Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probes

Pancreatic cancer is one of the deadliest cancers worldwide, mainly due to late diagnosis. Therefore, there is an urgent need for novel diagnostic approaches to identify the disease as early as possible. We have developed a diagnostic assay for pancreatic cancer based on the detection of naturally o...

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Authors: Corzana, Francisco, Asín, Alicia, Eguskiza, Ander, De Tomi, Elisa, Martín-Carnicero, Alfonso, Martínez-Moral, María P., Mangini, Vincenzo, Papi, Francesco, Bretón, Carmen, Oroz, Paula, Lagartera, Laura, Jiménez-Moreno, Ester, Avenoza, Alberto, Busto, Jesús H., Nativi, Cristina, Asensio, Juan L., Hurtado-Guerrero, Ramón, Peregrina, Jesús M., Malerba, Giovanni, Martínez, Alfredo, Fiammengo, Roberto
Format: article
Status:Published version
Publication Date:2024
Country:España
Institution:Universidad de Zaragoza
Repository:Zaguán. Repositorio Digital de la Universidad de Zaragoza
OAI Identifier:oai:zaguan.unizar.es:144611
Online Access:http://zaguan.unizar.es/record/144611
Access Level:Open access
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spelling Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probesCorzana, FranciscoAsín, AliciaEguskiza, AnderDe Tomi, ElisaMartín-Carnicero, AlfonsoMartínez-Moral, María P.Mangini, VincenzoPapi, FrancescoBretón, CarmenOroz, PaulaLagartera, LauraJiménez-Moreno, EsterAvenoza, AlbertoBusto, Jesús H.Nativi, CristinaAsensio, Juan L.Hurtado-Guerrero, RamónPeregrina, Jesús M.Malerba, GiovanniMartínez, AlfredoFiammengo, RobertoPancreatic cancer is one of the deadliest cancers worldwide, mainly due to late diagnosis. Therefore, there is an urgent need for novel diagnostic approaches to identify the disease as early as possible. We have developed a diagnostic assay for pancreatic cancer based on the detection of naturally occurring tumor associated autoantibodies against Mucin‐1 (MUC1) using engineered glycopeptides on nanoparticle probes. We used a structure‐guided approach to develop unnatural glycopeptides as model antigens for tumor‐associated MUC1. We designed a collection of 13 glycopeptides to bind either SM3 or 5E5, two monoclonal antibodies with distinct epitopes known to recognize tumor associated MUC1. Glycopeptide binding to SM3 or 5E5 was confirmed by surface plasmon resonance and rationalized by molecular dynamics simulations. These model antigens were conjugated to gold nanoparticles and used in a dot‐blot assay to detect autoantibodies in serum samples from pancreatic cancer patients and healthy volunteers. Nanoparticle probes with glycopeptides displaying the SM3 epitope did not have diagnostic potential. Instead, nanoparticle probes displaying glycopeptides with high affinity for 5E5 could discriminate between cancer patients and healthy controls. Remarkably, the best‐discriminating probes show significantly better true and false positive rates than the current clinical biomarkers CA19‐9 and carcinoembryonic antigen (CEA).2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://zaguan.unizar.es/record/144611reponame:Zaguán. Repositorio Digital de la Universidad de Zaragozainstname:Universidad de ZaragozaInglésinfo:eu-repo/grantAgreement/ES/AEI/BFU2016-75633-Pinfo:eu-repo/grantAgreement/ES/AEI/PID2019-105451GB-I00info:eu-repo/grantAgreement/ES/AEI/PID2021-127030OA-I00info:eu-repo/grantAgreement/ES/AEI/PID2022-133725-C21info:eu-repo/grantAgreement/ES/AEI/PID2022-136779OB-C31info:eu-repo/grantAgreement/ES/AEI/PID2022-141085NB-100info:eu-repo/grantAgreement/ES/DGA-FEDER/E34-R17info:eu-repo/grantAgreement/ES/DGA/LMP58-18info:eu-repo/grantAgreement/EC/H2020/956544This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 956544-DIRNANOinfo:eu-repo/grantAgreement/ES/MICINN AEI/PID2022-136362NB-I00info:eu-repo/grantAgreement/ES/MICINN/PID2021-127622OB-I00info:eu-repo/semantics/openAccessoai:zaguan.unizar.es:1446112026-05-29T13:59:51Z
dc.title.none.fl_str_mv Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probes
title Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probes
spellingShingle Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probes
Corzana, Francisco
title_short Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probes
title_full Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probes
title_fullStr Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probes
title_full_unstemmed Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probes
title_sort Detection of tumor-associated autoantibodies in the sera of pancreatic cancer patients using engineered muc1 glycopeptide nanoparticle probes
dc.creator.none.fl_str_mv Corzana, Francisco
Asín, Alicia
Eguskiza, Ander
De Tomi, Elisa
Martín-Carnicero, Alfonso
Martínez-Moral, María P.
