Abnormal <scp>DNA</scp> Methylation Profile Suggests the Extension of the Clinical Spectrum of the <scp><i>SETD2</i></scp>‐Related Disorders to a Syndromic Multiple Tumor Phenotype
Bibliographic record
Abstract
SETD2 has an essential role in epigenetic regulation. SETD2 pathogenic variants cause neurodevelopmental disorders (SETD2-NDDs) that most commonly include various degrees of intellectual disability and behavioral disorders, macrocephaly, brain malformations, and generalized overgrowth. A distinctive DNA methylation episignature has been identified for Luscan-Lumish syndrome. A less common phenotype, denoted SETD2-NDD with multiple congenital anomalies, failure to thrive, and profound intellectual disability, has been reported in association with a particular pathogenic variant (p.Arg1740Trp). To date, about 50 patients have been described in the literature with SETD2 causative variants. We report here an individual with a phenotype distinct from SETD2-NDDs, including normal cognition, distinctive facial features, and multiple tumor histories, including a sacral osteoblastoma at age 7, a benign femoral bone tumor at age 17, a peritoneal pseudomyxoma at age 27, and a hypophyseal macroadenoma and a low-grade optochiasmatic glioma at age 37 years. Trio exome sequencing identified a de novo heterozygous missense variant of unknown significance (p.Ser1658Leu) in the SETD2 gene. DNA methylation study by EpiSign assay confirmed the presence of an episignature profile compatible with SETD2-related disorders. Given the implication of somatic SETD2 variants in benign and malignant tumors, the implication of these SETD2 constitutional variants in tumorigenesis is discussed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".