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Published in: Journal of Cancer Research and Clinical Oncology 8/2010

01-08-2010 | Original Paper

Detection and identification of potential biomarkers of breast cancer

Authors: Yuxia Fan, Jiachen Wang, Yang Yang, Qiuliang Liu, Yingzhong Fan, Jiekai Yu, Shu Zheng, Mengquan Li, Jiaxiang Wang

Published in: Journal of Cancer Research and Clinical Oncology | Issue 8/2010

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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.
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Metadata
Title
Detection and identification of potential biomarkers of breast cancer
Authors
Yuxia Fan
Jiachen Wang
Yang Yang
Qiuliang Liu
Yingzhong Fan
Jiekai Yu
Shu Zheng
Mengquan Li
Jiaxiang Wang
Publication date
01-08-2010
Publisher
Springer-Verlag
Published in
Journal of Cancer Research and Clinical Oncology / Issue 8/2010
Print ISSN: 0171-5216
Electronic ISSN: 1432-1335
DOI
https://doi.org/10.1007/s00432-010-0775-1

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