Peptides derived from the dependence receptor ALK are proapoptotic for ALK-positive tumors
Bibliographic record
Abstract
ALK is a receptor tyrosine kinase with an oncogenic role in various types of human malignancies. Despite constitutive activation of the kinase through gene alterations, such as chromosomal translocation, gene amplification or mutation, treatments with kinase inhibitors invariably lead to the development of resistance. Aiming to develop new tools for ALK targeting, we took advantage of our previous demonstration identifying ALK as a dependence receptor, implying that in the absence of ligand the kinase-inactive ALK triggers or enhances apoptosis. Here, we synthesized peptides mimicking the proapoptotic domain of ALK and investigated their biological effects on tumor cells. We found that an ALK-derived peptide of 36 amino acids (P36) was cytotoxic for ALK-positive anaplastic large-cell lymphoma and neuroblastoma cell lines. In contrast, ALK-negative tumor cells and normal peripheral blood mononuclear cells were insensitive to P36. The cytotoxic effect was due to caspase-dependent apoptosis and required N-myristoylation of the peptide. Two P36-derived shorter peptides as well as a cyclic peptide also induced apoptosis. Surface plasmon resonance and mass spectrometry analysis of P36-interacting proteins from two responsive cell lines, Cost lymphoma and SH-SY5Y neuroblastoma, uncovered partners that could involve p53-dependent signaling and pre-mRNA splicing. Furthermore, siRNA-mediated knockdown of p53 rescued these cells from P36-induced apoptosis. Finally, we observed that a treatment combining P36 with the ALK-specific inhibitor crizotinib resulted in additive cytotoxicity. Therefore, ALK-derived peptides could represent a novel targeted therapy for ALK-positive tumors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".