A proteomic landscape of diffuse-type gastric cancer

Sai Ge(Peking University), Xia Xia(Peking University), Chen Ding(Peking University), Bei Zhen(Peking University), Quan Zhou(Peking University), Jinwen Feng(Peking University), Jiajia Yuan(Peking University), Rui Chen(Baylor College of Medicine), Yumei Li(Baylor College of Medicine), Zhongqi Ge(Baylor College of Medicine), Jiafu Ji(Peking University), Lianhai Zhang(Peking University), Jiayuan Wang(Peking University), Zhongwu Li(Peking University), Yumei Lai(Peking University), Ying Hu(Peking University), Yanyan Li(Baylor College of Medicine), Yilin Li(Baylor College of Medicine), Jing Gao(Peking University), Lin Chen(Chinese People's Liberation Army), Jianming Xu(Academy of Military Medical Sciences), Chunchao Zhang(Baylor College of Medicine), Sung Yun Jung(Baylor College of Medicine), Jong Min Choi(Baylor College of Medicine), Antrix Jain(Baylor College of Medicine), Mingwei Liu(Peking University), Lei Song(Peking University), Wanlin Liu(Peking University), Gaigai Guo(Peking University), Tongqing Gong(Peking University), Yin Huang(Peking University), Yang Qiu(Peking University), Wenwen Huang(Peking University), Tieliu Shi(East China Normal University), Weimin Zhu(Peking University), Yi Wang(Baylor College of Medicine), Fuchu He(Fudan University), Lin Shen(Peking University), Jun Qin(Baylor College of Medicine)
Nature Communications
March 2, 2018
10.1038/s41467-018-03121-2
Cited by 320Open Access
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Abstract

The diffuse-type gastric cancer (DGC) is a subtype of gastric cancer with the worst prognosis and few treatment options. Here we present a dataset from 84 DGC patients, composed of a proteome of 11,340 gene products and mutation information of 274 cancer driver genes covering paired tumor and nearby tissue. DGC can be classified into three subtypes (PX1-3) based on the altered proteome alone. PX1 and PX2 exhibit dysregulation in the cell cycle and PX2 features an additional EMT process; PX3 is enriched in immune response proteins, has the worst survival, and is insensitive to chemotherapy. Data analysis revealed four major vulnerabilities in DGC that may be targeted for treatment, and allowed the nomination of potential immunotherapy targets for DGC patients, particularly for those in PX3. This dataset provides a rich resource for information and knowledge mining toward altered signaling pathways in DGC and demonstrates the benefit of proteomic analysis in cancer molecular subtyping.

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