Integrated Proteomic and Phosphoproteomic Analysis Reveal Novel Targets and Suggest Rationale for Ibrutinib Efficacy in UM-CLL
Notice bibliographique
Résumé
Abstract Rationale: The BTK inhibitor ibrutinib has proved to be highly effective in both treatment naїve and refractory or relapsed CLL patients. In contrast to most other therapeutic options, where unmutated IGVH correlates with adverse prognosis, response to ibrutinib is independent of IGVH mutation status. This compulsorily raises the question why CLL cells with an unmutated IGVH are equally susceptible to BTK inhibition. One key aspect might be understanding the global (phospho)proteome of UM-CLL and M-CLL cells which has not been investigated so far. Methods: We performed a comprehensive proteomics and phosphopreoteomics analysis of 14 CLL samples with unmutated or mutated IgVH using quantitative mass spectrometry (MS). ITRAQ labelling and TiO2 enrichment/HILIC fractionation were utilized for this approach. Results: Altogether we identified 9184 phosphopeptides corresponding to 2854 proteins. We found the typical pS:pT:pY ratio, with 89% of all detected phosphopeptides containing a phosphorylated serine (pS), 10% a phosphorylated threonine (pT) and 1% a phosphorylated tyrosine (pY) in CLL samples. Strikingly, UM-CLL showed a higher basal phosphorylation level than M-CLL samples with significantly higher phosphorylation of 92 out of 102 identified proteins (P<0.05) Interestingly, ibrutinib reverted this phosphorylation pattern predominantly in UM-CLL but not M-CLL samples and led to a shift of the ratio towards phosphotyrosine in UM-CLL (pS:pT:pY in %: 30:9:61) but not in M-CLL (pS:pT:pY: 78:7:15). Most of the indentified phosphopeptides clustered in pathways that regulate migration and motility and cell survival and death. Regarding the BCR pathway, we identified known and novel p-sites: Lyn (8 sites), PIK3AP1 (5), PLCG2 (5), Syk (4), BLK (4), PIK3R4 (2), LCK (2), BTK (1), PIK3C2B (1), PIK3C3 (1), PIK3CD (1). In this context a novel molecule, MARCKS attracted our attention. We identified three different p-sites (S101, T150 and S170) which were differentially phosphorylated in M-CLL and UM-CLL. Moreover, our proteome approach revealed distinct expression levels of 38 proteins out of 3466 isolated proteins between the two groups (1,5-fold changes; P<0.01), among them MARCKS. Expression of MARCKS was significantly higher in M-CLL samples. MARCKS, a PKC substrate, was shown to play a critical role in invasiveness and metastasis of various cancer types, but its role in CLL is unclear. Since MARCKS has not been associated with CLL, we proved our findings from MS in a larger cohort of CLL patients both on protein level (n=36) and on transcription level (n=337). Strikingly, shorter PFS of CLL patients (n=337) undergoing chemoimmunotherapy correlates with low expression of MARCKS independently of the mutational status. We further investigated the cellular function of MARCKS in CLL cells utilizing CRISPR/Cas9 to generate KO cells. We were able to show that MARCKS regulates migration towards CXCL12 and that a loss of MARCKS leads to significantly increased migration. As MARCKS is upstream of AKT at the plasma membrane, we wondered if its expression might be relevant for AKT signalling. Importantly, we found that AKT phosphorylation (S473) was significantly upregulated in MARCKS KO cells indicating that MARCKS is involved in AKT regulation. Since MARCKS seems to be involved in tumor microenvironment (TME) interaction, we determined the influence of TME stimuli on MARCKS regulation. Interestingly, MARCKS was upregulated by CD40:CD40L interaction but phosphorylated upon BCR stimulation in both M-CLL and UM-CLL as assessed by immunoblot. Furthermore, we identified MARCKS to be targeted by ibrutinib, as phosphorylation at S170 was reduced upon ibrutinib treatment. Conclusion: For the first time we could show a comprehensive picture of the phosphoproteome and proteome of UM-CLL and M-CLL samples. Strikingly, the basal phosphorylation level was significantly higher in UM-CLL and was more susceptible to ibrutinib treatment. Our findings reveal a relevant association of MARCKS expression with CLL prognosis, supported by the functional evidence that MARCKS acts upstream as novel modulator of AKT signalling and controls migration towards CXCL12. These data indicate that MARCKS is a novel and relevant target of ibrutinib especially in the context of the TME. Disclosures Bahlo: Roche: Honoraria, Other: Travel Grants. Fischer:Roche: Other: Travel support. Wendtner:Roche: Consultancy, Honoraria, Other: travel support, Research Funding; Janssen: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Research Funding; Genetech: Consultancy, Honoraria, Other: travel support, Research Funding; GlaxoSmithKline: Consultancy, Honoraria, Other: travel support, Research Funding; Abbvie: Consultancy, Honoraria, Other: travel support, Research Funding; Mundipharma: Consultancy, Honoraria, Research Funding; MorphoSys: Consultancy, Honoraria, Other: travel support, Research Funding; Pharmacyclics: Consultancy, Honoraria, Other: travel support, Research Funding; Gilead: Consultancy, Honoraria, Other: travel support, Research Funding. Stilgenbauer:Pharmcyclics: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genzyme: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Mundipharma: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Genentech: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Boehringer-Ingelheim: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Hoffmann La-Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Hallek:Pharmacyclics: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Mundipharma: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Gilead: Honoraria, Research Funding; Abbvie: Honoraria, Research Funding; Roche: Honoraria, Research Funding.
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 | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 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 ».