Abstract 2083: Alternative splicing regulation by the androgen receptor in prostate cancer cells
Bibliographic record
Abstract
Abstract The androgen receptor (AR) is a transcription factor that drives prostate cancer (PCa) by modulating the expression of thousands of genes to promote proliferation and survival and to reprogram metabolism. However, how AR activation affects alternative splicing is mostly unknown. Our objective was to define its role in the transcriptome-wide regulation of alternative splicing. Three human PCa models–LNCaP, LAPC4, and 22Rv1 cells–were treated with and without androgens, and RNA was purified for deep-sequencing analyses (RNA-seq). Several bio-informatic tools were then used to study alternative splicing. We demonstrate that in the absence of androgens, alternative splicing complexity is similar among AR-positive PCa cells, with 48% of all transcripts having various levels of alternative splicing. We also describe splicing differences among cell lines, such as specific splicing of AR, REST, TSC2, and CTBP1. Interestingly, AR activation changed the alternative splicing of thousands of transcripts in all the cell lines tested. Overlap between AR-sensitive alternative splicing events revealed that genes linked to PCa metabolism are major targets for this specific modulation. These genes encode metabolic enzymes such as the prostate-specific membrane antigen (FOLH1), malate dehydrogenase 1 (MDH1), and malic enzyme 2 (ME2). Enzymatic assays revealed that AR alters their activities without changing their total gene expression levels, demonstrating that AR-driven regulation of alternative splicing has a direct effect on cancer cell metabolism. Overall, our study presents a comprehensive analysis of PCa cell transcriptome and its modulation by AR, revealing cell metabolism as a key target for AR-dependent regulation of alternative splicing. Citation Format: Lucas Germain, Camille Lafront, Jolyane Beaudette, Raghavendra Tejo Karthik Poluri, Cindy Weidmann, Etienne Audet-Walsh. Alternative splicing regulation by the androgen receptor in prostate cancer cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2083.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.003 | 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".