Correlation Engine 2.0
Clear Search sequence regions


Sizes of these terms reflect their relevance to your search.

Because there are ongoing efforts to identify and develop novel drugs in the treatment of refractory gastric cancer, it is necessary to develop effective preclinical studies. Here, the preclinical efficacy of gastric tumor xenograft (GTX)-derived cell line models for the personalized treatment of gastric cancer was investigated. Anti-cancer drugs were scanned with high-throughput screening (HTS) using pre-established GTX-derived cell lines. The efficacy of a selected drug (afatinib) was re-confirmed in vivo and intracellular signaling pathways were investigated in xenograft tumor cell lysates using western blotting. Validation studies, such as cell proliferation and caspase activity assays, were also conducted in vitro with GTX-derived cell lines. HTS indicated that afatinib was effective in one of the five GTX-derived cell lines (GTX-087). A xenograft mouse model was established from GTX-087, and administration of afatinib at 1 mg/20 g body weight/day per oral resulted in tumor-suppressive activity in vivo. The RAS-ERK pathway was inactivated by an increase in Bax and cleaved caspase-3 in this xenograft model. In vitro cell proliferation assay also revealed that afatinib was able to suppress the growth of the GTX-087 cell line. Caspase activity assay confirmed that afatinib had an apoptotic role on GTX-087 and showed that caspase-3/7 activity increased in a time dependent manner. The GTX-derived cell line model might be useful for estimating novel drug responses and could be an alternative to patient-derived xenograft animal models. Copyright © 2022 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Citation

Sung Eun Oh, Mi Yun Oh, Su Mi Kim, Sun Young Kim, Ji Yeong An, Jun Ho Lee, Tae Sung Sohn, Jae Moon Bae, Min-Gew Choi. Feasibility of Gastric Tumor Xenograft (GTX)-derived Cell Lines for Individualized Anti-cancer Drug Screening. Anticancer research. 2022 Jun;42(6):2883-2891

Expand section icon Mesh Tags

Expand section icon Substances


PMID: 35641282

View Full Text