Targeting a Highly Deregulated eIF4F Translation Initiation Complex Sensitises IM-Resistant Cells to Tyrosine Kinase Inhibitors and Effectively Suppresses BCR-ABL1 Protein Expression
Notice bibliographique
Résumé
Background We previously reported that Abelson helper integration site-1 (AHI-1) is highly deregulated in chronic myeloid leukemia (CML) leukemic stem cells (LSCs) and mediates tyrosine kinase inhibitor (TKI) resistance. AHI-1 physically interacts with BCR-ABL1 and its SH3 domain interacts with BCR-ABL1 substrates, like dynamin-2, which regulate leukemic properties of CML LSCs. However, the molecular and biological roles of AHI-1 and its interacting partners in mediating TKI resistance remain largely unknown. Objective To investigate the molecular functions of AHI-1 and its SH3 domain in regulation of TKI resistance, using advanced antibody microarray analysis. Methods A high content antibody microarray was performed in BCR-ABL1+ cells co-transduced with wild-type (WT) AHI-1 or the deletion of AHI-1 SH3 domain (SH3Δ) with or without imatinib (IM). Changes in antibody signals for protein expression or phosphorylation were determined using limma and pathway enrichment analysis by g:Profiler. eIF4G1 genetic inhibition by lentiviral-mediated shRNA or pharmacological inhibition by SBI-756, was performed in TKI-resistant cells to assay translation initiation activity by proximity ligation assay (PLA), o-propargyl-puromycin (OPP), and polysome profiling. Results The antibody microarray analysis revealed that WT AHI-1 cells have the greatest number of changes in the phospho-proteome and proteome compared to BCR-ABL1+ cells and AHI-1 SH3Δ cells with and without IM. Pathway enrichment analysis identified that the targets with significantly increased differential antibody signal after IM treatment in WT AHI-1 cells were related to the regulation of translation initiation complex (p < 0.0001). Interestingly, our RNA-seq dataset analysis further identified several eukaryotic initiation factor 4F (eIF4F) complex members to be significantly increased in CD34+ CML patient cells compared to normal bone marrow, particularly eIF4G1, the scaffold protein of the eIF4F complex (2-fold, p = 0.001). WT AHI-1 cells also showed increased expression and phosphorylation of eIF4G1 (>2-fold) and eIF4B (>2-fold), a cofactor that regulates the helicase activity of the eIF4F complex, and cyclin D3 (a downstream protein of eIF4F translational activity) as compared to BCR-ABL1+ cells, by immunoblotting. These results were similarly demonstrated in IM-resistant cells as compared to IM-sensitive cells (2-5-fold, p < 0.05). Mechanistically, eIF4G1 knockdown by shRNA impaired survival (5-fold, p < 0.0001) and increased TKI sensitivity in IM-resistant cells (p < 0.0021). These cells showed reduced levels of eIF4F complex formation by PLA assay (p = 0.013) and reduced protein expression of cyclin D3 (40%, p = 0.0036) and BCR-ABL1 (70%). Similarly, IM-resistant cells were more sensitive to SBI-756 treatment, an eIF4G1 inhibitor (50% reduction, p = 0.0001) than IM-sensitive cells (30% reduction); these effects were enhanced by a combination of SBI-756 and IM (80%, p < 0.02). Furthermore, SBI-756 treatment reduced PLA foci formation (p = 0.014) and global protein synthesis rates (p < 0.0001). Polysome profiling demonstrated that IM-resistant cells had higher levels of translation activity, which was inhibited by SBI-756 treatment. Most interestingly, SBI-756 treatment reduced protein expression of BCR-ABL1 (70%) and cyclin D3 (40%) in these cells. Conclusion We have uncovered that the eIF4F complex, the key regulator of the mRNA-ribosome recruitment phase of translation initiation, has increased activity in IM-resistant cells. eIF4G1 inhibitor treatment sensitises IM-resistant cells to TKI and reduces BCR-ABL1 protein expression, providing potential treatment strategies to overcome TKI resistance.
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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) | 0,002 | 0,001 |
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 ».