Integration of pharmacoproteomic and computational approaches reveals the cellular signal transduction pathways affected by apatinib in gastric cancer cell lines

Yosui Nojima; Masahiko Aoki; Suyong Re; Hidekazu Hirano; Yuichi Abe; Ryohei Narumi; Satoshi Muraoka; Hirokazu Shoji; Kazufumi Honda; Takeshi Tomonaga; Kenji Mizuguchi; Narikazu Boku; Jun Adachi

doi:10.1016/j.csbj.2023.03.006

Integration of pharmacoproteomic and computational approaches reveals the cellular signal transduction pathways affected by apatinib in gastric cancer cell lines

Comput Struct Biotechnol J. 2023 Mar 15:21:2172-2187. doi: 10.1016/j.csbj.2023.03.006. eCollection 2023.

Authors

Yosui Nojima^{1

2}, Masahiko Aoki^{3

4}, Suyong Re¹, Hidekazu Hirano^{3

5

6}, Yuichi Abe^{5

6

7}, Ryohei Narumi^{5

6}, Satoshi Muraoka^{5

6}, Hirokazu Shoji³, Kazufumi Honda^{8

9}, Takeshi Tomonaga^{5

6

10}, Kenji Mizuguchi^{1

11}, Narikazu Boku^{3

12}, Jun Adachi^{5

6

13}

Affiliations

¹ Artificial Intelligence Center for Health and Biomedical Research (ArCHER), National Institutes of Biomedical Innovation, Health and Nutrition, Osaka 567-0085, Japan.
² Center for Mathematical Modeling and Data Science, Osaka University, Osaka 560-8531, Japan.
³ Department of Gastrointestinal Medical Oncology, National Cancer Center Hospital, Tokyo 104-0045, Japan.
⁴ Department of Early Clinical Development, Graduate School of Medicine, Kyoto University Hospital, Kyoto 606-8507, Japan.
⁵ Laboratory of Proteome Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka 567-0085, Japan.
⁶ Laboratory of Proteomics for Drug Discovery, Center for Drug Design Research, National Institute of Biomedical Innovation, Health, and Nutrition, Osaka 567-0085, Japan.
⁷ Division of Molecular Diagnostics, Aichi Cancer Center Research Institute, Nagoya 464-8681, Japan.
⁸ Department of Biomarkers for Early Detection of Cancer, National Cancer Center Research Institute, Tokyo 104-0045, Japan.
⁹ Department of Bioregulation, Graduate School of Medicine, Nippon Medical School, Bunkyo-ku, Tokyo 113-8602, Japan.
¹⁰ Proteobiologics Co., Ltd., Osaka 567-0085, Japan.
¹¹ Institute for Protein Research, Osaka University, Osaka 565-0871, Japan.
¹² Department of Medical Oncology and General Medicine, IMSUT Hospital, Institute of Medical Science, University of Tokyo, Tokyo 108-8639, Japan.
¹³ Laboratory of Clinical and Analytical Chemistry, Center for Drug Design Research, National Institute of Biomedical Innovation, Health and Nutrition, Osaka 567-0085, Japan.

Abstract

Apatinib is known to be a highly selective vascular endothelial growth factor receptor 2 (VEGFR2) inhibitor with anti-angiogenic and anti-tumor properties. In a phase III study, the objective response rate to apatinib was low. It remains unclear why the effectivity of apatinib varies among patients and what type of patients are candidates for the treatment. In this study, we investigated the anti-tumor efficacy of apatinib against 13 gastric cancer cell lines and found that it differed depending on the cell line. Using integrated wet and dry approaches, we showed that apatinib was a multi-kinase inhibitor of c-Kit, RAF1, VEGFR1, VEGFR2, and VEGFR3, predominantly inhibiting c-Kit. Notably, KATO-III, which was the most apatinib-sensitive among the gastric cancer cell lines investigated, was the only cell line expressing c-Kit, RAF1, VEGFR1, and VEGFR3 but not VEGFR2. Furthermore, we identified SNW1 as a molecule affected by apatinib that plays an important role in cell survival. Finally, we identified the molecular network related to SNW1 that was affected by treatment with apatinib. These results suggest that the mechanism of action of apatinib in KATO-III cells is independent of VEGFR2 and that the differential efficacy of apatinib was due to differences in expression patterns of receptor tyrosine kinases. Furthermore, our results suggest that the differential efficacy of apatinib in gastric cell lines may be attributed to SNW1 phosphorylation levels at a steady state. These findings contribute to a deeper understanding of the mechanism of action of apatinib in gastric cancer cells.

Keywords: Apatinib; Bioinformatics; Computational biology; Gastric cancer; Proteomics; Rivoceranib.