IGF1R Derived PI3K/AKT Signaling Maintains Growth in a Subset of Human T-Cell Acute Lymphoblastic Leukemias
Bibliographic record
Abstract
Insulin-like growth factor 1 receptor (IGF1R) is a prevalent signaling pathway in human cancer that supports cell growth/survival and thus contributes to aggressive biological behavior. Much work has gone into development of IGF1R inhibitors; however, candidate agents including small molecule tyrosine kinase inhibitors and blocking antibodies have yet to fulfill their promise clinically. Understanding cellular features that define sensitivity versus resistance are important for effective patient selection and anticipation of outgrowth of a resistant clone. We previously identified an important role for IGF signaling in T-cell acute lymphoblastic leukemia (T-ALL) relying primarily upon genetically defined mouse models. We present here an assessment of IGF1R dependence in human T-ALL using a broad panel of 27 established cell lines that capture a spectrum of the genetic variation that might be encountered in clinical practice. We observed that a subset of cell lines are sensitive to IGF1R inhibition and are characterized by high levels of surface IGF1R expression and PTEN positivity. Interestingly, lentiviral expression or knock-down of PTEN in PTEN-negative/positive cell lines, respectively, had limited effects on their response to IGF1R inhibition, suggesting that PTEN contributes to, but does not define IGF dependence. Additionally, we characterize downstream PI3K/AKT signaling as dominant over RAS/RAF/MEK/ERK in mediating growth and/or survival in this context. Finally, we demonstrate that IGF and interleukin-7 (IL-7) fulfill non-overlapping roles in supporting T-ALL growth. These findings are significant in that they reveal cellular features and downstream mechanisms that may determine the response of an individual patient's tumor to IGF1R inhibitor therapy.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".