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

Chung, L; Moore, K; Phillips, L; Boyle, FM; Marsh, DJ; Baxter, RC

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

Chung, L Moore, K Phillips, L Boyle, FM Marsh, DJ

Baxter, RC

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Publication Type:: Journal Article
Citation:: Breast Cancer Research, 2014, 16 (3)
Issue Date:: 2014-06-16

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Field	Value	Language
dc.contributor.author	Chung, L	en_US
dc.contributor.author	Moore, K	en_US
dc.contributor.author	Phillips, L	en_US
dc.contributor.author	Boyle, FM	en_US
dc.contributor.author	Marsh, DJ https://orcid.org/0000-0001-5899-4931	en_US
dc.contributor.author	Baxter, RC	en_US
dc.date.available	2014-06-02	en_US
dc.date.issued	2014-06-16	en_US
dc.identifier.citation	Breast Cancer Research, 2014, 16 (3)	en_US
dc.identifier.issn	1465-5411	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127600
dc.description.abstract	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. © 2014 Chung et al.; licensee BioMed Central Ltd.	en_US
dc.relation.ispartof	Breast Cancer Research	en_US
dc.relation.isbasedon	10.1186/bcr3676	en_US
dc.subject.classification	Oncology & Carcinogenesis	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Breast Neoplasms	en_US
dc.subject.mesh	Prealbumin	en_US
dc.subject.mesh	Apolipoprotein A-I	en_US
dc.subject.mesh	Blood Proteins	en_US
dc.subject.mesh	Receptors, Estrogen	en_US
dc.subject.mesh	Tumor Markers, Biological	en_US
dc.subject.mesh	Disease-Free Survival	en_US
dc.subject.mesh	Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization	en_US
dc.subject.mesh	Middle Aged	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Complement C3a	en_US
dc.subject.mesh	Apolipoprotein C-I	en_US
dc.subject.mesh	beta 2-Glycoprotein I	en_US
dc.subject.mesh	Biomarkers, Tumor	en_US
dc.title	Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	16	en_US
utslib.for	1112 Oncology and Carcinogenesis	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	16	en_US

Abstract:

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. © 2014 Chung et al.; licensee BioMed Central Ltd.

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