A large germline deletion in the Chek2 kinase gene is associated with an increased risk of prostate cancer
Bibliographic record
Abstract
BACKGROUND: Germline mutations in the Chek2 kinase gene (CHEK2) have been associated with a range of cancer types. Recently, a large deletion of exons 9 and 10 of CHEK2 was identified in several unrelated patients with breast cancer of Czech or Slovak origin. The geographical and ethnic extent of this founder allele has not yet been determined. PARTICIPANTS AND METHODS: We assayed for the presence of this deletion, and of three other CHEK2 founder mutations, in 1864 patients with prostate cancer and 5496 controls from Poland. RESULTS: The deletion was detected in 24 of 5496 (0.4%) controls from the general population, and is the most common CHEK2 truncating founder allele in Polish patients. The deletion was identified in 15 of 1864 (0.8%) men with unselected prostate cancer (OR 1.9; 95% CI 0.97 to 3.5; p = 0.09) and in 4 of 249 men with familial prostate cancer (OR 3.7; 95% CI 1.3 to 10.8; p = 0.03). These ORs were similar to those associated with the other truncating mutations (IVS2+1G-->A, 1100delC). CONCLUSION: A large deletion of exons 9 and 10 of CHEK2 confers an increased risk of prostate cancer in Polish men. The del5395 founder deletion might be present in other Slavic populations, including Ukraine, Belarus, Russia, Baltic and Balkan countries. It will be of interest to see to what extent this deletion is responsible for the burden of prostate cancer in other populations.
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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".