Tyrosine kinase targeting uncovers oncogenic pathway plasticity in Tasmanian devil transmissible cancers
Bibliographic record
Abstract
Two transmissible cancers, Devil Facial Tumour 1 (DFT1) and Devil Facial Tumour 2 (DFT2), have caused a significant decline in the Tasmanian devil population. DFT1 is driven by ERBB, while DFT2 is driven by PDGFRA. We show that DFT cancer cells exhibit distinct kinase phosphorylation profiles that dictate their responses to tyrosine kinase inhibitors. Upon long-term treatment, both DFT cell lines develop resistance, with DFT1 cells rapidly evading ERBB inhibition without major copy number alterations or significant changes in phosphorylation, suggesting signalling plasticity and engagement of alternative oncogenic drivers. In contrast, DFT2 cells exhibit a slowed development of resistance to imatinib, a selective kinase inhibitor with known activity against PDGFRs. Moreover, DFT2 cell resistance is accompanied by copy number alterations and an activation of ERBB and JAK/STAT signalling with MHCI downregulation, resembling DFT1 signalling. Dual targeting of ERBB and PDGFR shows synergistic effects in DFT1 and may prevent resistance emergence. These findings provide critical insight into the adaptive capacity of transmissible cancers and inform conservation strategies. Moreover, they highlight broader principles of kinase-driven resistance relevant to human cancers with high pathway plasticity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".