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Record W2476304059 · doi:10.1158/1538-7445.am2016-1342

Abstract 1342: A production-scalable cabazitaxel cellulose nanoparticle exhibits significant efficacy in a bone model of docetaxel-resistant prostate cancer

2016· article· en· W2476304059 on OpenAlexaff
Joseph Bteich, Bryan Hoang, Elijus Undzys, Mohammed Mohammed, Ai Lin Su, Kevin Ou, David Emerson, Kenneth K. Sokoll, Shyh‐Dar Li, Mohit Trikha, Henry B. Lowman, Mark J. Ernsting

Bibliographic record

VenueCancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British ColumbiaPrecision Nanosystems (Canada)Ontario Institute for Cancer Research
Fundersnot available
KeywordsLNCaPDocetaxelProstate cancerChemistryCabazitaxelProstatePharmacologyCancerMedicineInternal medicineAndrogen deprivation therapy

Abstract

fetched live from OpenAlex

Abstract Purpose: This study aimed to: (1) evaluate the antitumor efficacy of a controlled release cabazitaxel cellulose nanoparticle (CBZed-Nano) in an orthotopic bone model of docetaxel-resistant LNCaP C4-2B prostate cancer, and (2) confirm the efficacy of dose preparation by scalable instrumentation (NanoAssemblr), in a subcutaneous PC3 prostate xenograft model. Methods: mPEG-OH and cabazitaxel (CBZ) were coupled to a carboxymethylcellulose acetate polymer to yield CBZed-Nano, according to established coupling and purification methods (1). Particles were prepared by nanoprecipitation of polymer into saline by either a manual vortex technique (1) or a NanoAssemblr™ (NA) microfluidic-based instrument. Particles were purified by dialysis and sterile filtration (1). Particle size was measured by a DLS Malvern Zetasizer, morphology was screened by TEM, and residual substances were measured by LC. Male NOD-SCID mice were inoculated via intrafemoral injection with docetaxel-resistant LNCaP C42B prostate cancer. One day after inoculation, mice were treated with vortex prep CBZed-Nano (55 mg/kg) or CBZ (2 mg/kg) on a q1,5,9d schedule. Survival curves were generated (n = 10 mice per group). To directly compare preparation technique, nude mice bearing s.c. PC3 prostate cancer xenografts were treated at Bolder BioPath (Boulder, US) with CBZed-Nano (NA and vortex prep, 85 to 142 mg/kg) and CBZ (15-25 mg/kg) on a q1,5,9d schedule. Results: The CBZed-Nano polymer conjugate contained 36 wt% CBZ and 11 wt% PEG, with residual free CBZ < 0.01 wt% of CBZ content. Particles prepared by vortex and NA were 94 and 70 nm respectively (by DLS). By TEM analysis, NA particles exhibit a more uniform spherical morphology. Mice bearing docetaxel resistant LNCaP C42B tumors exhibited a partial response to CBZ treatment, with a median survival of 61 days, compared to 34 days for vehicle controls. In contrast, mice treated with CBZed-Nano exhibited a significantly improved response, with 70% durable cure. Efficacy was observed regardless of CBZed-Nano preparation technique. Mice treated with CBZ exhibited a 38-63% durable cure in the 60, 75, and 100% MTD groups. In comparison, mice treated with CBZed-Nano exhibited a 92-100% durable cure, confirming both the superior activity of CBZed-Nano relative to free CBZ, and confirming antitumor activity of the scalable NanoAssemblr production. Conclusion: The CBZed-Nano preparation technique is scalable, with manual and NanoAssemblr™ produced dose being equally efficacious in a PC3 prostate cancer model. Significant efficacy (70% durable cure) in a docetaxel-resistant prostate cancer of the bone model was also observed. The data suggests that CBZed-Nano is more tolerable than CBZ, and that it may overcome taxane-resistant solid tumor indications. (1) Bioconjugate Chem 22 2011, 2474-2486 (2) Biomaterials 33 2012, 3931-3941 Citation Format: Joseph Bteich, Bryan Hoang, Elijus Undzys, Mohammed Mohammed, Ai Lin Su, Kevin Ou, David Emerson, Kenneth Sokoll, Shyh-Dar Li, Mohit Trikha, Henry Lowman, Mark J. Ernsting. A production-scalable cabazitaxel cellulose nanoparticle exhibits significant efficacy in a bone model of docetaxel-resistant prostate cancer. [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 1342.

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 score0.002
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 head0.088
GPT teacher head0.382
Teacher spread0.294 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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