MiR-137 Contributes to Drug Susceptibility and Chromosomal Instability of Multiple Myeloma through Targeting AURKA
Bibliographic record
Abstract
Abstract Background: MicroRNAs are non-coding small RNAs that modulate protein expression and implicated in the pathogenesis of much kind of cancers, including multiple myeloma (MM). Previous study revealed that mic-137 was significant down regulated in MM patients compared with health donors. The purpose of this study is to investigate how miR-137 involved in pathogenesis and drug resistance in MM and its potential as prognostic biomarker. Materials and Methods: Real-time RT-PCR was performed to identify the expression of miR-137 in 6 MM cell lines and CD138+ cell sorted from 21 MM patients and 10 healthy donors. The methylation status of miR-137 CpG island was determined by bisulfite pyrosequencing, methylation specific polymerase chain reaction （MSP）and bisulfite sequencing PCR (BSP). The functional roles of miR-137 in MM were characterized by CCK-8 assay, soft agar clonogenic- formation, standard apoptosis assay and CGH array (CytoScan"HD Array, Affymetrix). Effect of miR-137 on MM progression in vivo was assessed in the NOD/SCID mice models. In addition, to further identify miR-137 targets, we used bioinformatics analysis and confirmed by luciferase reporter assay. In addition, a total of 19 paired sequential samples with GEP and clinical data, obtained from published studies, were analyzed. Results: The expression of miR-137 was down regulated in all 6 MM cell lines and MM patients (p=0.0017). Further study revealed that methylation of the miR-137 CpG islands was frequently observed in MM cell lines (p<0.0001) and patients (p=0.004) compared with healthy donor by MSP and BSP. Functional study of Cck-8 assay, soft agar clonogenic assay and standard apoptosis assay showed miR-137-OE NCI-H929 significantly inhibited cell proliferation and increased cell drug sensitivity compared with NCI-H929-EV in vitro. Meanwhile, the tumorigenicity of miR-137 overexpressed NCI-H929 reduces tumor volume in xenograft models at day 20 and prolonged the survival of NOD-SCID mice following tail vein injection of miR-137-OE NCI-H929 compared with control (p=0.0198). Overexpression of miR-137 inactivates both AKT and MAPK/ERK Signaling pathway by up-regulating p53 and down-regulating pAKT. Interestingly, CGH-array analysis indicated miR-137 overexpression could decrease chromosomal instability in NCI-H929, such as gain at 1q21, loss at 12p13.31 and 14q22.2 etc. To explore the mechanism of miR-137 involved in chromosome instability, our results demonstrated miR-137 mainly through up regulated AURKA expression and luciferase assay confirmed miR-137 targeted at position 374-380 of AURKA 3’UTR. Conclusion: Our data suggested that miR-137 was epigenetic silenced and targeted AURKA expression to contribute to drug susceptibility and chromosomal Instability in MM. Future studies will be performed on how miR-137 targets AURKA linked to the p53 pathway and evaluating miR-137 as prognostic biomarkers and targets for treatment in MM. Disclosures No relevant conflicts of interest to declare.
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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) | 0.003 | 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".