The miRNA-193 Family Is a Potent Tumor-Suppressor and a Biomarker for Poor Prognosis in Acute Myeloid Leukemia
Bibliographic record
Abstract
Abstract Deregulated microRNA (miRNA) expression has been implicated in the pathogenesis of acute myeloid leukemia (AML). We previously showed that miR-193b is a STAT5-regulated miRNA that controls hematopoietic stem and progenitor cell (HSPC) expansion by modulating cytokine receptor signaling. Here we demonstrate that the miR-193 family members miR-193a and 193b are potent tumor suppressors in AML. Both miRNAs were downregulated in several cytogenetically-defined subgroups of pediatric and adult AML (n=202), whereas low miR-193b expression was an independent indicator for poor prognosis and survival. Accordingly, ectopic retroviral Hoxa9-Meis1 expression in HSPCs from miR-193b-/- mice resulted in a more aggressive disease with significantly shortened latency and survival as compared to miR-193bWT/WT HSPCs. Inversely, ectopic miR-193 expression in leukemic cells belonging to various AML subgroups decreased leukemic growth in vitro and prolonged survival of mice suffering from Hoxa9-Meis1-induced leukemia through a G1/S phase block. These effects were mediated by targeting c-KIT, KRAS and SOS2 - key factors of the KIT-RAS-RAF-MEK-ERK signaling cascade - as well as the downstream cell cycle regulator CCND1. Knockdown of each of these genes partially recapitulated the anti-proliferative effect of ectopic lentiviral miR-193 expression. As the tumor suppressive function is independent of patient age or AML cytogenetic background, these observations suggest an opportunistic role for miR-193 in future AML therapies. With the notion that a single miRNA can control aberrant MAPK signaling at multiple levels, restoring miR-193 expression in AML cells with constitutive activation of this cascade would assure high antileukemic efficacy, while avoiding the fast development of resistance mechanisms. Disclosures Heuser: Bayer Pharma AG: Research Funding; Novartis: Consultancy, Research Funding; BerGenBio: Research Funding; Tetralogic: Research Funding; Karyopharm Therapeutics Inc: Research Funding; Celgene: Honoraria; Pfizer: Research Funding. Mulaw:NuGEN: Honoraria. Baruchel:Jazz: Consultancy; Servier: Consultancy; Celgene: Consultancy; Novartis: Consultancy; Baxalta: Research Funding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".