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Bioinformatics Analysis Identifies Potential Ferroptosis Key Genes in the Pathogenesis of Pulmonary Fibrosis.

ABSTRACT: Objective: Ferroptosis has an important role in developing pulmonary fibrosis. The present project aimed to identify and validate the potential ferroptosis-related genes in pulmonary fibrosis by bioinformatics analyses and experiments. Methods: First, the pulmonary fibrosis tissue sequencing data were obtained from Gene Expression Omnibus (GEO) and FerrDb databases. Bioinformatics methods were used to analyze the differentially expressed genes (DEGs) between the normal control group and the pulmonary fibrosis group and extract ferroptosis-related DEGs. Hub genes were screened by enrichment analysis, protein-protein interaction (PPI) analysis, and random forest algorithm. Finally, mouse pulmonary fibrosis model was made for performing an exercise intervention and the hub genes' expression was verified through qRT-PCR. Results: 13 up-regulated genes and 7 down-regulated genes were identified as ferroptosis-related DEGs by comparing 103 lung tissues with idiopathic pulmonary fibrosis (IPF) and 103 normal lung tissues. PPI results indicated the interactions among these ferroptosis-related genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway enrichment and Genome-Ontology (GO) enrichment analyses showed that these ferroptosis-related genes involved in the organic anion transport, response to hypoxia, response to decrease oxygen level, HIF-1 signaling pathway, renal cell carcinoma, and arachidonic acid metabolism signaling pathway. The confirmed genes using PPI analysis and random forest algorithm included CAV1, NOS2, GDF15, HNF4A, and CDKN2A. qRT-PCR of the fibrotic lung tissues from the mouse model showed that the mRNA levels of NOS2 and GDF15 were up-regulated, while CAV1 and CDKN2A were down-regulated. Also, treadmill training led to an increased expression of CAV1 and CDKN2A and a decrease in the expression of NOS2 and GDF15. Conclusion: Using bioinformatics analysis, 20 potential genes were identified to be associated with ferroptosis in pulmonary fibrosis. CAV1, NOS2, GDF15, and CDKN2A were demonstrated to be influencing the development of pulmonary fibrosis by regulating ferroptosis. These findings suggested that, as an aerobic exercise treatment, treadmill training reduced ferroptosis in the pulmonary fibrosis tissues, and thus, reduces inflammation in the lungs. Aerobic exercise training initiate concomitantly with induction of pulmonary fibrosis reduces ferroptosis in lung. These results may develop our knowledge about pulmonary fibrosis and may contribute to its treatment.

SUBMITTER: He J

PROVIDER: S-EPMC8770739 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Objective: Ferroptosis is a type of cell death involved in various human diseases, including nerve injury. However, the role of ferroptosis in lumbosacral spinal root avulsion (LSRA) remains unknown. This study aims to investigate whether ferroptosis is induced after LSRA and the key ferroptosis-related genes and their potential function in LSRA. Methods: The biochemical and morphological changes of ferroptosis were determined by detection of iron accumulation and by transmission electron microscopy in a rat LSRA model. The transcriptional expression profile following LSRA was investigated by RNA sequencing and ferroptosis-related genes were downloaded from FerrDb and used to identify ferroptosis differentially expressed genes (DEGs). The differential expressions of ferroptosis DEGs were confirmed by qRT-PCR analysis. The potential functions of ferroptosis DEGs were revealed by DAVID 6.8 and WebGestalt. A protein-protein interaction (PPI) network and gene-miRNA interaction network were further constructed to identify key modules in ferroptosis DEGs, and the results were verified by qRT-PCR and western blot analysis. Results: LSRA was followed by ferroptosis-specific changes, such as shrunken mitochondria and increased iron accumulation, that can be alleviated by ferroptosis inhibitor deferoxamine (DFO). A total of 2,446 DEGs and 46 ferroptosis DEGs were identified after LSRA, and over 90% of the ferroptosis DEGs were confirmed to be differentially expressed following LSRA, which can also be eliminated by DFO treatment. Functional analysis demonstrated significant enrichment of the ferroptosis DEGs in pathways related to the oxidative stress response, the HIF-1 signaling pathway, and the tumor necrosis factor signaling pathway. PPI network analysis demonstrated that a set of key modules in ferroptosis DEGs were related to the HIF-1 signaling pathway: Il6, Nos2, Stat3, Hif1a, Vegfa, Cdkn1a, and Rela. Construction of a gene-miRNA network predicted miRNAs targeting four key ferroptosis DEGs-Stat3, Hif1a, Vegfa, and Rela, and further western blot analysis confirmed their upregulation after LSRA, which can be alleviated by DFO pretreatment. Conclusion: The data revealed the induction of ferroptosis in a rat LSRA model and identified possible regulatory roles for ferroptosis-related genes in the molecular mechanisms of LSRA, which provides new insights into the pathogenesis and helps to find new molecular targets for the treatment of LSRA.

