miR-137 and miR-197 Induce Apoptosis and Suppress Tumorigenicity by Targeting MCL-1 in Multiple Myeloma
Bibliographic record
Abstract
PURPOSE: Deregulation of miRNA has been implicated in the pathogenesis of multiple myeloma. We identified miR-137 and miR-197, mapped to the chromosome 1p (12)-(21) deletion region, and examined their antimyeloma activity as tumor suppressors. EXPERIMENTAL DESIGN: The expression of miR-137/197 was examined in multiple myeloma and normal plasma cells by qRT-PCR. Functional effect of miR-137/197 was analyzed by cell viability, apoptosis, clonogenic, and migration assays. Antimyeloma activity of miR-137/197 was further evaluated in vivo by lentiviral-based or lipid-based delivery in a mouse xenograft model of multiple myeloma. RESULTS: miR-137/197 expression was significantly lower in multiple myeloma cell lines and multiple myeloma patient samples compared with normal plasma cells. Transfection of miR-137/197 resulted in reduction of MCL-1 protein expression, as well as alteration of apoptosis-related genes, and induction of apoptosis, inhibition of viability, colony formation, and migration in multiple myeloma cells. MCL-1 was further validated as a direct target of miR-137/197. Conversely, overexpression of MCL-1 partially reverted the effect of miR-137/197. Importantly, in vivo lentiviral-mediated or intratumor delivery of miR-137/197 induced regression of tumors in murine xenograft models of multiple myeloma. CONCLUSIONS: Our study reveals a novel role of miR-137/197 as tumor suppressors in mediating apoptosis in multiple myeloma cells by targeting MCL-1. Our findings provide a proof-of-principle that lentivirus-based or formulated synthetic miR-137/197 exerts therapeutic activity in preclinical models, and support a framework for development of miR-137/197-based treatment strategies in patients with multiple myeloma.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".