The PERK-eIF2α phosphorylation arm is a pro-survival pathway of BCR-ABL signaling and confers resistance to imatinib treatment in chronic myeloid leukemia cells
Bibliographic record
Abstract
Activation of adaptive mechanisms plays a crucial role in cancer progression and drug resistance by allowing cell survival under stressful conditions. Therefore, inhibition of the adaptive response is considered as a prospective therapeutic strategy. The PERK-eIF2α phosphorylation pathway is an important arm of the unfolded protein response (UPR), which is induced under conditions of endoplasmic reticulum (ER) stress. Our previous work showed that ER stress is induced in chronic myeloid leukemia (CML) cells. Herein, we demonstrate that the PERK-eIF2α phosphorylation pathway is upregulated in CML cell lines and CD34+ cells from CML patients and is associated with CML progression and imatinib resistance. We also show that induction of apoptosis by imatinib results in the downregulation of the PERK-eIF2α phosphorylation arm. Furthermore, we demonstrate that inactivation of the PERK-eIF2α phosphorylation arm decreases the clonogenic and proliferative capacities of CML cells and sensitizes them to death by imatinib. These findings provide evidence for a pro-survival role of PERK-eIF2α phosphorylation arm that contributes to CML progression and development of imatinib resistance. Thus, the PERK-eIF2α phosphorylation arm may represent a suitable target for therapeutic intervention for CML disease.
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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 | 0.000 |
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.
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".