate under current research and plays an important role in disease regulation.

Objective

In this study, the literature management software Bibexcel and knowledge graph tool VOSviewer were used to summarize and analyze the international research trends and hotspots about ferroptosis in recent years, which highlight the disease mechanism, diagnosis, and treatment related to ferroptosis. Material/Methods. The core collection database of Web of Science was used for retrieving ferroptosis research literature. The information such as the amount of text, the country, the period, the institution, the fund, and the keywords was extracted by the bibliometric tool Bibexcel. The cooccurrence and clustering function of VOSviewer were used to analyze the high-frequency keywords and the cooperative network of the author, institution, and country.

Results

The research of ferroptosis started late and was formally proposed in 2012. It has developed rapidly and presented an “exponential” growth trend. China, the United States, Germany, Japan, and France are the main national forces of ferroptosis research development. The United States and China have a relatively high degree of support and attention to ferroptosis. Exploring oxidative stress, inducers/inhibitors, synergistic antitumor effect, relationships with other cell death types, GSH/GPX4 and iron metabolism imbalance related mechanisms of ferroptosis, and ferroptosis in the nervous system disease, ischemia-reperfusion injury, tumor, inflammation, and age-related diseases are the hot research directions.

Conclusion

Ferroptosis has been a research hotspot in the field of biomedicine in recent years and has attracted the attention of scholars all over the world. The occurrence mechanism of ferroptosis and its application in neurological diseases, ischemia and reperfusion injury, tumors, inflammation, and aging are the hot directions of current research. In the future, ferroptosis can be appropriately considered for strengthening new approaches, new diseases, new inductors, new inhibitors, clinical transformation, and traditional medicine research.

Identification of Autophagy- and Ferroptosis-Related lncRNAs Functioned through Immune-Related Pathways in Head and Neck Squamous Carcinoma

The interplay between autophagy and ferroptosis has been highlighted as an important event to decide cancer cell fate. However, the underlying mechanisms remain largely unclear. In this study, we systematically explored the expression, prognostic value and functional roles of lncRNA in autophagy and ferroptosis. By a set of bioinformatics analyses, we identified 363 autophagy- and ferroptosis-related lncRNAs (AF-lncRNAs) and found 17 of them are dramatically related to the prognosis of head and neck squamous cell carcinoma (HNSC) patients, named as prognosis-related AF-lncRNAs (PAF-lncRNAs). Based on six key PAF-lncRNAs, a risk score model was developed and used to categorize the TCGA-retrieved HNSC patients into two groups (high-risk vs. low-risk). Functional analysis showed the differentially expressed genes (DEGs) between the two groups were mainly enriched in immune-related pathways and regulated by a PAF-lncRNA-directed ceRNA (competitive endogenous RNA) network. Combined with a variety of immune infiltration analyses, we also found a decreased landscape of immune cell infiltration in high-risk groups. Together, by revealing PAF-lncRNAs with tumor prognostic features functioned through immune-related pathways, our work would contribute to show the pathogenesis of a lncRNA-directed interplay among autophagy, ferroptosis and tumor immunity in HNSC and to develop potential prognostic biomarkers and targets for tumor immunotherapy.

Identification of Ferroptosis-Related Long Noncoding RNA and Construction of a Novel Prognostic Signature for Gastric Cancer

Background

Gastric cancer is the most common malignant tumor of the digestive system. It has a poor prognosis and is clinically challenging to treat. Ferroptosis is a newly defined mode of programmed cell death. The roles and prognostic value of ferroptosis-related long noncoding RNAs (lncRNAs) in gastric cancer remain unknown.

Results

In the current study, 20 ferroptosis-related lncRNAs were identified via univariate Cox analysis, least absolute shrinkage, and selection operator Cox regression analysis and used to construct a prognostic signature and classify gastric cancer patients into high-risk and low-risk groups. The signature was validated using TCGA training and testing cohorts. The risk signature was an independent prognostic indicator of survival and accurately predicted the prognoses of patients with gastric cancer. It was also associated with immune cell infiltration. Gene set enrichment analysis was used to investigate underlying mechanisms that the 20 ferroptosis-related lncRNAs were involved in. Chemosensitivity and immune checkpoint inhibitor analyses indicated that high-risk patients were more sensitive to the immune checkpoint inhibitor programmed cell death protein 1.

Conclusions

The important role of ferroptosis-related lncRNAs in immune infiltration identified in the current study may assist the determination of personalized prognoses and treatments in patients with gastric cancer. These 20 lncRNAs can be used as the diagnostic and prognostic markers for gastric cancer.

