Targeting Abnormally Increased Expression of ULK1 Sensitizes Acute Myeloid Leukemia Resistant Cells to Venetoclax
Bibliographic record
Abstract
Background Venetoclax (VEN) is a potent B-cell lymphoma-2 (BCL-2) inhibitor used for treatment of acute myeloid leukemia (AML). However, some patients display marked resistance to VEN, limiting its efficacy. BCL-2 is overexpressed in AML cells, and acts as both an inhibitor of apoptosis and autophagy, indicating an interaction between these two pathways in AML which may provide insight into the origins of resistance, though specific molecular and biological changes remain unknown. Objective To investigate the interplay of apoptosis and autophagy in mediating VEN resistance via genomic and gene expression analysis of VEN-treated AML patient cells, as well as identify and characterize key autophagic and biological changes in VEN resistant AML cells. Methods Gene expression analysis was performed on 176 specimens with both RNA-seq and VEN drug sensitivity screen data from the BEAT AML patient dataset using DESeq2 to identify differentially expressed genes. These genes were cross matched with 199 autophagy-associated genes, then further refined via selecting druggable targets or known key regulators of autophagy to identify specific genes of interest. Genes of interest were further investigated in cell lines via qRT-PCR and Western blotting. Resistant cell lines were generated from MV4-11 and MOLM13 cell lines via culturing in increasing concentrations of VEN for 14 weeks. Autophagic flux reporter lines were generated via viral transduction with an RFP-GFP-LC3 tandem reporter. Molecular and biological changes were then investigated in VEN-resistant cells. Results Gene expression analysis of the BEAT-AML dataset revealed 2,788 genes to be significantly elevated with a corrected p value <0.01 in VEN-resistant patients. When compared to a list of 199 autophagy-associated genes, 56 were identified from those 2,788 elevated genes. From this, 11 genes were short listed for further investigation due to their roles as druggable targets or known key autophagic regulators. RT-PCR in several cell lines revealed from this shortlist that ULK1 exhibited highly elevated expression in resistant lines, which was confirmed via western blotting of both phosphorylation and total ULK1 protein levels (ULK1: > 2-fold, p < 0.01; pULK1: > 2-fold, p < 0.01) VEN resistance was confirmed in our newly generated resistant lines via cell viability and apoptosis assays, with resistant lines showing a marked lack of response to VEN compared to parental lines (40-fold , p < 0.001). Inhibition of ULK1 via SBI-0206965 and a more potent inhibitor, SBP-7455, re-sensitized resistant cell lines to VEN, with increased cell killing seen in co-treatment of ULK1 inhibitor and VEN resulting in decreased viability compared to treatment of VEN alone (> 2-fold decrease, p < 0.01). Notably, there was no significant decrease in viability with ULK1 inhibitor treatment alone without VEN. Apoptosis assays further confirmed this, with increased levels of apoptotic and necrotic cells under co-treatment conditions. Analysis of autophagy-related processes specifically further revealed dysregulation in this process in resistant cells. Imaging displayed increased autophagic puncta in resistant lines under starvation conditions (2-fold, p < 0.0001), indicating increased autophagic activity, corresponding with increased ULK1 and pULK1 expression. This increased activity was further confirmed via western blotting, with resistant cells showing increased expression of autophagy-associated genes and cleavage. Conclusion We have discovered that ULK1, a necessary inducer of autophagy, displays increased expression and activity in VEN-resistant AML cells, and that these cells experience dysregulated autophagic processes. Inhibition of ULK1 via SBI and SBP inhibitors sensitizes VEN-resistant cells to VEN, indicating a potential strategy to combat VEN resistance in AML. Keywords AML stem cells, drug resistance, Venetoclax, Autophagy, ULK1, BCL-2
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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".