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Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis.

ABSTRACT: Background: In order to reveal the functions of ferroptosis in prostate cancer (PCa), a ferroptosis potential index (FPI) was built. This study researched the influence of ferroptosis on gene mutations, various cellular signaling pathways, biochemical recurrence (BCR), and drug resistance in both FPI-high and FPI-low groups. Methods: RNA-seq, somatic mutation data, and clinical data were obtained from The Cancer Genome Atlas (TCGA). FPI values were calculated. All samples were divided into FPI-high and FPI-low groups. The BCR-free survival rate, tumor mutation burden (TMB) value, cellular signaling pathway, differentially expressed genes (DEGs), and drug resistance in the two FPI groups were identified. Human PCa cells, LNCaP, were treated with ferroptosis inducer erastin or inhibitor ferrostatin-1. The expression of hub genes was detected by qRT-PCR and Western blot. Results: A high FPI level was significantly related to poor BCR-free survival. Also, higher TMB value was found in the FPI-high group, and FPI was shown to be associated with gene mutations. Then, genes in both groups were revealed to be enriched in different pathways. A total of 310 DEGs were identified to be involved in muscle system processes and neuroactive ligand-receptor interactions. A total of 101 genes were found to be related to BCR-free survival, and a protein-protein interaction (PPI) network was constructed. Two sub-modules were identified by MCODE, and eight hub genes were screened out, among which SYT4 had higher expression levels and poorer BCR-free survival in the FPI-high group, while the remaining hub genes had lower expression levels and poorer BCR-free survival. Drug sensitivity was revealed to be different in the two groups by study on the IC₅₀ data of different molecules and ferroptosis regulator gene (FRG) expressions. Finally, erastin increased the expression of SYT4 in LNCaP and decreased the expression of the other four genes (ACTC1, ACTA1, ACTN2, and MYH6), while ferrostatin-1 led to the opposite results. The molecular experimental results were consistent with those of bioinformatics analysis, except TNNI1, TNNC2, and NRAP. Conclusion: The current research depicted the ferroptosis level and FRGs in PCa. Ferroptosis was related to TMB value, BCR-free survival, and drug resistance. This study will be beneficial to further research studies on ferroptosis-related molecular mechanisms.

SUBMITTER: Wo Q

PROVIDER: S-EPMC9289098 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeFerroptosis plays a crucial role in the development and progression of abdominal aortic aneurysm (AAA). The aim of this study was to identify differentially expressed genes associated with ferroptosis in AAA through bioinformatics analysis combined with experimental validation.Materials and methodsFirstly, the mRNA expression profile datasets GSE57691 and GSE47472 from Gene Expression Omnibus database were screened, and principal component analysis was carried out. Next, the R software (version 4.0.0) was used to analyze potentially differentially expressed genes associated with AAA and ferroptosis. Subsequently, protein-protein interaction analysis, gene ontology enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed on the selected candidate genes. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of the first five selected abnormal ferroptosis-related genes in clinical samples obtained from patients with AAA and healthy controls.ResultsBased on the information contained in the two datasets, a total of 20 differentially expressed ferroptosis-related genes (three upregulated genes and 17 downregulated genes) were selected. Protein-protein interaction analysis demonstrated interaction between these genes, while gene ontology enrichment analysis of ferroptosis genes with differential expression indicated that some enrichment items were associated with oxidative stress. The qRT-PCR results showed that the expression levels of interleukin-6 (IL-6), peroxiredoxin 1 (PRDX1), and stearoyl-CoA desaturase (SCD) were consistent with the bioinformatics prediction results obtained from the mRNA chip.ConclusionBioinformatics analysis identified 20 potential ferroptosis-related differentially expressed genes in AAA. Further verification by qRT-PCR showed that IL-6, PRXD1, and SCD might affect the process of AAA by regulating ferroptosis. Our results might assist in further understanding the pathogenesis of AAA and guiding treatment.

Project description:The underlying causes of esophageal cancer (EC) are unknown. To explore the molecular mechanisms that lead to EC, gene expression profiles of large cohorts of patients with EC were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus (GEO) databases (GSE5364, GSE20347 and GSE23400). The present study identified 83 upregulated and 22 downregulated genes between EC and normal tissue using R statistical software and the GEO2R web tool. The Database for Annotation, Visualization and Integrated Discovery was used to identify the associated pathways, and for functional annotation of the differentially expressed genes (DEGs). Protein-protein interactions of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database, and hub genes were visualized using Cytoscape software. An online Kaplan-Meier plotter survival analysis tool was utilized to evaluate the prognostic value of hub gene expression in patients with EC. Further analysis of an additional dataset from GEO (GSE21293) revealed that these genes were associated with infiltration and metastasis in EC. In addition, the Gene Expression Profiling Interactive Analysis tool was used to evaluate expression levels of hub genes in patients with EC for different pathological stages. The Ualcan analysis tool was used to evaluate the expression levels of hub genes for different histological types. Overall, ubiquitin conjugating enzyme E2 C, cyclin dependent kinase inhibitor 3, CDC28 protein kinase regulatory subunit 2, kinesin family member 20A (KIF20A) and RAD51 associated protein 1 (RAD51AP1) were upregulated in EC tissues compared with normal tissues, and upregulation of these genes was a poor prognostic factor for patients with EC, indicating that these genes may mediate EC cell infiltration and metastasis. Among the hub genes, KIF-20A had potential value for predicting the pathological stage of EC. KIF20A and RAD51AP1 were more informative biomarkers of esophageal squamous cell carcinoma. Further studies are required to explore the value of these genes in the treatment of EC.

Project description:Colorectal cancer (CRC) is a prevalent malignant tumour type arising from the colon and rectum. The present study aimed to explore the molecular mechanisms of the development and progression of CRC. Initially, differentially expressed genes (DEGs) between CRC tissues and corresponding non-cancerous tissues were obtained by analysing the GSE15781 microarray dataset. The Database for Annotation, Visualization and Integrated Discovery was then utilized for functional and pathway enrichment analysis of the DEGs. Subsequently, a protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes and Proteins database and visualized by Cytoscape software. Furthermore, CytoNCA, a Cytoscape plugin, was used for centrality analysis of the PPI network to identify crucial genes. Finally, UALCAN was employed to validate the expression of the crucial genes and to estimate their effect on the survival of patients with colon cancer by Kaplan-Meier curves and log-rank tests. A total of 1,085 DEGs, including 496 upregulated and 589 downregulated genes, were screened out. The DEGs identified were enriched in various pathways, including 'metabolic pathway', 'cell cycle', 'DNA replication', 'nitrogen metabolism', 'p53 signalling' and 'fatty acid degradation'. PPI network analysis suggested that interleukin-6, MYC, NOTCH1, inhibin subunit βA (INHBA), CDK1, cyclin (CCN)B1 and CCNA2 were crucial genes, and their expression levels were markedly upregulated. Survival analysis suggested that upregulated INHBA significantly decreased the survival probability of patients with CRC. Conversely, upregulation of CCNB1 and CCNA2 expression levels were associated with increased survival probabalities. The identified DEGs, particularly the crucial genes, may enhance the current understanding of the genesis and progression of CRC, and certain genes, including INHBA, CCNB1 and CCNA2, may be candidate diagnostic and prognostic markers, as well as targets for the treatment of CRC.

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Identification of Ferroptosis-Associated Genes in Prostate Cancer by Bioinformatics Analysis.

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