Mutational Loss of PTEN Induces Resistance to NOTCH1 Inhibition in T-ALL.
Bibliographic record
Abstract
Abstract Activating mutations in NOTCH1 are common in T-cell lymphoblastic leukemias (T-ALL), making this receptor a promising target for drugs such as gamma-secretase inhibitors (GSIs), which block NOTCH1 activation. However, enthusiasm for these therapies has been tempered by tumor resistance and the paucity of information on the oncogenic programs regulated by NOTCH1. Here, we identify the loss of the PTEN tumor suppressor gene and activation of the PI3K-AKT signaling pathway as critical factors that determine the resistance of T-ALL cells to inhibition of NOTCH1 signaling with GSIs. Mutational loss of PTEN is found in 17% of T-ALL cases and in the majority of T-ALL cell lines. Importantly, 8/8 T-ALL lines sensitive to NOTCH inhibition with GSIs retain wild type PTEN, while this tumor suppressor is lost in 8/8 GSI-resistant T-ALLs analyzed (P<0.001). Furthermore, both the expression of a constitutively active form of AKT (Myr AKT) and PTEN shRNA knockdown induced resistance to GSIs in T-ALLs and promoted cell growth, proliferation and glucose metabolism. The close association between GSI resistance and PTEN loss prompted us to analyze the interaction between NOTCH1 signaling and the PI3K-AKT pathway. Analysis of normal and leukemic T-cells demonstrated that NOTCH1 signaling regulates PTEN expression and AKT signaling. Thus, inhibition of NOTCH1 with GSIs results in transcriptional upregulation of PTEN and concomitant downregulation of PI3K/AKT signaling in T-ALL. A similar effect -transcriptional upregulation of Pten upon loss of Notch signaling- was observed in primary mouse thymocytes, which are highly dependent on Notch1 to sustain the activity of the Akt signaling pathway. ChIP-on-chip and reporter assays demonstrate that regulation of PTEN is mediated by HES1, a transcriptional repressor directly controlled by NOTCH1. In agreement with these observations, HES1 shRNA knockdown induced transcriptional upregulation of PTEN in T-ALL cells. These results were perfectly recapitulated in a Drosophila model of Notch-induced tumorigenesis. Thus, activation of Notch signaling via expression of Delta and activation of the PI3K-AKT pathway by Akt showed marked synergism in tumor formation in the fly eye. Importantly, also in Drosophila, activation of Akt reverses the growth defect phenotype induced by the loss of Notch signaling, highlighting the importance of the interaction between these two pathways for the control of cell growth. Finally, we proposed that mutational loss of PTEN could induce an oncogene addition switch that makes T-ALL cells resistant to NOTCH inhibitors but enhanced their sensitivity to AKT inhibitors. Treatment with SH-6, a phosphatidylinositol analog inhibitor of AKT, showed a strong antileukemic effect against GSI-resistant/PTEN-null T-ALLs but not against GSI-sensitive/PTEN-positive cells, confirming this hypothesis. These results demonstrate the importance of the interaction of NOTCH1 with the PI3K-AKT pathway in T-cell homeostasis and response to therapy and provide the basis for the design of new therapeutic strategies for T-ALL.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".