Extracellular vesicles from genetically unstable, oncogene-driven cancer cells trigger micronuclei formation in endothelial cells
Bibliographic record
Abstract
Oncogenic transformation impacts cancer cell interactions with their stroma, including through formation of abnormal blood vessels. This influence is often attributed to angiogenic growth factors, either soluble, or associated with tumor cell-derived extracellular vesicles (EVs). Here we examine some of the cancer-specific components of EV-mediated tumor-vascular interactions, including the impact of genetic driver mutations and genetic instability. Cancer cells expressing mutant HRAS oncogene exhibit aberrations of chromatin architecture, aneuploidy, cytoplasmic chromatin deposition and formation of micronuclei with a non-random chromosome content. EVs released from such HRAS-driven cells carry genomic DNA, including oncogenic sequences, and transfer this material to endothelial cells while inducing abnormal formation of micronuclei, along with cell migration and proliferation. Micronuclei were also triggered following treatment with EVs derived from glioma cells (and stem cells) expressing EGFRvIII oncogene, and in both endothelial cells and astrocytes. EVs from HRAS and EGFRvIII-driven cancer cells carry 19 common proteins while EVs from indolent control cells exhibit more divergent proteomes. Immortalized endothelial cell lines with disrupted TP53 pathway were refractory to EV-mediated micronuclei induction. We suggest that oncogenic transformation and intercellular trafficking of cancer-derived EVs may contribute to pathological vascular responses in cancer due to intercellular transmission of genomic instability.
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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 | 0.000 | 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) | 0.000 | 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".