Small-Molecule Targeting of Musashi RNA-Binding Activity in Acute Myeloid Leukemia
Notice bibliographique
Résumé
Abstract RNA-binding proteins (RBPs) play critical roles in cell homeostasis by controlling gene expression post-transcriptionally, contributing to mRNA processing events (splicing, polyadenylation, localization, stability, export and translation). The involvement of RBPs to tumorigenesis, through genetic perturbation or epigenetic dysregulation, has been found in a variety of human cancers. The RBP MUSASHI-2 (MSI2) contributes to the pathogenesis of a spectrum of solid tumors and hematologic malignancies and predicts a worse clinical outcome in patients with myeloid and acute lymphoblastic leukemia (MDS, AML and ALL). Thus, MSI2 has been proposed as a putative biomarker for diagnosis as well as a potential therapeutic target for AML. However, there are currently no specific inhibitors for MSI. Previous work from our lab reported a Fluorescent Polarization (FP) screen with 6,208 compounds identifying small-molecules with MSI RNA-binding inhibition activity. Here, we characterize Ro 08-2750 (Ro), best FP screen hit, as a MSI RNA-competitive inhibitor. Electrophoresis Mobility Shift Assays (EMSA) demonstrated Ro inhibition of MSI2-RNA complexes formation. MicroScale Thermophoresis (MST) interaction studies showed that the compound interacts with MSI2 full-length and RNA-Recognition Motif 1 (RRM1) with μM affinity and with nearly 20-fold lower KD to an RBP control (SYNCRIP). We obtained the crystal structure of MSI2 RRM1 at 1.7Å and docking and mutagenesis validation confirmed K22, F66, F97 and R100 as crucial binding residues in the RNA-binding pocket. To further prove structure activity relationship, we used two chemical analogs: Ro-OH, an alcohol derivative of the Ro's aldehyde, showed 10-fold reduced activity and Ro-NGF, containing the Ro isoalloxazine scaffold, showed no binding or activity in vitro. Of note, in proliferation assays Ro EC50 was 2.6±0.1 μM in MLL-AF9 bone marrow cells and an average of 8.4±1.1 μM in MOLM13 and K562 human AML cells, whereas RoOH and RoNGF showed 10-fold or >50 μM EC50, respectively. Ro significantly reduced binding of MSI2 to its mRNA targets (such as cMYC, CDKN1A or SMAD3) in an RNA-IP and a direct effect in their protein translation in human leukemia cells. RNA-sequencing of 4h Ro treated MOLM13 and K562 AML cells resulted in gene expression changes that enriched for the gene expression profiling after shRNA mediated depletion of MSI2 in CML-BC and AML cell lines. Ro demonstrated a significant therapeutic index abolishing MLL-AF9+ BM colony formation at concentrations that did not affect the plating efficiency of normal Lin-Sca+cKit+ (LSK) cells. Similarly, Ro demonstrated differential sensitivity in three AML patient samples colony formation compared to normal human CD34+ cord blood cells. Finally, we sought to determine Ro in vivo activity by using an aggressive murine MLL-AF9 murine leukemia model. Acute treatment (4h and 12hr) with 13.75 mg/kg Ro in DMSO reduced c-KIT protein abundance and intracellular c-MYC. Administration of the same Ro dose every 3 days was well tolerated and showed a significant reduction in spleen weights, white blood cell counts and c-MYC levels compared to the controls. These data provide the feasibility that targeting MSI in vivo could have therapeutic efficacy in AML. This study identifies and characterizes Ro 08-2750 as a compound selectively inhibiting the oncogenic RNA-binding activity of MSI in myeloid leukemia. Ro targeting an RRM motif to block RNA activity represents a valuable proof of concept for the general inhibition of these class of RNA regulators. Overall, we provide a framework to identify and test novel RBP inhibitors thus validating this class of proteins as chemically "druggable" novel therapeutic targets in cancer. Disclosures Chodera: Schrödinger: Consultancy, Membership on an entity's Board of Directors or advisory committees.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».