miR-181c regulates MCL1 and cell survival in GATA2 deficient cells
Bibliographic record
Abstract
GATA2 is a transcription factor critical for hematopoiesis. Germline mutations in GATA binding protein 2 (GATA2) led to haploinsufficiency, severe cytopenias of multiple cell lineages, susceptibility to infections and strong propensity to develop myelodysplastic syndrome, and acute myeloid leukemia. Mechanisms of progressive cytopenias remain unclear. MicroRNA (miRNA) represents a unique mechanism of post-transcriptional gene regulation. In this study, miRNA profiles were evaluated and eight miRNAs were found to be differentially expressed (≥2-fold, P ≤ 0.05) in patient-derived cell lines (N = 13) in comparison to controls (N = 10). miR-9, miR-181a-2-3p, miR-181c, miR-181c-3p, miR-486-3p, and miR-582 showed increased expression, whereas miR-223 and miR-424-3p showed decreased expression. Cell death assays indicated that miR-181c potently induces cell death in lymphoid (Ly-8 and SP-53) and myeloid (HL-60) cell lines. miR-181c was predicted to target myeloid cell leukemia (MCL)1, which was confirmed by transfection assays, resulting in significantly reduced MCL1 mRNA and decreased live cell numbers. Bone marrow analysis of 34 GATA2 patients showed significantly decreased cellularity, CD34-positive cells, monocytes, dendritic cells, NK cells, B cells, and B cell precursors in comparison to healthy controls (N = 29; P < 0.001 for each), which was accompanied by decreased levels of MCL1 (P < 0.05). GATA2 expression led to significant repression of miR-181c expression in transfection experiments. Conversely, knockdown of GATA2 led to increased miR-181c expression. These findings indicate that miR-181c expression is increased and MCL1 levels decreased in GATA2 deficiency cells, and that GATA2 represses miR-181c transcription. Increased miR-181c may contribute to elevated cell death and cytopenia in GATA2 deficiency potentially through down-regulation of MCL1.
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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 | 0.001 |
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".