Abstract C010: Association of a germline KDM3C polymorphism with early cancer diagnosis
Bibliographic record
Abstract
Abstract Background: The rise in early-onset cancers remains an urgent challenge, with multiple genetic, environmental, and lifestyle factors likely contributing. We have identified a single nucleotide polymorphism (SNP) in KDM3C/JMJD1C, a histone demethylase required for DNA damage repair, that correlates with chemoradiotherapy response and is associated with defective double-strand break repair across multiple cellular models. We hypothesized that carriers of this SNP develop genomic instability earlier in life, predisposing them to younger ages at cancer diagnosis. Methods: As the SNP is common in the population, we analyzed data from the United Kingdom Biobank (UKB), a prospective cohort of 501,946 participants (ages 40–69 at recruitment, 2006–2010; 30-year follow-up planned). Descriptive statistics (median, proportion) were used to describe baseline characteristics of the exposed and unexposed groups in the UKB. Cancer sub-cohorts were derived from the UKB Cancer Register, clustered by ICD10 code, and stratified by age <45 vs ≥45 years. Associations between SNP (absent, heterozygous, and homozygous) status and cancer diagnosis were evaluated using contingency tables, risk ratios (RR), and chi-square tests (α=0.05). Results: The UK Biobank cohort included 501,946 participants (median age 58; 54% female), of whom 10% were <45 years of age at recruitment. The homozygous SNP was present in 56% of the overall cohort. Homozygosity for SNP varied by genetic ancestry (58% White, 11% Black, 12% Chinese populations). The cancer register cohort included 117,409 patients (median diagnosis age 63.7; 7% <45 years). Compared with the absence of SNP, heterozygosity was not associated with increased risk of cancer overall (p=0.95). Compared with the absence of SNP, homozygosity was associated with increased risk of cancer overall (RR=1.02; p=0.0065) and in those <45 years (RR=1.07; p=0.029), but not ≥45 years (p=0.16). Among cancer sub-cohorts, homozygosity was associated with increased risk of skin cancer at all ages (RR=1.14; p<0.05) and was not associated with cervical carcinoma in situ (p=0.63). In patients age <45, the association with skin cancer strengthened (RR=1.22; p=0.02), and homozygosity became significantly associated with cervical carcinoma in situ (RR=1.28; p=0.03). Conclusion: These findings suggest that the KDM3C SNP may predispose to early-onset cancers, particularly skin and cervical cancers. Given the rising incidence of early-onset cancers, integrating KDM3C SNP status into risk stratification may enhance early detection and prevention strategies, though validation in independent cohorts will be essential. Citation Format: Zachary AC. Kiss, Adria Hasan, Raksha Shastry, Elena V. Demidova, Philip Czyzewicz, Yan Zhou, Johnathan Whetstine, Joshua E. Meyer, Sanjeevani Arora. Association of a germline KDM3C polymorphism with early cancer diagnosis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr C010.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.010 | 0.001 |
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".