The crucial role of DNA-dependent protein kinase and myelin transcription factor 1-like protein in the miR-141 tumor suppressor network
Bibliographic record
Abstract
Glioblastoma is the most aggressive brain tumor. Although miR-141 has been demonstrated to primarily function as a tumor suppressor in numerous malignancies, including glioblastoma, the mechanisms involved remain poorly understood. Here, it is shown that miR-141 is downregulated in glioblastoma cell lines and tissues and may exert its biological function via directly targeting myelin transcription factor 1-like (MYT1L). Using two glioblastoma cell lines that differ from each other by the functionality of DNA-dependent protein kinase (DNAPK), a functional involvement of DNAPK in the miR-141 tumor suppression network was observed. In M059K cells with a normal function of DNAPK, the enforced expression of miR-141 attenuated MYT1L expression and suppressed cell proliferation. Conversely, the inhibition of miR-141 expression promoted cell proliferation; however, in M059J cells with a loss-of-function DNAPK, miR-141 constitutively inhibited cell proliferation upon ectopic overexpression or inhibition. An overexpression of miR-141 suppressed M059J cell migration, while it had no effect on M059K. Furthermore, the ectopic expression of miR-141 induced an S-phase arrest in both cell lines, whereas the inhibition of miR-141 caused a G1 arrest in M059J and accelerated the S phase in M059K. An overexpression and suppression of miR-141 resulted in an aberrant expression of cell-cycle proteins, including p21. Moreover, MYT1L may be a transcription factor of p21 in p53-mutant cells, whereas DNAPK may function as a repressor of MYT1L. The findings revealed the crucial role of DNAPK in miR-141-mediated suppression of gliomagenesis and demonstrated that it may be a target molecule in miR-141-associated therapeutic interventions for glioblastoma.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".