The 14q32.31 <i>DLK1-DIO3 MIR300 tumor suppressor</i> promotes leukemogenesis by inducing cancer stem cell quiescence and inhibiting NK cell anti-cancer immunity
Bibliographic record
Abstract
ABSTRACT Drug-resistance of tumor-initiating cells, impaired NK cell immune-response, PP2A loss-of-function and aberrant miRNA expression are cancer features resulting from microenvironmental- and tumor-specific signals. Here we report that genomic-imprinted MIR300 is a cell context-independent dual function tumor suppressor which is upregulated in quiescent leukemic stem (LSC) and NK cells by microenvironmental signals to induce quiescence and impair immune-response, respectively, but inhibited in CML and AML proliferating blasts to prevent PP2A-induced apoptosis. MIR300 anti-proliferative and PP2A-activating functions are differentially activated through dose-dependent CCND2/CDK6 and SET inhibition, respectively. LSCs escape PP2A-mediated apoptosis through TUG1 lncRNA that uncouples and limits MIR300 functions to cytostasis by regulating unbound- MIR300 levels. Halting MIR300 homeostasis restores NK cell activity and suppresses leukemic but not normal hematopoiesis by eradicating nearly all LSCs. Thus, MIR300 tumor suppressor activity is essential and therapeutically important for LSC-driven leukemias.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".