Abstract 2367: Characterizing the reciprocal regulation of an ABI1-dependent androgen receptor axis in prostate cancer
Bibliographic record
Abstract
Abstract Background: Prostate cancer (PCa) affects nearly 50% of males over 60. Therapies for advanced PCa primarily target the androgen receptor (AR), a ligand-activated transcription factor, which is a key driver of PCa tumor growth. Our previous research demonstrated that ABI1 acts as a tumor suppressor in PCa. ABI1 is a scaffold protein for the WAVE Regulatory Complex, positively regulates cell adhesion, and inhibits integrin activation through sequestering key kinases. We have observed a physical interaction between AR and ABI1. In this study, we aim to characterize the ABI1-dependent AR regulation in PCa. Method: We generated an ABI1 KO cell line model in LNCaP cells using CRISPR-Cas9. We then used mutagenesis to develop ABI1 binding mutants (W485N and ∆SH3) and generated ABI1 rescue cell lines in ABI1-KO. We performed qPCR, co-immunoprecipitation, subcellular fractionation, western blotting, in vitro assay, live-cell imaging, and PLA. We purified both AR and ABI1 proteins for in vitro analysis, performed turbidity and liquid-liquid droplet formation assays under DIC. Results: In cellulo binding assays indicate interaction of AR-NTD with the ABI1-SH3 domain. Expression of ABI1-W485N in KO cell line showed decreased binding, while ABI1-∆SH3 showed no observable binding to AR in co-IP assays compared to wildtype control. We then performed subcellular fractionation assays and saw decreased AR nuclear localization compared to ABI1-WT control. Decreased nuclear localization in ABI1-W485N was associated with decreased mRNA expression of hallmark AR target genes, KLK3 and FKBP5. In vitro turbidity assays indicated the conditions in which AR and ABI1 have propensity to phase separate. We then performed a liquid-liquid droplet assay. AR and ABI1 formed liquid-liquid droplets individually. We labeled ABI1 with Alexaflour 488 and saw that ABI1 was recruited to AR droplets indicating that AR and ABI1 can co-phase separate. PLA assays in cellulo and in vivo patient tumor samples showed positive interactions of AR-ABI1 in the nucleus. We then used live-cell observation and saw co-localization of biomolecular condensates for AR and ABI1. Conclusions: Our studies demonstrate that ABI1 plays a role in AR transcriptional pathway. Loss of ABI1 resulted in decreased nuclear AR and subsequent decrease in mRNA expression of AR target genes. Due to the intrinsically disordered structure of AR and ABI1, they were both able to phase separate individually as well as together. AR stimulation increased PLA interactions in nucleus of cells. The co-localization of AR and ABI1 in biomolecular condensates was changed upon androgen deprivation conditions. Future studies will investigate if anti-AR treatments could lead to the dysregulation of ABI1 and promote reactivation of AR pathway through ABI1-AR axis. Findings will allow for novel insights into the mechanisms underlying AR and ABI1 in prostate metastatic progression. Citation Format: Baylee A. Porter-Hansen, Alaji Bah, Alfonso Urbanucci, Konsta Kukkonen, Fan Zhang, Sonia Kung, Ladan Fazli, Martin E. Gleave, Gennady Bratslavsky, Leszek Kotula. Characterizing the reciprocal regulation of an ABI1-dependent androgen receptor axis in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2367.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".