Abstract 220: Proteomic identification of therapeutics targets for Enzalutamide resistance in Castration Resistant Prostate Cancer
Bibliographic record
Abstract
Abstract Prostate cancer (PC) is the most frequently diagnosed cancer in Canadian men and is the 3rd cause of cancer mortality. The Androgen Receptor (AR) is activated by androgens (e.g. testosterone), which leads to prostatic cell proliferation. The primary treatment for advanced PC is androgen-deprivation therapy, which is achieved via surgical or chemical castration. Nevertheless, most PC will become castration-resistant (CRPC). Although new anti-androgens (e.g. Enzalutamide) were developed to improve patients’ survival, their efficacy is still very limited and most CRPC patients will die from the disease within a few years. We postulate that by gaining insights into AR signalling networks in the context of CRPC, we could better direct patients towards the best-suited therapy and propose new therapeutic targets. To this aim, we took advantage of an innovative proteomics approach, namely proximity-labeling (BioID), to characterize global AR signalling networks in hormone-dependant LAPC4 cells. We identified 45 AR-associated proteins in non-stimulated cells, 35 of which were not previously reported. Upon androgenic stimulation, the AR signalling network increased to 320 proteins, including 278 (253 were novel) that were restricted to androgen-stimulated cells. Enzalutamide treatment resulted in a loss of 259 proteins from the network when compared to stimulated cells. As expected, this reproduced quite faithfully the status of non-stimulated LAPC4 cells. Interestingly, we identified 4 proteins in the AR network specifically after Enzalutamide treatment. These are interesting targets that may be relevant for the acquisition or the prediction of Enzalutamide resistance. Hence, they could become in time alternative therapeutic targets for CRPC treatment, to be used when Enzalutamide fails. Citation Format: Lauriane VELOT, Dominique Levesque, François-Michel Boisvert, Nicolas Bisson, Frédéric Pouliot. Proteomic identification of therapeutics targets for Enzalutamide resistance in Castration Resistant Prostate Cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 220. doi:10.1158/1538-7445.AM2017-220
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".