Journal of Cancer Research and Clinical Oncology

, Volume 136, Issue 8, pp 1243–1254

Detection and identification of potential biomarkers of breast cancer

  • Yuxia Fan
  • Jiachen Wang
  • Yang Yang
  • Qiuliang Liu
  • Yingzhong Fan
  • Jiekai Yu
  • Shu Zheng
  • Mengquan Li
  • Jiaxiang Wang
Original Paper

DOI: 10.1007/s00432-010-0775-1

Cite this article as:
Fan, Y., Wang, J., Yang, Y. et al. J Cancer Res Clin Oncol (2010) 136: 1243. doi:10.1007/s00432-010-0775-1

Abstract

Purpose

Noninvasive and convenient biomarkers for early diagnosis of breast cancer remain an urgent need. The aim of this study was to discover and identify potential protein biomarkers specific for breast cancer.

Methods

Two hundred and eighty-two (282) serum samples with 124 breast cancer and 158 controls were randomly divided into a training set and a blind-testing set. Serum proteomic profiles were analyzed using SELDI-TOF-MS. Candidate biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays and western blot technique.

Results

A total of 3 peaks (m/z with 6,630, 8,139 and 8,942 Da) were screened out by support vector machine to construct the classification model with high discriminatory power in the training set. The sensitivity and specificity of the model were 96.45 and 94.87%, respectively, in the blind-testing set. The candidate biomarker with m/z of 6,630 Da was found to be down-regulated in breast cancer patients, and was identified as apolipoprotein C-I. Another two candidate biomarkers (8,139, 8,942 Da) were found up-regulated in breast cancer and identified as C-terminal-truncated form of C3a and complement component C3a, respectively. In addition, the level of apolipoprotein C-I progressively decreased with the clinical stages I, II, III and IV, and the expression of C-terminal-truncated form of C3a and complement component C3a gradually increased in higher stages.

Conclusions

We have identified a set of biomarkers that could discriminate breast cancer from non-cancer controls. An efficient strategy, including SELDI-TOF-MS analysis, HPLC purification, MALDI-TOF-MS trace and LC-MS/MS identification, has been proved very successful.

Keywords

BiomarkerBreast cancerLC-MS/MSMALDI-TOF-MSProteomicsSELDI-TOF-MS

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Yuxia Fan
    • 1
  • Jiachen Wang
    • 1
  • Yang Yang
    • 2
  • Qiuliang Liu
    • 1
  • Yingzhong Fan
    • 1
  • Jiekai Yu
    • 3
  • Shu Zheng
    • 3
  • Mengquan Li
    • 1
  • Jiaxiang Wang
    • 1
  1. 1.Department of General Surgery, The First Affiliated HospitalZhengzhou UniversityZhengzhouPeople’s Republic of China
  2. 2.Department of Thoracic Surgery, Union Hospital, Tongji Medical CollegeHuazhong University of Science and TechnologyWuhanPeople’s Republic of China
  3. 3.Institute of Cancer, The Second Affiliated Hospital, College of MedicineZhejiang UniversityHangzhouPeople’s Republic of China