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Record W2335153152 · doi:10.1158/1538-7445.am10-596

Abstract 596: Oncolytic vesicular stomatitis virus selectively kills bladder cancer cells which have a low level of type I interferon receptor

2010· article· en· W2335153152 on OpenAlexaff
Kevin Zhang, Yoshiyuki Matsui, Boris Hadaschik, Cleo Lee, William Jia, John C. Bell, Ladan Fazli, Alan So, Paul S. Rennie

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsOntario Institute for Cancer ResearchUniversity of British Columbia
Fundersnot available
KeywordsVesicular stomatitis virusOncolytic virusInterferonBladder cancerCancerCancer researchVirologyVirusBiologyMedicineImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Bladder cancer is the second most common genitourinary malignancy. Current treatments options are of limited efficacy since approximately 80% of patients will develop recurrent tumors of which 20-30% evolve into more aggressive, potentially lethal cancers. A new strategy to treat bladder cancer is the intra-vesical application of vesicular stomatitis virus (VSV), which is a replication competent oncolytic virus that relies on an aberrant interferon signaling pathway within cancer cells. Using a tissue microarray composed of human bladder cancer cores and by immunohistochemistry, we observed that expression of type I interferon (IFN) receptor (IFNAR) was decreased relative to normal bladder tissue. Advanced bladder cancers had even lower expression of IFNAR. We observed that VSV preferentially targeted high grade bladder cancer cells which were resistant to type I IFN treatment. We also found that these high grade bladder cancer cells susceptible to VSV-induced lysis had low expression of IFNAR. Furthermore, siRNA knockdown of IFNAR indeed facilitated replication of VSV in cells previously resistant to VSV treatment. Consequently, intra-vesicular instillation of wildtype VSV and the Delta51M strain, which has an impaired ability to shutdown innate immunity, significantly inhibited high grade tumor growth by 98% and 90% respectively as compared to controls treated with UV-inactivated VSV. No evidence of toxicity or systemic viral infection in either group was found. In conclusion, down-regulation of IFNAR in bladder cancer may be one of the primary molecular mechanisms for clinical IFN resistance. However, this also facilitates VSV replication and oncolysis in high risk bladder cancers and provides a basis for selecting bladder cancer patients for IFN or oncolytic VSV therapy in future clinical trials. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 596.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.071
GPT teacher head0.398
Teacher spread0.327 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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