Abstract 2269: Transcription factor relationships associated with androgen-deprivation therapy response and metastatic progression in prostate cancer
Bibliographic record
Abstract
Abstract Patients with recurrent, aggressive prostate cancer typically undergo androgen-deprivation therapy (ADT), but the benefits are often short-lived, and responses are variable. Failure to respond to ADT invariably leads to metastatic disease, and ultimately death. To investigate differential responses to ADT, we performed whole-transcriptome analysis of 20 patient-matched pre-ADT biopsies and post-ADT prostatectomy specimens, and observed that all patients lost transcriptional signatures indicative of the androgen receptor (AR)-dependent subtype, after treatment. We also identified two subgroups of patients with either a strong or weak transcriptional response to ADT. The strong responders maintained the more aggressive subtype signal, while the weak responders lost expression of these genes and more resembled an AR-suppressed, basal subtype. We generated a strong responder transcriptional network using the PANDA program and integrated expression data from our cohort, protein-protein interaction, and DNA binding motif data. We also leveraged the expression data from a large public dataset of over 800 metastatic and primary samples to construct a metastatic lesion transcriptional network. We identified 20 common transcription factor coordinated groups (TFCGs) associated with both the strong responders and metastatic lesions, including GLI3/GLI2, SOX4/FOXA2/GATA4, ERF/ETV5/ETV3/ELF4, and a TFCG containing JUN, JUNB, JUND, FOS, FOSB, and FOSL1. Many TFCGs in the metastatic network were subsets of larger groups in the strong responders network, implicating these transcription factor associations as potentially critical for both the differential ADT response and metastatic disease progression. Citation Format: Nitya V. Sharma, Kathryn L. Pellegrini, Veronique Ouellet, Felipe O. Giuste, Selvi Ramalingam, Kenneth Watanabe, Eloise Adam-Granger, Lucresse Fossouo, Sungyong You, Michael R. Freeman, Paula Vertino, Karen Conneely, Adeboye O. Osunkoya, Dominique Trudel, Anne-Marie Mes-Masson, John A. Petros, Fred Saad, Carlos S. Moreno. Transcription factor relationships associated with androgen-deprivation therapy response and metastatic progression in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2269.
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
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 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".