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Record W2112321541 · doi:10.1016/j.juro.2008.05.001

Is Vascular Endothelial Growth Factor Modulation a Predictor of the Therapeutic Efficacy of Gefitinib for Bladder Cancer?

2008· article· en· W2112321541 on OpenAlexaff
Wassim Kassouf, Gordon Brown, Peter C. Black, Mark B. Fisher, Teruo Inamoto, Tony Luongo, David Gallagher, Menashe Bar‐Eli, David J. McConkey, Liana Adam, Colin P. Dinney

Bibliographic record

VenueThe Journal of Urology · 2008
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsMcGill University Health Centre
FundersNational Cancer InstituteAstraZeneca
KeywordsGefitinibVascular endothelial growth factorMedicineEpidermal growth factor receptorAngiogenesisEpidermal growth factorCancer researchEndothelial stem cellEndocrinologyVascular endothelial growth factor AGrowth factor receptor inhibitorInternal medicineGrowth factorCell growthCancerBiologyReceptorIn vitroBiochemistry

Abstract

fetched live from OpenAlex

PURPOSE: The epidermal growth factor receptor inhibitor gefitinib (Iressa) is currently being studied in patients with bladder cancer and it has significant anti-angiogenic activity. We investigated the relationship between the modulation of vascular endothelial growth factor (Santa Cruz Biotechnology, Santa Cruz, California) expression and the biological efficacy of gefitinib for bladder cancer. MATERIALS AND METHODS: In vitro the 4 bladder cancer cell lines 253JB-V, UMUC-3, KU-7 and UMUC-13 were treated with gefitinib and vascular endothelial growth factor secretion was measured. The effects of gefitinib on vascular endothelial growth factor promoter, proliferation, cell cycle and downstream signals were evaluated. In vivo 253JB-V and UMUC-13 were injected into nude mice and tumors were treated with 2 mg gefitinib per day. Tumor kinetics were determined and the levels of phospho-epidermal growth factor receptor (Biosource), vascular endothelial growth factor, phospho-vascular endothelial growth factor (Cell Signaling Technology), angiogenesis and apoptosis were measured. RESULTS: Epidermal growth factor receptor (Neomarkers, Fremont, California) phosphorylation was blocked efficiently in all cell lines at concentrations of 0.5 microM or greater. Gefitinib (1 microM) induced an accumulation of cells in G0/G1 without apoptosis in 253J B-V cells, whereas it had no effect in other cell lines. Gefitinib inhibited vascular endothelial growth factor secretion in 253JB-V and UMUC-13 (concentration inhibiting a 50% response 0.5 and 0.1 microM, respectively) but not in UMUC-3 or KU-7. Gefitinib decreased vascular endothelial growth factor promoter activity in 253JB-V and UMUC-13 by 40% to 60%. In vivo the growth of 253JB-V tumors was significantly inhibited by gefitinib, whereas no effect was demonstrated in UMUC-13 tumors. Vascular endothelial growth factor expression and vascular endothelial growth factor receptor activation were significantly decreased in 253JB-V tumors and to a greater extent in resistant UMUC-13 tumors. Gefitinib inhibited angiogenesis and induced apoptosis in sensitive 253JB-V tumors only. CONCLUSIONS: Epidermal growth factor receptor blockade exerts an anti-angiogenic effect on bladder cancer cells, in part by modulating vascular endothelial growth factor expression. However, down-regulation of vascular endothelial growth factor expression is not sufficient to inhibit bladder cancer growth and it should not be used as a predictor of the therapeutic efficacy of gefitinib.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.318
Teacher spread0.287 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2008
Admission routes1
Has abstractyes

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