GCT-09. Transcriptome and methylome profiles of CNS germ cell tumors and their comparison with testicular counterpart
Bibliographic record
Abstract
Abstract BACKGROUND: The pathophysiology of CNS germ cell tumors (GCTs) has yet to be fully unraveled, resulting in the paucity of treatment options. The biological comparison with its testicular counterpart has not been interrogated. METHODS: In total, 84 cases of CNS GCT were investigated for methylation and transcriptome analyses, and an integrative analysis of the normal cells undergoing embryogenesis and testicular GCTs was conducted. RESULTS: Transcriptome analysis revealed germinoma and non-germinomatous GCTs (NGGCTs) were clearly separated. On transcriptome, germinoma was characterized by primitive cell state, closely related to primordial germ cell (PGC) with meiosis/mitosis potentials. NGGCT had a feature of more differentiated cell state directed toward organogenesis. Germinoma was subdivided into two clusters on integrated transcriptome and methylation analysis, and they are different in the age distribution and tumor cell content. CNS and testicular GCTs were divided based on histology, either germinoma/seminoma or NGGCT/non-seminomatous GCTs on methylation. Expression analysis mainly clustered them depending on the site of origin and histology. CONCLUSIONS: Expression profiles of CNS GCTs distinctly reflect the histological variabilities. Germinoma may be clustered into two groups, with possible differentiation in treatment intensity in the future. GCTs at CNS and gonads seem to have a mutual cell-of-origin and similar genomic backgrounds, which potentiates site-agnostic treatment development.
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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) | 0.000 | 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) | 0.002 | 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".