Abstract B006: Tissue-specific mutational outcomes underlying the late effects of anthracyclines on tumours, blood, and heart
Bibliographic record
Abstract
Abstract Motivation: Anthracyclines, a cornerstone chemotherapy, disproportionately contributes to several late effects burdening survivors of cancer, including cancer relapse, therapy-related blood cancers, and fatal cardiotoxicity. Despite decades of clinical use, the mechanisms underlying these late effects – particularly how anthracyclines damage the genome of various tissues (tumours, blood, and heart) – remain poorly understood. Methods: We assembled a cohort of untreated or anthracycline-treated tumour, blood, and heart samples. Tumours and blood were leveraged from childhood cancer patients enrolled in the SickKids Cancer Sequencing Program. Heart samples were obtained from cancer survivors who received anthracyclines and later developed severe cardiotoxicity that required a heart transplant. We sequenced the DNA of each tissue type to identify anthracycline-induced somatic mutations. Results: Our initial results revealed minimal genome-wide mutational differences between anthracycline-treated versus untreated samples across all tissue types. We hypothesized that anthracyclines may instead alter the topography, rather than burden, of somatic mutations. Indeed, we found that anthracycline-treated tissues had a strong enrichment of somatic mutations in open chromatin of their respective cell of origin. Anthracycline-treated tumours had a unique enrichment of single nucleotide variants, especially C>T mutations, in promoters and introns. Open chromatin promoter regions demonstrated a unique enrichment for C[C>T]G mutations, reminiscent of a thiopurine signature seen in relapsed acute lymphoblastic leukemia. To validate these findings, we generated and sequenced doxorubicin resistant cancer cell lines, which confirmed that anthracycline-induced somatic mutations preferentially occur in open chromatin regions. Despite the heart’s non-proliferative capacity, anthracycline-treated hearts had a significant enrichment of insertion-deletions in fetal cardiomyocyte open chromatin and non-B DNA regions. However, we did not find any exonic mutations in anthracycline-treated hearts, suggesting that disruption of the non-coding genome results in cardiotoxicity. Unexpectedly, we did not find any enrichment of somatic mutations in open chromatin regions for anthracycline-treated blood samples. Lastly, comparative analysis of the somatic mutational profiles of anthracycline-exposed hearts, tumours, and blood samples, we uncovered previously underappreciated tissue-specific mutational signatures. Significance: This study is the first to characterize the tissue-specific genomic consequences of anthracyclines on tumours, blood, and heart. We establish a foundation for developing tissue-specific mutational signatures as predictive biomarkers for the late effects. The early identification of high-risk patients will transform survivorship care, ensuring children with cancer do not merely survive their diagnosis – they thrive beyond it. Citation Format: Mathepan Jeya Mahendralingam, Mehdi Layeghifard, Burçak Otlu, Timmy Wen, Yael Babichev, Syed Kashif Daud, Shreya Gramolini, Rebecca Gladdy, Anita Villani, Seema Mital, Filio Billia, Adam Shlien. Tissue-specific mutational outcomes underlying the late effects of anthracyclines on tumours, blood, and heart [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Discovery and Innovation in Pediatric Cancer— From Biology to Breakthrough Therapies; 2025 Sep 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl_2):Abstract nr B006.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".