Abstract C020: Novel insights from the investigation of experimental mutational signatures in early-onset colorectal cancer and colonic polyps
Bibliographic record
Abstract
Abstract Introduction: Profiling colorectal cancers (CRCs) for tumor mutational signatures (TMS) offers new opportunities to characterize molecular subtypes. Recently, COSMIC published a comprehensive set of experimental mutational signatures that directly link specific environmental exposures to mutational patterns observed in human cancers. Environmental exposures are recognized as major contributors to CRC development and have been hypothesized to drive the recent rise in early-onset CRC (EOCRC), but the molecular fingerprints of these exposures in EOCRCs have not been systematically characterized. Methods: We performed whole exome sequencing (WES) on tumor and matched blood-derived DNA from 324 non-hereditary, mismatch repair proficient early-onset samples (diagnosed <55 years of age) comprising 277 CRCs and 47 pre-malignant polyps. Mutational signatures were calculated using a novel approach that combined COSMIC v3.4 signatures previously observed in CRC (n=26) and a curated set of experimental mutational signatures (n=50). Environmental signatures were filtered to human iPSC-derived signatures, excluding those with a negative AMES test, those marked as controls, and signatures not seen previously in CRC. Signature definitions with >95% cosine similarity were merged. Results: On average, 24.7% ± 10.1% (mean ± s.d, range 0.1%-60.1%) of somatic mutations were assigned to environmental signatures. Across the cohort, 14% (46/324) exhibited a dominant environmental signature, with N-nitrosopyrrolidine being the most prevalent (6.2%, 20/324). Premalignant lesions showed higher rates of dominant environmental signatures (21%, 10/47) compared to invasive cancers, suggesting environmental exposures may be a key component in early carcinogenesis. Conclusions: This study provides a comprehensive view of the landscape of mutational processes in non-hereditary mismatch repair proficient EOCRC and early-onset polyps through assessment of both tumor mutational signatures and experimental mutational signatures. Environmental exposures represent a significant component of the mutational landscape in early-onset colorectal neoplasia, with enhanced prevalence in premalignant lesions. These findings support the likely role of environmental drivers in the rising incidence of EOCRC. Citation Format: Peter Georgeson, Alysha Prisc, Jihoon Joo, Khalid Mahmood, Romy Walker, Mark Clendenning, Julia Como, Natalie Diepenhorst, Julie McDonald, Steven Gallinger, Robert Grant, Dylan E. O’Sullivan, Darren R. Brenner, Finlay Macrae, Christophe Rosty, Ingrid M. Winship, Mark A. Jenkins, Daniel D. Buchanan. Novel insights from the investigation of experimental mutational signatures in early-onset colorectal cancer and colonic polyps [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 C020.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".