Determinants of Sensitivity and Resistance to Rapamycin-Chemotherapy Drug Combinations <i>In vivo</i>
Bibliographic record
Abstract
The phosphatidylinositol-3-OH kinase [PI(3)K] pathway is frequently activated in human cancers and represents a rational target for therapeutic intervention. We have previously shown that enforced expression of Akt, which is a downstream effector of PI(3)K, could promote tumorigenesis and drug resistance in the Emu-myc mouse lymphoma model, and that these tumors were particularly sensitive to inhibition of mammalian target of rapamycin (mTOR) with rapamycin when combined with conventional chemotherapy. We now show that reduced dosage of PTEN, a negative regulator of PI(3)K signaling, is sufficient to activate Akt, but has only a modest effect on lymphomagenesis in the same model. Nonetheless, loss of even one PTEN allele resulted in lymphomas that were resistant to conventional chemotherapy yet sensitive to rapamycin/chemotherapy combinations. These effects could be recapitulated by using RNA interference to suppress PTEN expression in lymphomas, which were previously established in the absence of PI(3)K lesions. Finally, the introduction of lesions that act downstream of mTOR (eIF4E) or disable apoptosis (Bcl-2 and loss of p53) into PTEN+/- lymphomas promoted resistance to rapamycin/chemotherapy combinations. Thus, whether activation of the PI(3)K pathway confers sensitivity or resistance to therapy depends on the therapy used as well as secondary genetic events. Understanding these genotype-response relationships in human tumors will be important for the effective use of rapamycin or other compounds targeting the PI(3)K pathway in the clinic.
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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 | 0.000 |
| 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".