Characterization and validation of potential therapeutic targets based on the molecular signature of patient-derived xenografts in gastric cancer.
Characterization and validation of potential therapeutic targets based on the molecular signature of patient-derived xenografts in gastric cancer.
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DOI:
10.1186/s13045-018-0563-y
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发表时间:
2018-02-13
影响因子:
28.5
通讯作者:
Shen L
中科院分区:
文献类型:
--
作者:
Chen Z;Huang W;Tian T;Zang W;Wang J;Liu Z;Li Z;Lai Y;Jiang Z;Gao J;Shen L
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). 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. 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. 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. The online version of this article (10.1186/s13045-018-0563-y) contains supplementary material, which is available to authorized users.
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影响因子:
3.8
作者:
Luber B;Deplazes J;Keller G;Walch A;Rauser S;Eichmann M;Langer R;Höfler H;Hegewisch-Becker S;Folprecht G;Wöll E;Decker T;Endlicher E;Lorenzen S;Fend F;Peschel C;Lordick F
通讯作者:
Lordick F
影响因子:
7.3
作者:
Gao J;Aksoy BA;Dogrusoz U;Dresdner G;Gross B;Sumer SO;Sun Y;Jacobsen A;Sinha R;Larsson E;Cerami E;Sander C;Schultz N
通讯作者:
Schultz N
影响因子:
--
作者:
Derks S;Liao X;Chiaravalli AM;Xu X;Camargo MC;Solcia E;Sessa F;Fleitas T;Freeman GJ;Rodig SJ;Rabkin CS;Bass AJ
通讯作者:
Bass AJ
影响因子:
11.5
作者:
Lee, Hye Won;Lee, Jung-il;Nam, Do-Hyun
通讯作者:
Nam, Do-Hyun
影响因子:
8.8
作者:
Lee, H. E.;Kim, M. A.;Lee, H. S.;Jung, E-J;Yang, H-K;Lee, B. L.;Bang, Y-J;Kim, W. H.
通讯作者:
Kim, W. H.