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Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients

Pancreatic Ductal Adenocarcinoma (PDA) is an aggressive malignancy with a very poor outcome. Although chemotherapy (CT) treatment has poor efficacy, it can enhance tumor immunogenicity. Tumor-Associated Antigens (TAA) are self-proteins that are overexpressed in tumors that may induce antibody produc...

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Autores principales: Mandili, Giorgia, Follia, Laura, Ferrero, Giulio, Katayama, Hiroyuki, Hong, Wang, Momin, Amin A., Capello, Michela, Giordano, Daniele, Spadi, Rosella, Satolli, Maria Antonietta, Evangelista, Andrea, Hanash, Samir M., Cordero, Francesca, Novelli, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140049/
https://www.ncbi.nlm.nih.gov/pubmed/32245227
http://dx.doi.org/10.3390/cancers12030746
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author Mandili, Giorgia
Follia, Laura
Ferrero, Giulio
Katayama, Hiroyuki
Hong, Wang
Momin, Amin A.
Capello, Michela
Giordano, Daniele
Spadi, Rosella
Satolli, Maria Antonietta
Evangelista, Andrea
Hanash, Samir M.
Cordero, Francesca
Novelli, Francesco
author_facet Mandili, Giorgia
Follia, Laura
Ferrero, Giulio
Katayama, Hiroyuki
Hong, Wang
Momin, Amin A.
Capello, Michela
Giordano, Daniele
Spadi, Rosella
Satolli, Maria Antonietta
Evangelista, Andrea
Hanash, Samir M.
Cordero, Francesca
Novelli, Francesco
author_sort Mandili, Giorgia
collection PubMed
description Pancreatic Ductal Adenocarcinoma (PDA) is an aggressive malignancy with a very poor outcome. Although chemotherapy (CT) treatment has poor efficacy, it can enhance tumor immunogenicity. Tumor-Associated Antigens (TAA) are self-proteins that are overexpressed in tumors that may induce antibody production and can be PDA theranostic targets. However, the prognostic value of TAA-antibody association as Circulating Immune Complexes (CIC) has not yet been elucidated, mainly due to the lack of techniques that lead to their identification. In this study, we show a novel method to separate IgG, IgM, and IgA CIC from sera to use them as prognostic biomarkers of CT response. The PDA Immune-Complexome (IC) was identified using a LTQ-Orbitrap mass spectrometer followed by computational analysis. The analysis of the IC of 37 PDA patients before and after CT revealed differential associated antigens (DAA) for each immunoglobulin class. Our method identified different PDA-specific CIC in patients that were associated with poor prognosis patients. Finally, CIC levels were significantly modified by CT suggesting that they can be used as effective prognostic biomarkers to follow CT response in PDA patients.
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spelling pubmed-71400492020-04-13 Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients Mandili, Giorgia Follia, Laura Ferrero, Giulio Katayama, Hiroyuki Hong, Wang Momin, Amin A. Capello, Michela Giordano, Daniele Spadi, Rosella Satolli, Maria Antonietta Evangelista, Andrea Hanash, Samir M. Cordero, Francesca Novelli, Francesco Cancers (Basel) Article Pancreatic Ductal Adenocarcinoma (PDA) is an aggressive malignancy with a very poor outcome. Although chemotherapy (CT) treatment has poor efficacy, it can enhance tumor immunogenicity. Tumor-Associated Antigens (TAA) are self-proteins that are overexpressed in tumors that may induce antibody production and can be PDA theranostic targets. However, the prognostic value of TAA-antibody association as Circulating Immune Complexes (CIC) has not yet been elucidated, mainly due to the lack of techniques that lead to their identification. In this study, we show a novel method to separate IgG, IgM, and IgA CIC from sera to use them as prognostic biomarkers of CT response. The PDA Immune-Complexome (IC) was identified using a LTQ-Orbitrap mass spectrometer followed by computational analysis. The analysis of the IC of 37 PDA patients before and after CT revealed differential associated antigens (DAA) for each immunoglobulin class. Our method identified different PDA-specific CIC in patients that were associated with poor prognosis patients. Finally, CIC levels were significantly modified by CT suggesting that they can be used as effective prognostic biomarkers to follow CT response in PDA patients. MDPI 2020-03-21 /pmc/articles/PMC7140049/ /pubmed/32245227 http://dx.doi.org/10.3390/cancers12030746 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mandili, Giorgia
Follia, Laura
Ferrero, Giulio
Katayama, Hiroyuki
Hong, Wang
Momin, Amin A.
Capello, Michela
Giordano, Daniele
Spadi, Rosella
Satolli, Maria Antonietta
Evangelista, Andrea
Hanash, Samir M.
Cordero, Francesca
Novelli, Francesco
Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients
title Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients
title_full Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients
title_fullStr Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients
title_full_unstemmed Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients
title_short Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients
title_sort immune-complexome analysis identifies immunoglobulin-bound biomarkers that predict the response to chemotherapy of pancreatic cancer patients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7140049/
https://www.ncbi.nlm.nih.gov/pubmed/32245227
http://dx.doi.org/10.3390/cancers12030746
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