Stroma-derived miR-214 coordinates tumor dissemination
Bibliographic record
Abstract
Abstract Background Tumor progression is based on a close interaction between cancer cells and Tumor MicroEnvironment (TME). Here, we focus on the role that Cancer Associated Fibroblasts (CAFs), Mesenchymal Stem Cells (MSCs) and microRNAs (miRs) play in breast cancer and melanoma malignancy. Methods We used public databases to investigate miR-214 expression in the stroma compartment of primary human samples and evaluated tumor formation and dissemination following tumor cell injections in miR-214 overexpressing (miR-214 over ) and knock out (miR-214 ko ) mice. In addition, we dissected the impact of Conditioned Medium (CM) or Extracellular Vesicles (EVs) derived from miR-214-rich or depleted stroma cells on cell metastatic traits. Results We evidence that the expression of miR-214 in human cancer or metastasis samples mostly correlates with stroma components and, in particular, with CAFs and MSCs. We present data revealing that the injection of tumor cells in miR-214 over mice leads to increased extravasation and metastasis formation. In line, treatment of cancer cells with CM or EVs derived from miR-214-enriched stroma cells potentiate cancer cell migration/invasion in vitro . Conversely, dissemination from tumors grown in miR-214 ko mice is impaired and metastatic traits significantly decreased when CM or EVs from miR-214-depleted stroma cells are used to treat cells in culture. Instead, extravasation and metastasis formation are fully re-established when miR-214 ko mice are pretreated with miR-214-rich EVs of stroma origin. Mechanistically, we also show that tumor cells are able to induce miR-214 production in stroma cells, following the activation of IL-6/STAT3 signaling, which is then released via EVs subsequently up-taken by cancer cells. Here, a miR-214-dependent pro-metastatic program becomes activated. Conclusions Our findings highlight the relevance of stroma-derived miR-214 and its release in EVs for tumor dissemination, which paves the way for miR-214-based therapeutic interventions targeting not only tumor cells but also the TME.
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 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 | 0.002 | 0.001 |
| 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".