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[Proteome analysis for identification of tumor-associated biomarkers in breast cancer].

Authors :
Wang X
Liang WJ
Zhu ZY
Yang MT
Zeng YX
Source :
Ai zheng = Aizheng = Chinese journal of cancer [Ai Zheng] 2004 Nov; Vol. 23 (11 Suppl), pp. 1577-81.
Publication Year :
2004

Abstract

Background & Objective: Pre-symptomatic screening of early-stage breast cancer may greatly reduce tumor-related mortality. Some tumor markers, such as CA15-3 and CA27-29, are recommended only for monitoring therapy of advanced or relapsed breast cancer. This study was to find new biomarkers that could be used individually or in combination with an existing modality for cost-effective screening of breast cancer by proteome analysis.<br />Methods: Protein expression differences among 128 serum samples of 64 breast cancer patients (19 of stage I, 24 of stage II, and 21 of stage III), 52 patients with benign breast diseases, and 12 healthy women were analyzed with IMAC3 and WCX2 Ciphergen ProteinChip Arrays.<br />Results: On WCX2 chip, a panel of 5 proteins (9 116, 8 905, 8 749, 9 470, and 9 692 Da) was selected based on their collective contribution to the optimal separation between breast cancer patients and both non-cancer patients and healthy women, and expression of another 2 proteins (9 405 and 6 424 Da) was different between patients with breast cancer of stage I and stage III. On IMAC3 chip, a panel of 9 proteins (5 236, 7 823, 7 464, 5 213, 5 334, 5 064, 5 374, 7 756, and 7 623 Da) was selected based on their collective contribution to the optimal separation between breast cancer patients and both non-cancer patients and healthy women, and expression of another 3 proteins (7 922, 4 641, and 5 910 Da) was different between patients with breast cancer of stage I and stage III.<br />Conclusion: Protein expression in breast cancer patients is different from that in both non-cancer patients and healthy women, and those proteins with different expression may be used as new biomarkers in breast cancer.

Details

Language :
Chinese
Volume :
23
Issue :
11 Suppl
Database :
MEDLINE
Journal :
Ai zheng = Aizheng = Chinese journal of cancer
Publication Type :
Academic Journal
Accession number :
15566683