Ferroptosis-Related Gene Signature and Patterns of Immune Infiltration Predict the Overall Survival in Patients With Lung Adenocarcinoma

Background: Lung adenocarcinoma (LUAD) is a malignant tumor with high heterogeneity and poor prognosis. Ferroptosis, a form of regulated cell-death–related iron, has been proven to trigger inflammation-associated immunosuppression in the tumor microenvironment, which promotes tumor growth. Therefore, the clinical prognostic value of ferroptosis-related genes in LUAD needs to be further explored.

Method: In this study, we downloaded the mRNA expression profiles and corresponding clinical data of LUAD patients from the Cancer Genome Atlas database. The least absolute shrinkage and selection operator (LASSO) Cox regression model was utilized to construct ferroptosis-related gene signature. Based on these, we established the nomograms for prognosis prediction and validated the model in the GSE72094 dataset. The cell type was identified using the CIBERSORT algorithm for estimating relative subsets of RNA transcripts, which was then used to screen significant tumor immune-infiltrating cells associated with the LUAD prognosis prediction model. Subsequently, we applied co-expression analysis to reveal the relationship between ferroptosis-related genes and significant immune cells.

Results: The univariate COX regression analysis showed that 20 genes were associated with the overall survival (OS) as prognostic differentially expressed genes (DEGs) (FDR <0.05). Patients were divided into two risk groups using a 13-gene signature, with the high-risk group having a significantly worse OS than their low-risk counterparts (p < 0.001). We used receiver operating characteristic (ROC) curve analysis to confirm the predictive capacity of the signature. Besides, we identified seven pairs of ferroptosis-related genes and tumor-infiltrating immune cells associated with the prognosis of LUAD patients.

Conclusion: In this study, we construct a ferroptosis-related gene signature that can be used for prognostic prediction in LUAD. In addition, we reveal a potential connection between ferroptosis and tumor-infiltrating immune cells.

Tetrahydroxy stilbene glycoside ameliorates Alzheimer's disease in APP/PS1 mice via glutathione peroxidase related ferroptosis

Amyloid beta peptide (Aβ) has been confirmed to be an essential reason of Alzheimer's disease (AD) for a long time. Ferroptosis is a newly recognized oxidative cell death mechanism, which is highly related to AD. Recently, tetrahydroxy stilbene glycoside (TSG) has been beneficial in alleviating learning and memory of AD and aged mouse model. Unfortunately, the underlying mechanisms between TSG and ferroptosis in AD are poorly understood. Herein, we investigated whether neural cells in cerebral cortex and hippocampus that were seriously afflicted in APP/PS1 mice might be vulnerable to ferroptosis. Treatment with non-toxic TSG dose-dependently resisted Aβ-caused cytotoxic death in neuronal cells by regulating ferroptosis related proteins and enzymes in APP/PS1 mice. TSG also alleviated cellular oxidative stress and inflammatory damage in response to Aβ by attenuating the levels of oxidation products. Importantly, TSG administration abrogated Aβ-caused brain damage, indicating that TSG rescued brain cells. Subsequently, TSG promoted the activation of GSH/GPX4/ROS and Keap1/Nrf2/ARE signaling pathways. Notably, markers related to ferroptosis including increased lipid peroxidation, enhanced neuroinflammation such as NLRP3, and also the expression of DMT1, ACSL4 and NCOA4, were reduced by TSG administration. In addition, TSG enhanced antioxidative stress via the upregulation of SOD, and the expression of FTH1, CD98 and xCT. Taken together, our data indicated a novel mechanism of TSG in reversing Aβ-caused injury through restoring mitochondrial function via several signaling pathways, implying a promising candidate against neurodegenerative diseases especially AD. Hence, TSG should be taken into consideration during treatment of AD in the future.

Identification of a prognostic ferroptosis-related lncRNA signature in the tumor microenvironment of lung adenocarcinoma

Ferroptosis is closely linked to various cancers, including lung adenocarcinoma (LUAD); however, the factors involved in the regulation of ferroptosis-related genes are not well established. In this study, we identified and characterized ferroptosis-related long noncoding RNAs (lncRNAs) in LUAD. In particular, a coexpression network of ferroptosis-related mRNAs and lncRNAs from The Cancer Genome Atlas (TCGA) was constructed. Univariate and multivariate Cox proportional hazards analyses were performed to establish a prognostic ferroptosis-related lncRNA signature (FerRLSig). We obtained a prognostic risk model consisting of 10 ferroptosis-related lncRNAs: AL606489.1, AC106047.1, LINC02081, AC090559.1, AC026355.1, FAM83A-AS1, AL034397.3, AC092171.5, AC010980.2, and AC123595.1. High risk scores according to the FerRLSig were significantly associated with poor overall survival (hazard ratio (HR) = 1.412, 95% CI = 1.271–1.568; P < 0.001). Receiver operating characteristic (ROC) curves and a principal component analysis further supported the accuracy of the model. Next, a prognostic nomogram combining FerRLSig with clinical features was established and showed favorable predictive efficacy for survival risk stratification. In addition, gene set enrichment analysis (GSEA) revealed that FerRLSig is involved in many malignancy-associated immunoregulatory pathways. Based on the risk model, we found that the immune status and response to immunotherapy, chemotherapy, and targeted therapy differed significantly between the high-risk and low-risk groups. These results offer novel insights into the pathogenesis of LUAD, including the contribution of ferroptosis-related lncRNAs, and reveal a prognostic indicator with the potential to inform immunological research and treatment.

