Abstract IA23: Lessons from a rare childhood cancer syndrome on replication repair deficiency and hypermutation
Bibliographic record
Abstract
Abstract In order to divide, cells need to replicate their DNA. Replication is done by DNA polymerase epsilon and delta (POLE and POLD1) and creates thousands of mistakes per each replication cycle. The major components safeguarding our genome against such mutations are the proofreading capacity of both polymerases and the mismatch repair (MMR) genes. Germline mutations in either POLE or the MMR genes result in the most aggressive childhood cancer syndromes with high penetrance of cancers during childhood with the hallmark of extreme hypermutation. Data from the International Replication Repair Deficiency (RRD) Consortium reveal that this phenomenon is not restricted to the rare cancer syndrome and affects 5% of childhood cancers throughout many tissues. Hypermutation is observed in up to 10% of recurrent childhood cancers and 20% of adult cancers. Recent data reveal that there are a variety of mutational signatures that are associated with each cause of RRD and hypermutation. These mutations can be traced to the germline or previous therapy. Furthermore, signatures are not restricted to SNV but can be observed by insertions and deletions in microsatellites. Animal models of RRD shed new light on the process of tumorigenesis and mutation progression in RRD cancers and their impact on inter- and intratumoral heterogeneity. Together, these data provide an Achilles heel to these tumors where immunotherapy and combinations can improve survival for patients with germline RRD and children with RRD hypermutant cancers. Novel biomarkers of response to immunotherapy provide insight into the patterns of immune and tumor interactions in these patients. Citation Format: Uri Y. Tabori. Lessons from a rare childhood cancer syndrome on replication repair deficiency and hypermutation [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr IA23.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Case report | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | medium |
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".