IGF Signaling Is Critical for Growth and Survival of T-Cell Acute Lymphoblastic Leukemia Cells and Is Potentiated by Notch Upregulation of IGF1R
Bibliographic record
Abstract
Abstract T-cell acute lymphoblastic leukemia (T-ALL) is a malignancy of immature T cell progenitors in which we described activating mutations of Notch1 to occur in over 50% of cases. As well, others have identified loss-of-function mutations in Sel10/Fbw7 to occur in 8–16% of cases, which also enhance Notch signaling. Notably, inhibition of Notch signaling in these cells induces growth arrest and in some cases apoptosis as well. Subsequent studies have characterized c-myc as a critical downstream target of Notch signaling in this context. More recently, mutations in PTEN (occurring in 17% of cases) were shown to potentiate PI3K/Akt signaling and proposed to confer resistance to Notch signaling inhibition, but then impose “addiction” to PI3K/Akt. Most leukemias likely derive cooperative growth/survival signals from Notch and PI3K/Akt pathways, as evidenced by synergistic effects of gamma-secretase inhibitors (GSI) which block Notch signaling and rapamycin which blocks mTOR downstream of PI3K/Akt. In mouse models, combined activation of c-myc and b-catenin with inactivation of PTEN elicited T-ALL which was devoid of Notch mutations, suggesting Notch signaling coordinately activates c-myc, Wnt, and PI3K/Akt signaling pathways. In studying the mechanism for PI3K/Akt activation in T-ALL with activated Notch signaling, we examined insulin-like growth factor receptor-1 (IGF1R) as a candidate upstream initiator of PI3K/Akt activation. We observed IGF1R expression consistently in T-ALL cells from primary human leukemias and cell lines, as well as in primary mouse leukemias derived experimentally by retroviral transduction of marrow with activated forms of Notch1. In all cases, inhibition of IGF1R signaling either with blocking antibody or small molecule kinase inhibitors resulted in growth suppression and apoptosis of leukemia cells. We further observed that inhibition of Notch signaling either by small molecule GSI or transduction with a dominant negative coactivator, Mastermind, resulted in a 2–3 fold decrease in IGF1R expression. Given that the PI3K/Akt/mTOR pathway is known to be important for growth/survival of T-ALL leukemia cells, we hypothesized that Notch might be potentiating activation of this pathway by upregulating IGF1R expression. In fact, we found leukemia cells with active Notch and higher IGF1R levels showed 20-fold greater sensitivity to IGF-1 ligand induced Akt activation as compared to leukemia cells with inactive Notch and lower IGF1R levels. This enhanced signaling output cannot be explained by Notch suppression of PTEN as this effect was noted in both PTEN wild-type and PTEN null leukemia cells. Additionally, cells with wild type PTEN demonstrated only minimal if any changes in PTEN protein levels after Notch inhibition as measured by a highly quantitative flow cytometry assay. In sum, we have identified IGF-1 signaling as being critical to growth and survival of T-ALL leukemia cells, and provide evidence that Notch may potentiate PI3K/Akt signaling by upregulating expression of IGF1R. These data are of immediate clinical relevance as several IGF1R inhibitors are currently in Phase 3 clinical trial and hopefully will provide additional therapeutic options to refractory/relapsed patients and/or in combination with front-line therapy in newly diagnosed patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".