CD9 mediates the uptake of extracellular vesicles from cancer-associated fibroblasts that promote pancreatic cancer cell aggressiveness
Bibliographic record
Abstract
In pancreatic ductal adenocarcinoma (PDAC), signaling from stromal cells is implicated in metastatic progression. Tumor-stroma cross-talk is often mediated through extracellular vesicles (EVs). We previously reported that EVs derived from cancer-associated stromal fibroblasts (CAFs) that are abundant in annexin A6 (ANXA6 + EVs) support tumor cell aggressiveness in PDAC. Here, we found that the cell surface glycoprotein and tetraspanin CD9 is a key component of CAF-derived ANXA6 + EVs for mediating this cross-talk. CD9 was abundant on the surface of ANXA6 + CAFs isolated from patient PDAC samples and from various mouse models of PDAC. CD9 colocalized with CAF markers in the tumor stroma, and CD9 abundance correlated with tumor stage. Blocking CD9 impaired the uptake of ANXA6 + EVs into cultured PDAC cells. Signaling pathway arrays and further analyses revealed that the uptake of CD9 + ANXA6 + EVs induced mitogen-activated protein kinase (MAPK) pathway activity, cell migration, and epithelial-to-mesenchymal transition (EMT). Blocking either CD9 or p38 MAPK signaling impaired CD9 + ANXA6 + EV–induced cell migration and EMT in PDAC cells. Analysis of bioinformatic datasets indicated that CD9 abundance was an independent marker of poor prognosis in patients with PDAC. Our findings suggest that CD9-mediated stromal cell signaling promotes PDAC progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".