Abstract 3698: Conditionally reprogrammed cells from patient-derived xenograft to model neuroendocrine prostate cancer development
Bibliographic record
Abstract
Abstract Treatment-emergent neuroendocrine prostate cancer (t-NEPC) is a lethal subtype of advanced prostate cancer that occurs via NE transdifferentiation of prostate adenocarcinomas in response to androgen receptor (AR)-inhibition therapy. Study of t-NEPC has been hampered by a lack of clinically relevant models. We previously established a unique and first-in-field patient-derived xenograft (PDX) model of adenocarcinoma (LTL331)-to-NEPC (LTL331R) transdifferentiation. In this study, we established conditionally reprogrammed (CR) cells from the adenocarcinoma PDX tumor line LTL331. These LTL331-derived CR (LTL331-CR) cells retained the same genomic mutations of the parental tumor and, can be genetically manipulated and continuously propagated in vitro. Further androgen deprivation treatment on LTL331-CR cells showed no effect on cell proliferation. Transcriptomic analyses of the LTL331-CR cells revealed profound downregulation of androgen response pathway, and enrichment of stem/progenitor-like marker genes, compared with the parental tumor LTL331. Notably, when grafted back into the subrenal capsule of male NOD/SCID mice, these LTL331-CR cells gave rise to NEPC tumors directly as manifested by histological expression of NE markers. Transcriptomic analyses of the newly developed NEPC tumors also demonstrated marked enrichment of NEPC signature genes and loss of AR signaling genes. This study provides a novel strategy to investigate the mechanisms underlying t-NEPC development with a unique PDX by enabling gene manipulation ex vivo and subsequent functional evaluation in vivo. Citation Format: Xinpei Ci, Jun Hao, Xin Dong, Hui Xue, Rebecca Wu, Anne M. Haegert, Colin C. Collins, Dong Lin, Yuzhuo Wang. Conditionally reprogrammed cells from patient-derived xenograft to model neuroendocrine prostate cancer development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3698.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".