Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/146679
Title: Anti-tumor efficacy evaluation of a novel monoclonal antibody targeting neutral amino acid transporter ASCT2 using patient-derived xenograft mouse models of gastric cancer
Authors: Kasai N.
Sasakawa A.
Hosomi K.
Poh T.W.
Chua B.L.
Yong W.P.
So J. 
Chan S.L.
Soong R.
Kono K.
Ishii T.
Yamano K.
Keywords: Antibody
ASCT2
Biomarker
Gastric cancer
Patient-derived xenograft model
Issue Date: 15-Jul-2017
Publisher: E-Century Publishing Corporation
Citation: Kasai N., Sasakawa A., Hosomi K., Poh T.W., Chua B.L., Yong W.P., So J., Chan S.L., Soong R., Kono K., Ishii T., Yamano K. (2017-07-15). Anti-tumor efficacy evaluation of a novel monoclonal antibody targeting neutral amino acid transporter ASCT2 using patient-derived xenograft mouse models of gastric cancer. American Journal of Translational Research 9 (7) : 3399-3410. ScholarBank@NUS Repository.
Abstract: ASC amino acid transporter 2 (ASCT2), also known as solute linked carrier family 1 member A5 (SLC1A5) is a Na+-dependent glutamine/neutral amino acid transporter. ASCT2 acts as a high-affinity transporter of L-glu-tamine (Gln) and has been reported to be up-regulated in a variety of cancerous tissues including stomach, liver, and kidney. In this study, we evaluated anti-tumor efficacy of a novel anti-ASCT2 humanized monoclonal antibody, KM8094, which has a neutralizing activity against glutamine uptake, as a therapeutic antibody against gastric cancer and explored clinical predictive biomarker candidates by utilizing patient-derived xenograft (PDX) mouse models. Anti-tumor efficacy studies revealed that some of the PDX models used were responsive to KM8094 and the others were not. Interestingly, we observed a correlation between anti-tumor efficacy and low antigen expression as well as low basal levels of glutamine uptake, suggesting ASCT2 expression level could be a potential predictive biomarker for KM8094. We then further explored predictive biomarker candidates by multi-omics analysis on gastric cancer PDX mouse models. As a result, a few potential candidates such as TFF2, MUC13, and ANG were selected by gene expression and DNA methylation array analyses. In addition, metabolomics analysis revealed clear differences in intracellular energy status and redox status between responsive and non-responsive PDX models. � 2017, E-Century Publishing Corporation. All rights reserved.
Source Title: American Journal of Translational Research
URI: http://scholarbank.nus.edu.sg/handle/10635/146679
ISSN: 19438141
Appears in Collections:Staff Publications

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