Detection and identification of potential biomarkers of breast cancer.
OBJECTIVE
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.
Fan
Yuxia
Y
Department of General Surgery, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, Henan, People's Republic of China.
Wang
Jiachen
J
Yang
Yang
Y
Liu
Qiuliang
Q
Fan
Yingzhong
Y
Yu
Jiekai
J
Zheng
Shu
S
Li
Mengquan
M
Wang
Jiaxiang
J
D000595:Amino Acid Sequence; D014408:Biomarkers, Tumor / Q000032:analysis / Q000235:genetics*; D001798:Blood Proteins / Q000737:chemistry / Q000235:genetics; D001943:Breast Neoplasms / Q000097:blood / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D002851:Chromatography, High Pressure Liquid; D015926:Complement C3a / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling; D005822:Genetic Vectors; D024601:Glyceraldehyde 3-Phosphate Dehydrogenase (NADP+) / Q000737:chemistry / Q000235:genetics; D006801:Humans; D013058:Mass Spectrometry; D008969:Molecular Sequence Data; D009367:Neoplasm Staging; D020411:Oligonucleotide Array Sequence Analysis; D010446:Peptide Fragments / Q000737:chemistry; D012016:Reference Values; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; D015996:Survival Rate
D014408:Biomarkers, Tumor; D001798:Blood Proteins; D010446:Peptide Fragments; D015926:Complement C3a; D024601:Glyceraldehyde 3-Phosphate Dehydrogenase (NADP+)