Abstract A12: Identification of pathways associated with abiraterone resistance in metastatic castration resistant prostate cancer: Preliminary results from the SU2C/AACR West Coast Prostate Cancer Dream Team
Bibliographic record
Abstract
Abstract Background: The efficacy of androgen signaling inhibitors such as Abiraterone (Abi) or Enzalutamide (Enz) has changed the standard of care in mCRPC. However, adaptive resistance to these agents is a consistent outcome with this therapy that undermines their benefit. The mechanisms underlying acquired resistance to Abi or Enz are poorly understood. The goals of the WCDT project are to identify the molecular pathways underlying the adaptive response to these targeted therapies through expression and mutational analysis of metastatic biopsies. Methods: Following central radiologic review, eligible mCRPC pts underwent biopsy at one of 5 WCDT clinical sites, using a uniform biopsy protocol. Tissue was both frozen, and formalin fixed/paraffin embedded (FFPE). Frozen samples were subject to laser capture microdissection for isolation of RNA and DNA enriched for mCRPC. FFPE tissue underwent a CLIA-certified assessment of a mutational panel, IHC for PTEN, and fluorescence in situ hybridization (FISH) for AR+. Pathway assessment is performed using RNA-seq and mutation data from mCRPC biopsies mapped onto a comprehensive pathway database connecting a tumor sample with genetic regulatory logic. Results: 70 of 300 planned mCRPC pts have undergone a metastasis biopsy. To date, biopsies have been obtained prior to treatment and following progression from one patient receiving Abi and one receiving Enz. Data collection from biopsies has been possible in 52 of 72 samples (72% success rate), and clinically actionable results have been returned to the care providers for 50 samples. The most commonly mutated gene assessed by the mutational panel was p53. Importantly, acquired mutation did not appear to be a mechanism for drug resistance in mCRPC, as the prevalence of tumors positive for mutations in genes contained in the panel was lower in patients who had progressed on Abi or Enz (9 of 16, 56%) than it was in treatment naïve patients (14 of 17, 82%). Gene expression-based signatures uncovered several pathways enriched in Abiraterone naïve compared to resistant samples. Conclusions: Genomic sequencing and expression analysis can be accomplished in small bone and soft tissue mCRPC biopsies. Pathway-based gene expression analysis appears to be a promising strategy to identify adaptive processes and targeting opportunities in Abi resistant mCRPC. Citation Format: Jack F. Youngren, Adam Foye, George Thomas, Joshua M. Stuart, Ted Goldstein, Baertsch Robert, Adrian Bivol, Artem Sokolov, Charles J. Ryan, Nader Pourmand, Tomasz M. Beer, Christopher P. Evans, Christopher P. Evans, Primo Lara, Jr., Martin E. Gleave, Kim N. Chi, Robert E. Reiter, Matthew Rettig, Owen Witte, Eric J. Small. Identification of pathways associated with abiraterone resistance in metastatic castration resistant prostate cancer: Preliminary results from the SU2C/AACR West Coast Prostate Cancer Dream Team. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Drug Sensitivity and Resistance: Improving Cancer Therapy; Jun 18-21, 2014; Orlando, FL. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(4 Suppl): Abstract nr A12.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".