Abstract 820: Somatic mutations to identify tumors for highly selective chemosensitization by Nrf2 depletion
Bibliographic record
Abstract
Abstract Therapeutic resistance remains a critical challenge in cancer treatment. Effective chemosensitizers must target more than a single mechanism of resistance and must also selectively sensitize only tumor and not normal tissue. Nrf2 is a transcription factor that regulates a battery of cytoprotective genes, and is shown in multiple experimental systems to have a significant impact on sensitivity to cytotoxic treatments. Regulation of Nrf2 levels is largely post-translationally, as a result of its physical interaction with adapter protein Keap1, which targets it for proteosomal degradation. An increasing number of human tumors and cancer cell lines are found to have loss of function mutations in Keap1 that results in constitutively elevated Nrf2 and drug resistance. In such circumstances alternative pathways for Nrf2 degradation may predominate, including the PI3kinase pathway protein GSK-3β, which exports Nrf2 from the nucleus to the proteosome. When relatively common somatic mutations in the PI3kinase pathway result in phosphorylation of GSK-3β at Ser9, it is inactivated. However, the addition of a PI3kinase pathway inhibitors increases GSK-3β, depletes Nrf2 and significantly sensitizes these cells. We are further exploring mechanisms, and at the same time screening biobanks of various tumors to determine the incidence of somatic loss of function mutations in Keap1 and mutations in the Pi3K pathway that activate it. This would represent a molecular signature of tumors that would be highly selectively sensitized by this strategy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 820. doi:1538-7445.AM2012-820
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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 | 0.000 |
| 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 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".