Germline MUTYH Mutation in a Pediatric Cancer Survivor Developing a Secondary Malignancy
Bibliographic record
Abstract
Radiotherapy-induced second malignant neoplasms (SMNs) are a severe late complication in pediatric cancer survivors. Germline mutations in tumor suppressor genes contribute to SMNs; however, the most relevant germline variants mediating susceptibility are not fully defined. The authors performed matched whole-exome sequencing analyses of germline and tumor DNA from 4 pediatric solid tumor survivors who subsequently developed radiation-associated SMNs. Pathogenic and predicted deleterious germline variants were identified for each patient and validated with Sanger sequencing. These germline variants were compared with germline variants in a cohort of 59 pediatric patients diagnosed with primary sarcomas. Pathway analysis was performed to test for similarities in the germline variant profiles between individuals diagnosed with SMNs or primary sarcomas. One index patient was found to have a pathogenic germline monoallelic mutation in the MUTYH gene, which encodes the base excision repair enzyme adenine DNA glycosylase. This specific germline mutation is associated with a form of familial adenomatous polyposis, a new diagnosis in the patient. Germline-level genetic similarity exists between SMN-developing patients and patients developing primary sarcomas, with relevant genes involved in signal transduction and DNA repair mechanisms. The authors identify a germline MUTYH mutation in a pediatric cancer survivor developing an SMN. Germline mutations involving specific pathways such as base excision repair may identify individuals at risk for developing SMNs. The composition of germline variants in individual patients may enable estimates of patient-specific risk for developing SMNs. The authors anticipate that further analyses of germline genomes and epigenomes will reveal diverse genes and mechanisms influencing cancer risk.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".