Skp2 Inhibition Diminishes Essential Cell Survival Markers c-Maf and c-Myc, Enhancing Therapeutic Efficacy Against Drug Resistant Multiple Myeloma
Notice bibliographique
Résumé
Multiple Myeloma (MM) presents challenges as a hematologic malignancy, with drug resistance leading to limited curative options and disease relapse despite advancements in therapy. Understanding the molecular mechanisms driving MM's development and progression is vital for identifying new treatment approaches. Clinical and experimental evidence supports the role of S-phase kinase-associated protein 2 (Skp2) in driving the progression of several cancers, including MM. We interrogated a public microarray dataset derived from clinical specimens of MM patients and observed a significantly higher expression of Skp2 within the relapsed patient cohort (N=28) compared to the newly diagnosed group (N=63) (P=0.0041). Additionally, we observed elevated Skp2 levels and decreased P27 Kip1 levels in drug-resistant MM cell lines (MM.1R and RPMI 8226.R5) compared to their parental cell lines (MM.1S and RPMI 8226). Hence, a comprehensive understanding of Skp2's molecular functions in drug-resistant MM becomes paramount for facilitating the development of precision-targeted interventions. We investigated Skp2's molecular interactions in MM by performing a targeted knockdown with siRNA in drug-resistant and sensitive cell lines (OPM1, RPMI.8226, MM.1S, and MM.1R). Immunoblot analysis showed reduced STAT3 activation and decreased levels of cell survival markers c-Maf and c-Myc. Treatment with 10uM of the small molecule inhibitor SkpinC1 also inhibited STAT3 activation and led to significant reductions in c-Maf and c-Myc protein levels compared to the vehicle-treated groups. These findings hold immense significance as c-Maf and c-Myc are intricately associated with MM progression and poorer outcomes, although there is limited information on their regulation by the Skp2/P27 axis. Functionally, treatment of the MM cell lines with increasing dosages of SkpinC1 showed a progressive decrease in MM cell line survival, with IC50 values spanning 5-15uM, signifying the broad applicability of the inhibitor among the tested cell lines. Moreover, flow cytometry-based analysis of the surviving cell population demonstrated that SkpinC1 based inhibition of the Skp2/P27 axis considerably decreased the percentage of proliferating M-phase cells, while elevating the proportion of quiescent and apoptotic cells relative to the control group. At the molecular level, targeted inhibition of the Skp2/P27 axis by SkpinC1 caused the accumulation of cell cycle inhibitors P27 Kip1, P21 (Cip1/Waf1), and P57 Kip2, activation of the tumor suppressive TP53 protein with a simultaneous decrease in phospho-MDM2 levels in addition to an increase in the levels of apoptotic markers cleaved PARP and Caspase 3. From a clinical perspective, we also probed the applicability of Skp2 inhibition using SkpinC1 as a potential strategy for managing therapeutic resistance in MM. We treated multiple MM cell lines (OPM1, RPMI.8226, MM.1S and MM.1R) using a combination of Lenalidomide (an immune modulator) or Bortezomib (a proteasomal inhibitor) with SkpinC1 and compared it with single agent treatments. Both Lenalidomide/SkpinC1 as well as Bortezomib/SkpinC1 showed a strong dose dependent decrease in the percentage of surviving cells relative to the single agent treatments, thereby highlighting the remarkable potential of targeting the Skp2/P27 axis for clinical therapy in MM. To gain deeper insights into the molecular roles of Skp2/P27 axis inhibition by SkpinC1, we subjected drug-resistant MM.1R cells to 10uM SkpinC1 treatment for 24 hours, followed by single-cell transcriptome sequencing. This approach illuminated considerable heterogeneity between the drug-treated and control cells, accompanied by global changes in various signaling pathways associated with cell survival. In conclusion, the inhibition of Skp2 in MM cells exerts a significant impact on crucial cell survival pathways, notably c-Maf and c-Myc, thereby promoting apoptosis and offering a promising therapeutic avenue to combat drug resistance in MM. The precise targeting of Skp2 using small molecule inhibitors, such as SkpinC1, demonstrates substantial therapeutic potential, enhancing the efficacy of combinatorial treatment approaches for more effective interventions in MM.
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 | 0,001 |
| 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 ».