CSIG-17. COMPENSATORY ACTIVATION OF STAT3 TRIGGERED BY EGFR INHIBITION: A MECHANISM OF RESISTANCE IN GBM BRAIN TUMOR INITIATING CELLS
Bibliographic record
Abstract
Despite advances in delineating the mutations and aberrant signaling pathways underlying glioblastoma multiforme (GBM), the prognosis for GBM patients remains dismal. New therapeutic options are desperately needed in order to make this devastating disease manageable. In cancer cells, when one survival signaling pathway is inhibited, network redundancy leads to compensatory mechanisms that activate other survival/proliferation pathways. This mechanism may explain the poor clinical translation of EGFR inhibitors in GBM to date. JAK2/STAT3 signaling is important for tumor cell survival, growth, and invasion and becomes trans-activated upon EGFR inhibition. Given that both EGFR and JAK2/STAT3 are crucial signaling hubs in GBM, if targeted concurrently, this may provide the survival advantage that monotherapies have failed to offer. To test this hypothesis, we examined the actions of the JAK2 inhibitor pacritinib in combination with the EGFR inhibitor afatinib on GBM brain tumor initiating cells (BTICs). STAT3 activation triggered by EGFR inhibition was confirmed in multiple BTIC lines. Protein and mRNA levels of STAT3 and IL6 were found to increase, highlighting a possible mechanism of resistance to EGFR inhibition. We demonstrated that concurrent inhibition of STAT3 and EGFR exhibited striking responses, with extensive synergy and dramatic decreases in BTIC viability and sphere-forming capacity. Western blotting assays showed that the increased phospho-STAT3 observed with EGFR inhibition was abolished with combined treatment. Consistent with in vitro results, EGFR inhibition with afatinib induced an increase in phospho-STAT3 in vivo, in BTIC orthotopic xenografts. This increase was abolished with the combination of afatinib and pacritinib. These data suggest that, in GBM, EGFR inhibition remains of high therapeutic relevance, when combined with inhibition of other pro-oncogenic pathways. Our ongoing studies are aimed at further understanding the mechanism by which STAT3 is activated upon EGFR inhibition and the translational potential of inhibiting these two pathways in combination.
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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 | 0.001 |
| 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".