Identification of a Highly Deregulated eIF4F Translation Initiation Complex in Drug-Resistant BCR-ABL + Cells By a Phospho-Proteomic Antibody Microarray
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".