Tumor Suppressive Role of miR-342-5p in Human Chondrosarcoma Cells and 3D Organoids
Bibliographic record
Abstract
Chondrosarcomas are malignant bone tumors. Their abundant cartilage-like extracellular matrix and their hypoxic microenvironment contribute to their resistance to chemotherapy and radiotherapy, and no effective therapy is currently available. MicroRNAs (miRNAs) may be an interesting alternative in the development of therapeutic options. Here, for the first time in chondrosarcoma cells, we carried out high-throughput functional screening using impedancemetry, and identified five miRNAs with potential antiproliferative or chemosensitive effects on SW1353 chondrosarcoma cells. The cytotoxic effects of miR-342-5p and miR-491-5p were confirmed on three chondrosarcoma cell lines, using functional validation under normoxia and hypoxia. Both miRNAs induced apoptosis and miR-342-5p also induced autophagy. Western blots and luciferase reporter assays identified for the first time Bcl-2 as a direct target of miR-342-5p, and also Bcl-xL as a direct target of both miR-342-5p and miR-491-5p in chondrosarcoma cells. MiR-491-5p also inhibited EGFR expression. Finally, only miR-342-5p induced cell death on a relevant 3D chondrosarcoma organoid model under hypoxia that mimics the in vivo microenvironment. Altogether, our results revealed the tumor suppressive activity of miR-342-5p, and to a lesser extent of miR-491-5p, on chondrosarcoma lines. Through this study, we also confirmed the potential of Bcl-2 family members as therapeutic targets in chondrosarcomas.
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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".