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Record W2053457803 · doi:10.1158/1538-7445.am2011-5157

Abstract 5157: A role of the FGF-pathway in the VEGF/VEGFR targeting

2011· article· en· W2053457803 on OpenAlexaff
Ilya Tsimafeyeu, Lev Demidov, N. Wynn

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective Tissue Growth Factor Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAngiogenesisSunitinibBasic fibroblast growth factorBevacizumabVascular endothelial growth factorMedicineNeovascularizationFibroblast growth factorInternal medicineEndocrinologyPharmacologyVEGF receptorsReceptorGrowth factorCancerChemotherapy

Abstract

fetched live from OpenAlex

Abstract Background: The growth of new blood vessels is regulated at multiple steps by interactions between several pro- and antiangiogenic factors. We believe that the angiogenesis induced by basic fibroblast growth factor (bFGF) is resistant to anti-VEGF/VEGFR (vascular endothelial growth factor/receptor) therapy. Methods: The Corneal Micro Pocket Assay was performed. 70 Charles River female C57BL/6 mice (age at start day, 6 weeks) were randomized to 7 arms (10 mice in each group): 1) bFGF; 2) VEGF-A; 3) bFGF negative, VEGF-A negative; 4) bFGF and sunitinib; 5) VEGF-A and sunitinib; 6) bFGF and bevacizumab; 7) VEGF-A and bevacizumab. Doses of bFGF, VEGF-A (R&D Systems), sunitinib (Pfizer), and bevacizumab (Roche) were 200 ng, 400 ng, 10 mg/kg, 50 mg/kg per animal, respectively. Hydron pellets preparation, surgical procedure, and quantification of angiogenesis (angiogenic score) were performed as previously reported (Kenyon BM et al.). Statistical significance was determined by the Student's t test. Results: There was no neovascularization in bFGF negative, VEGF-A negative group (mean, 0). The effect of 200 ng/pellet of bFGF (mean, 4.2; SEM, 0.05) was compared with that of 400 ng/pellet VEGF-A (mean, 4.08; SEM, 0.09), P=0.7. In bFGF-induced angiogenesis, sunitinib (mean, 3.9; SEM, 0.1; P=0.2) and bevacizumab (mean, 4.71; SEM, 0.33; P=0.85) did not impact on neovascularization in comparison with bFGF positive control. The angiogenic effect of VEGF-A was significantly inhibited by both sunitinib (mean, 0.38; SEM, 0.06; P=0.001) and bevacizumab (mean, 0.75; SEM, 0.05; P=0.001) in comparison with VEGF-A positive control. No significant differences between 2 targeted agents in bFGF and VEGF-A models were obtained. Conclusion: Our recent findings demonstrate that anti-VEGF(R) therapy significantly impacts on VEGF-A-induced angiogenesis and not on bFGF-induced neovascularization. Further studies are needed to assess the role of FGF-pathway in resistance to VEGF(R) therapy. The study was supported by Terry Fox Foundation. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 5157. doi:10.1158/1538-7445.AM2011-5157

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.086
GPT teacher head0.372
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2011
Admission routes1
Has abstractyes

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