Abstract CN06-01: Lineage plasticity and the neuroendocrine phenotype as a resistance mechanism in prostate cancer
Bibliographic record
Abstract
Abstract Loss of androgen receptor (AR) signaling dependence occurs in approximately 15-20% of treatment resistant prostate cancers, and this may manifest clinically as transformation from a prostate adenocarcinoma histology to a castration resistant neuroendocrine prostate cancer (CRPC-NE). The diagnosis of CRPC-NE currently relies on a metastatic tumor biopsy, which is invasive for patients and often challenging to diagnose due to tumor heterogeneity. By studying whole exome sequencing and whole genome bisulfite sequencing of metastatic tumor biopsies and matched cell free DNA (cfDNA), we identified distinct genomic and epigenomic features of CRPC-NE and patterns of tumor evolution that occur during clinical progression and treatment resistance. Loss of RB1 and TP53 are enriched in CRPC-NE compared with castration resistant prostate adenocarcinoma, as are significant changes in DNA methylation, which are detectable by cfDNA. There was significantly higher concordance between cfDNA and biopsy tissue genomic alterations in CRPC-NE patients compared to castration resistant adenocarcinoma, supporting greater intra-individual genomic consistency across metastases. cfDNA and serial tumor biopsies allowed for the tracking of dynamic clonal and subclonal tumor cell populations as patients progressed and identified CRPC-NE alterations sometimes prior to the development of clinical features. CRPC-NE appears to arise clonally from a prostate adenocarcinoma precursor likely through a dynamic process of clonal selection and trans-differentiation that occurs during resistance to AR-directed therapies. In addition to loss of AR expression and canonical AR signaling, we identified a dysregulation of key pathways in CRPC-NE including loss of Notch signaling, reactivation of developmental programs, and gain of neuronal/neuroendocrine programs including critical lineage determining transcription factors (LDTFs) such as ASCL1, MYCN, BRN2, pointing to novel biomarkers and potential targets for CRPC-NE. Patient-derived organoids and xenografts were used to interrogate the timing by which genomic and epigenomic changes and LDTFs contribute to lineage plasticity and the development of CRPC-NE as a resistance mechanism in prostate cancer. Citation Format: Himisha Beltran, Sheng-Yu Ku, Vincenza Conteduca, Alessandro Romanel, Loredana Puca, Michael Sigouros, Juan Miguel Mosquera, Scott T. Tagawa, Andrea Sboner, Olivier Elemento, David Goodrich, David Rickman, Amina Zoubeidi, Francesca Demichelis. Lineage plasticity and the neuroendocrine phenotype as a resistance mechanism in prostate cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr CN06-01. doi:10.1158/1535-7163.TARG-19-CN06-01
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".