Genetic Variation in the Chromosome 17q23 Amplicon and Breast Cancer Risk
Bibliographic record
Abstract
BACKGROUND: Gene amplification leading to overexpression is a common event in breast tumors that is linked to tumor development and progression. The 17q23 region is amplified in >40% of breast tumors and contains several candidate oncogenes. Because common genetic variation in several oncogenes has been associated with cancer risk, we assessed the relevance of common variants in the 17q23 candidate oncogenes to breast cancer. METHODS: We investigated 60 polymorphisms in the TUBD1, SEPT4, PRKCA, TBX2, TBX4, TEX14, TLK2, YPEL2, and PPM1E genes from this amplicon for association with breast cancer risk among 798 Caucasian breast cancer cases and 843 unaffected Caucasian controls from the Mayo Clinic. RESULTS: Eight polymorphisms in PRKCA, TBX4, TLK2, and YPEL2 displayed significant dose-response associations with breast cancer risk (P(trend) < 0.05). Of these, PRKCA rs7342847 and TLK2 rs2245092 and rs733025 were also associated with hormone receptor-positive breast cancer: PRKCA rs7342847 (odds ratio, 0.7; 95% confidence interval, 0.6-0.9; P(trend) = 0.002) and TLK2 rs733025 and rs2245092 (both: odds ratio, 0.8; 95% confidence interval, 0.7-1.0; P(trend) = 0.03). Interactions between SEPT4 rs758377 and TEX14 rs302864 (P(interaction) = 0.0003) and between TLK2 rs733025 and YPEL2 rs16943468 (P(interaction) = 0.05) for risk of breast cancer were also observed. CONCLUSION: These findings suggest that single polymorphisms and combinations of polymorphisms within candidate oncogenes from the 17q23 amplicon may influence risk of breast cancer overall and possibly specific molecular subtypes of breast tumors. The findings are discussed within the context of the results from two independent data sets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".