Systems biology analysis of lung fibrosis-related genes in the bleomycin mouse model

Toren, Dmitri; Yanai, Hagai; Taha, Reem Abu; Bunu, Gabriela; Ursu, Eugen; Ziesche, Rolf; Tăcutu, Robi; Fraifeld, Vadim E.

doi:10.1038/s41598-021-98674-6

Cited by 9 publications

(7 citation statements)

References 44 publications

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“…Notably, KL (Klotho) gene, which is a pro-longevity gene, was found to be overexpressed in healthy control lung tissues in our study. Consistently, (Toren et al, 2021) also demonstrated that KL is a pro-longevity and anti-fibrotic gene. However, other genes screened in our bioinformatic analysis were not mentioned in the study by Toren et al This discrepancy could be due to the differences in the study design and aims of the two studies.…”

Section: Discussionmentioning

confidence: 60%

“…These results support the findings of our bioinformatic analysis and suggest that IGFBP2 may be a promising biomarker of IPF. Moreover, Toren et al (2021) investigated the relationship between lung fibrosis-related and longevity-associated genes in a mouse model of bleomycin-induced fibrosis; they highlighted age as an important risk factor for pulmonary fibrosis and found that pro-longevity genes tended to be related to anti-fibrosis. Our results are partially consistent with these findings.…”

Section: Discussionmentioning

confidence: 99%

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Identification and Validation of Aging-Related Genes in Idiopathic Pulmonary Fibrosis

2022

Front. Genet.

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Aging plays a significant role in the occurrence and development of idiopathic pulmonary fibrosis (IPF). In this study, we aimed to identify and verify potential aging-associated genes involved in IPF using bioinformatic analysis. The mRNA expression profile dataset GSE150910 available in the Gene Expression Omnibus (GEO) database and R software were used to identify the differentially expressed aging-related genes involved in IPF. Hub gene expression was validated by other GEO datasets. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on differentially expressed aging-related genes. Subsequently, aging-related genes were further screened using three techniques (least absolute shrinkage and selection operator (LASSO) regression, support vector machine, and random forest), and the receiver operating characteristic curves were plotted based on screening results. Finally, real-time quantitative polymerase chain reaction (qRT-PCR) was performed to verify the RNA expression of the six differentially expressed aging-related genes using the blood samples of patients with IPF and healthy individuals. Sixteen differentially expressed aging-related genes were detected, of which the expression of 12 were upregulated and four were downregulated. GO and KEGG enrichment analyses indicated the presence of several enriched terms related to senescence and apoptotic mitochondrial changes. Further screening by LASSO regression, support vector machine, and random forest identified six genes (IGF1, RET, IGFBP2, CDKN2A, JUN, and TFAP2A) that could serve as potential diagnostic biomarkers for IPF. Furthermore, qRT-PCR analysis indicated that among the above-mentioned six aging-related genes, only the expression levels of IGF1, RET, and IGFBP2 in patients with IPF and healthy individuals were consistent with the results of bioinformatic analysis. In conclusion, bioinformatics analysis identified 16 potential aging-related genes associated with IPF, and clinical sample validation suggested that among these, IGF1, RET, and IGFBP2 might play a role in the incidence and prognosis of IPF. Our findings may help understand the pathogenesis of IPF.

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Section: Discussionmentioning

confidence: 60%

Section: Discussionmentioning

confidence: 99%

Identification and Validation of Aging-Related Genes in Idiopathic Pulmonary Fibrosis

2022

Front. Genet.

