Cytokine Expression Profiling in Idiopathic Pulmonary Fibrosis: Insights From Integrative Proteomic Analysis

TL;DR

This study identifies key cytokines and proteins involved in idiopathic pulmonary fibrosis, offering new insights into disease mechanisms and potential drug targets.

Contribution

The paper provides a comprehensive proteomic analysis of cytokine expression in IPF lung tissues and identifies novel therapeutic targets.

Findings

32 differentially expressed cytokines were identified, enriched in cell chemotaxis and growth factor binding.

Five hub proteins (FGF2, HGF, HBEGF, ERBB3, and ANGPT2) were identified through PPI network analysis.

Immune infiltration analysis revealed higher resting NK cell presence in IPF lung tissue.

Abstract

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive fibrotic lung disease with a poor prognosis and no effective pharmacological treatments. Cytokines are a class of small-molecule proteins with diverse biological activities. Many cytokines—most notably transforming growth factor β—have been demonstrated to play an important role in IPF. However, a few studies have systematically described the relationship between cytokines and IPF.

Lung tissues from controls and patients with IPF were collected during lung transplantation. The expression profiles of 440 cytokines in lung tissues were obtained using protein microarrays. Proteomic analysis was performed, and differentially expressed proteins (DEPs) were identified. Furthermore, an integrative bioinformatics analysis was performed and included functional enrichment analysis, protein–protein interaction (PPI) network construction, hub protein determination, immune cell infiltration analysis, potential drug prediction, and single-cell analysis. The hub protein expression was validated through Gene Expression Omnibus (GEO) database evaluation and immunochemical analysis.

32 DEPs were identified from the two groups. They were mainly enriched in cell chemotaxis, basal part of cell, and growth factor binding and were involved in PI3K–Akt signaling. The PPI network was constructed for the DEPs, and five hub proteins (FGF2, HGF, HBEGF, ERBB3, and ANGPT2) were identified. The immune infiltration analysis demonstrated a significantly higher percentage of resting NK cells in IPF lung tissue. The drug prediction analyses identified 13 potential candidates targeting the five hub proteins. The single-cell analysis predicted the cellular localization of each key cytokine.

Using protein microarrays, we obtained comprehensive cytokine expression profiles in control and IPF lung tissues and conducted an integrated bioinformatics analysis of the proteomic data. Our findings may improve the comprehension of the role of cytokines in IPF and the underlying mechanisms. Moreover, they provide novel targets for developing safe and efficacious drugs for treating IPF.

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