HG-80ISSUES IN THE MANAGEMENT OF CHILDREN WITH BRAIN TUMORS AND BIALLELIC MISMATCH GENE REPAIR DEFICIENCY SYNDROME
Bibliographic record
Abstract
Biallelic mismatch repair deficiency (bMMRD) is a rare cancer predisposition syndrome, presenting in childhood. Affected patients have café-au-lait skin lesions and develop various hematological, gastrointestinal and CNS malignancies. Although guidelines are available for surveillance, there is scarce information about optimal therapy. We report the pedigree, diagnostic studies and clinical course of a consanguinous family with four children, the index case, his sister and two first cousins, affected by the syndrome. The index case developed glioblastoma and T-cell leukemia and died from infection while in complete remission. His sister is under treatment for a high-grade glioma, and his two first-cousins died of their brain cancer. DNA from peripheral blood, saliva and buccal swabs, skin biopsies and paraffin blocks from tumor tissue were used for genetic testing. Both tumor and normal tissue were stained for the presence of the MMR proteins through immunohistochemistry and revealed absence of the PMS2 protein in both tissues. Molecular analysis was performed using Sanger sequencing and MLPA of the 4 MMR genes. A pathogenic, heterozygous mutation was identified in the PMS2 gene (exon15del c.2446-?_2589 + ?del) in the affected children and their fathers. Review of the clinical course of the index case revealed increased morbidity and toxicity compared to other children undergoing therapy on the same protocol. We suggest more adapted treatment protocols for these patients. This family illustrates difficulties encountered in the diagnosis, surveillance and choice of therapy for children affected with bMMRD and the need for increased awareness and more information about this rare but important syndrome.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".