Project description:Melanoma is the deadliest skin tumor and is prone to distant metastases. The incidence of melanoma has increased rapidly in the past few decades, and current trends indicate that this growth is continuing. This study was aimed to explore the molecular mechanisms of melanoma pathogenesis and discover underlying pathways and genes associated with melanoma. We used high-throughput expression data to study differential expression profiles of related genes in melanoma. The differentially expressed genes (DEGs) of melanoma in GSE15605, GSE46517, GSE7553, and the Cancer Genome Atlas (TCGA) datasets were analyzed. Differentially expressed genes (DEGs) were identified by paired t-test. Then the DEGs were performed cluster and principal component analyses and protein-protein interaction (PPI) network construction. After that, we analyzed the differential genes through bioinformatics and got hub genes. Finally, the expression of hub genes was confirmed in the TCGA databases and collected patient tissue samples. Total 144 up-regulated DEGs and 16 down-regulated DEGs were identified. A total of 17 gene ontology analysis (GO) terms and 11 pathways were closely related to melanoma. Pathway of pathways in cancer was enriched in 8 DEGs, such as junction plakoglobin (JUP) and epidermal growth factor receptor (EGFR). In the PPI networks, 9 hub genes were obtained, such as loricrin (LOR), filaggrin (FLG), keratin 5 (KRT5), corneodesmosin (CDSN), desmoglein 1 (DSG1), desmoglein 3 (DSG3), keratin 1 (KRT1), involucrin (IVL), and EGFR. The pathway of pathways in cancer and its enriched DEGs may play important roles in the process of melanoma. The hub genes of DEGs may become promising melanoma candidate genes. Five key genes FLG, DSG1, DSG3, IVL, and EGFR were identified in the TCGA database and melanoma tissues. The results suggested that FLG, DSG1, DSG3, IVL, and EGFR might play important roles and potentially be valuable in the prognosis and treatment of melanoma. These hub genes might well have clinical significance as diagnostic markers.

Project description:BackgroundIntrauterine growth retardation (IUGR) affects approximately 10% to 15% of all pregnancies worldwide. IUGR is not only associated with stillbirth and newborn death, but also the delay of cognition in childhood and the promotion of metabolic and vascular disorders in adulthood. Figuring out the mechanism of IUGR is rather meaningful and valuable.MethodsDatasets related to IUGR were searched in the Gene Expression Omnibus website. Principal component analysis (PCA) was used for normalization. Differential expressed genes (DEGs) were screened out using the ggpot2 tool. DEGs were used to conduct Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analyses, and protein-protein interaction (PPI) analysis. IUGR related genes were searched in the OMIM website to look for the intersection with the DEGs. The DEGs were analyzed for tissue-specific expression by the online resource BioGPS. The results were displayed through volcano map, Venn map, box plot, heat map, and GSEA enrichment plots drawn by R language packages.ResultsEleven DEGs were screened out of 2 datasets. One hundred ninety-five genes related to IUGR in OMIM were retrieved. EGR2 was the only intersection gene that was found in both groups. Genes associated with placental tissue expression include COL17A1, HSD11B1, and LGALS14. Molecular functions of the DEGs are related to the oxidoreductase activity. The following 4 signaling pathways, reactome signaling by interleukins, reactome collagen degradation, Naba secreted factors, and PID NFAT tfpathway, were enriched by GSEA. Two critical modules comprising 5 up-regulated genes (LEP, PRL, TAC3, MMP14, and ADAMTS4) and 4 down-regulated genes (TIMP4, FOS, CCK, and KISS1) were identified by PPI analysis. Finally, we identified 6 genes (PRL, LGALS14, EGR2, TAC3, LEP, and KISS1) that are potentially relevant to the pathophysiology of IUGR.ConclusionThe candidate down-regulated genes LGALS14 and KISS1, as well as the up-regulated genes PRL, EGR2, TAC3, and LEP, were found to be closely related to IUGR by bioinformatics analysis. These hub genes are related to hypoxia and oxidoreductase activities in placental development. We provide useful and novel information to explore the potential mechanism of IUGR and make efforts to the prevention of IUGR.

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Bioinformatics Analysis Identifies Potential Ferroptosis Key Genes in the Pathogenesis of Pulmonary Fibrosis.

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