Association of PHB 1630 C>T and MTHFR 677 C>T polymorphisms with breast and ovarian cancer risk in BRCA1/2 mutation carriers: results from a multicenter study
Bibliographic record
Abstract
BACKGROUND: The variable penetrance of breast cancer in BRCA1/2 mutation carriers suggests that other genetic or environmental factors modify breast cancer risk. Two genes of special interest are prohibitin (PHB) and methylene-tetrahydrofolate reductase (MTHFR), both of which are important either directly or indirectly in maintaining genomic integrity. METHODS: To evaluate the potential role of genetic variants within PHB and MTHFR in breast and ovarian cancer risk, 4102 BRCA1 and 2093 BRCA2 mutation carriers, and 6211 BRCA1 and 2902 BRCA2 carriers from the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA) were genotyped for the PHB 1630 C>T (rs6917) polymorphism and the MTHFR 677 C>T (rs1801133) polymorphism, respectively. RESULTS: There was no evidence of association between the PHB 1630 C>T and MTHFR 677 C>T polymorphisms with either disease for BRCA1 or BRCA2 mutation carriers when breast and ovarian cancer associations were evaluated separately. Analysis that evaluated associations for breast and ovarian cancer simultaneously showed some evidence that BRCA1 mutation carriers who had the rare homozygote genotype (TT) of the PHB 1630 C>T polymorphism were at increased risk of both breast and ovarian cancer (HR 1.50, 95%CI 1.10-2.04 and HR 2.16, 95%CI 1.24-3.76, respectively). However, there was no evidence of association under a multiplicative model for the effect of each minor allele. CONCLUSION: The PHB 1630TT genotype may modify breast and ovarian cancer risks in BRCA1 mutation carriers. This association need to be evaluated in larger series of BRCA1 mutation carriers.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".