Abstract P037: Association between circulating osteoprotegerin levels and estimated risk of <i>BRCA1</i>-associated breast cancer
Notice bibliographique
Résumé
Abstract Purpose: Dysregulation of the receptor activator of nuclear factor κB (RANK) pathway may contribute to the pathogenesis of BRCA1-associated breast cancer. Specifically, lower levels of osteoprotegerin (OPG), an endogenous inhibitor of RANK-ligand (RANKL) that competes with RANK for RANKL binding, have been reported among women with pathogenic or likely pathogenic variant (mutation) in the BRCA1 gene. It has been suggested that lower OPG levels may be associated with an increased risk of breast cancer, proposing that OPG may serve as a biomarker for breast cancer risk. Whether OPG is associated with estimated breast cancer risk remains unknown. The goal of this study was to evaluate the relationship between OPG and the estimated risk of breast cancer in women with a BRCA1 mutation. Methods: Women were eligible for inclusion if they had a BRCA1 mutation, were between ages 18 and 79, had a pedigree, had no prior history of cancer, had not undergone prophylactic bilateral mastectomy and provided a blood sample available for OPG analysis. Detailed information on various risk factors (i.e., reproductive, hormonal, family history) was collected using biennial questionnaires. An enzyme-linked immunosorbent assay was used to quantify serum OPG levels (pg/mL). Risk of breast cancer was estimated using Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm version 6 incorporated in the CanRisk tool. The relationship between OPG and estimated lifetime (up to age 80) and ten-year (age 40–50) risks of breast cancer was evaluated using quantile regression analyses. Analyses were further stratified by age (≤50 vs &gt;50 years). Results: A total of 539 women were included in the analysis. The median age at blood collection was 39 years (18–77 years). For lifetime breast cancer risk, a 1 standard deviation (SD; 38.40 pg/ml) increase in OPG level was associated with a 5.4% lower risk at the 25th percentile (P ≤ 0.001), a 4.2% lower risk at the 50th percentile (P ≤ 0.001), and a 1.5% lower risk at the 75th percentile (P ≤ 0.001). For ten-year breast cancer risk, a 1 SD increase in OPG level was associated with a 1.2% lower risk at the 25th percentile (P ≤ 0.001), a 0.8% lower risk at the 50th percentile (P ≤ 0.001), and a 0.8% lower risk at the 75th percentile (P = 0.005). The association between OPG and both estimated risks did not vary in the analysis stratified by age (≤50 vs &gt;50 years). Conclusion: Higher circulating OPG levels were associated with significantly lower estimated lifetime and ten-year risks of BRCA1-associated breast cancer. These associations were stronger for women at a lower risk of developing lifetime breast cancer. Further research is needed to determine whether integrating circulating OPG levels can improve existing risk prediction models. These data contribute to ongoing interest in the role of RANK signaling in mammary tumorigenesis. Inhibiting RANK signaling may therefore be a potential target for breast cancer prevention in women with a BRCA1 mutation and other high-risk populations. Citation Format: Sarah S. Park, Tasnim Zaman, Shana J. Kim, Jennifer D. Brooks, Andy K. O. Wong, Jan Lubiński, Steven A. Narod, Leonardo Salmena, Joanne Kotsopoulos. Association between circulating osteoprotegerin levels and estimated risk of BRCA1-associated breast cancer. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P037.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».