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Record W3214381809 · doi:10.1182/blood-2021-149185

Identification of a Highly Deregulated eIF4F Translation Initiation Complex in Drug-Resistant BCR-ABL + Cells By a Phospho-Proteomic Antibody Microarray

2021· article· en· W3214381809 on OpenAlexaff
Ryan Yen, Lambert Yue, Steven Pelech, Xiaoyan Jiang

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicChronic Myeloid Leukemia Treatments
Canadian institutionsTerry Fox Research InstituteKinexus Bioinformatics Corporation (Canada)University of British Columbia
Fundersnot available
KeywordsBiologyPhosphorylationAntibody microarrayMicroarray analysis techniquesCancer researchMyeloid leukemiaABLImatinib mesylatebreakpoint cluster regionTyrosine kinaseProgenitor cellImatinibStem cellAntibodyCell biologyMolecular biologySignal transductionImmunologyGene expressionGeneticsReceptorGene

Abstract

fetched live from OpenAlex

Abstract Protein-tyrosine kinase inhibitors (TKIs) have been effective for treatment of early stages of chronic myeloid leukemia (CML). However, BCR-ABL-dependent resistance mechanisms and TKI-unresponsive quiescent leukemic stem cells (LSCs) can result in drug resistance and disease relapse. We have demonstrated that Abelson helper integration site-1 (AHI-1) is a highly deregulated protein in CML LSCs. It interacts with BCR-ABL through the AHI-1 WD40 domain and with other proteins, like dynamin-2 (DNM2), through its SH3 domain, to enhance leukemic-initiating activities and TKI resistance. To uncover downstream effects of the AHI-1-BCR-ABL-DNM2 complex and its biological role in mediating TKI resistance in CML stem/progenitor cells, an advanced antibody microarray analysis was then used to investigate differences in the proteome and phosphorylation landscape of BCR-ABL + cells co-transduced with wild-type Ahi-1 or Ahi-1 SH3 Δ mutant in the presence or absence of imatinib (IM). The microarray simultaneously quantified the differences in expression and phosphorylation sites of proteins in multiple signaling pathways using 1325 antibodies in duplicate measurements, and each microarray analysis was performed in duplicate. Significant changes in antibody signals for protein expression or phosphorylation were determined using limma. This analysis revealed that the overexpression of wild-type Ahi-1 (WT Ahi-1) has a profound differential effect, compared to the SH3 domain deleted Ahi-1 (Ahi-1 SH3 Δ), on the expression and phosphorylation status of proteins in BCR-ABL + cells with and without IM treatment. BCR-ABL + cells co-expressing WT Ahi-1 had a greater number of significantly differential antibody signals (7 increases, 42 decreases) when compared to BCR-ABL + cells, while Ahi-1 SH3 Δ expressing cells resulted in fewer significantly differential antibody signals (12 increases, 2 decreases) compared to BCR-ABL + cells. IM treatment resulted in WT Ahi-1 expressing cells having the greatest number of significantly differential antibody signals (7 increases, 56 decreases) compared to BCR-ABL + cells (5 decreases) and those co-expressing Ahi-1 SH3 Δ (2 increases, 9 decreases). Pathway enrichment analysis, using gProfiler, identified that the targets with significantly increased differential antibody signal after IM treatment in WT Ahi-1 cells were related to the regulation of translation initiation complex (p>0.0001). Interestingly, our RNA-seq dataset analysis further identified several members of the eukaryotic initiation factor 4F (eIF4F) complex to be significantly upregulated in CD34 + CML patient cells compared to normal bone marrow, particularly eIF4G1, the scaffold protein of the eIF4F complex involved in translation initiation (2-fold, p=0.001), as well as mTOR, a key regulator that controls the assembly of the eIF4F complex. This finding prompted us to further explore the regulation of translation initiation and the members of the eIF4F complex in BCR-ABL + cells. Immunoblotting demonstrated that BCR-ABL + cells co-transduced with WT Ahi-1 showed increased expression of eIF4G1 (3-fold) and eIF4B (2-fold), a cofactor that regulates the helicase activity of the eIF4F complex, compared to BCR-ABL + cells. Additionally, Cyclin D3, a gene reported to be sensitive to eIF4F translational activity, was found to have slightly increased expression (1.4-fold) in WT Ahi-1 cells compared to BCR-ABL + cells. Most interestingly, these results were also demonstrated in IM-resistant CML cells as compared to IM-sensitive cells, with an increase in eIF4G1 expression (2-fold), phosphorylation of eIF4B (5-fold, p=0.003), and Cyclin D3 expression (4-fold, p<0.05). Mechanistically, eIF4G1 knockdown by shRNA impaired survival (5-fold, p<0.0001) and increases TKI sensitivity in IM-resistant cells (3-fold, p<0.05). A new protein interaction between eIF4G1 and the mRNA cap-binding protein eIF4E was further identified in these cells using a proximity ligation assay. Thus, we have uncovered that the eIF4F complex, the key regulator of the mRNA-ribosome recruitment phase of translation initiation, has increased activity in IM-resistant cells, which may contribute to the regulation of TKI resistance in CML. Disclosures No relevant conflicts of interest to declare.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.262
Teacher spread0.248 · 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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Citations1
Published2021
Admission routes1
Has abstractyes

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