Germline Mutations in the Kallikrein 6 Region and Predisposition for Aggressive Prostate Cancer
Bibliographic record
Abstract
Background: There is a need for markers that can specifically identify individuals at increased risk of harboring aggressive forms of prostate cancer (PCa). Methods: We surveyed the Kallikrein ( KLK ) region ( KLK 1-15) for single-nucleotide polymorphisms (SNPs) associated with aggressive PCa (Gleason Score ≥ 8) in 1858 PCa patients. Discovery cohorts (Swiss arm of the European Randomized Study of Screening for PCa, n = 379; Toronto, Canada, n = 540) and a validation cohort (Prostate, Lung, Colorectal and Ovarian [PLCO] screening trial, n = 939) were analyzed. Fine-mapping within the KLK region was carried out by genotyping and imputation in the discovery cohort, whereas PLCO data were provided through database of Genotypes and Phenotypes ( dbGaP ). The influence of SNPs of interest on biochemical-free survival was evaluated in a cohort of localized PCa from the International Cancer Genome Consortium (ICGC; n = 130) analyzed with next-generation sequencing. Single- and multi-SNP association studies, as well as haplotype analyses, were performed. All statistical tests were two-sided. Results: Several SNPs in very strong linkage disequilibrium in the KLK 6 region and located within the same haplotype (rs113640578, rs79324425, rs11666929, rs28384475, rs3810287), identified individuals at increased risk of aggressive PCa in both discovery (odds ratio [OR] = 3.51-3.64, 95% confidence interval [CI] = 2.01 to 6.36, P = 1.0x10 -5 -8.4x10 -6 ) and validation (OR = 1.89-1.96, 95% CI = 0.99 to 3.71, P = .04-.05) cohorts. The overall test of haplotype association was highly statistically significant in each cohort ( P = 3.5x10 -4 and .006, respectively) and in the three data sets combined ( P = 2.3x10 -5 ). These germline SNPs independently predicted relapse in the ICGC cohort (hazard ratio = 3.15, 95% CI = 1.57 to 6.34, P = .001). Conclusions: Our fine-mapping study has identified novel loci in the KLK 6 region strongly associated with aggressive PCa.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".