Membrane Derived Micorvesicles - Underappreciated Components of the Tumor Microenvironment That Modulate Tumor Growth, Vascularization and Metastasis.
Bibliographic record
Abstract
Abstract Viable eukaryotic cells shed circular membrane fragments called microvesicles (MV) from the cell surface and secrete them from the endosomal compartments. These MV, which are different from apoptotic bodies, are enriched in lipids, proteins and mRNA. We postulate that MV play an important and underappreciated role in cell-cell communication by i) stimulating target cells with ligands that the MV express, ii) fusing with target cells and thus transferring various receptors to their surface, and iii) delivering mRNA, lipids and proteins. Since tumor cells secrete large quantities of MV we hypothesized that the latter are important constituents of the tumor microenvironment and their role in tumor progression merited investigation. First, we observed that human and murine lung cancer cell lines secrete more MV in response to non-apoptotic doses of hypoxia, irradiation and chemotherapy. The MV derived from human cancer cells chemoattracted bone marrow-, lymph node- and lung-derived fibroblasts and endothelial cells and activated in these stromal cells the phosphorylation of MAPKp42/44 and AKT. Furthermore, they also induced in bone marrow- and lung-derived fibroblasts expression of LIF, OSM, IL-11, VEGF and MMP-9. Moreover, conditioned media from marrow fibroblasts exposed to MV induced phosphorylation of STAT-3 proteins and chemoattracted lung cancer cells in a LIF- and OSM-dependent manner and, together with IL-11 and VEGF, activated osteoclasts and endothelial cells. Furthermore, MV from cancer cells embedded in Matrigel implants strongly stimulated angiogenesis. We also found that tumor-derived MV express tissue factor (TF) and activate platelets and as a result of this MV derived from activated platelets transfer several adhesion molecules from platelets to the tumor cell surface. This increases adhesiveness of lung cancer cells in endothelium and their metastatic spread in vivo after injection into syngeneic mice. Finally, we found that formation of MV depends on the formation of membrane lipid rafts. Thus we postulate that tumor- and platelet-derived MV are underappreciated constituents of the tumor microenvironment and play a pivotal role in tumor progression/metastasis and angiogenesis. As MV formation appears to be lipid raft-dependent, we suggest that inhibitors of membrane lipid raft formation (e.g, statins or polyene antibiotics) could decrease MV-dependent tumor spread/growth and we are currently testing this hypothesis in animal models in vivo.
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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".