MP84-11 BONE MICROENVIRONMENT TARGETED NANOPARTICLES FOR METASTATIC PROSTATE CANCER TREATMENT
Bibliographic record
Abstract
AR-driven transcriptome away from genes associated with prostate epithelial differentiation towards genes associated with cell survival and mitosis.Previously we showed that Gli proteins bind to the enigmatic N-terminal tau5 transactivation domain of AR and co-activate full-length and truncated ARs.When exogenously overexpressed in androgen growth-dependent LNCaP cells, Gli proteins can elicit androgen growth-independence (AI).Here we show that interference with Gli-AR binding in AI LNCaP variants suppresses the alternate AR transcriptome, restores the AR differentiation transcriptome and suppresses AI growth.METHODS: Androgen growth-independent, enzalutamide-(ENZ-) resistant LNCaP cell variants, LNCaP-AI and LN95, were treated with Gli inhibitors (GANT61 and HPI-1) or transfected with Gli3 siRNA or transfected with a small decoy peptide from the Gli2 AR-binding domain (Gli-DP) to disrupt intracellular Gli-AR interactions.RNAs were extracted and expressions of differentiation genes (DGs), PSA and KLK2 or mitotic-regulatory genes (MRGs), UBE2C, CDK1 and CDC20 were measured by real-time qRT-PCR and compared to control-treated (vehicle, non-targeting siRNA or empty vector transfected) cells.Cell growth after Gli manipulation(s) was measured on the Incuyte-Zoom instrument that quantifies realtime cell growth and was compared to control cells.Increasing doses of Enzalutamide (ENZ) were titrated into Gli-DP transfected cells to test whether it cooperates with Gli-AR binding disruption in suppressing AI growth.RESULTS: Suppression of global Gli activity, Gli3-specific knockdown and exogenous Gli-DP expression significantly suppressed expressions of MRGs but increased expressions of DGs in both AI cell types.These actions also significantly slowed growth of the cells, with Gli inhibitors and Gli3 knockdown showing complete growth suppression whereas the Gli-DP achieved half-suppression.ENZ treatments further increased growth suppression of the Gli-DP expressing cells.CONCLUSIONS: Our results identify the potential for Gli-AR binding interference as a means to control AI/CRPC growth.This interference further cooperates with ENZ to provide very robust growth suppression showing that combined targeting of AR N-terminal and C-terminal domains holds the key for more effective treatments for CRPC.
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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".