CSIG-19. RECEPTOR TYROSINE KINASE PHOSPHORYLATION IN A MODEL SYSTEM OF GBM
Bibliographic record
Abstract
Glioblastoma Multiforme (GBM) is the most common brain tumour in adults, and despite our best treatments is fatal. Multiple receptor tyrosine kinases (RTKs) are amplified in GBM: 45% have elevated expression of Epidermal Growth Factor Receptor (EGFR) and 13% overexpress Platelet Derived Growth Factor Receptor (PDGFR). While the proposed role of RTKs in GBM initiation and maintenance make them attractive therapeutic targets the clinical efficacy of RTK inhibition has been limited: targeting PDGFR has been unsuccessful, and only 10-20% of patients respond incompletely and briefly to EGFR inhibition. Therapeutic advances may be possible if we can understand why these targeted treatments have been ineffective. Using a murine model of PDGF-AA initiated GBM, the role of RTKs in sustaining proliferative signaling was explored. Phospho-RTK arrays, which provide the phosphorylation status of a broad spectrum of RTKs were used to characterize cell lines, and tyrosine kinase inhibitors were used to asses the role of RTKs in sustaining viability. Transformed cell lines retained phosphorylation of PDGFRα in the PDGF-AA independent state. Concurrent phosphorylation of additional receptors was also observed. Five different patterns of phosphorylation were documented: PDGFRα alone and PDGFRα in combination with EGFR, IGFR, AXL-R or HGFR. These patterns of phosphorylation were retained in orthotopic xenografts and remained consistent over time as these cell lines transitioned from the pre-transformed to transformed state. Targeted treatments revealed PDGFRα inhibition in cell lines with co-phosphorylation had minimal effect on cell viability. However, when multiple RTKs are targeted overall receptor phosphorylation and viability decreased. The simultaneous activation of multiple RTKs has been observed in this model, suggesting that multiple RTKs may be involved in sustaining these murine GBMs. If these findings also apply to human GBM, resistance to single RTK inhibitors can be expected and combination therapies needed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".