Synchronous T-lymphoblastic lymphoma and neuroblastoma in a 3-yr-old with novel germline<i>SMARCA4</i>and<i>EZH2</i>variants
Bibliographic record
Abstract
T-lymphoblastic lymphoma (T-LLy) is the most common lymphoblastic lymphoma in children and often presents with a mediastinal mass. Lymphomatous suprarenal masses are possible but rare. Here, we discuss the case of a previously healthy 3-yr-old male who presented with mediastinal T-LLy with bilateral suprarenal masses. Following initial treatment, surgical biopsy of persisting adrenal masses revealed bilateral neuroblastoma (NBL). A clinical genetics panel for germline cancer predisposition did not identify any pathogenic variants. Combination large panel (864 genes) profiling analysis in the context of a precision oncology study revealed two novel likely pathogenic heterozygous variants:SMARCA4c.1420-1G > T p.? andEZH2c.1943G > C p.(Ile631Phefs*44). Somatic analysis revealed potential second hits/somatic variants inEZH2(in the T-LLy) and a segmental loss in Chromosome 19p encompassingSMARCA4(in the NBL). Synchronous cancers, especially at a young age, warrant genetic evaluation for cancer predisposition; enrollment in a precision oncology program assessing germline and tumor DNA can fulfill that purpose, particularly when standard first-line genetic testing is negative and in the setting of tumors that are not classic for common cancer predisposition syndromes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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, 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".