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Record W2906744624 · doi:10.1182/blood-2018-99-118235

Integrated Proteomic and Phosphoproteomic Analysis Reveal Novel Targets and Suggest Rationale for Ibrutinib Efficacy in UM-CLL

2018· article· en· W2906744624 on OpenAlexaff
Laura Beckmann, Valeska Berg, Clarissa Dickhut, Johannes Bloehdorn, Jasmin Bahlo, Sandra Robrecht, Malte F. Hülsemann, Stefan Loroch, Olaf Merkel, Kirsten Fischer, Clemens‐Martin Wendtner, Stephan Stilgenbauer, Albert Sickmann, Michael Hallek, René P. Zahedi, Lukas P. Frenzel

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsIbrutinibBruton's tyrosine kinasePhosphorylationCancer researchChronic lymphocytic leukemiaProteomeSerineChemistryBiologyLeukemiaTyrosine kinaseBiochemistrySignal transductionImmunology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.296
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2018
Admission routes1
Has abstractyes

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