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Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer

INTRODUCTION: Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identi...

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Autores principales: Chung, Liping, Moore, Katrina, Phillips, Leo, Boyle, Frances M, Marsh, Deborah J, Baxter, Robert C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4095593/
https://www.ncbi.nlm.nih.gov/pubmed/24935269
http://dx.doi.org/10.1186/bcr3676
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author Chung, Liping
Moore, Katrina
Phillips, Leo
Boyle, Frances M
Marsh, Deborah J
Baxter, Robert C
author_facet Chung, Liping
Moore, Katrina
Phillips, Leo
Boyle, Frances M
Marsh, Deborah J
Baxter, Robert C
author_sort Chung, Liping
collection PubMed
description INTRODUCTION: Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel. METHODS: Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated. RESULTS: From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with estrogen receptor (ER)-negative tumors (n = 50, P = 0.003) compared to ER-positive (n = 131, P = 0.161), although the influence of ER status needs to be confirmed after longer follow-up. CONCLUSIONS: Protein mass profiling by MS has revealed five serum proteins which, in combination, can distinguish between serum from women with breast cancer and healthy control subjects with high sensitivity and specificity. The five-protein panel significantly predicts recurrence-free survival in women with ER-negative tumors and may have value in the management of these patients.
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spelling pubmed-40955932014-07-14 Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer Chung, Liping Moore, Katrina Phillips, Leo Boyle, Frances M Marsh, Deborah J Baxter, Robert C Breast Cancer Res Research Article INTRODUCTION: Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel. METHODS: Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated. RESULTS: From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with estrogen receptor (ER)-negative tumors (n = 50, P = 0.003) compared to ER-positive (n = 131, P = 0.161), although the influence of ER status needs to be confirmed after longer follow-up. CONCLUSIONS: Protein mass profiling by MS has revealed five serum proteins which, in combination, can distinguish between serum from women with breast cancer and healthy control subjects with high sensitivity and specificity. The five-protein panel significantly predicts recurrence-free survival in women with ER-negative tumors and may have value in the management of these patients. BioMed Central 2014 2014-06-16 /pmc/articles/PMC4095593/ /pubmed/24935269 http://dx.doi.org/10.1186/bcr3676 Text en Copyright © 2014 Chung et al.; licensee BioMed Central Ltd. 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 work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Chung, Liping
Moore, Katrina
Phillips, Leo
Boyle, Frances M
Marsh, Deborah J
Baxter, Robert C
Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer
title Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer
title_full Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer
title_fullStr Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer
title_full_unstemmed Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer
title_short Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer
title_sort novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4095593/
https://www.ncbi.nlm.nih.gov/pubmed/24935269
http://dx.doi.org/10.1186/bcr3676
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