Abstract A2: Development of a phenotypic profiling platform with high predictive value for the identification of novel antiangiogenic drugs.
Bibliographic record
Abstract
Abstract Deregulation of angiogenesis plays a major role in a number of human diseases, most notably cancer. Although angiogenesis inhibitors are among the most promising anticancer drug candidates, existing FDA approved drugs have shown limited efficacy in the clinic. The majority of angiogenesis inhibitors under clinical development have been designed with the help of high-throughput screening techniques focused on single molecular targets. Although these methods have yielded several candidates, it has been long recognized that a lack of correlation with activity in in vivo preclinical models has resulted in high levels of attrition during the early stages of drug discovery. Here we introduce a novel high-content cell-specific fluorescence platform for discovery of antiangiogenic agents, which we have validated by screening the 1970 small molecules part of the NCI Diversity Set. The platform features a primary screening based on high content growth and tube formation assays using phenotypically defined fluorescent reporter endothelial cells. Tube formation assays were performed using VEGFR2-nonexpressing endothelial cells and quantitatively evaluated in an automated fashion with the newly developed image analysis software AngioApplication. 2.3% (46) of all the small molecules in the library showed growth inhibition activity and 3.5% (70) significantly blocked tube formation. Interestingly, 0.5% (11) of the small molecules showed growth and tube formation inhibitory activity. None of the lead compounds interfered with tubulin polymerization or inhibited receptor tyrosine kinase activity. Seven lead compounds were evaluated in xenograft tumor angiogenesis models. All showed anti-tumor activity, and two of the compounds (CID 5458317 and CID 429599) blocked tumor growth in an in vivo leiomyosarcoma xenograft model of angiogenesis with comparable efficacy as bevacizumab. Gene expression profiling showed that the number of proangiogenic pathways down-regulated in endothelial cells recovered from drug-exposed tube formation assays was predictive of tumor growth inhibition in vivo. High-throughput chicken chorioallantoic assays closely mimicked the efficacy of tested drugs in the tumor xenograft models and supported an antiangiogenic mechanism of action. Histological assessment of xenograft tumors treated with CID 5458317 showed a drastic diminution of their vascular network compared to vehicle treated tumors. Preliminary data using intravital microscopy on a mouse dorsal skin chamber model showed massive leakiness and vascular regression in tumor vasculature exposed to CID 5458317. In conclusion, we have developed a platform for the identification of novel antiangiogenic drugs with high predictive value. Using this platform, several small molecules with potentially novel antiangiogenic mechanisms of action have been identified. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2011 Nov 12-16; San Francisco, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2011;10(11 Suppl):Abstract nr A2.
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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 | 0.000 |
| 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".