Confirmation of 5p12 As a Susceptibility Locus for Progesterone-Receptor–Positive, Lower Grade Breast Cancer
Bibliographic record
Abstract
BACKGROUND: The single-nucleotide polymorphism (SNP) 5p12-rs10941679 has been found to be associated with risk of breast cancer, particularly estrogen receptor (ER)-positive disease. We aimed to further explore this association overall, and by tumor histopathology, in the Breast Cancer Association Consortium. METHODS: Data were combined from 37 studies, including 40,972 invasive cases, 1,398 cases of ductal carcinoma in situ (DCIS), and 46,334 controls, all of white European ancestry, as well as 3,007 invasive cases and 2,337 controls of Asian ancestry. Associations overall and by tumor invasiveness and histopathology were assessed using logistic regression. RESULTS: For white Europeans, the per-allele OR associated with 5p12-rs10941679 was 1.11 (95% CI = 1.08-1.14, P = 7 × 10(-18)) for invasive breast cancer and 1.10 (95% CI = 1.01-1.21, P = 0.03) for DCIS. For Asian women, the estimated OR for invasive disease was similar (OR = 1.07, 95%CI = 0.99-1.15, P = 0.09). Further analyses suggested that the association in white Europeans was largely limited to progesterone receptor (PR)-positive disease (per-allele OR = 1.16, 95% CI = 1.12-1.20, P = 1 × 10(-18) vs. OR = 1.03, 95% CI = 0.99-1.07, P = 0.2 for PR-negative disease; P(heterogeneity) = 2 × 10(-7)); heterogeneity by ER status was not observed (P = 0.2) once PR status was accounted for. The association was also stronger for lower grade tumors [per-allele OR (95% CI) = 1.20 (1.14-1.25), 1.13 (1.09-1.16), and 1.04 (0.99-1.08) for grade 1, 2, and 3/4, respectively; P(trend) = 5 × 10(-7)]. CONCLUSION: 5p12 is a breast cancer susceptibility locus for PR-positive, lower grade breast cancer. IMPACT: Multicenter fine-mapping studies of this region are needed as a first step to identifying the causal variant or variants.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".