Abstract 847: Foretinib, a multi-kinase inhibitor of cMET and PDGFRα, in the treatment of disseminated medulloblastoma
Bibliographic record
Abstract
Abstract Medulloblastoma (MB) is the most common malignant brain tumor in childhood accounting for around 10% of all pediatric cancer deaths. Dissemination occurs in 30% of the patients at the time of diagnosis and essentially defines children with incurable disease given that metastatic disease is refractory to current treatments. Therefore, there is an urgent need for new therapies to treat metastatic MB. The hepatocyte growth factor (HGF)/cMET signaling pathway has been recently implicated in the pathogenesis of MB. Overexpression of cMET and HGF is associated with group C tumors which have high incidence of metastasis and poor outcome. Moreover, overexpression of the platelet-derived growth factor receptor (PDGFR) was also identified in metastatic MB. Using foretinib, a multi-kinase inhibitor of cMET and PDGFRα, we aimed to target two important pathways involved in MB dissemination. Using three MB cell lines (Daoy, ONS - 76 and D425) that express different amounts of the receptors (cMET and PDGF), we performed dose-response experiments with foretinib, measuring downstream targets of cMET and PDGFRα activation. We showed that foretinib inhibits proliferation, migration, invasion and anchorage independent growth of MB cell lines in a dose-dependent manner. By immunofluorecence, we observed that foretinib induces polyploidy and using flow cytometry analysis we found that it also induces apoptosis and cell cycle arrest in G2-M phase. To test the efficacy of foretinib in vivo we have created a disseminated mouse model of MB injecting MB cells in the fourth ventricle of nude mice, mimicking the process of dissemination in children. The cells were previously transfected with a luciferase expressing vector allowing weekly monitoring of tumor growth and dissemination by bioluminescence imaging. Foretinib was able to reduce tumor growth and metastasis in xenografts, increasing survival when compared to controls. Altogether these results suggest that small molecule inhibitors of cMET and PDGFR may represent a new therapeutic strategy in the treatment of disseminated MB. Given that foretinib is already being tested in clinical trials for other forms of cancer, the findings from our experiments may lead to the design of identical trials in children with metastatic medulloblastoma. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 847. doi:1538-7445.AM2012-847
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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 | 0.001 | 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 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".