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Identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis

BACKGROUND: Pancreatic cancer continues to prove difficult to clinically diagnose. Multiple simultaneous measurements of plasma biomarkers can increase sensitivity and selectivity of diagnosis. Proximity ligation assay (PLA) is a highly sensitive technique for multiplex detection of biomarkers in pl...

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Autores principales: Chang, Stephanie T, Zahn, Jacob M, Horecka, Joe, Kunz, Pamela L, Ford, James M, Fisher, George A, Le, Quynh T, Chang, Daniel T, Ji, Hanlee, Koong, Albert C
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2796647/
https://www.ncbi.nlm.nih.gov/pubmed/20003342
http://dx.doi.org/10.1186/1479-5876-7-105
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author Chang, Stephanie T
Zahn, Jacob M
Horecka, Joe
Kunz, Pamela L
Ford, James M
Fisher, George A
Le, Quynh T
Chang, Daniel T
Ji, Hanlee
Koong, Albert C
author_facet Chang, Stephanie T
Zahn, Jacob M
Horecka, Joe
Kunz, Pamela L
Ford, James M
Fisher, George A
Le, Quynh T
Chang, Daniel T
Ji, Hanlee
Koong, Albert C
author_sort Chang, Stephanie T
collection PubMed
description BACKGROUND: Pancreatic cancer continues to prove difficult to clinically diagnose. Multiple simultaneous measurements of plasma biomarkers can increase sensitivity and selectivity of diagnosis. Proximity ligation assay (PLA) is a highly sensitive technique for multiplex detection of biomarkers in plasma with little or no interfering background signal. METHODS: We examined the plasma levels of 21 biomarkers in a clinically defined cohort of 52 locally advanced (Stage II/III) pancreatic ductal adenocarcinoma cases and 43 age-matched controls using a multiplex proximity ligation assay. The optimal biomarker panel for diagnosis was computed using a combination of the PAM algorithm and logistic regression modeling. Biomarkers that were significantly prognostic for survival in combination were determined using univariate and multivariate Cox survival models. RESULTS: Three markers, CA19-9, OPN and CHI3L1, measured in multiplex were found to have superior sensitivity for pancreatic cancer vs. CA19-9 alone (93% vs. 80%). In addition, we identified two markers, CEA and CA125, that when measured simultaneously have prognostic significance for survival for this clinical stage of pancreatic cancer (p < 0.003). CONCLUSIONS: A multiplex panel assaying CA19-9, OPN and CHI3L1 in plasma improves accuracy of pancreatic cancer diagnosis. A panel assaying CEA and CA125 in plasma can predict survival for this clinical cohort of pancreatic cancer patients.
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spelling pubmed-27966472009-12-22 Identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis Chang, Stephanie T Zahn, Jacob M Horecka, Joe Kunz, Pamela L Ford, James M Fisher, George A Le, Quynh T Chang, Daniel T Ji, Hanlee Koong, Albert C J Transl Med Research BACKGROUND: Pancreatic cancer continues to prove difficult to clinically diagnose. Multiple simultaneous measurements of plasma biomarkers can increase sensitivity and selectivity of diagnosis. Proximity ligation assay (PLA) is a highly sensitive technique for multiplex detection of biomarkers in plasma with little or no interfering background signal. METHODS: We examined the plasma levels of 21 biomarkers in a clinically defined cohort of 52 locally advanced (Stage II/III) pancreatic ductal adenocarcinoma cases and 43 age-matched controls using a multiplex proximity ligation assay. The optimal biomarker panel for diagnosis was computed using a combination of the PAM algorithm and logistic regression modeling. Biomarkers that were significantly prognostic for survival in combination were determined using univariate and multivariate Cox survival models. RESULTS: Three markers, CA19-9, OPN and CHI3L1, measured in multiplex were found to have superior sensitivity for pancreatic cancer vs. CA19-9 alone (93% vs. 80%). In addition, we identified two markers, CEA and CA125, that when measured simultaneously have prognostic significance for survival for this clinical stage of pancreatic cancer (p < 0.003). CONCLUSIONS: A multiplex panel assaying CA19-9, OPN and CHI3L1 in plasma improves accuracy of pancreatic cancer diagnosis. A panel assaying CEA and CA125 in plasma can predict survival for this clinical cohort of pancreatic cancer patients. BioMed Central 2009-12-11 /pmc/articles/PMC2796647/ /pubmed/20003342 http://dx.doi.org/10.1186/1479-5876-7-105 Text en Copyright ©2009 Chang et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Chang, Stephanie T
Zahn, Jacob M
Horecka, Joe
Kunz, Pamela L
Ford, James M
Fisher, George A
Le, Quynh T
Chang, Daniel T
Ji, Hanlee
Koong, Albert C
Identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis
title Identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis
title_full Identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis
title_fullStr Identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis
title_full_unstemmed Identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis
title_short Identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis
title_sort identification of a biomarker panel using a multiplex proximity ligation assay improves accuracy of pancreatic cancer diagnosis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2796647/
https://www.ncbi.nlm.nih.gov/pubmed/20003342
http://dx.doi.org/10.1186/1479-5876-7-105
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