MB-08FUNCTIONAL ROLES OF CCL2 IN MEDULLOBLASTOMA LEPTOMENINGEAL METASTASIS
Bibliographic record
Abstract
Metastatic medulloblastoma is a high-risk disease, because the majority of children dying of medulloblastoma expire from metastases rather than recurrence of the primary tumor. In this study, we aim to identify the mechanism of medulloblastoma leptomeningeal metastasis. RNA sequencing from primary and matched metastatic compartment from patient derived samples suggest that CCL2 expression is significantly higher in metastasis compartment than in the primary tumor. Then we analyzed the functional roles of CCL2 in medulloblastoma metastasis. We intracranially injected CCL2 overexpressing MB cells into the cerebellum of immunodeficient mice and dissected the spinal cord when the mice got sick due to the primary tumor. We found that leptomeningeal metastasis is significantly increased when we injected CCL2 overexpressing cells than when injected control cells. In addition, we also analyzed the funcitional roles of CCL2 in medulloblastoma metastasis using used the RCAS induced murine medulloblastoma models. When we induced Shh + CCL2 into the mice, we found significant difference in the incidence of leptomeningeal metastasis compared with when we induced Shh alone while brain tumor incidence was not different between these two groups. These results suggest that CCL2 is involved in medulloblastoma leptomeningeal metastasis and could be a potential therapeutic target of medulloblastoma metastasis.
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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 | 0.000 |
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".