A Receptor Tyrosine Kinase Inhibitor Sensitivity Prediction Model Identifies AXL Dependency in Leukemia

Ahmad Nasimian; Lina Al Ashiri; Mehreen Ahmed; Hongzhi Duan; Xiaoyue Zhang; Lars Rönnstrand; Julhash U Kazi

doi:10.3390/ijms24043830

A Receptor Tyrosine Kinase Inhibitor Sensitivity Prediction Model Identifies AXL Dependency in Leukemia

Int J Mol Sci. 2023 Feb 14;24(4):3830. doi: 10.3390/ijms24043830.

Authors

Ahmad Nasimian^{1

2}, Lina Al Ashiri^{1

2}, Mehreen Ahmed^{1

2}, Hongzhi Duan^{1

2}, Xiaoyue Zhang^{1

2}, Lars Rönnstrand^{1

2

3}, Julhash U Kazi^{1

2}

Affiliations

¹ Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, 22381 Lund, Sweden.
² Lund Stem Cell Center, Department of Laboratory Medicine, Lund University, 22184 Lund, Sweden.
³ Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, 22185 Lund, Sweden.

Abstract

Despite incredible progress in cancer treatment, therapy resistance remains the leading limiting factor for long-term survival. During drug treatment, several genes are transcriptionally upregulated to mediate drug tolerance. Using highly variable genes and pharmacogenomic data for acute myeloid leukemia (AML), we developed a drug sensitivity prediction model for the receptor tyrosine kinase inhibitor sorafenib and achieved more than 80% prediction accuracy. Furthermore, by using Shapley additive explanations for determining leading features, we identified AXL as an important feature for drug resistance. Drug-resistant patient samples displayed enrichment of protein kinase C (PKC) signaling, which was also identified in sorafenib-treated FLT3-ITD-dependent AML cell lines by a peptide-based kinase profiling assay. Finally, we show that pharmacological inhibition of tyrosine kinase activity enhances AXL expression, phosphorylation of the PKC-substrate cyclic AMP response element binding (CREB) protein, and displays synergy with AXL and PKC inhibitors. Collectively, our data suggest an involvement of AXL in tyrosine kinase inhibitor resistance and link PKC activation as a possible signaling mediator.

Keywords: TabNet; XGBoost; drug resistance; drug sensitivity prediction; machine learning; targeted therapy.

MeSH terms

Cell Line, Tumor
Drug Resistance, Neoplasm* / genetics
Humans
Leukemia, Myeloid, Acute* / drug therapy
Leukemia, Myeloid, Acute* / genetics
Mutation
Sorafenib* / therapeutic use
Tyrosine Kinase Inhibitors*
fms-Like Tyrosine Kinase 3 / genetics

Substances

fms-Like Tyrosine Kinase 3
Sorafenib
Tyrosine Kinase Inhibitors

Grants and funding

This research was supported by the Kungliga Fysiografiska Sällskapet i Lund (A.N. and M.A.), the Crafoord Foundation (J.U.K), the Swedish Cancer Society (J.U.K. and L.R.), the Swedish Research Council (L.R.), the Swedish Childhood Cancer Foundation (J.U.K.), and SUS Stiftelser och Donationer (L.R.), Governmental Funding of Clinical Research within the National Health Service (ALF) (L.R.).