PTK2-associated gene signature could predict the prognosis of IPF
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Author
Feng, A.Caro, Y.M.
Gardner, C.
Grischo, G.
Liang, Y.
Wickremasinghe, P.D.
Polmann, M.
Kala, M.
Marlowe, T.
Black, S.M.
Knox, K.S.
Wang, T.

Affiliation
Department of Internal Medicine, University of Arizona, PhoenixIssue Date
2023-12-06
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BioMed Central LtdCitation
Feng, A., Caro, Y.M., Gardner, C. et al. PTK2-associated gene signature could predict the prognosis of IPF. Respir Res 24, 304 (2023). https://doi.org/10.1186/s12931-023-02582-4Journal
Respiratory ResearchRights
© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal lung disease with a poor prognosis. Current/available clinical prediction tools have limited sensitivity and accuracy when evaluating clinical outcomes of IPF. Research has shown that focal adhesion kinase (FAK), produced by the protein tyrosine kinase 2 (PTK2) gene, is crucial in IPF development. FAK activation is a characteristic of lesional fibroblasts; Thus, FAK may be a valuable therapeutic target or prognostic biomarker for IPF. This study aimed to create a gene signature based on PTK2-associated genes and microarray data from blood cells to predict disease prognosis in patients with IPF. PTK2 levels were found to be higher in lung tissues of IPF patients compared to healthy controls, and PTK2 inhibitor Defactinib was found to reduce TGFβ-induced FAK activation and increase α-smooth muscle actin. Although the blood PTK2 levels were higher in IPF patients, blood PTK level alone could not predict IPF prognosis. From 196 PTK2-associated genes, 11 genes were prioritized to create a gene signature (PTK2 molecular signature) and a risk score system using univariate and multivariate Cox regression analysis. Patients were divided into high-risk and low-risk groups using PTK2 molecular signature. Patients in the high-risk group experienced decreased survival rates compared to patients in the low-risk group across all discovery and validation cohorts. Further functional enrichment and immune cell proportion analyses revealed that the PTK2 molecular signature strongly reflected the activation levels of immune pathways and immune cells. These findings suggested that PTK2 is a molecular target of IPF and the PTK2 molecular signature is an effective IPF prognostic biomarker. © 2023, The Author(s).Note
Open access journalISSN
1465-9921PubMed ID
38053045Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1186/s12931-023-02582-4
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Except where otherwise noted, this item's license is described as © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.
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