Androgen-Regulated SPARCL1 in the Tumor Microenvironment Inhibits Metastatic Progression
Bibliographic record
Abstract
Prostate cancer is a leading cause of cancer death in men due to the subset of cancers that progress to metastasis. Prostate cancers are thought to be hardwired to androgen receptor (AR) signaling, but AR-regulated changes in the prostate that facilitate metastasis remain poorly understood. We previously noted a marked reduction in secreted protein, acidic and rich in cysteine-like 1 (SPARCL1) expression during invasive phases of androgen-induced prostate growth, suggesting that this may be a novel invasive program governed by AR. Herein, we show that SPARCL1 loss occurs concurrently with AR amplification or overexpression in patient-based data. Mechanistically, we demonstrate that SPARCL1 expression is directly suppressed by androgen-induced AR activation and binding at the SPARCL1 locus via an epigenetic mechanism, and these events can be pharmacologically attenuated with either AR antagonists or HDAC inhibitors. We establish using the Hi-Myc model of prostate cancer that in Hi-Myc/Sparcl1(-/-) mice, SPARCL1 functions to suppress cancer formation. Moreover, metastatic progression of Myc-CaP orthotopic allografts is restricted by SPARCL1 in the tumor microenvironment. Specifically, we show that SPARCL1 both tethers to collagen in the extracellular matrix (ECM) and binds to the cell's cytoskeleton. SPARCL1 directly inhibits the assembly of focal adhesions, thereby constraining the transmission of cell traction forces. Our findings establish a new insight into AR-regulated prostate epithelial movement and provide a novel framework whereby SPARCL1 in the ECM microenvironment restricts tumor progression by regulating the initiation of the network of physical forces that may be required for metastatic invasion of 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) | 0.002 | 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".