An infant with <scp><i>MLH</i></scp><i>3</i> variants, <scp><i>FOXG</i></scp><i>1</i>‐duplication and multiple, benign cranial and spinal tumors: A clinical exome sequencing study
Bibliographic record
Abstract
A 4-month-old male infant presented with severe developmental delay, cerebellar, brainstem, and cutaneous hemangiomas, bilateral tumors (vestibular, hypoglossal, cervical, and lumbar spinal), and few café-au-lait macules. Cerebellar and lumbar tumor biopsies revealed venous telangiectasia and intraneural perineuroma, respectively. Sequencing NF1, NF2, and RASA1 (blood), and NF2 and SMARCB1 (lumbar biopsy) was negative for pathogenic mutations. Clinical exome sequencing (CES), requested for tumor syndrome diagnosis, revealed two heterozygous missense variants, c.359T>C;p.Phe120Ser and c.3344G>A;p.Arg1115Gln, in MLH3 (NM_001040108.1), a DNA mismatch repair (MMR) gene, Polyphen-predicted as probably damaging, and benign, respectively. Sanger sequencing confirmed both variants in the proband, and their absence in the mother; biological father unavailable. Both biopsied tissues were negative for microsatellite instability, and expressed MLH1, MSH2, PMS2, MSH6, and MLH3 immunohistochemically. Chromosomal microarray showed a 133 kb segment copy number duplication of 14q12 region encompassing FOXG1, possibly explaining the developmental delay, but not the tumors. The presence of MLH3 variants with multiple benign neural and vascular tumors was intriguing for their possible role in the pathogenesis of these neoplasms, which were suspicious for, but not diagnostic of, constitutional MMR deficiency. However, functional assays of non-neoplastic patient-derived cells showed intact base-base MMR function. Also, no previous FOXG1-aberrant patient was reported with tumors. We now report a 3-year-old FOXG1-duplicated patient with a yet undescribed tumor syndrome with clinical features of neurofibromatosis types I and II, where several validation studies could not ascertain the significance of CES findings; further studies may elucidate precise mechanisms and diagnosis for clinical management, including tumor surveillance.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".