Characterization and validation of potential therapeutic targets based on the molecular signature of patient-derived xenografts in gastric cancer

根据胃癌患者异种移植瘤的分子特征对潜在治疗靶点进行表征和验证

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作者:Zuhua Chen, Wenwen Huang, Tiantian Tian, Wanchun Zang, Jingyuan Wang, Zhentao Liu, Zhongwu Li, Yumei Lai, Zhi Jiang, Jing Gao, Lin Shen

Background

Patient-derived xenograft (PDX) models with definite molecular signature are attractive preclinical models for development of novel targeted drugs. Here, we profiled and explored potential therapeutic targets based on characterized PDX models for advanced gastric cancer (AGC).

Conclusions

PDX models with defined molecular signature are useful for preclinical studies with targeted drugs, and the results should be validated in larger studies with PDX models or in clinical trials.

Methods

The genomic variation and molecular profile of 50 PDX models from AGC patients were analyzed by targeted next-generation sequencing, in situ hybridization, and immunohistochemistry. The antitumor activities of several targeted drugs were investigated in the PDX models. Furthermore, response biomarkers were explored.

Results

Each PDX model had individual histopathological and molecular features, and recurrent alterations in the MAPK, ErbB, VEGF, mTOR, and cell cycle signaling pathways were major events in these PDX models. Several potential drug targets, such as EGFR, MET, and CCNE1, were selected and validated in this study. Volitinib demonstrated strong antitumor activity in PDX models with MET and phosphorylated MET (pMET) overexpression. The EGFR monoclonal antibodies BK011 and cetuximab inhibited tumor growth in a PDX model with EGFR amplification. Afatinib inhibited tumor growth in the PDX models with EGFR amplification, EGFR overexpression, or HER2 amplification. Apatinib was more sensitive in the PDX models with high microvessel density. The CDK1/2/9 inhibitor AZD5438 had superior anti-tumor activity in two models with higher copy number of CCNE1. Conclusions: PDX models with defined molecular signature are useful for preclinical studies with targeted drugs, and the results should be validated in larger studies with PDX models or in clinical trials.

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