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“…Toren et al found that longevity gene can resist IPF gene through animal experiments, and con rmed that age is an important risk factor for IPF [55].…”

Section: Discussionmentioning

confidence: 99%

Construction and evaluation of prognostic model of genes related to cell burial in idiopathic pulmonary fibrosis (IPF)

Sun

Zhang

et al. 2023

Preprint

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Background Idiopathic pulmonary fibrosis (IPF) is a complex lung disease. Efferocytosis was related to IPF initiation and progression. The study aimed to mine efferocytosis-related genes (ECRGs) and establish corresponding prognostic signature in IPF. Methods Differentially expressed ECRGs (DEECRGs) were obtained by overlapping differentially expressed genes (DEGs) between IPF and normal samples and ECRGs. Univariate COX and the least absolute shrinkage and selection operator (LASSO) regression were applied to construct a risk model. The model was evaluated by Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curves. Multivariate Cox model was performed, nomogram was further constructed. Moreover, gene set variation analysis (GSVA) and immune infiltration of two risk groups were explored. Last, the study evaluated the predictive power of EC-related model genes in both GSE70866 training dataset and GSE10667 validation dataset. Results A risk model was constructed with 5 ECRGs (CXCR4, ODC1, AXL, DOCK5 and MERTK). K-M analysis showed IPF patients in high risk group performed noteworthy poorer survival than those in low risk group. ROC curves indicated good performance of the risk model. GSVA illustrated that biological processes of diacyl bacterial lipopeptide and amino acid betaine biosynthetic process, and KEGG pathways of clycosaminoglycan biosynthesis chondroitin sulfate and butanoate metabolism signaling pathway were significantly different in two risk groups. Immune infiltration analysis showed that there were significant differential immune cells(Mast cells, naive B cells, actiated NK cells, M0 Macrophages, resting Dendritic cell and resting Mast cell)in two risk groups. Conclusions A risk model consisting of 5 ECRGs (CXCR4, ODC1, AXL, DOCK5 and MERTK) was successfully constructed, which could provide a new idea for the prognosis of IPF.

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“…The mouse bleomycin-induced fibrosis model is generally viewed as the standard in modeling pulmonary fibrosis (Jenkins et al, 2017). Recent studies revealed that genes related to the mouse bleomycin-induced fibrosis model and human IPF have much in common (Bauer et al, 2015;Toren et al, 2021). Interleukin (IL)-13 is a type 2 cytokine with important roles in inflammatory and fibrotic diseases (Gieseck et al, 2018;Bieber, 2020).…”

Section: Discussionmentioning

confidence: 99%

A potential three-gene-based diagnostic signature for idiopathic pulmonary fibrosis

Qiu

Dong

et al. 2023

Front. Genet.

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Background: Idiopathic pulmonary fibrosis (IPF) is a life-threatening disease whose etiology remains unknown. This study aims to explore diagnostic biomarkers and pathways involved in IPF using bioinformatics analysis.Methods: IPF-related gene expression datasets were retrieved and downloaded from the NCBI Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened, and weighted correlation network analysis (WGCNA) was performed to identify key module and genes. Functional enrichment analysis was performed on genes in the clinically significant module. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms were run to screen candidate biomarkers. The expression and diagnostic value of the biomarkers in IPF were further validated in external test datasets (GSE110147).Results: 292 samples and 1,163 DEGs were screened to construct WGCNA. In WGCNA, the blue module was identified as the key module, and 59 genes in this module correlated highly with IPF. Functional enrichment analysis of blue module genes revealed the importance of extracellular matrix-associated pathways in IPF. IL13RA2, CDH3, and COMP were identified as diagnostic markers of IPF via LASSO and SVM-RFE. These genes showed good diagnostic value for IPF and were significantly upregulated in IPF.Conclusion: This study indicates that IL13RA2, CDH3, and COMP could serve as diagnostic signature for IPF and might offer new insights in the underlying diagnosis of IPF.

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Systems biology analysis of lung fibrosis-related genes in the bleomycin mouse model

Cited by 9 publications

References 44 publications

Identification and Validation of Aging-Related Genes in Idiopathic Pulmonary Fibrosis

Identification and Validation of Aging-Related Genes in Idiopathic Pulmonary Fibrosis

Construction and evaluation of prognostic model of genes related to cell burial in idiopathic pulmonary fibrosis (IPF)

A potential three-gene-based diagnostic signature for idiopathic pulmonary fibrosis

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