KIT-SNAP-tag/cell membrane chromatography model coupled with liquid chromatography-mass spectrometry for anti-GIST compound screening from Evodia rutaecarpa.

ABSTRACT

Gastrointestinal mesenchymal tumors, as the most common mesenchymal tumors in the gastrointestinal tract, are adjuvantly treated with multi-targeted tyrosine kinase inhibitors, such as imatinib and sunitinib, but there are problems of drug resistance and complex methods of monitoring therapeutic agents. The pathogenesis of this disease is related to mutations in tyrosine kinase (KIT) or platelet-derived growth factor receptor α, an important target for drug therapy. In recent years, the screening of relevant tyrosine kinase inhibitors from traditional Chinese medicine has become a hotspot in antitumor drug research. In the current study, the KIT-SNAP-tag cell membrane chromatography (KIT-SNAP-tag/CMC) column was prepared with satisfying specificity, selectivity, and reproducibility by chemically bonding high KIT expression cell membranes to the silica gel surface using the SNAP-tag technology. The KIT-SNAP-tag/CMC-HPLC-MS two-dimensional coupling system was investigated using the positive drug imatinib, and the results showed that the system was a reliable model for screening potential antitumor compounds from complex systems. This system screened and identified three potential active compounds of evodiamine (EVO), rutaecarpin (RUT), and dehydroevodiamine (DEVO), which possibly target the KIT receptor, from the alcoholic extract of the traditional Chinese medicine Evodia rutaecarpa. Then, the KD values of the interaction of EVO, RUT, and DEVO with KIT receptors measured using nonlinear chromatography were 7.75 (±4.93) × 10-6, 1.42 (±0.71) × 10-6, and 2.34 (±1.86) × 10-6 mol/L, respectively. In addition, the methyl thiazolyl tetrazolium assay validated the active effects of EVO and RUT in inhibiting the proliferation of high KIT-expressing cells in the ranges of 0.1-10 µmol/L and 0.1-50 µmol/L, respectively. In conclusion, the KIT-SNAP-tag/CMC could be a reliable model for screening antitumor components from complex systems.