Inhibition of Pten deficient Castration Resistant Prostate Cancer by Targeting of the SET - PP2A Signaling axis
Bibliographic record
Abstract
The PP2A signaling axis regulates multiple oncogenic drivers of castration resistant prostate cancer (CRPC). We show that targeting the endogenous PP2A regulator, SET (I2PP2A), is a viable strategy to inhibit prostate cancers that are resistant to androgen deprivation therapy. Our data is corroborated by analysis of prostate cancer patient cohorts showing significant elevation of SET transcripts. Tissue microarray analysis reveals that elevated SET expression correlates with clinical cancer grading, duration of neoadjuvant hormone therapy (NHT) and time to biochemical recurrence. Using prostate regeneration assays, we show that in vivo SET overexpression is sufficient to induce hyperplasia and prostatic intraepithelial neoplasia. Knockdown of SET induced significant reductions in tumorgenesis both in murine and human xenograft models. To further validate SET as a therapeutic target, we conducted in vitro and in vivo treatments using OP449 - a recently characterized PP2A-activating drug (PAD). OP449 elicits robust anti-cancer effects inhibiting growth in a panel of enzalutamide resistant prostate cancer cell lines. Using the Pten conditional deletion mouse model of prostate cancer, OP449 potently inhibited PI3K-Akt signaling and impeded CRPC progression. Collectively, our data supports a critical role for the SET-PP2A signaling axis in CRPC progression and hormone resistant disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".