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Mapping Microenvironment-Mediated Signaling Dependency of Targeted Inhibitors: A Mechanism-Based Approach of Selecting Effective Therapy Targeting Drug Resistant AML

2015· article· en· W2606117552 on OpenAlexaff
Zhihong Zeng, Wenbin Liu, Twee Tsao, Yihua Qiu, Ismael Samudio, Keith Baggerly, Steven M. Kornblau, Hagop M. Kantarjian, Michael Andreeff, Marina Konopleva

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsCentre for Drug Research and Development
Fundersnot available
KeywordsTemsirolimusCancer researchStromal cellPI3K/AKT/mTOR pathwayTumor microenvironmentMyeloid leukemiaDrug resistanceBiologyProtein kinase BLeukemiaPharmacologySignal transductionImmunologyCell biology

Abstract

fetched live from OpenAlex

Abstract Acute myeloid leukemia (AML) has a high relapse rate, with drug resistance often observed in relapsed patients. The leukemic microenvironment shelters surviving AML cells following initial treatment, and facilitates the development of drug resistance in AML that accompanies disease relapse (Konopleva et al., JCO 2011). Activation of PI3K/AKT/mTOR, anti-apoptotic Bcl-2 and MDM2/p53 signaling have all been detected in relapsed AML, and were reported as resistance mechanisms mediated by stromal cells in the leukemia microenvironment. Temsirolimus, ABT737 and Nutlin3a are small molecule inhibitors that block key molecules (mTOR, Bcl-2 and MDM2) in their respective pathways; each demonstrated therapeutic efficacy in AML treatment (Zeng, et al., Blood 2007; Konopleva et al., Cancer Cell 2006; Kojima et al., Blood 2011). In this study, we investigated stroma-mediated drug-resistance mechanisms to these target inhibitors, aiming to identify effective combinations to eradicate residual AML. Using reverse phase-protein array (RPPA) technology we profiled 53 key molecules in 11 signaling pathways (Figure 1) in 20 primary AML samples that were treated with temsirolimus, ABT-737, or Nutlin3a alone; or the combination of temsirolimus plus ABT-737 or Nutlin3a under mono-culture and stroma co-culture conditions. Stroma-mediated mechanisms of resistance were identified by comparing the signaling network alterations triggered by single inhibitor or dual inhibitors under the different culture conditions. Our results indicate that alterations in the stroma-regulated network responsible for cell surivial are specific to each inhibitor. Stroma upregulated p53-independent MDM2 expression (14/20 samples) and activated p-BAD Ser136 (9/20) in samples treated with temsirolimus; activated p-AKT Ser473 (14/20), p-PRAS40 Thr246 (10/20), increased expression of Foxo3A (10/20), and upregulated p53-independent MDM2 (12/20) in samples treated with ABT-737; it activated p-AKT Ser473 (13/20) and upregulated p53-independent MDM2 expression (14/20) in samples treated with Nultin3a. The finding that activation of the PI3K/AKT/mTOR pathway was a common survival mechanism mediated by stroma in response to Bcl-2 and MDM2 inhibition provided the rationale for combination strategies using temsirolimus plus ABT-737 or Nutlin3a. Mapping of the signaling network revealed that the number of affected targets and pathways were significantly increased in the co-cultured samples treated with dual inhibitors: temsirolimus plus ABT-737 (15 targets in 7 pathways), temsirolimus plus Nutlin3a (13 targets in 5 pathways), as compared to those treated with single agent: temsirolimus (7 targets in 3 pathways), ABT-737 (6 targets in 2 pathways) and Nutlin3a (2 targets in 2 pathways). Network analysis revealed that temsirolimus plus ABT-737 blocked up- and downstream targets within the PI3K/AKT/mTOR pathway (#1) (PDK1 vs. 4EBP1), and simultaneously inhibited targets in multiple pro-survival pathways: AKT/mTOR downstream targets (#2), STAT3 (#4), IAP family (#8), p53 family (#7), Wnt-beta Catenin (#6), Bcl-2 family (#5). Similarly, temsirolimus and Nutlin3a blocked the targets within the PI3K/AKT/mTOR signaling (#1) (AKT, mTOR, p-4EPB1, p-S6), and the targets in pro-survival pathways such as targets downstream of AKT/mTOR (#2), cell cycle regulation (#9), p53 family (#7), Wnt-beta Catenin (#6). Apoptosis was measured in 11 of 20 samples under co-culture condition; both combinations showed increased apoptosis induction: temsirolimus (mean± SE) 8.5 ± 2.7%, ABT737 21.1± 2 %, temsirolimus plus ABT737 37 ± 2.7% (n =11); temsirolimus 13.9 ± 3.6%, Nutlin3a 16.9 ± 5.4%, temsirolimus plus Nutlin3a 35.7 ± 2.8% (n=6). Altogether, using proteomic profiling we identified stroma-mediated resistance mechanisms to target-specific inhibitors, and examined the effects of combined blockade of PI3K/AKT/mTOR signaling with Bcl-2 and MDM2 inhibition at the molecular level. We demonstrated that the mechanism-based selection of combined inhibition is able to abrogate stroma-mediated drug-resistance and facilitate cell death. This approach offers the important guidance for clinical drug selection and tailoring treatment regimens to eliminate resistant AML. Disclosures Konopleva: Novartis: Research Funding; AbbVie: Research Funding; Stemline: Research Funding; Calithera: Research Funding; Threshold: 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 score0.003

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 communication0.0000.000
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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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
Published2015
Admission routes1
Has abstractyes

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