Exosomes secreted by mesenchymal stromal/stem cell-derived adipocytes promote breast cancer cell growth via activation of Hippo signaling pathway
Bibliographic record
Abstract
OBJECTIVE: Although adipocytes are the most abundant stromal cell component in breast cancer tissues, their interaction with breast cancer cells has been less investigated compared to cancer-associated fibroblasts or macrophages. Exosomes are a novel way of cell-cell communication and have been demonstrated to play an important role in various biological processes. However, to our knowledge, only a few studies have reported the effects of adipocyte exosomes on tumor development. Here, utilizing exosomes isolated from in vitro mesenchymal stromal/stem cell (MSC)-differentiated adipocytes, we systematically investigated this issue in a breast cancer model. MATERIAL AND METHODS: Exosomes were isolated from MSC-differentiated adipocytes and added to breast cancer cells MCF7. Cell proliferation was detected by MTS, and migration was analyzed by wound healing and transwell assay. An in vivo mouse xenograft model was used to evaluate MSC-differentiated adipocyte exosomes' contribution to tumor growth. Signaling pathway activation was evaluated by western blot and immunofluorescence staining. RESULTS: We found MSC-differentiated adipocyte-derived exosomes are actively incorporated by breast cancer cell MCF7 and subsequently promote MCF7 proliferation and migration as well as protect MCF7 from serum derivation or chemotherapeutic drug-induced apoptosis in vitro. In the in vivo mouse xenograft model, depletion of exosomes reduces tumor-promoting effects of adipocytes. Transcriptomic analysis of MSC-differentiated adipocyte exosome-treated MCF7 identified several activated signaling pathways, among which we confirm the Hippo signaling pathway and found a blockade of this pathway leads to a reduced growth-promoting effect of adipocyte exosomes. CONCLUSION: Taken together, our findings provide new insights into the role of adipocyte exosomes in the tumor microenvironment.
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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 | 0.001 | 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".