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. 2022 Nov 10:9:1010918.
doi: 10.3389/fnut.2022.1010918. eCollection 2022.

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

Yinjiang Zhang  1   2 , Yashuo Zhang  1   2 , Rongfei Yao  1   2 , Xu He  1   2 , Linyi Zhao  1   2 , Xiangyu Zuo  1   2 , Binan Lu  1   2 , Zongran Pang  1   2
Affiliations

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

Yinjiang Zhang et al. Front Nutr. .

Abstract

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

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

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

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

Keywords: biomarkers; ferroptosis; immune microenvironment; ischemic stroke; subtypes.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Workflow chart. DEGs, differentially expressed genes; TFs, transcriptional factors.
FIGURE 2
FIGURE 2
GSE16561 data set preprocessing. Box plot showing the gene expression level between different samples before (A) and after (B) normalization. 2D and 3D PCA plots demonstrated the distribution of samples before (C,D) and after (E,F) pretreatment. PCA, principal components analysis.
FIGURE 3
FIGURE 3
Analysis of differentially expressed genes. (A) Screening of DEGs shown by volcano plot. (B) Heatmap of the 40 genes expressed differently in IS samples compared to normal samples. (C) Venn diagram showing 21 ferroptosis-related DEGs. (D) Circle diagram showing the correlation of 21 ferroptosis-related DEGs. (E,F) 2D and 3D PCA plots showing PCA analysis based on 21 ferroptosis-related genes in GSE16561. (G,H) 2D and 3D PCA plots showing PCA analysis based on 21 ferroptosis-related genes in GSE37587. DEGs, differentially expressed genes; IS, ischemic stroke; PCA, principal components analysis.
FIGURE 4
FIGURE 4
Enrichment analysis. Box plot described the expression pattern of the 21 ferroptosis-related genes between IS and normal samples in GSE16561 (A) and GSE37587 (B). (C) 21 ferroptosis-related genes enrichment analysis. IS, ischemic stroke. *p < 0.05, **p < 0.01, and ***p < 0.001.
FIGURE 5
FIGURE 5
Clinical correlation analysis. Box plot showing the expression pattern of the 21 ferroptosis-related genes between <78 and ≥78 patients in GSE16561 (A) and GSE37587 (B). Box plot showing the expression pattern of the 21 ferroptosis-related genes between male and female patients in GSE16561 (C) and GSE37587 (D). ns: p ≥ 0.05, *p < 0.05, **p < 0.01, and ***p < 0.001.
FIGURE 6
FIGURE 6
ROC analysis. Diagnostic ROC analysis of 21 ferroptosis-related genes in GSE16561 (A–C) and GSE37587 (D–F). ROC, receiver operating characteristic; AUC, area under curve; FPR, false positive rate; TPR, true positive rate.
FIGURE 7
FIGURE 7
Hub gene analysis. (A) Based on the 21 ferroptosis-related genes, a PPI network was generated based on the STRING online database. (B) Hub genes were analyzed using the plug-in cytoNCA. (C) The top 11 hub genes were identified by calculating the betweenness, closeness, and degree. (D) Enrichment analysis of 11 hub genes by GeneMANIA online database.
FIGURE 8
FIGURE 8
Unsupervised clustering of 11 hub genes. (A) Consensus matrix heatmap when k = 2. (B) Tracking plot showing the sample classification when k = 2–10. (C) PCA plots showing a remarkable difference in transcriptome between two subtypes. (D) Heatmap showing the expression of 11 hub genes in two subtypes. (E) Age ratio distribution in the two subtypes. (F) Gender ratio distribution in the two subtypes. PCA, principal components analysis.
FIGURE 9
FIGURE 9
The features of the immunological microenvironment differ between subtypes. Box plots showing that there were differences in hub genes (A), immune checkpoints (B), HLA genes (C), and immune cell infiltration (D) between the two subtypes. *p < 0.05, **p < 0.01, and ***p < 0.001.
FIGURE 10
FIGURE 10
Functional analysis between two different subtypes. The DEGs were shown by volcano plot (A) and heat map (B) between two subtypes. (C) GO enrichment analysis was performed on the DEGs. GO terms are represented on the y-axis, gene ratios are shown on the x-axis, circle sizes refer to gene numbers, and colors represent p-values. (D) GO enrichment analysis of the DEGs. Different colors represent various significant GO terms and related enriched genes. (E) KEGG pathway analysis was performed on the DEGs. The y-axis represents different pathways, gene ratios enriched in relative pathways by the x-axis, circles represent gene numbers, and colors represent p-values. (F) KEGG pathway analysis of the DEGs. Different colors represent various significant pathways and related enriched genes. DEGs, differentially expressed genes; KEGG, Kyoto Encyclopedia of Genes and Genomes; GO, Gene Ontology.
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