MEDU-26. LATENT SOX9-POSITIVE CELLS RESPONSIBLE FOR MYC-DRIVEN MEDULLOBLASTOMA RECURRENCE
Bibliographic record
Abstract
Abstract Tumor recurrence is the leading cause of death among children with medulloblastoma, the most common type of malignant pediatric brain tumors. The mechanisms behind medulloblastoma recurrence are not fully understood. We previously showed that the transcription factor SOX9 promotes cisplatin treatment resistance in medulloblastoma. Here we show that SOX9 levels correlate with poor prognosis in Group 3 tumors. By studying paired primary-recurrent medulloblastoma samples and patient-derived xenograft (PDX) models we further identified rare SOX9-positive slow-cycling, therapy-resistant tumor cells that accumulate in relapses and in leptomenigeal metastases of Group 3 and Group 4 patients. By using an inducible Tet-OFF transgenic (GTML) mouse model for malignant MYCN-driven Group 3 tumors we identified rare SOX9-positive, quiescent brain tumor cells that are more resistant to cisplatin. Dox treatment normally cures GTML transgenic animals that developed aggressive medulloblastoma by turning MYCN off. However, when crossing the Tet-OFF GTML model with a Tet-ON rtTA-Sox9 model we can redirect MYCN expression to the Sox9 promoter ultimately driving brain tumor recurrence from rare SOX9-positive cells with 100% penetrance. In this novel animal model, recurrent tumors were actively disseminating from the hindbrain to the spinal cord and into the forebrain similar to distant relapses found in patients. By overexpressing SOX9 in human Group 3 tumor cells, MYC was directly inhibited and cell proliferation was decreased. PDX models of Group 3 tumors further showed increased levels of SOX9-positivity and less proliferative cells in metastatic compartments. Expression profiling revealed that recurrences were more inflammatory, metastatic, immune evasive and showed elevated MGMT methyltransferase levels which depleted recurrent cells and sensitized them for chemotherapy when using the MGMT inhibitor lomeguatrib. To summarize, our data clarify important and complex mechanisms by which latent medulloblastoma cells fail to respond to standard therapy and generate relapses.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
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".