Identification of diagnostic gene biomarkers related to immune infiltration in patients with idiopathic pulmonary fibrosis based on bioinformatics strategies

The study aims to identify potential diagnostic markers of idiopathic pulmonary fibrosis (IPF) and analyze the significance of immune cell infiltration in this pathology. Download two publicly available gene expression profiles (GSE10667 and GSE24206 datasets) from the GEO database including 48 Idio...

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Published in:Frontiers in medicine Vol. 9; p. 959010
Main Authors: Dai, Xiangdong, Yang, Zhihua, Zhang, Wenjing, Liu, Shuai, Zhao, Qianru, Liu, Tao, Chen, Lu, Li, Lin, Wang, Yi, Shao, Rui
Format: Journal Article
Language:English
Published: Switzerland Frontiers Media SA 24.11.2022
Frontiers Media S.A
Subjects:
biomarker
Biomarkers
CIBERSORT
Datasets
diagnostic
idiopathic pulmonary fibrosis
immune infiltration
Lung diseases
Medicine
Support vector machines
diagnostic
idiopathic pulmonary fibrosis
immune infiltration
biomarker
CIBERSORT
ISSN:2296-858X, 2296-858X
Online Access:Get full text
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Summary:The study aims to identify potential diagnostic markers of idiopathic pulmonary fibrosis (IPF) and analyze the significance of immune cell infiltration in this pathology. Download two publicly available gene expression profiles (GSE10667 and GSE24206 datasets) from the GEO database including 48 Idiopathic pulmonary fibrosis (IPF) samples and 21 human control samples and select for distinctly expressed genes (DEG) from them. Lasso regression model and support vector machine recursive feature elimination S,V,R,F analysis were used to check candidate biomarkers. The area under the subject's work characteristic curve (AUC) value is used to evaluate its recognition ability. The GSE53845 dataset (40 IPF patients and 8 controls) continue to validate the expression level and diagnostic value of biomarkers in IPF. Comprehensive analysis of immune infiltrated cells of IPF was performed using R software and immune cell infiltration estimation analysis tool- deconvolution algorithm (CIBERSORT). 43 DEGs were identified in total. The identified DEGs mostly involve pneumonia, lung disease, collagen disease, obstructive pulmonary disease and other diseases. The activation of IL-17 signaling pathways, amoebic disease, interaction of viral proteins with cytokines and cytokine receptors, protein digestion and absorption, and flaccid hormone signaling pathways in IPF were different from the control group. The expression degree of CRTAC1, COL10A1, COMP, RPS4Y1, IGFL2, NECAB1, SCG5, SLC6A4, and SPP1 in IPF tissue were prominently higher than the normal group. Immune cell infiltration analysis showed that CRTAC1, COL10A1, COMP, IGFL2, NECAB1, SCG5, SLC6A4, and SPP1 were associated with monocytes, plasma cells, neutrophils, and regulatory (treg) T cells. CRTAC1, COL10A1, COMP, IGFL2, NECAB1, SCG5, SLC6A4, and SPP1 can be used as diagnostic markers for IPF, providing new ideas for the future study of IPF occurrence and molecular mechanisms.
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These authors have contributed equally to this work
Edited by: Federica Meloni, University of Pavia, Italy
Reviewed by: Barbara Ruaro, University of Trieste, Italy; Jingyu Li, Sichuan University, China
This article was submitted to Pulmonary Medicine, a section of the journal Frontiers in Medicine
ISSN:2296-858X
2296-858X
DOI:10.3389/fmed.2022.959010