Estrogen receptor (ER)-positive/progesterone receptor (PR)-positive invasive ductal carcinoma accounts for ~45 % of invasive breast cancer (BC) diagnoses in the U.S. Despite reductions in BC mortality attributable to mammography screening and adjuvant hormonal therapy, an important challenge remains the development of clinically useful blood-based biomarkers for risk assessment and early detection. The objective of this study was to identify novel protein markers for ER+/PR+ ductal BC. A nested case-control study was conducted within the Women's Health Initiative observational study. Pre-clinical plasma specimens, collected up to 12.5 months before diagnosis from 121 cases and 121 matched controls, were equally divided into training and testing sets and interrogated using a customized antibody array targeting >2000 proteins. Statistically significant differences (P < 0.05) in matched case versus control signals were observed for 39 candidates in both training and testing sets, and four markers (CSF2, RYBP, TFRC, ITGB4) remained significant after Bonferroni correction (P < 2.03 × 10(-5)). A multivariate modeling procedure based on elastic net regression with Monte Carlo cross-validation achieved an estimated AUC of 0.75 (SD 0.06). Most candidates did not overlap with those described previously for triple-negative BC, suggesting sub-type specificity. Gene set enrichment analyses identified two GO gene sets as upregulated in cases-microtubule cytoskeleton and response to hormone stimulus (P < 0.05, q < 0.25). This study has identified a pool of novel candidate plasma protein biomarkers for ER+/PR+ ductal BC using pre-diagnostic biospecimens. Further validation studies are needed to confirm these candidates and assess their potential clinical utility for BC risk assessment/early detection.
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http://dx.doi.org/10.1007/s10549-015-3554-5 | DOI Listing |
Biomed Phys Eng Express
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Shandong University of Traditional Chinese Medicine, Qingdao Academy of Chinese Medical Sciences, Jinan, Shandong, 250355, CHINA.
Mild cognitive impairment (MCI) is a significant predictor of the early progression of Alzheimer's disease, and it can be used as an important indicator of disease progression. However, many existing methods focus mainly on the image itself when processing brain imaging data, ignoring other non-imaging data (e.g.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
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View Article and Find Full Text PDFJMIR Hum Factors
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New College of Florida, Sarasota, FL, United States.
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Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts.
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Eur Thyroid J
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D Yabe, Department of Diabetes, Endocrinology and Nutrition, Kyoto University Graduate School of Medicine Faculty of Medicine, Kyoto, Japan.
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