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Systematic identification of genetic modifiers in the response to targeted therapies in acute myeloid leukemia.

Periodic Reporting for period 1 - AML-SynergyX (Systematic identification of genetic modifiers in the response to targeted therapies in acute myeloid leukemia.)

Berichtszeitraum: 2022-09-01 bis 2024-08-31

Acute myeloid leukemia (AML) is a deadly blood cancer with a long-term survival below 30%. In last decades, treatment strategy has not changed substantially and consists of intensive chemotherapy and/or allogeneic stem cell transplantation. Novel targeted therapies exist and are very potent in the initial course of treatment, however, most patients unfortunately develop resistance. While it is widely accepted that turning oncogene-targeted therapeutics into curative therapies will require drug combinations, the pre-clinical and clinical development of rational combination therapies remains challenging at multiple levels.

In AML-SynergyX project, we focused on the FLT3 gene that is one of the most frequently mutated genes in AML and has been associated with high relapse rate and poor survival prognosis. Although specific inhibitors of mutated FLT3 are effective in the initial treatment, patients eventually develop the drug-resistant disease. We anticipate that by providing e will uncover new entry points for rational combination therapies that are urgently needed to turn the recent clinical success of FLT3 inhibitors into the cure.

Our work has identified a surface molecule CD70 as a top hit. CD70 is a member of the tumor necrosis factor (TNF) superfamily and the ligand for the cytokine receptor CD27. Interestingly, it has also been reported to be upregulated specifically on AML blasts and leukemia stem cells, but not on healthy stem cells, progenitors, or differentiated blood cells. Role of CD70 in the adaptation of leukemia cells has been described previously. In conclusion, while the project did not identify novel drug targets as initially hoped, it made significant contributions to the development of genetic screening tools, provided valuable insights into the transcriptional responses to FLT3 inhibition in AML, and supported the established role of CD70 as a potential target in AML.
We employed the optimized functional-genetic tools based on CRISPR/Cas9 gene editing and RNA interference combined with RNA profiling method called SLAM-seq, that can dynamically investigate transcriptional responses, to provide deep understanding of cellular responses and adaptation mechanisms of AML cells in the response to FLT3 inhibition. We investigated the cellular responses and adaptation mechanisms for two clinically approved FLT3 inhibitors gilteritinib and quizartinib in established FLT3 human AML models.

Key Achievements:

1. Development of improved tools for pooled genetic screens:
- genome-wide sgRNA library with two guides per gene, making it more efficient for large-scale experiments.
- focused shRNA library targeting about 5000 genes identified as cancer dependencies, aimed at studying the function of essential genes.

2. Execution of drug-modifier genetic screens:
- Performed CRISPR/Cas9-based and shRNA-based screens to identify genetic modifiers of response to FLT3 inhibitors.
- Identified CD70 as a promising target in gilteritinib-treated AML cells.

3. Time-resolved transcriptome profiling:
- Used SLAM-seq to analyze transcriptional changes in response to FLT3 inhibitors at different time points.
- Identified both immediate and adaptive transcriptional responses to drug treatment, including CD70.
Impact:

- The developed screening tools (2-guide CRISPR/Cas9 library and focused shRNA library) have become valuable resources for genetic screening and studying essential gene functions.

- The project provided valuable insights into the transcriptional responses to FLT3 inhibition in AML, showcasing that the transcriptional signatures of both clinically approved FLT3 inhibitors gilteritinib and quizartinib were conserved.

-Our results support the established role of CD70 as a potential target in AML.
graphical abstract of the project
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