Haploinsufficiency of miR-143 and miR-145 reveal targetable dependencies in resistant del(5q) myelodysplastic neoplasm
Bibliographic record
Abstract
Myelodysplastic neoplasms (MDS) are stem cell disorders characterized by ineffective hematopoiesis and risk of transformation to acute myeloid leukemia (AML). Chromosomal alterations are frequent in MDS, with interstitial deletion of chromosome 5q (del(5q)) being the most common. Lenalidomide is the current first-line treatment for del(5q) MDS and its efficacy relies on degradation of CK1α which is encoded by the CSNK1A1 gene located in the commonly deleted region (CDR) of chromosome 5q. However, lenalidomide-resistance is common, often secondary to loss-of-function mutations in TP53 or RUNX1. The CDR in del(5q) harbors several genes, including noncoding miRNAs, the loss of which contribute to disease phenotypes. miR-143 and miR-145 are located within the del(5q) CDR, but precise understanding of their role in human hematopoiesis and in the pathogenesis of del(5q) MDS is lacking. Here we provide evidence that deficiency of miR-143 and miR-145 plays a role in clonal expansion of del(5q) MDS. We show that insulin-like growth factor 1 receptor (IGF-1R) is a direct target of both miR-143 and miR-145. Our data demonstrate that IGF-1R inhibition reduces proliferation and viability of del(5q) cells in vitro and in vivo, and that lenalidomide-resistant del(5q) MDS cells depleted of either TP53 or RUNX1 are sensitive to IGF-1R inhibition. Resistant del(5q) MDS-L cells, as well as primary MDS marrow cells, are also sensitive to targeting of IGF-1R-related dependencies in del(5q) MDS, which include the Abl and MAPK signaling pathways. This work thus provides potential new therapeutic avenues for lenalidomide-resistant del(5q) MDS.
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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) | 0.002 | 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".