Asporin Restricts Mesenchymal Stromal Cell Differentiation, Alters the Tumor Microenvironment, and Drives Metastatic Progression
Bibliographic record
Abstract
Abstract Tumor progression to metastasis is not cancer cell autonomous, but rather involves the interplay of multiple cell types within the tumor microenvironment. Here we identify asporin (ASPN) as a novel, secreted mesenchymal stromal cell (MSC) factor in the tumor microenvironment that regulates metastatic development. MSCs expressed high levels of ASPN, which decreased following lineage differentiation. ASPN loss impaired MSC self-renewal and promoted terminal cell differentiation. Mechanistically, secreted ASPN bound to BMP-4 and restricted BMP-4–induced MSC differentiation prior to lineage commitment. ASPN expression was distinctly conserved between MSC and cancer-associated fibroblasts (CAF). ASPN expression in the tumor microenvironment broadly impacted multiple cell types. Prostate tumor allografts in ASPN-null mice had a reduced number of tumor-associated MSCs, fewer cancer stem cells, decreased tumor vasculature, and an increased percentage of infiltrating CD8+ T cells. ASPN-null mice also demonstrated a significant reduction in lung metastases compared with wild-type mice. These data establish a role for ASPN as a critical MSC factor that extensively affects the tumor microenvironment and induces metastatic progression. Significance: These findings show that asporin regulates key properties of mesenchymal stromal cells, including self-renewal and multipotency, and asporin expression by reactive stromal cells alters the tumor microenvironment and promotes metastatic progression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".