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  4. The plasma proteome and breast cancer risk.
 
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The plasma proteome and breast cancer risk.

Journal
Breast cancer research : BCR
Series/Report No.
Breast Cancer Research
Journal Volume
27
Journal Issue
1
Start Page
Article number 157
ISSN
1465-542X
Date Issued
2025-09-01
Author(s)
Wu, Hui-Chen
Liao, Yuyan
Lai, Yunjia
Lin, Po-Han  
Santella, Regina M
Miller, Gary W
Terry, Mary Beth
DOI
10.1186/s13058-025-02110-w
URI
https://scholars.lib.ntu.edu.tw/handle/123456789/735044
Abstract
Background: Plasma proteins may serve as biomarkers for breast cancer. This study aimed to characterize the blood proteomic signatures of women with a higher risk of breast cancer due to their family history. Methods: We conducted a nested case-control study (median followup: 9.8 years) within the New York site of the Breast Cancer Family Registry (BCFR) (n = 39 cases and 48 age-matched controls). We measured the expression levels as Normalized Protein Expression (NPX) of 92 proteins using the Olink Oncology panel. We then utilized an integrative network analysis of statistically significant protein markers and metabolomic profiles to better understand the potential molecular pathways involved in breast cancer. Results: We found four proteins were positively associated with breast cancer risk; the adjusted odds ratios (ORs) (95% confidence interval (CI) per 1-standard deviation (SD) increase in NPX were 1.87 (95% CI: 1.07, 3.28) for folate receptor (FR)-alpha, 2.72 (1.36, 5.44) for C-X-C motif chemokine 13 (CXCL13), 2.63 (1.32, 5.23) for amphiregulin (AREG), and 3.59 (95% CI: 1.58, 8.19) for mesothelin (MSLN). These results were no longer statistically significant after adjusting for multiple comparisons. Results from integrative network analysis using xMWAS suggested that the candidate protein markers were associated with distinct subsets of metabolites, forming single-protein-multiple metabolite clusters (|r|>0.3, p < 0.05). Conclusions: While our results should be interpreted with caution, if replicated in larger prospective cohorts, these findings will have translational significance, attesting to the power of high-throughput profiling of circulating protein markers in identifying breast cancer biomarkers and important pathways involved in cancer development.
Subjects
BOADICEA
Biomarker
Breast cancer
Integrative network analysis
Metabolomics
Nested case-control study
Proteomics
SDGs

[SDGs]SDG3

Publisher
Springer Science and Business Media LLC
Type
journal article

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