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Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF

RATIONALE: Biomarkers in easily accessible compartments like peripheral blood that can predict disease progression in idiopathic pulmonary fibrosis (IPF) would be clinically useful regarding clinical trial participation or treatment decisions for patients. In this study, we used unbiased proteomics...

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Autores principales: Ashley, Shanna L., Xia, Meng, Murray, Susan, O’Dwyer, David N., Grant, Ethan, White, Eric S., Flaherty, Kevin R., Martinez, Fernando J., Moore, Bethany B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4973878/
https://www.ncbi.nlm.nih.gov/pubmed/27490795
http://dx.doi.org/10.1371/journal.pone.0159878
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author Ashley, Shanna L.
Xia, Meng
Murray, Susan
O’Dwyer, David N.
Grant, Ethan
White, Eric S.
Flaherty, Kevin R.
Martinez, Fernando J.
Moore, Bethany B.
author_facet Ashley, Shanna L.
Xia, Meng
Murray, Susan
O’Dwyer, David N.
Grant, Ethan
White, Eric S.
Flaherty, Kevin R.
Martinez, Fernando J.
Moore, Bethany B.
author_sort Ashley, Shanna L.
collection PubMed
description RATIONALE: Biomarkers in easily accessible compartments like peripheral blood that can predict disease progression in idiopathic pulmonary fibrosis (IPF) would be clinically useful regarding clinical trial participation or treatment decisions for patients. In this study, we used unbiased proteomics to identify relevant disease progression biomarkers in IPF. METHODS: Plasma from IPF patients was measured using an 1129 analyte slow off-rate modified aptamer (SOMAmer) array, and patient outcomes were followed over the next 80 weeks. Receiver operating characteristic (ROC) curves evaluated sensitivity and specificity for levels of each biomarker and estimated area under the curve (AUC) when prognostic biomarker thresholds were used to predict disease progression. Both logistic and Cox regression models advised biomarker selection for a composite disease progression index; index biomarkers were weighted via expected progression-free days lost during follow-up with a biomarker on the unfavorable side of the threshold. RESULTS: A six-analyte index, scaled 0 to 11, composed of markers of immune function, proteolysis and angiogenesis [high levels of ficolin-2 (FCN2), cathepsin-S (Cath-S), legumain (LGMN) and soluble vascular endothelial growth factor receptor 2 (VEGFsR2), but low levels of inducible T cell costimulator (ICOS) or trypsin 3 (TRY3)] predicted better progression-free survival in IPF with a ROC AUC of 0.91. An index score ≥ 3 (group ≥ 2) was strongly associated with IPF progression after adjustment for age, gender, smoking status, immunomodulation, forced vital capacity % predicted and diffusing capacity for carbon monoxide % predicted (HR 16.8, 95% CI 2.2–126.7, P = 0.006). CONCLUSION: This index, derived from the largest proteomic analysis of IPF plasma samples to date, could be useful for clinical decision making in IPF, and the identified analytes suggest biological processes that may promote disease progression.
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spelling pubmed-49738782016-08-18 Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF Ashley, Shanna L. Xia, Meng Murray, Susan O’Dwyer, David N. Grant, Ethan White, Eric S. Flaherty, Kevin R. Martinez, Fernando J. Moore, Bethany B. PLoS One Research Article RATIONALE: Biomarkers in easily accessible compartments like peripheral blood that can predict disease progression in idiopathic pulmonary fibrosis (IPF) would be clinically useful regarding clinical trial participation or treatment decisions for patients. In this study, we used unbiased proteomics to identify relevant disease progression biomarkers in IPF. METHODS: Plasma from IPF patients was measured using an 1129 analyte slow off-rate modified aptamer (SOMAmer) array, and patient outcomes were followed over the next 80 weeks. Receiver operating characteristic (ROC) curves evaluated sensitivity and specificity for levels of each biomarker and estimated area under the curve (AUC) when prognostic biomarker thresholds were used to predict disease progression. Both logistic and Cox regression models advised biomarker selection for a composite disease progression index; index biomarkers were weighted via expected progression-free days lost during follow-up with a biomarker on the unfavorable side of the threshold. RESULTS: A six-analyte index, scaled 0 to 11, composed of markers of immune function, proteolysis and angiogenesis [high levels of ficolin-2 (FCN2), cathepsin-S (Cath-S), legumain (LGMN) and soluble vascular endothelial growth factor receptor 2 (VEGFsR2), but low levels of inducible T cell costimulator (ICOS) or trypsin 3 (TRY3)] predicted better progression-free survival in IPF with a ROC AUC of 0.91. An index score ≥ 3 (group ≥ 2) was strongly associated with IPF progression after adjustment for age, gender, smoking status, immunomodulation, forced vital capacity % predicted and diffusing capacity for carbon monoxide % predicted (HR 16.8, 95% CI 2.2–126.7, P = 0.006). CONCLUSION: This index, derived from the largest proteomic analysis of IPF plasma samples to date, could be useful for clinical decision making in IPF, and the identified analytes suggest biological processes that may promote disease progression. Public Library of Science 2016-08-04 /pmc/articles/PMC4973878/ /pubmed/27490795 http://dx.doi.org/10.1371/journal.pone.0159878 Text en © 2016 Ashley et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ashley, Shanna L.
Xia, Meng
Murray, Susan
O’Dwyer, David N.
Grant, Ethan
White, Eric S.
Flaherty, Kevin R.
Martinez, Fernando J.
Moore, Bethany B.
Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF
title Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF
title_full Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF
title_fullStr Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF
title_full_unstemmed Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF
title_short Six-SOMAmer Index Relating to Immune, Protease and Angiogenic Functions Predicts Progression in IPF
title_sort six-somamer index relating to immune, protease and angiogenic functions predicts progression in ipf
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4973878/
https://www.ncbi.nlm.nih.gov/pubmed/27490795
http://dx.doi.org/10.1371/journal.pone.0159878
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