Abstract

IntroductionSerum 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.MethodsTraining 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.ResultsFrom 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.ConclusionsProtein 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.

Highlights

  • Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC)

  • We investigated the association between this serum protein panel and patient outcome to determine its potential prognostic utility

  • More than 90% of cancer patients had an invasive tumor and more than half of these were of high histological grade

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Summary

Introduction

Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). Serum biomarkers have not yet played a major role in breast cancer diagnostic or prognostic practice [1,2], an effective biomarker panel in an accessible biological fluid would be a valuable and minimally invasive adjunct to other clinical and pathological approaches [3]. As whole blood provides a dynamic representation of physiological and pathological status, serum or plasma represents the most extensively studied biological matrix for cancer biomarkers [4]. Numerous proteomics-based studies of serum and plasma have reported discriminatory peptide/protein ion peaks, either as identified proteins or on the basis of their mass/charge (m/z) values, for breast cancer diagnosis or prognosis. Not all have reported protein identities for the discriminatory ion peaks

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