Concurrent gain of 17q and the <i>MYC</i> oncogene in a medullomyoblastoma
Bibliographic record
Abstract
Medullomyoblastoma (MMB) is a rare cerebellar childhood tumor containing both myoblastic and primitive neuroectodermal components. Similar to the scenario in classical medulloblastoma, which contains the primitive neuroectodermal component only, gain of sequences from the long arm of chromosome 17 (17q) and gain of the MYC gene in 8q have been implicated in the pathogenesis of MMB. Because karyotypic analysis has not previously been performed for MMB, the mechanisms behind genomic imbalances in this tumor have remained unknown. Several other central aspects of this tumor, such as histocytogenetic origin, clinical characteristics, tumor behavior and prognosis, also remain unknown. We here report neuropathological and cytogenetic features of an MMB in a 3-year-old boy. Chromosome banding analysis and multicolor karyotyping revealed a hyperdiploid karyotype including an unbalanced 1; 17 translocation and isochromosome 17q formation, both leading to gain of 17q. There were also two extra copies of chromosome 8, leading to gain of the MYC oncogene, trisomies 5 and 13, and monosomy 9. Clonal chromosome changes were present in both the myoblastic and neuroectodermal components. Our findings support the notion that MMB and classical medulloblastoma arise through similar genetic mechanisms and that the two main tissue components in MMB are clonally related.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".