Exploring B7-H4’s Role in Prostate Cancer Dormancy after Androgen Deprivation Therapy: Extracellular Matrix Interactions and Therapeutic Opportunities
Bibliographic record
Abstract
Prostate cancer is mainly managed with androgen deprivation therapy (ADT), but this often leads to a dormant state and subsequent relapse as lethal castration-resistant prostate cancer (CRPC). Using our unique prostate cancer patient-derived xenograft dormancy models, we investigated this critical dormant phase and discovered a selective increase in B7-H4 expression during the dormancy period following mouse host castration. This finding is supported by observations in clinical specimens of patients with prostate cancer treated with ADT. Differential expression analyses revealed the enrichment of extracellular matrix (ECM)-cell interaction pathways in B7-H4-positive cells. Functional assays demonstrated a crucial role of B7-H4 in maintaining dormancy within the ECM niche. Specifically, B7-H4 expression in LNCaP cells reduced proliferation within the dormant ECM in vitro and significantly delayed relapse in castrated hosts in vivo. These results shed light on the dynamic regulation of B7-H4 during prostate cancer dormancy and underscore its potential as a therapeutic target for preventing CRPC relapse. Implications: Our study identified membranous B7-H4 expression during ADT-induced dormancy, highlighting its potential as a therapeutic target for managing dormant prostate cancer and preventing fatal CRPC relapse.
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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) | 0.001 | 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".