Marcks Inhibition By a Peptide Inhibitor, MPS, Cooperates with Bortezomib to Effectively Eliminate Drug Resistance in Multiple Myeloma
Notice bibliographique
Résumé
Abstract Overexpression of myristoylated alanine-rich C kinase substrate (MARCKS) has been implicated in the progression of multiple cancer types including multiple myeloma (MM). Our previous study showed that overexpression of MARCKS in MM cells plays an important role in drug resistance. However; the mechanism(s) underlying MARCKS overexpression and its association with drug resistance in MM remain undefined. Using miRNA target scan algorithms, we identified miR-34a as a regulator of MARCKS, which is underexpressed in drug-resistant MM cells (8226-R5 and MM1R) in comparison to parental cells (8226 and MM1S, respectively). Using luciferase assays, we demonstrated direct targeting of MARCKS by miR-34a. Notably, targeting of MARCKS by miR-34a overexpression re-sensitized the resistant cells to anti-myeloma drugs. Moreover, since all known biological functions of MARCKS including its oncogenic effects are conducted by its phosphorylated form, we investigated whether inhibitor of MARCKS phosphorylation could antagonize drug resistance in MM cells. We showed that a MARCKS PSD peptide inhibitor (MPS) had a dose dependent cytotoxic effect on drug resistant MM cells in comparison to its mutated (inactive) form, but minimal cytotoxicity on normal peripheral blood mononuclear cells (PBMCs). Furthermore, MPS treatment sensitized drug-resistant MM cells to bortezomib (BTZ), a first line proteasome inhibitor that is widely used in the treatment of MM. We further investigated the effect of MPS on tumorigenesis in mouse xenograft models of MM resistant cells. Combination of BTZ plus MPS significantly suppressed tumor growth and prolonged overall survival as compared with MPS alone, BTZ alone or vehicle treated controls. IHC analysis of xenograft tumor sections revealed that combination treatment of MPS and BTZ resulted in decreased proliferation (Ki67) and increased apoptosis (TUNEL), compared to either BTZ or MPS alone. These results support that targeting of phospho-MARCKS by MPS contributes to drug sensitivity in MM resistant cells. Furthermore, we investigated the mechanisms by which MPS induces cell death and overcome bortezomib resistance. Following MPS treatment, PUMA was accumulated both in MM1R and 8226R5 MM cell lines, indicating that MPS treatment may lead to apoptosis. Interestingly, the level of LC3BII, a marker of autophagy, was also significantly upregulated, suggesting enhanced autophagic flux after MARCKS inhibition. The significant upregulation of LC3BII observed in both MM1R and 8226R5 MM cell lines after MARCKS silencing further confirmed the correlation between MARCKS inhibition and autophagy induction. Remarkably, MARCKS-silenced drug resistant MM cells were more vulnerable than negative control cells to the autophagy inhibitor chloroquine (CQ). More significant cytotoxicity of the BTZ plus CQ combo was also detected in MARCKS-inhibited MM cells than in negative control cells. Mechanistically, co-immuno-precipitation assays revealed increased interactions of PUMA with both Mcl-1 and Bcl-xL in MARCKS-silenced 8226R5 cells, while the interaction between Beclin-1 and Bcl-xL in MARCKS silenced 8226R5 cells was dampened. These results suggest that PUMA upregulation after MRCKS inhibition enhances the initiation of autophagic response by sequestering Bcl-2 family proteins like Bcl-xL from Beclin-1/Vps34 complexes. Taken together, our results demonstrate that the MPS peptide can sensitize drug resistant MM cell to anti-myeloma drugs by inhibiting MARCKS phosphorylation in vitro and in vivo. These findings underscore the importance of MARCKS suppression in antagonizing adaptive BTZ resistance and provide novel venues to treat MM. Disclosures No relevant conflicts of interest to declare.
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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) | 0,001 | 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 ».