Recurrent, bilateral, and metastatic pheochromocytoma in a young patient with Beckwith-Wiedemann syndrome: A genetic link?
Bibliographic record
Abstract
Beckwith-Wiedemann syndrome (BWS) is a genetic disorder at chromosome 11p15 that leads to increased activity of insulin-like growth factor-2 (IGF2) and reduced activity, with no active copy of the inhibitor of cell proliferation, CDKN1C, resulting in excessive growth and increased risk of tumour formation. Isolated cases of patients with Beckwith-Wiedemann syndrome and pheochromocytoma are reported in the literature; however, none have described a molecular or cytogenetic evaluation for associated genetic abnormalities.We present a case of an adolescent female with Beckwith-Wiedemann syndrome who developed recurrent, bilateral, and metastatic pheochromocytoma despite low-risk histopathology. Genotyping studies, which evaluated for genetic predisposition to pheochromocytoma or paraganglioma (PHEO/PGL), including the PGLNext sequencing panel of 12 associated genes, and a whole genome comparative genome hybridization microarray, were performed. Genomic studies were unexpectedly negative. Additionally, the histopathology of the PHEO/PGL of our patient had low-risk features, which is unusual in cases of metastases, occurring in less than 4% of cases.1 This case suggests that the BWS in itself could predispose to formation of a PHEO/PGL phenotype with aggressive behaviour. The following manuscript summarizes the case report, reviews pertinent literature, and proposes a possible mechanism for this association.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".