Microparticle Encapsulation of a Prostate-targeted Biologic for the Treatment of Liver Metastases in a Preclinical Model of Castration-resistant Prostate Cancer
Bibliographic record
Abstract
Abstract PRX302 is a highly potent, mutant bacterial pore-forming biologic protoxin engineered for selective activation by PSA, a serine protease expressed by benign and malignant prostate epithelial cells. Although being developed as a local therapy for benign prostatic hyperplasia and localized prostate cancer, PRX302 cannot be administered systemically as a treatment for metastatic disease due to binding to ubiquitously expressed glycosylphosphatidylinositol (GPI)-anchored proteins, which leads to poor accumulation within the tumor microenvironment. To overcome this limitation, poly-lactic-co-glycolic acid (PLGA) microparticles encapsulating the protoxin were developed, which are known to accumulate in the liver, a major site of metastasis for prostate cancer and other solid tumors. A highly sensitive and reproducible sandwich ELISA to quantify PRX302 released from microparticles was developed. Utilizing this assay, PRX302 release from different microparticle formulations was assessed over multiple days. Hemolysis assays documented PSA-dependent pore formation and lytic potential (i.e., function) of the released protoxin. MTT assays demonstrated that conditioned supernatant from PRX302-loaded, but not blank (i.e., unloaded), PLGA microparticles was highly cytotoxic to PC3 and DU145 human prostate cancer cells in the presence of exogenous PSA. Microparticle encapsulation prevented PRX302 from immediately interacting with GPI-anchored proteins as demonstrated in a competition assay, which resulted in an increased therapeutic index and significant antitumor efficacy following a single dose of PRX302-loaded microparticles in a preclinical model of prostate cancer liver metastasis with no obvious toxicity. These results document that PRX302 released from PLGA microparticles demonstrate in vivo antitumor efficacy in a clinically relevant preclinical model of metastatic prostate cancer.
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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 | 0.001 |
| 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 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".