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The molecular and pathway characterization of patients with metastatic castration resistant prostate cancer (mCRPC) refractory to therapy with abiraterone acetate or enzalutamide: Preliminary results from the SU2C/PCF/AACR West Coast Prostate Cancer Dream Team (WCDT).

2014· article· en· W103407665 on OpenAlexaff
Eric J. Small, Jack Youngren, Tomasz M. Beer, Charles J. Ryan, George Thomas, Nader Pourmand, Robert E. Reiter, Joshi J. Alumkal, Joshua M. Stuart, Christopher P. Evans, Martin Gleave, Kim N., Alex Toschi, Adam Foye, Primo N. Lara, Owen N. Witte

Bibliographic record

VenueJournal of Clinical Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsEnzalutamideProstate cancerAbiraterone acetateMedicineComparative genomic hybridizationProstateBiopsyCancer researchCancerLiquid biopsyOncologyPTENPathologyAndrogen receptorInternal medicineAndrogen deprivation therapyBiologyGenePI3K/AKT/mTOR pathwayGenetics

Abstract

fetched live from OpenAlex

79 Background: Progressive metastatic castration resistant prostate cancer (mCRPC) has historically been challenging to biopsy and characterize on a molecular basis because of its bone tropism. Since mechanisms of resistance to androgen signaling inhibitors such as enzalutamide or abiraterone are not fully understood, both an unbiased and a targeted assessment of the molecular landscape of these patients is required. Methods: Patients (pts) with mCRPC undergo biopsy at one of five West Coast Prostate Cancer Dream Team (WCDT) clinical sites, using a uniform biopsy protocol, following central radiologic review. Tissue is both frozen, and formalin fixed/paraffin embedded (FFPE). Frozen tissue undergoes laser capture microdissection (LCM) for RNA seq, DNA seq, and array comparative genomic hybridization (aCGH). An RNA seq process was developed that allows using extremely small quantities of RNA (approximately 1 ng). FFPE tissue undergoes a CLIA-certified assessment of a 37-gene mutational panel, FISH for AR, and IHC for PTEN. Peripheral blood is collected for miRNA, immune responses, and CTC analysis including aCGH. Pathway assessment integrating clinical, RNA seq, DNA seq, aCGH data is undertaken using PARADIGM analysis. Results: Thirty six of 300 planned mCRPC pts have undergone a metastasis biopsy: 17 from bone, eight from liver, one from lung, and 10 from distant lymph nodes. Tumor is present in around 75% of the frozen specimens. To date, LCM has been undertaken in 11 samples, with RNA seq done in six, DNA whole exome seq in one, aCGH in four. FFPE tissue has been evaluated by mutational panel sequencing (n=9), FISH for AR (n=11), and IHC for PTEN (n=13). CTC have been isolated in 33 pts. aCGH has been successfully undertaken in paired CTC and biopsy specimens. Expression data from patients with full RNA sequencing have been analyzed by PARADIGM, with top disrupted pathways identified. Conclusions: Biopsies of mCRPC, including from bony sites, can be undertaken and used for molecular and pathway analysis. Sufficient tissue for unbiased and targeted assessment can be obtained. Linkage of results from these studies to the clinical characteristics of these patients will reveal important insights into mechanisms of resistance.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.055
GPT teacher head0.388
Teacher spread0.333 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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