Abstract 4812: A novel EGFL7-derived peptide, E7C13, is a potent anti-tumor agent that inhibits angiogenesis in a beta 1 integrin- and thrombospondin-dependent manner
Bibliographic record
Abstract
Abstract As a tumor grows beyond 1mm, it recruits new blood vessels through the process of angiogenesis. The selective inhibition of the vascular endothelial growth factor (VEGF) pathway increases the efficacy of chemotherapy and has beneficial effects on multiple advanced cancers, but response is often limited and the disease eventually progresses. This highlights the necessity to develop novel therapeutics that target alternate angiogenic signaling pathways. The epidermal growth factor-like domain 7 (EGFL7) is a secreted protein that is up-regulated in actively remodeling endothelium, localizing to the perivascular extracellular matrix. Inhibition of EGFL7 in zebrafish disrupts vascular tube formation during vasculogenesis, while knockout of EGFL7 in mice prevents endothelial lumen formation and tubulogenesis. EGFL7 expression is associated with poor prognosis in malignant glioma, hepatocellular carcinoma and non-small cell lung cancer, and therefore is a promising therapeutic target for anti-cancer strategies. In this study we investigated the impact of tumor-localized EGFL7 in tumor growth and angiogenesis. When EGFL7 is over-expressed in HT1080 fibrosarcoma or MDA-MB-231 breast cancer we saw no effect on tumor cell proliferation yet we observed a dramatic inhibition of tumor growth and angiogenesis in animal models. Indeed, we demonstrate that EGFL7 interacts with thrombospondin, and that it promotes endothelial cell spreading and adhesion in a beta 1 integrin- and TSP-dependent manner. In an attempt to isolate the domain of EGFL7 that is responsible for this angiogenesis inhibition activity, we identified and characterized a novel EGFL7-derived peptide, E7C13. This peptide inhibited sprouting and tube formation of human endothelial cells in vitro in 2D and 3D assays, and inhibited angiogenesis induced by tumor cells in vivo in the chicken embryo CAM assay and in the mouse DIVAA assay. Treatment of HT1080 tumor-bearing mice with E7C13 peptide intravenously at 75 mg/kg led to significantly reduced tumor growth and increased survival. Tumors from E7C13-treated animals were significantly less vascularized compared to controls. These data suggest that E7C13 is a promising new anti-vascular agent, and may provide a basis for a novel anti-angiogenesis approach to treat cancer. Citation Format: Choi-Fong Cho, Laura A. Fung, Tienabe Nsiama, Lihai Yu, Alisha Kadam, Daniela F. Quail, Katia Carmine-Simmen, Desmond Pink, Lynne-Marie Postovit, Leonard G. Luyt, John D. Lewis. A novel EGFL7-derived peptide, E7C13, is a potent anti-tumor agent that inhibits angiogenesis in a beta 1 integrin- and thrombospondin-dependent manner. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4812. doi:10.1158/1538-7445.AM2014-4812
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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) | 0.000 | 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 | 0.001 |
| 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".