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

• Published in: International journal of molecular sciences 2023-02, Vol.24 (4), p.3830
• Main Authors: Nasimian, Ahmad, Al Ashiri, Lina, Ahmed, Mehreen, Duan, Hongzhi, Zhang, Xiaoyue, Rönnstrand, Lars, Kazi, Julhash U
• Format: Article
• Language: English
• Subjects: Accuracy; Acute myeloid leukemia; Antimitotic agents; Antineoplastic agents; Apoptosis; Axl protein; Basic Medicine; Cancer; Cancer therapies; Care and treatment; Cell growth; Cell Line, Tumor; Chemotherapy; Clinical Medicine; Cyclic AMP; Cyclic AMP response element-binding protein; Drug resistance; Drug Resistance, Neoplasm - genetics; drug sensitivity prediction; Drug therapy; Drug tolerance; Enzyme inhibitors; Farmakologi och toxikologi; fms-Like Tyrosine Kinase 3 - genetics; Gene expression; Genes; Genetic transcription; Health aspects; Hematologi; Hematology; Humans; Kinases; Klinisk medicin; Leukemia; Leukemia, Myeloid, Acute - drug therapy; Leukemia, Myeloid, Acute - genetics; machine learning; Medical and Health Sciences; Medicin och hälsovetenskap; Medicinska och farmaceutiska grundvetenskaper; Mutation; Peptides; Pharmacogenomics; Pharmacology; Pharmacology and Toxicology; Phenols; Phosphorylation; Prediction models; Protein binding; Protein kinase C; Protein Kinase Inhibitors/pharmacology; Protein kinases; Protein-tyrosine kinase receptors; Proteins; Scientific equipment and supplies industry; Sensitivity; Sorafenib - therapeutic use; TabNet; targeted therapy; Tyrosine; Tyrosine Kinase Inhibitors; Tyrosine Protein Kinase Inhibitors; XGBoost
• ISSN: 1422-0067; 1661-6596; 1422-0067
• DOI: 10.3390/ijms24043830

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.