Overcoming Multidrug Resistance in B Cell Malignancies By Antagonism of Stromal Mediated TGF-β Signalling
Notice bibliographique
Résumé
Novel targeted therapies have substantially improved the prognosis of patients with B cell malignancies. However, a substantial fraction of patients still relapse, even after initially achieving deep remissions. Many studies have characterized the interactions between tumor cells and their microenvironment as integral to leukemia/ lymphoma homeostasis and for the provision of survival signals, also contributing to drug resistance (referred to as environment-mediated drug resistance (EMDR)). Therapeutic efforts to antagonize microenvironment-emanating survival cues have predominantly focused on perturbation of tumour cell adhesion enabling the physical displacement from protective niches (e.g. BCR-inhibitors). In an effort to address whether direct stromal targeting could more precisely mitigate EMDR, we recently characterised the molecular mechanisms underlying tumor-stroma interactions in B cell malignancies and identified a protein kinase C-β (PKC-β) as an essential kinase, required for activation of NF-κB in mesenchymal stromal cells (Lutzny et al Cancer Cell 2013). The dependency on stroma PKC-β was uniformly found for acute (ALL) and chronic (CLL, MCL) B cell malignancies. Importantly, our data further demonstrate that targeting stroma PKC-β is of key importance for multi-drug resistance of malignant B cells and can be used for therapeutic interventions (Park et al Science Trans Med 2020). Here we demonstrate novel mechanistic insights into stroma-mediated drug resistance in B cell malignancies. We identified that stroma PKC-β drives a transcriptional program in tumor cells, dependent on the activation of TGF-β and BMP-signaling, which ultimately leads to the stabilisation of BCL-XL. Our data show that BCL-XL expression in tumor cells is associated with SMAD1-induction by cytotoxic therapies, which simultaneously suppress SMAD4 expression. Importantly, SMAD1 expression was strictly dependent on stromal PKC-β activity. Antagonizing stroma signals with TGF-β inhibitors inhibits SMAD1 induction, abrogates the up-regulation of BCL-XL and overcomes stroma-dependent resistance to Venetoclax and conventional chemotherapy. The TGF-β pathway operates in parallel to the activation of the transcription factor EB (TFEB) as a down-stream target of PKC-β. Interference with these signaling pathways impairs plasma membrane integrity of stromal cells by down-regulation of numerous adhesion and signaling molecules, such as ADAM17, required for the reciprocal stabilization of BCL-XL in tumor cells. The significance of microenvironment PKC-β for drug resistance was demonstrated in vivo, using C57B/6 mice, diseased with EμTCL-1 driven B cell tumors and treated with Venetoclax in combination with or without PKC-β inhibitors. Combined treatment significantly prolonged survival, based on PKC-β mediated impairment of EMDR. Similarly, concurrent treatment of PKC-β inhibitors with chemotherapy also improved survival in an ALL-PDx model Our data demonstrate that mitigating EMDR with small molecule inhibitors of PKC-β or TGF-β signalling enhance the effectiveness of both targeted and non-targeted chemotherapies and moreover, has the ability to overcome Venetoclax resistance in B cell malignancies. Clinical trials with repurposed drugs inhibiting the here described pathways mediating EMDR are in planning. Disclosures No relevant conflicts of interest to declare. OffLabel Disclosure: Midostaurin as inhibitor of stroma PKC-β
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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 | 0,001 |
| 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 ».