Role of Secreted Frizzled-Related Protein 1 in Early Mammary Gland Tumorigenesis and Its Regulation in Breast Microenvironment
Bibliographic record
Abstract
In mice, the lack of secreted frizzled-related protein 1 (SFRP1) is responsible for mammogenesis and hyperplasia, while, in bovines, its overexpression is associated with post-lactational mammary gland involution. Interestingly, there are no reports dealing with the role of SFRP1 in female involution. However, SFRP1 dysregulation is largely associated with human tumorigenesis in the literature. Indeed, the lack of SFRP1 is associated with both tumor development and patient prognosis. Considering the increased risk of breast tumor development associated with incomplete mammary gland involution, it is crucial to demystify the “grey zone” between physiological age-related involution and tumorigenesis. In this review, we explore the functions of SFRP1 involved in the breast involution processes to understand the perturbations driven by the disappearance of SFRP1 in mammary tissue. Moreover, we question the presence of recurrent microcalcifications identified by mammography. In bone metastases from prostate primary tumor, overexpression of SFRP1 results in an osteolytic response of the tumor cells. Hence, we explore the hypothesis of an osteoblastic differentiation of mammary cells induced by the lack of SFRP1 during lobular involution, resulting in a new accumulation of hydroxyapatite crystals in the breast tissue.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".