MB-05 * PHARMACOLOGICAL INHIBITION OF MRK/ZAK KINASE FOR THE TREATMENT OF MEDULLOBLASTOMA
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Bibliographic record
Abstract
Medulloblastoma is a cerebellar tumor and the most common pediatric brain malignancy. Radiation therapy is part of the standard care for this tumor, but its effectiveness is accompanied by significant neurocognitive sequelae due to the deleterious effects of radiation on the developing brain. We have previously shown that the protein kinase MRK/ZAK protects tumor cells from radiation-induced cell death by regulating cell cycle arrest after ionizing radiation. Here, we show that siRNA-mediated MRK depletion sensitizes medulloblastoma primary cells to radiation. We have, therefore, designed and tested a small molecule inhibitor of MRK, M443, which binds to MRK in an irreversible fashion and inhibits its activity. We found that M443 strongly radio-sensitizes UW228 medulloblastoma cells as well as IMB226 patient-derived primary cells. M443 also inhibits radiation-induced activation of both p38 and Chk2, two proteins that act downstream of MRK and are involved in DNA damage-induced cell cycle arrest. We also tested the effect of M443 in an animal model of medulloblastoma that employs orthotopic implantation of IMB226 medulloblastoma cells in nude mice. Intra-tumoral delivery of M443 alone significantly extended animal survival by 5 days compared to vehicle treatment. Combination treatment of M443 with radiation at 2 x 3 Gy, that is not effective on its own (1 day of additional survival over control), achieved a synergistic increase in survival (15 days over the control survival time). Western blotting of tumor lysates demonstrated strong inhibition of MRK activity. In conclusion, we have developed a new small molecule inhibitor of MRK/ZAK that radio-sensitizes medulloblastoma cells. We hypothesize that combining radio-therapy with M443 will allow us to lower the radiation dose while maintaining therapeutic efficacy, thereby minimizing radiation-induced side effects.
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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 | 0.000 |
| 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) | 0.000 | 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 it