ArticleBreast cancer research : BCR2025
The plasma proteome and breast cancer risk.
Article in Breast cancer research : BCR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Proteomic Biomarker Discovery in Breast Cancer: Advances, Challenges, and Translational Prospects.Journal of biochemical and molecular toxicology · 2026Review
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Authors and funding
7 authors.
Funding
Abstract
backgroundPlasma 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.
methodsWe 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.
resultsWe 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).
conclusionsWhile 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.
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