Development and Validation of a Novel Plasma Protein Signature for Breast Cancer Diagnosis by Using Multiple Reaction Monitoring-based Mass Spectrometry

Authors
Lee, Han-ByoelKang, Un-BeomMoon, Hyeong-GonLee, JiwooLee, Kyung-MinYi, MinjuPark, Yong SunLee, Jong WonYu, Jong-HanChoi, Seung HoCho, Sang HeonLee, CheoljuHan, WonshikNoh, Dong-Young
Issue Date
2015-11
Publisher
INT INST ANTICANCER RESEARCH
Citation
ANTICANCER RESEARCH, v.35, no.11, pp.6271 - 6279
Abstract
Aim: We aimed to develop a plasma protein signature for breast cancer diagnosis by using multiple reaction monitoring (MRM)-based mass spectrometry. Materials and Methods: Based on our previous studies, we selected 124 proteins for MRM. Plasma samples from 80 patients with breast cancer and 80 healthy women were used to develop a plasma proteomic signature by an MRM approach. The proteomic signature was then validated in plasma samples from 100 patients with breast cancer and 100 healthy women. Results: A total of 56 proteins were optimized for MRM. In the verification cohort, 11 proteins exhibited significantly differential expression in plasma from patients with breast cancer. Three proteins (neural cell adhesion molecule L1-like protein, apolipoprotein C-1 and carbonic anhydrase-1) with highest statistical significance which gave consistent results for patients of stage I and II breast cancer were selected and a 3-protein signature was developed using binary logistic regression analysis [area under the curve (AUC)=0.851, sensitivity=80.6%]. The 3-protein signature showed similar performance in an independent validation cohort with an AUC of 0.797 and sensitivity of 77.2% for detection of stage I and II breast cancer. Conclusion: We developed a distinct plasma protein signature for breast cancer diagnosis based on an MRM-based approach, and the clinical value of the 3-protein signature was validated in an independent cohort.
Keywords
SERUM BIOMARKERS; PROTEOMIC ANALYSIS; IDENTIFICATION; DISCOVERY; FRAGMENT; PATTERN; TISSUE; MODEL; SERUM BIOMARKERS; PROTEOMIC ANALYSIS; IDENTIFICATION; DISCOVERY; FRAGMENT; PATTERN; TISSUE; MODEL; Breast cancer; proteomics; multiple reaction monitoring; diagnosis; plasma
ISSN
0250-7005
URI
https://pubs.kist.re.kr/handle/201004/124854
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KIST Article > 2015
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