Cell culture and<i>Drosophila</i>model systems define three classes of anaplastic lymphoma kinase mutations in neuroblastoma
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Bibliographic record
Abstract
Neuroblastoma is a childhood extracranial solid tumour that is associated with a number of genetic changes. Included in these genetic alterations are mutations in the kinase domain of the anaplastic lymphoma kinase (ALK) receptor tyrosine kinase (RTK), which have been found in both somatic and familial neuroblastoma. In order to treat patients accordingly requires characterisation of these mutations in terms of their response to ALK tyrosine kinase inhibitors (TKIs). Here, we report the identification and characterisation of two novel neuroblastoma ALK mutations (A1099T and R1464STOP), which we have investigated together with several previously reported but uncharacterised ALK mutations (T1087I, D1091N, T1151M, M1166R, F1174I and A1234T). In order to understand the potential role of these ALK mutations in neuroblastoma progression, we have employed cell culture-based systems together with the model organism Drosophila as a readout for ligand-independent activity. Mutation of ALK at position 1174 (F1174I) generates a gain-of-function receptor capable of activating intracellular targets such as ERK (extracellular signal regulated kinase) and STAT3 (signal transducer and activator of transcription 3) in a ligand-independent manner. Analysis of these previously uncharacterised ALK mutants and comparison with ALK(F1174) mutants suggests that ALK mutations observed in neuroblastoma fall into three classes. These classes are: (i) gain-of-function ligand-independent mutations such as ALK(F1174l), (ii) kinase-dead ALK mutants, e.g. ALK(I1250T) (Schönherr et al., 2011a) and (iii) ALK mutations that are ligand-dependent in nature. Irrespective of the nature of the observed ALK mutants, in every case the activity of the mutant ALK receptors could be abrogated by the ALK inhibitor crizotinib (Xalkori/PF-02341066), albeit with differing levels of sensitivity.
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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 it