A Novel Locus on 6p21.2 for Cancer Treatment–Induced Cardiac Dysfunction Among Childhood Cancer Survivors
Bibliographic record
Abstract
BACKGROUND: Adult survivors of childhood cancer are at increased risk of cardiac late effects. METHODS: Using whole-genome sequencing data from 1870 survivors of European ancestry in the St. Jude Lifetime Cohort (SJLIFE) study, genetic variants were examined for association with ejection fraction (EF) and clinically assessed cancer therapy-induced cardiac dysfunction (CCD). Statistically significant findings were validated in 301 SJLIFE survivors of African ancestry and 4020 survivors of European ancestry from the Childhood Cancer Survivor Study. All statistical tests were 2-sided. RESULTS: A variant near KCNK17 showed genome-wide significant association with EF (rs2815063-A: EF reduction = 1.6%; P = 2.1 × 10-8) in SJLIFE survivors of European ancestry, which replicated in SJLIFE survivors of African ancestry (EF reduction = 1.5%; P = .004). The rs2815063-A also showed a 1.80-fold (P = .008) risk of severe or disabling or life-threatening CCD and replicated in 4020 Childhood Cancer Survivor Study survivors of European ancestry (odds ratio = 1.40; P = .04). Notably, rs2815063-A was specifically associated among survivors exposed to doxorubicin only, with a stronger effect on EF (3.3% EF reduction) and CCD (2.97-fold). Whole blood DNA methylation data in 1651 SJLIFE survivors of European ancestry showed statistically significant correlation of rs2815063-A with dysregulation of KCNK17 enhancers (false discovery rate <5%), which replicated in 263 survivors of African ancestry. Consistently, the rs2815063-A was associated with KCNK17 downregulation based on RNA sequencing of 75 survivors. CONCLUSIONS: Leveraging the 2 largest cohorts of childhood cancer survivors in North America and survivor-specific polygenomic functional data, we identified a novel risk locus for CCD, which showed specificity with doxorubicin-induced cardiac dysfunction and highlighted dysregulation of KCNK17 as the likely molecular mechanism underlying this genetic association.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".