Genetic drivers of metastatic dissemination in sonic hedgehog medulloblastoma
Bibliographic record
Abstract
Leptomeningeal dissemination (LMD), the metastatic spread of tumor cells via the cerebrospinal fluid to the brain and spinal cord, is an ominous prognostic sign for patients with the pediatric brain tumor medulloblastoma. The need to reduce the risk of LMD has driven the development of aggressive treatment regimens, which cause disabling neurotoxic side effects in long-term survivors. Transposon-mediated mutagenesis studies in mice have revealed numerous candidate metastasis genes. Understanding how these genes drive LMD will require functional assessment using in vivo and cell culture models of medulloblastoma. We analyzed two genes that were sites of frequent transposon insertion and highly expressed in human medulloblastomas: Arnt (aryl hydrocarbon receptor nuclear translocator) and Gdi2 (GDP dissociation inhibitor 2). Here we show that ectopic expression of Arnt and Gdi2 promoted LMD in mice bearing Sonic hedgehog (Shh)-induced medulloblastomas. We overexpressed Arnt and Gdi2 in a human medulloblastoma cell line (DAOY) and an immortalized, nontransformed cell line derived from mouse granule neuron precursors (SHH-NPD) and quantified migration, invasiveness, and anchorage-independent growth, cell traits that are associated with metastatic competence in carcinomas. In SHH-NPD cells. Arnt and Gdi2 stimulated all three traits. In DAOY cells, Arnt had the same effects, but Gdi2 stimulated invasiveness only. These results support a mechanism whereby Arnt and Gdi2 cause cells to detach from the primary tumor mass by increasing cell motility and invasiveness. By conferring to tumor cells the ability to proliferate without surface attachment, Arnt and Gdi2 favor the formation of stable colonies of cells capable of seeding the leptomeninges.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".