Primary Aldosteronism: Metabolic Reprogramming and the Pathogenesis of Aldosterone-Producing Adenomas

Simple Summary

Primary aldosteronism is a common form of endocrine hypertension often caused by a hyper-secreting tumor of the adrenal cortex called an aldosterone-producing adenoma. Metabolic reprogramming plays a role in tumor progression and influences the tumor immune microenvironment by limiting immune-cell infiltration and suppressing its anti-tumor function. We hypothesized that the development of aldosterone-producing adenomas involves metabolic adaptations of its component tumor cells and intrinsically influences tumor pathogenesis. Herein, we use state-of-the-art computational tools for the comprehensive analysis of array-based gene expression profiles to demonstrate metabolic reprogramming and remodeling of the immune microenvironment in aldosterone-producing adenomas compared with paired adjacent adrenal cortical tissue. Our findings suggest metabolic alterations may function in the pathogenesis of aldosterone-producing adenomas by conferring survival advantages to their component tumor cells.

Abstract

Aldosterone-producing adenomas (APAs) are characterized by aldosterone hypersecretion and deregulated adrenocortical cell growth. Increased energy consumption required to maintain cellular tumorigenic properties triggers metabolic alterations that shape the tumor microenvironment to acquire necessary nutrients, yet our knowledge of this adaptation in APAs is limited. Here, we investigated adrenocortical cell-intrinsic metabolism and the tumor immune microenvironment of APAs and their potential roles in mediating aldosterone production and growth of adrenocortical cells. Using multiple advanced bioinformatics methods, we analyzed gene expression datasets to generate distinct metabolic and immune cell profiles of APAs versus paired adjacent cortex. APAs displayed activation of lipid metabolism, especially fatty acid β-oxidation regulated by PPARα, and glycolysis. We identified an immunosuppressive microenvironment in APAs, with reduced infiltration of CD45⁺ immune cells compared with adjacent cortex, validated by CD45 immunohistochemistry (3.45-fold, p < 0.001). APAs also displayed an association of lipid metabolism with ferroptosis and upregulation of antioxidant systems. In conclusion, APAs exhibit metabolic reprogramming towards fatty acid β-oxidation and glycolysis. Increased lipid metabolism via PPARα may serve as a key mechanism to modulate lipid peroxidation, a hallmark of regulated cell death by ferroptosis. These findings highlight survival advantages for APA tumor cells with metabolic reprogramming properties.

Identification and Validation of a Ferroptosis-Related Long Non-coding RNA Signature for Predicting the Outcome of Lung Adenocarcinoma

BACKGROUND

Ferroptosis is a recently recognized type of programmed cell death that is involved in the biological processes of various cancers. However, the mechanism of ferroptosis in lung adenocarcinoma (LUAD) remains unclear. This study aimed to determine the role of ferroptosis-associated long non-coding RNAs (lncRNAs) in LUAD and to establish a prognostic model.

METHODS

We downloaded ferroptosis-related genes from the FerrDb database and RNA sequencing data and clinicopathological characteristics from The Cancer Genome Atlas. We randomly divided the data into training and validation sets. Ferroptosis-associated lncRNA signatures with the lowest Akaike information criteria were determined using COX regression analysis and the least absolute shrinkage and selection operator. The risk scores of ferroptosis-related lncRNAs were calculated, and patients with LUAD were assigned to high- and low-risk groups based on the median risk score. The prognostic value of the risk scores was evaluated using Kaplan-Meier curves, Cox regression analyses, and nomograms. We then explored relationships between ferroptosis-related lncRNAs and the immune response using gene set enrichment analysis (GSEA).

RESULTS

Ten ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan-Meier and Cox regression analyses confirmed that the risk scores were independent predictors of LUAD outcome in the training and validation sets (all P < 0.05). The area under the curve confirmed that the signatures could determine the prognosis of LUAD. The predictive accuracy of the established nomogram model was verified using the concordance index and calibration curve. The GSEA showed that the 10 ferroptosis-related lncRNAs might be associated with tumor immune response.

