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Record W4282959844 · doi:10.1158/1538-7445.am2022-3099

Abstract 3099: Biological evaluation of a novel AKR1C3 inhibitor in patient-derived prostate cancer cell line and xenograft models

2022· article· en· W4282959844 on OpenAlexaff
Joy C. Yang, Shu Ning, Hans Adomat, Martin Gleave, Allen C. Gao, Christopher P. Evans, Chengfei Liu

Bibliographic record

VenueCancer Research · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnzalutamideProstate cancerCancer researchCancerAndrogen receptorCarcinogenesisCell cultureProstateMedicineAbiraterone acetateBiologyInternal medicineOncologyAndrogen deprivation therapy

Abstract

fetched live from OpenAlex

Abstract INTRODUCTION AND OBJECTIVES: Prostate cancer is a highly heterogeneous cancer type with distinct genomic and phenotypic characteristics that drive tumorigenesis and the differential response to drug therapies. A limit number of prostate cancer cell lines and patient-derived xenograft (PDX) models hinders research to improve disease outcome. Some currently available PDX models were derived from the primary tumor samples are insufficient to recapitulate the clinical response at more advanced stages. In this study, we developed patient-derived models from patients with advanced disease and evaluated a novel AKR1C3 inhibitor in these models. METHODS: Samples received from our Pathology Biorepository Shared Resource were divided into four groups and subjected to pathological staining, RNA extraction, xenografting in NSG mice via renal capsule and subcutaneous implantation in SCID mice and conditional reprogramed cultures (CRCs) or organoid culturing. The AKR1C3 inhibitor PB was modified from celecoxib. Androgen receptor (AR), AR-V7 and AKR1C3 expression were determined by western blot. The effects of the AKR1C3 inhibitor on enzalutamide sensitivity were characterized by growth assay and colony formation assay. RESULTS: Eight PDX models have been developed from prostate cancer patients with high Gleason score and/or at the castration-resistant stages. Among the PDX models, one spontaneous indefinite cell line PS1172 was established. Early passage CRCs showed the epithelial morphology with AR positive expression. Through serially passaging PS1172 PDX with castration in SCID mice, the castration resistant cell line 1172CR was re-cultured from castration-resistant PS1172 PDX tumors. 1172CR cells were resistant to enzalutamide treatment and expressed high level of AKR1C3 and AR-V7. A novel AKR1C3 inhibitor (PB) which displayed superior potential to inhibit AKR1C3 activity and suppress enzalutamide resistant prostate cancer cell growth was tested in these models. At the same dose, PB significantly suppressed 1172CR cell growth and colony formation compared to indomethacin and enzalutamide. PB also significantly suppressed AR/AR-V7 protein expression compared to indomethacin in 1172CR cells. CONCLUSION: PS1172 and castration-resistant 1172CR cells are novel models with significant characteristics such as AR-V7 and AKR1C3. These novel prostate cancer models are ideal for small molecule testing and resistant mechanism investigating. Citation Format: Joy C. Yang, Shu Ning, Hans Adomat, Martin Gleave, Allen Gao, Christopher P. Evans, Chengfei Liu. Biological evaluation of a novel AKR1C3 inhibitor in patient-derived prostate cancer cell line and xenograft models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3099.

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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.251
GPT teacher head0.454
Teacher spread0.203 · 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
Published2022
Admission routes1
Has abstractyes

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