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Record W2493026365 · doi:10.1158/1538-7445.am2016-4409

Abstract 4409: Assessment of sonic hedgehog pathway inhibition in a novel orthotopic xenograft bladder cancer murine model

2016· article· en· W2493026365 on OpenAlexaff
Peter A. Raven, Sebastian Frees, Betty Zhou, Claudia Chávez‐Muñoz, Michael Cox, Alan So

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBladder cancerSmoothenedGLI1Cancer researchMedicineHedgehog signaling pathwayCancerSonic hedgehogPathologyBiologySignal transductionInternal medicineCell biology

Abstract

fetched live from OpenAlex

Abstract Purpose of the study: To develop a reliable and reproducible bladder cancer murine model for the evaluation of the SHH pathway. Introduction: The sonic hedgehog (SHH) signaling pathway has been shown to play an integral role in the maintenance and progression of bladder cancer. Smoothened inhibitors are currently used in the clinic for treatment of some skin cancers, however they have failed to be effective in bladder cancers in vitro. Blocking alternative downstream molecules of the SHH pathway may be an efficacious strategy for bladder cancer treatment. In vitro assays possess a number of limitations such as environmental differences, loss of heterogenicity and vascularization and artificial levels of growth factors and cytokines within the cell culture media. To overcome this animal models are needed to facilitate the study of carcinogenesis mechanisms. A new bladder cancer model is now required to evaluate experimental therapeutics as previous animal models have utilized the mistakenly identified cervical cancer cell line KU7. Methods: A novel orthotopic murine bladder cancer model was developed to assess the role of the SHH signalling pathway in tumor growth and disease progression. The model comprises the instillation of luciferase-expressing UM-UC3 human transitional cell carcinoma cells into the bladder of athymic nude mice following a poly-L-lysine irrigation of the bladder. Tumors are measured by bioluminescent imaging after intra-peritoneal injection of luciferin. Antisense oligonucleotides (ASO) targeted to the SHH pathway transcription factors, Gli family zinc fingers 1 and 2 (Gli1, Gli2), were assessed in this model. Immunohistochemistry (IHC) of proteins in the SHH pathway were evaluated and compared to our in-house tissue microarray (TMA) of clinical bladder cancer samples. Results: Tumors in this model grew in an average period of time of 40 days with high rates of engraftment and reproducibility. In vitro analysis of SHH pathway inhibition showed a decrease in bladder cancer cell viability and increase in apoptosis following Gli ASO treatment. This effect bypasses smoothened protein regulation which was found to be ineffective in some cell lines. Gli ASO treatment reduced tumor size, and prevented further growth, of UM-UC3 bladder cancers in this mouse model. IHC confirmed Gli2 knock-down and showed increased apoptosis and decreased proliferation in the in vivo tumors. Comparison of modelled tumors to clinical samples showed an increased and diffused Gli2 staining throughout the tissue in both cases. Conclusions: A murine intravesical model consisting of human tumors provides a robust and effective in vivo system for the assessment of cancer inhibiting treatments. Gli2 ASO proved to be a promising treatment for bladder cancer by inhibiting tumor growth and disease progression. Citation Format: Peter A. Raven, Sebastian Frees, Betty Zhou, Claudia Chavez-Munoz, Michael Cox, Alan So. Assessment of sonic hedgehog pathway inhibition in a novel orthotopic xenograft bladder cancer murine model. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4409.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.020
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.102
GPT teacher head0.427
Teacher spread0.325 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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