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Radioproteomics stratifies molecular response to antifibrotic treatment in pulmonary fibrosis
David Lauer, Cheryl Y. Magnin, Luca R. Kolly, Huijuan Wang, Matthias Brunner, Mamta Chabria, Grazia M. Cereghetti, Hubert S. Gabryś, Stephanie Tanadini-Lang, Anne-Christine Uldry, Manfred Heller, Stijn E. Verleden, Kerstin Klein, Adela-Cristina Sarbu, Manuela Funke-Chambour, Lukas Ebner, Oliver Distler, Britta Maurer, Janine Gote-Schniering
David Lauer, Cheryl Y. Magnin, Luca R. Kolly, Huijuan Wang, Matthias Brunner, Mamta Chabria, Grazia M. Cereghetti, Hubert S. Gabryś, Stephanie Tanadini-Lang, Anne-Christine Uldry, Manfred Heller, Stijn E. Verleden, Kerstin Klein, Adela-Cristina Sarbu, Manuela Funke-Chambour, Lukas Ebner, Oliver Distler, Britta Maurer, Janine Gote-Schniering
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Research Article Pulmonology Therapeutics

Radioproteomics stratifies molecular response to antifibrotic treatment in pulmonary fibrosis

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Abstract

Antifibrotic therapy with nintedanib is the clinical mainstay in the treatment of progressive fibrosing interstitial lung disease (ILD). High-dimensional medical image analysis, known as radiomics, provides quantitative insights into organ-scale pathophysiology, generating digital disease fingerprints. Here, we performed an integrative analysis of radiomic and proteomic profiles (radioproteomics) to assess whether changes in radiomic signatures can stratify the degree of antifibrotic response to nintedanib in (experimental) fibrosing ILD. Unsupervised clustering of delta radiomic profiles revealed 2 distinct imaging phenotypes in mice treated with nintedanib, contrary to conventional densitometry readouts, which showed a more uniform response. Integrative analysis of delta radiomics and proteomics demonstrated that these phenotypes reflected different treatment response states, as further evidenced on transcriptional and cellular levels. Importantly, radioproteomics signatures paralleled disease- and drug-related biological pathway activity with high specificity, including extracellular matrix (ECM) remodeling, cell cycle activity, wound healing, and metabolic activity. Evaluation of the preclinical molecular response–defining features, particularly those linked to ECM remodeling, in a cohort of nintedanib-treated fibrosing patients with ILD, accurately stratified patients based on their extent of lung function decline. In conclusion, delta radiomics has great potential to serve as a noninvasive and readily accessible surrogate of molecular response phenotypes in fibrosing ILD. This could pave the way for personalized treatment strategies and improved patient outcomes.

Authors

David Lauer, Cheryl Y. Magnin, Luca R. Kolly, Huijuan Wang, Matthias Brunner, Mamta Chabria, Grazia M. Cereghetti, Hubert S. Gabryś, Stephanie Tanadini-Lang, Anne-Christine Uldry, Manfred Heller, Stijn E. Verleden, Kerstin Klein, Adela-Cristina Sarbu, Manuela Funke-Chambour, Lukas Ebner, Oliver Distler, Britta Maurer, Janine Gote-Schniering

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Figure 3

Delta radiomic features reflect changes in disease-relevant molecular pathway activity.

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Delta radiomic features reflect changes in disease-relevant molecular pa...
(A) Workflow schematic. Variable importance of each delta radiomic feature (n = 244) for assignment of clusters was assessed by univariate analysis, retaining only “response-defining” features (n = 54) with classification score ≥ 0.90. Radioproteomic association modules were compiled by assigning the set of highly correlating proteins (Spearman’s | ρ| ≥ 0.6, P < 0.05) to each response-defining feature. (B) Heatmap displaying Reactome pathways enriched (GeneRatio ≥ 0.10, Padj < 0.05) in radioproteomic association modules for positively (Spearman’s ρ ≥ 0.6, P < 0.05) or negatively (Spearman’s ρ ≤ –0.6, P < 0.05) correlating proteins. Only pathways enriched in at least 2 radioproteomic association modules are displayed. Association modules without enriched pathways following filtering are not displayed. Pathway names shortened for R-MMU-6791226 (*) and R-MMU-163200 (†). (C) Heatmap displaying cell type signatures enriched (P < 0.01) in radioproteomic association modules for positively (Spearman’s ρ ≥ 0.6, P < 0.05) or negatively (Spearman’s ρ ≤ –0.6, P < 0.05) correlating proteins. Association modules without enriched cell type signatures are not displayed. (D) Representative IF stainings of fibrotic lung regions exhibiting a low (left) and high (right) fraction of α-SMA+ myofibroblasts. Relative expression of 2 selected delta radiomic features (LLH_GLSZM_GLnonuniformity_norm and LHL_mGLCM_MCC) showing positive or negative enrichment for myofibroblast cell type signatures, respectively, is indicated. Images show nuclei (DAPI), AT2 cells (proSP-C), myofibroblasts (α-SMA), and AT1 cells (PDPN). Scale bar: 100 μm. Each point represents the average fraction of α-SMA+ cells of 5 representative fibrotic regions. (E) Scatter plot of the Pearson correlation coefficient between the α-SMA+ cell fraction quantified by IF and the Z scored delta radiomic feature expression of LHL_mGLCM_MCC and LLH_GLSZM_GLnonuniformity_norm. Displayed is the linear model with the best fit (red) together with 95% CIs (gray).

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