Papillary Tumor of the Pineal Region Identified by DNA Methylation Leads to the Incidental Finding of Germline Mutation PTEN G132D Associated with PTEN Hamartoma Tumor Syndrome: A Case Report and Systematic Review
Bibliographic record
Abstract
Distinct subgroups of rare brain tumors can be molecularly classified using whole genome DNA methylation profiling and next-generation sequencing. Furthermore, these tools can identify germline mutations contributing to carcinogenesis. Access to molecular testing in the clinical setting is vital for pathology laboratories to make an accurate diagnosis. One molecularly unique brain tumor requiring such tools is the papillary tumor of the pineal region (PTPR). Herein, we present a case report of a 21-year-old male presenting with macrocephaly and obstructive hydrocephalus due to the PTPR. Next-generation sequencing identified a pathogenic PTEN p.G132D mutation in the tumor and matched germline findings further identified PTEN Hamartoma Tumor Syndrome (PHTS). The case report tumor was initially misdiagnosed as ependymoma while methylation profiling classified it more specifically as a PTPR, Group B. To better understand the current status of PTPRs, we conducted a systematic review of recent cases reporting on the diagnostics, treatments, and outcomes for PTPR patients. To our knowledge, this is the first case report for PTPRs revealing an association with PHTS. Our review revealed inconsistencies in diagnostics, treatments, and outcomes for PTPR, and an underutilization of definitive molecular testing.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".