Transcriptome and methylome analysis of CNS germ cell tumor finds its cell-of-origin in embryogenesis and reveals shared similarities with testicular counterparts
Bibliographic record
Abstract
BACKGROUND: CNS germ cell tumors (GCTs) predominantly develop in pediatric and young adult patients with variable responses to surgery, radiation, and chemotherapy. This study aimed to examine the complex and largely unknown pathogenesis of CNS GCTs. METHODS: We used a combined transcriptomic and methylomic approach in 84 cases and conducted an integrative analysis of the normal cells undergoing embryogenesis and testicular GCTs. RESULTS: Genome-wide transcriptome analysis in CNS GCTs indicated that germinoma had a transcriptomic profile representative of primitive cells during early embryogenesis with high meiosis/mitosis potentials, while nongerminomatous GCTs (NGGCTs) had differentiated phenotypes oriented toward tissue formation and organogenesis. Co-analysis with the transcriptome of human embryonic cells revealed that germinomas had expression profiles similar to those of primordial germ cells, while the expression profiles of NGGCTs were similar to those of embryonic stem cells. Some germinoma cases were characterized by extensive immune-cell infiltration and high expression of cancer-testis antigens. NGGCTs had significantly higher immune-cell infiltration, characterized by immune-suppression phenotype. CNS and testicular GCTs (TGCTs) had similar mutational profiles; TGCTs showed enhanced copy number alterations. Methylation analysis clustered germinoma/seminoma and nongerminoma/nonseminoma separately. Germinoma and seminoma were co-categorized based on the degree of the tumor microenvironment balance. CONCLUSIONS: These results suggested that the pathophysiology of GCTs was less dependent on their site of origin and more dependent on the state of differentiation as well as on the tumor microenvironment balance. This study revealed distinct biological properties of GCTs, which will hopefully lead to future 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) | 0.001 | 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".