Inhibition of PI3K/mTOR Pathways with GDC-0980 in Pediatric Leukemia: Impact on Abnormal FLT-3 Activity and Cooperation with Intracellular Signaling Targets
Bibliographic record
Abstract
BACKGROUND: GDC-0980 is a selective small molecule inhibitor of class I PI3K and mTOR pathway with a potent anti-proliferative activity. OBJECTIVE: We set out to evaluate the efficacy of GDC-0980, in pre-clinical studies, against pediatric leukemia cells. METHODS: The anti-neoplastic activity of GDC-0980 was evaluated in vitro using five different pediatric leukemia cells. RESULTS: Our data show that GDC-0980 significantly inhibited the proliferation of leukemia cell lines, KOPN8 (IC50, 532 nM), SEM (IC50,720 nM), MOLM-13 (IC50,346 nM), MV4;11 (IC50,199 nM), and TIB-202 (IC50, 848 nM), compared to normal control cells (1.23 µM). This antiproliferative activity was associated with activation of cellular apoptotic mechanism characterized by a decrease in Bcl-2 protein phosphorylation and enhanced PARP cleavage. Western blot analyses of GDC-0980 treated cells also showed decreased phosphorylation levels of mTOR, Akt and S6, but not ERK1/2. Notably, FLT3 phosphorylation was decreased in Molm-13 and MV4;11 cells following the application of GDC-0980. We further examined cellular viability of GDC-0980-treated primary leukemia cells isolated from pediatric leukemia patients. This study revealed a potential therapeutic effect of GDC-0980 on two ALL patients (IC50's, 1.23 and 0.625 µM, respectively). Drug combination analyses of GDC-0980 demonstrated a synergistic activity with the MEK inhibitor Cobimetinib (MV4-11; 11, CI, 0.25, SEM, CI, 0.32, and TIB-202, CI, 0.55) and the targeted FLT3 inhibitor, Crenolanib (MV4-11; 11, CI, 0.25, SEM, CI, 0.7, and TIB-202, CI, 0.42). CONCLUSION: These findings provide initial proof-of-concept data and rationale for further investigation of GDC-0980 in selected subgroups of pediatric leukemia 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 | 0.001 |
| 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".