Mangini, Vincenzo
Papi, Francesco
Bretón, Carmen
Oroz, Paula
Lagartera, Laura
Jiménez-Moreno, Ester
Avenoza, Alberto
Busto, Jesús H.
Nativi, Cristina
Asensio, Juan L.
Hurtado-Guerrero, Ramón
Peregrina, Jesús M.
Malerba, Giovanni
Martínez, Alfredo
Fiammengo, Roberto
author Corzana, Francisco
author_facet Corzana, Francisco
Asín, Alicia
Eguskiza, Ander
De Tomi, Elisa
Martín-Carnicero, Alfonso
Martínez-Moral, María P.
Mangini, Vincenzo
Papi, Francesco
Bretón, Carmen
Oroz, Paula
Lagartera, Laura
Jiménez-Moreno, Ester
Avenoza, Alberto
Busto, Jesús H.
Nativi, Cristina
Asensio, Juan L.
Hurtado-Guerrero, Ramón
Peregrina, Jesús M.
Malerba, Giovanni
Martínez, Alfredo
Fiammengo, Roberto
author_role author
author2 Asín, Alicia
Eguskiza, Ander
De Tomi, Elisa
Martín-Carnicero, Alfonso
Martínez-Moral, María P.
Mangini, Vincenzo
Papi, Francesco
Bretón, Carmen
Oroz, Paula
Lagartera, Laura
Jiménez-Moreno, Ester
Avenoza, Alberto
Busto, Jesús H.
Nativi, Cristina
Asensio, Juan L.
Hurtado-Guerrero, Ramón
Peregrina, Jesús M.
Malerba, Giovanni
Martínez, Alfredo
Fiammengo, Roberto
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
description Pancreatic cancer is one of the deadliest cancers worldwide, mainly due to late diagnosis. Therefore, there is an urgent need for novel diagnostic approaches to identify the disease as early as possible. We have developed a diagnostic assay for pancreatic cancer based on the detection of naturally occurring tumor associated autoantibodies against Mucin‐1 (MUC1) using engineered glycopeptides on nanoparticle probes. We used a structure‐guided approach to develop unnatural glycopeptides as model antigens for tumor‐associated MUC1. We designed a collection of 13 glycopeptides to bind either SM3 or 5E5, two monoclonal antibodies with distinct epitopes known to recognize tumor associated MUC1. Glycopeptide binding to SM3 or 5E5 was confirmed by surface plasmon resonance and rationalized by molecular dynamics simulations. These model antigens were conjugated to gold nanoparticles and used in a dot‐blot assay to detect autoantibodies in serum samples from pancreatic cancer patients and healthy volunteers. Nanoparticle probes with glycopeptides displaying the SM3 epitope did not have diagnostic potential. Instead, nanoparticle probes displaying glycopeptides with high affinity for 5E5 could discriminate between cancer patients and healthy controls. Remarkably, the best‐discriminating probes show significantly better true and false positive rates than the current clinical biomarkers CA19‐9 and carcinoembryonic antigen (CEA).
publishDate 2024
dc.date.none.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://zaguan.unizar.es/record/144611
url http://zaguan.unizar.es/record/144611
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/ES/AEI/BFU2016-75633-P
info:eu-repo/grantAgreement/ES/AEI/PID2019-105451GB-I00
info:eu-repo/grantAgreement/ES/AEI/PID2021-127030OA-I00
info:eu-repo/grantAgreement/ES/AEI/PID2022-133725-C21
info:eu-repo/grantAgreement/ES/AEI/PID2022-136779OB-C31
info:eu-repo/grantAgreement/ES/AEI/PID2022-141085NB-100
info:eu-repo/grantAgreement/ES/DGA-FEDER/E34-R17
info:eu-repo/grantAgreement/ES/DGA/LMP58-18
info:eu-repo/grantAgreement/EC/H2020/956544
This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 956544-DIRNANO
info:eu-repo/grantAgreement/ES/MICINN AEI/PID2022-136362NB-I00
info:eu-repo/grantAgreement/ES/MICINN/PID2021-127622OB-I00
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv
publisher.none.fl_str_mv
dc.source.none.fl_str_mv reponame:Zaguán. Repositorio Digital de la Universidad de Zaragoza
instname:Universidad de Zaragoza
instname_str Universidad de Zaragoza
reponame_str Zaguán. Repositorio Digital de la Universidad de Zaragoza
collection Zaguán. Repositorio Digital de la Universidad de Zaragoza
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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