Abstract B070: Chemotherapy is a major mutagen in relapsed childhood cancer
Bibliographic record
Abstract
Abstract Treatment at a young age places survivors of childhood cancers at a significantly elevated risk of developing life-threatening conditions such as cardiac dysfunction and secondary neoplasms. To better define the genomic impact of cancer therapy in children, we studied a diverse cohort of childhood tumors that had been heavily treated with multiple chemotherapies. We retrospectively collected detailed therapeutic data (including drug and dosage for each treatment cycle) for three cohorts of aggressive and hard-to-cure pediatric cancers: KiCS (The Hospital for Sick Children Toronto), ZCC (Zero Childhood Cancer, Sydney, Australia), and MSK (Memorial Sloan Kettering, New York, USA). We observed that therapy had a sizeable contribution to the mutation load in the treated samples, some of which could be detected in the form of mutational signatures. Performing a comprehensive signature analysis, we detected 69 mutational signatures, including 49 COSMIC and 20 novel signatures. We observed almost three times more exclusive signatures in treated tumors (14 vs 5 in untreated tumors). Excluding the hypermutator tumors, the difference became even more striking: 15 signatures were exclusively found in treated tumors while there were no signatures exclusive to treatment-naïve tumors. Platinum chemotherapies were the most potent DNA-damaging therapies – leading to the most somatic mutations, in the shortest time. In addition to known COSMIC platinum signatures, we found five novel putative signatures of platinum resistance. Using detailed therapy exposure data extracted from clinical charts, we found that a minimum 91 days and a burden of 0.5 mut/Mb were required to detect evidence of resistance. Nearly three quarters of the tumors passing both thresholds displayed the relevant resistance-associated signatures. Remarkably, over a third (35%) of tumors treated with platinum drugs displayed measurable resistance-associated mutations after just 12 months. This reached the 50% mark at the 33-month timepoint, then plateaued. Similar, albeit slower, trends were detected for other therapies. We also found that therapy signatures could appear at both clonal and subclonal levels as well as among clustered events. This multi-center analysis of heavily treated childhood tumors presents preliminary insights with potential to monitor drug resistance or interfere with its development. Citation Format: Mehdi Layeghifard, Nicholas Light, Erik Bergstrom, Marcos Diaz Gay, Mathepan J. Mahendralingam, Sasha Blay, Scott Davidson, Pedro L. Ballester, Rawan Hammad, Noemi Fuentes Bolanos, Shimaa Nassif, Nirav H. Thacker, Chelsea Mayoh, David Malkin, Elli Papaemmanuil, Mark J. Cowley, Anita Villani, Ludmil B. Alexandrov, Adam Shlien. Chemotherapy is a major mutagen in relapsed childhood cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr B070.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".