CONCLUSION

We established a novel signature involving 10 ferroptosis-related lncRNAs (LINC01843, MIR193BHG, AC091185.1, AC027031.2, AL021707.2, AL031667.3, AL606834.1, AC026355.1, AC124045.1, and AC025048.4) that can accurately predict the outcome of LUAD and are associated with the immune response. This will provide new insights into the development of new therapies for LUAD.

Role of ferroptosis-related genes in prognostic prediction and tumor immune microenvironment in colorectal carcinoma

Background and Aim

Colorectal cancer (CRC) ranks the second most common cause of cancer-related mortality worldwide. Ferroptosis, a recently discovered form of programmed cell death different from other, raises promising novel opportunities for therapeutic intervention of CRC. This study intended to systematically assess the prognosis value and multiple roles of the ferroptosis-related genes in the tumor immune microenvironment of CRC.

Materials and Methods

Of 1,192 CRC patients with complete information from the public datasets (TCGA CRC, GEO GSE39582 and GSE17538 cohorts) were selected for analysis. Firstly, K-means consensus clustering was performed to identify ferroptosis-associated subtypes in CRC patients. Subsequently, we constructed a risk signature based on ferroptosis-related genes in TCGA cohort and acquired its validation in two GEO cohorts. Additionally, we established a nomogram integrating the risk signature and clinical factors to improve risk assessment of CRC patients.

Results

Five molecular subtypes were identified by consensus clustering for ferroptosis-related genes. There were significant differences in the overall survival, immune cells infiltration status and PD1/PD-L1 mRNA among the five clusters. Then, a risk signature based on the ten-gene was constructed which could distinguish effectively high-risk group among CRC patients in both training and validation sets. The high-risk patients were more likely to have an inhibitory immune microenvironment and lower stemness features. A prognostic nomogram integrated risk signature and clinicopathological features could be used as a more accurate prognostic prediction visualization tool than TNM stage alone.

Conclusion

This ferroptosis risk signature may accurately differentiate between different risk populations and predict the prognosis of CRC. Besides, this study elucidated the crucial role of ferroptosis in tumor immune microenvironment.

Development and Validation of a Ferroptosis-Related Gene Signature for Overall Survival Prediction in Lung Adenocarcinoma

Background: Ferroptosis is an iron-dependent programmed cell death process. Recent studies have found that ferroptosis inducers hold promising potential in the treatment of lung adenocarcinoma (LUAD). However, the comprehensive analysis about the prognostic value of ferroptosis-related genes in LUAD remains to be elucidated. Methods: The RNA sequencing data and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A total of 259 ferroptosis-related genes were extracted from FerrDb website. The ferroptosis-related prognostic signature was developed by least absolute shrinkage and selection operator (LASSO) Cox regression analysis in TCGA LUAD cohort, and then validated by 5 independent GEO cohorts. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) were performed to identify the difference in biological processes and functions between different risk groups. The expression levels of core prognostic genes were then verified in LUAD samples by immunohistochemistry (IHC) and erastin-treated LUAD cell lines by real-time polymerase chain reaction (PCR). The potential roles of GPX2 and DDIT4 as ferroptosis drivers in LUAD cell line were further confirmed by in vitro experiments. Results: A total of 20 intersecting genes between 70 ferroptosis-related DEGs and 45 potential prognostic genes were obtained for LASSO Cox regression analysis. The ferroptosis-related prognostic signature was developed by 7 core prognostic DEGs, and stratified LUAD patients into two risk groups. Kaplan-Meier analysis showed that the overall survival (OS) of LUAD patients in the high-risk group was significantly worse than that of the low-risk group. External validation of 5 independent GEO cohorts further confirmed that the ferroptosis-related prognostic signature was an ideal biomarker for predicting the survival of LUAD patients. Significant enrichment of fatty acid metabolism and cell cycle-related pathways were found in different risk groups. The expression patterns of 7 core prognostic genes in LUAD and adjacent normal lung tissues were validated by IHC, which was almost consistent with the results from public database. Furthermore, the changes related to cell cycle and ferroptosis after erastin treatment were also validated in LUAD cell lines. In addition, silencing GPX2 or DDIT4 could partially reverse the erastin-induced ferroptosis. Conclusion: In summary, the ferroptosis-related prognostic signature based on 7 core prognostic DEGs indicated superior predictive performance of LUAD patients. Targeting ferroptosis holds potential to be a therapeutic alternative for LUAD.