Characterization of neuroendocrine prostate cancer (NEPC) in patients with metastatic castration resistant prostate cancer (mCRPC) resistant to abiraterone (Abi) or enzalutamide (Enz): Preliminary results from the SU2C/PCF/AACR West Coast Prostate Cancer Dream Team (WCDT).
Bibliographic record
Abstract
5003 Background: Mechanisms of resistance to androgen signaling inhibitors such as Abi or Enz are poorly understood. An increasing % of these pts develop NEPC. Pathologic (path), clinical, and genomic characterization of pts with NEPC was undertaken in the context of the WCDT project, which seeks to identify genetic pathways underlying primary and acquired resistance to Abi and Enz. Methods: Eligible mCRPC pts underwent a metastasis (met) biopsy (bx) at one of 5 WCDT centers, using a standardized bx protocol, and were uniformly followed for clinical outcomes. Tissue was both frozen, and formalin fixed/paraffin embedded. Independent path review was undertaken by 3 pathologists. Frozen specimens underwent laser capture micro-dissection, RNA isolation, library preparation and RNA sequencing (seq). Machine learning was used to derive a NEPC expression signature. Results: 150 of 300 planned mCRPC pts have undergone bx. Path review has been undertaken in 101. Classic small cell cancer (SmCC) was identified in 12%, adenocarcinoma (adenoca) in 33%. An intermediate histology distinct from SmCC or adenoca was seen in 27%. The remaining 28% were mixed histologies or were not classifiable. Anatomic site of bx (node, bone, liver) did not appear to enrich for a particular histology. Median overall survival was: not reached at 22 mos of follow-up in pts with adenoca, 8.9 mos in pts with intermediate histology, and 6.6 mos in pts with SmCC (log rank p = 0.027). RNAseq data are available on 45 biopsies. A 50 gene signature with 97% accuracy for NEPC (defined as SmCC or intermediate histology) was developed. Conclusions: RNAseq and expression analysis can be accomplished in small bone and soft tissue mCRPC biopsies. A distinct histology, intermediate to SmCC and adeno, was observed in 27% of pts. The development of NEPC in mCRPC resistant to Abi or Enz is far more common than previously appreciated and appears to result in poor survival. A 50 gene NEPC expression signature was derived which provides insight into the biology and potential treatment of NEPC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".