Abstract 1509: RUNX1 dosage dictates gene signature and <i>in vitro</i> response to glucocorticoids in acute myeloid leukemia
Bibliographic record
Abstract
Abstract Background: Poor prognosis subgroups of Acute Myeloid Leukemia (AML), such as RUNX1-mutated (RUNX1mut) AML, would greatly benefit from more efficacious therapies that target leukemic stem cells (LSC) and improve patient outcome. To understand factors that predict sensitivity to drugs, we used a chemogenomic approach to interrogate primary AML specimens. Methods: We performed RNA sequencing of 415 primary AML specimens comprising various cytogenetic subgroups. Using culture conditions that support LSC activity ex vivo, we carried out a viability screen including 20 primary AML specimens and ~5,100 low molecular weight compounds. RUNX1mut specimens showed increased sensitivity to glucocorticoid compounds (GCs). Validation screens were done in 248 primary AML samples and 32 AML cell lines treated with selected GCs in a dose-response manner. The effect of RUNX1 dosage in the in vitro response to drugs was assessed by shRNA gene knockdown. GCs target, the glucocorticoid receptor (GR), was validated by chemical blockage and shRNA silencing. Results: RUNX1mut specimens were associated with older age, French-American-British (FAB) M0 morphology, intermediate-risk cytogenetics with abnormal karyotype and poor patient survival. RUNX1mut gene expression signature showed the overexpression of previously described genes such as DNTT, BAALC and CD34, as well as novel genes such as PROM1 and EGFEM1P. Most interestingly, the expression levels of these genes was influenced by the nature of the RUNX1 mutations, with levels progressively increasing with mutations corresponding to decreased levels of functional RUNX1. Chemical screens comprising 33 RUNX1mut specimens confirmed that RUNX1mut are more sensitive to GCs than RUNX1 wild-type samples. In agreement with the RUNX1mut gene signature, the anti-proliferative effect of GCs anti-correlated with levels of functional RUNX1. Specimens harboring loss-of-function and dominant-negative RUNX1 mutations showed increased sensitivity to GCs when compared to samples carrying missense mutations expected to have little impact on RUNX1 function. Mutations in other genes, such as CEBPA and SRSF2, had an additive effect on GC sensitivity when combined with RUNX1 mutations. In accordance with our hypothesis, the downregulation of RUNX1 could reverse GC-resistance in AML cell lines, and the sensitivity to compounds was proportional to knockdown levels. Treatment of cell lines with the GR antagonist RU486 blocked the inhibitory response induced by GCs and GR silencing completely abrogated the anti-proliferative effects of GCs in GC-sensitive cells, confirming that GC operate through the GR in AML. Conclusion: Altogether, these findings highlight the impact of RUNX1 dosage on gene expression and GCs sensitivity in AML cells in vitro. Further studies should investigate the benefits of repositioning GCs in the treatment of RUNX1mut AML patients. Citation Format: Laura Simon, Vincent-Philippe Lavallée, Marie-Eve Bordeleau, Jana Krosl, Irène Baccelli, Geneviève Boucher, Bernhard Lehnertz, Tara MacRae, Réjean Ruel, Sébastien Lemieux, Anne Marinier, Josée Hébert, Guy Sauvageau. RUNX1 dosage dictates gene signature and in vitro response to glucocorticoids in acute myeloid leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1509. doi:10.1158/1538-7445.AM2017-1509
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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".