Title |
Development and Validation of a Novel Plasma Protein Signature for Breast Cancer Diagnosis by Using Multiple Reaction Monitoring-based Mass Spectrometry.
|
---|---|
Published in |
Anticancer Research: International Journal of Cancer Research and Treatment, November 2015
|
Pubmed ID | |
Authors |
Han-Byoel Lee, Un-Beom Kang, Hyeong-Gon Moon, Jiwoo Lee, Kyung-Min Lee, Minju Yi, Yong Sun Park, Jong Won Lee, Jong-Han Yu, Seung Ho Choi, Sang Heon Cho, Cheolju Lee, Wonshik Han, Dong-Young Noh |
Abstract |
We aimed to develop a plasma protein signature for breast cancer diagnosis by using multiple reaction monitoring (MRM)-based mass spectrometry. 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. 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. 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 23 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 6 | 26% |
Researcher | 3 | 13% |
Student > Master | 3 | 13% |
Professor > Associate Professor | 2 | 9% |
Student > Bachelor | 2 | 9% |
Other | 4 | 17% |
Unknown | 3 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 7 | 30% |
Biochemistry, Genetics and Molecular Biology | 4 | 17% |
Agricultural and Biological Sciences | 3 | 13% |
Chemistry | 2 | 9% |
Physics and Astronomy | 1 | 4% |
Other | 3 | 13% |
Unknown | 3 | 13% |