Human bone marrow adipocytes drive prostate cancer bone metastasis progression via lipid-mediated induction of Angiopoietin-like 4
Bibliographic record
Abstract
Abstract Bone is the main metastatic site in advanced prostate cancer (PCa) and contains bone marrow adipocytes (BMAds), which account for more than 70% of adult bone marrow. However, their role in the progression of PCa metastases remains poorly understood. Herein, we developed a physiologically relevant 3D culture model using primary human BMAds from red hematopoietic rich-areas (rBMAds) and we showed that rBMAds engage in metabolic crosstalk with PCa cells. Specifically, rBMAds release free fatty acids (FFAs) through a non-canonical lipolytic pathway and these FFAs are taken up by PCa cells inducing a transcriptional reprogramming that promotes motility. Among the responsive genes, Angiopoietin like 4 (ANGPTL4) is the most upregulated via a peroxisome proliferator-activated receptor γ-dependent mechanism, and its silencing abolishes the rBMAd-driven migratory and invasive phenotype. Clinically, elevated ANGPTL4 expression is associated with poor overall survival specifically in PCa bone metastases, is maintained during metastatic progression, and is indicative of aggressive disease. Together, our findings uncover a novel adipocyte-tumor interaction and identify ANGPTL4 as a key mediator and potential therapeutic target in bone-metastatic PCa.
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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) | 0.002 | 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".