Abstract 930: Preclinical characterization of MG516, a novel inhibitor of receptor tyrosine kinases involved in resistance to targeted therapies.
Bibliographic record
Abstract
Abstract Despite breakthroughs in the clinical development of tyrosine kinase inhibitors, challenges remain in overcoming resistance to these molecular targeted therapies. Advances in our understanding of mechanisms of resistance to targeted agents will improve patient outcome. While secondary mutations play a key role, the activation of parallel signaling pathways has been shown to alter the sensitivity to targeted inhibition. Resistance to inhibitors of the EGFR or VEGFR families may occur through the activation of Met, EphA2 and Axl receptor tyrosine kinase pathways, suggesting combined inhibition of these targets as a strategy to prevent resistance to approved EGFR- and VEGFRs -targeted therapies. We have developed a novel multitargeted receptor tyrosine kinase inhibitor, MG516, with nanomolar activities in in vitro enzymatic assays against members of the Eph receptor family, Axl, Met and VEGFR1,2,3. In carcinoma cell lines, MG516 potently inhibits phosphorylation of EphA2, Axl and Met. Inhibition of Met downstream signaling as well as the inhibition of Met-dependent biological endpoints, such as motility and wound healing is also achieved. In human umbilical vein endothelial cells (HUVECs),VEGFR2 activation and VEGF-dependent angiogenesis are blocked. Potent anti-tumor activity is demonstrated across a broad range of human xenograft models including lung, gastric, glioblastoma, colorectal and breast carcinomas. Anti-tumor activity is achieved at oral doses as low as 2.5mg/kg in the absence of overt toxicity, weight loss or myelosuppression. Immunohistochemistry analyses of xenograft tumors after treatment with MG516 reveal a decrease in the proliferation of tumor cells, a decrease in tumor vascularization, pharmacodynamic inhibition of target phosphorylation and decreases in target expression, including EphA2. Consistent with targeting multiple oncogenic pathways simultaneously, the combination of MG516 with EGFR inhibition results in improved tumor growth inhibition. Importantly, in a gastric cancer model exhibiting resistance to sunitinib following prolonged treatment with this agent, MG516 induces tumor regression. Thus, MG516 offers potential for clinical development of a novel therapeutic, by targeting a combination of oncogenic kinases involved in tumor development, progression and resistance to targeted therapies. Citation Format: Normand Beaulieu, Helene Sainte-Croix, Claire Bonfils, Michael Mannion, Stephane Raeppel, Lubo Isakovic, Stephen Claridge, Oscar Saavedra, Franck Raeppel, Arkadii Vaisburg, James Wang, Marielle Fournel, Jeffrey M. Besterman, Christiane R. Maroun. Preclinical characterization of MG516, a novel inhibitor of receptor tyrosine kinases involved in resistance to targeted therapies. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 930. doi:10.1158/1538-7445.AM2013-930
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".