CSIG-25. OVERCOMING RESISTANCE TO THERAPIES TARGETING THE MAPK PATHWAY IN GLIOBLASTOMA
Bibliographic record
Abstract
Abstract Capicua (CIC) is a transcriptional repressor that inhibits expression of genes induced by receptor tyrosine kinase (RTK) activation. RTK/Ras/ERK signaling is one of the most tumorigenic pathways in cancer. In fact, the aggressive nature of the most common and lethal brain tumor, glioblastoma (GBM), has been attributed to hyperactivation of RTK. While CIC is mutated in other tumor types, we found that CIC has a tumor-suppressive function in GBM through an alternative mechanism. We show that Ras/ERK promotes degradation of CIC, resulting in de-repression of CIC targets and amplification of the tumorigenic Ras/ERK signal. Importantly, we show that sustained MEK/ERK inhibition fails to restore CIC protein levels desensitizing from upstream RTK/MEK/ERK inhibition. Our findings suggest the lack of efficacy of MEK/ERK inhibitors in GBM in the clinical context is due to the loss of CIC-mediated repression, hence exposing CIC as a potential therapeutic target in combination with MEK/ERK inhibitors. To uncover targetable pathways that stabilize CIC and sensitize towards MEK/ERK inhibitors in GBM we need to understand how CIC works and causes gene repression. We identified a novel CIC binding partner, Yin Yang 1 (YY1), a context dependent transcription factor important in GBM. We found that YY1/CIC binding co-regulates repression of genes downstream of RTK/Ras/ERK activation important in tumorigenesis. Importantly we uncovered a targetable pathway that leads to stabilization of CIC/YY1 on its target DNA which sensitizes towards MEK/ERK inhibition. These data provide insight into more effective therapeutic avenues to stabilize the CIC/YY1 co-repressor complex and re-sensitize towards RTK/Ras/MEK/ERK inhibition in GBM and likely in other tumors characterized with hyperactive Ras/ERK signaling and CIC loss.
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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".