Phosphoproteomics Enables Molecular Subtyping and Nomination of Kinase Candidates for Individual Patients of Diffuse-Type Gastric Cancer

The diffuse-type gastric cancer (DGC) constitutes a subgroup of gastric cancer with poor prognosis and no effective molecular therapies. Here, we report a phosphoproteomic landscape of DGC derived from 83 tumors together with their nearby tissues. Based on phosphorylation, DGC could be classified in...

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Vydáno v:iScience Ročník 22; s. 44 - 57
Hlavní autoři: Tong, Mengsha, Yu, Chunyu, Shi, Jinwen, Huang, Wenwen, Ge, Sai, Liu, Mingwei, Song, Lei, Zhan, Dongdong, Xia, Xia, Liu, Wanlin, Feng, Jinwen, Shi, Wenhao, Ji, Jiafu, Gao, Jing, Shi, Tieliu, Zhu, Weimin, Ding, Chen, Wang, Yi, He, Fuchu, Shen, Lin, Li, Tingting, Qin, Jun
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States Elsevier Inc 20.12.2019
Elsevier
Témata:
Biological Sciences
Cancer Systems Biology
Proteomics
Systems Biology
Biological Sciences
Systems Biology
Proteomics
Cancer Systems Biology
ISSN:2589-0042, 2589-0042
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Shrnutí:The diffuse-type gastric cancer (DGC) constitutes a subgroup of gastric cancer with poor prognosis and no effective molecular therapies. Here, we report a phosphoproteomic landscape of DGC derived from 83 tumors together with their nearby tissues. Based on phosphorylation, DGC could be classified into three molecular subtypes with distinct overall survival (OS) and chemosensitivity. We identified 16 kinases whose activities were associated with poor OS. These activated kinases covered several cancer hallmark pathways, with the MTOR signaling network being the most frequently activated. We proposed a patient-specific strategy based on the hierarchy of clinically actionable kinases for prioritization of kinases for further clinical evaluation. Our global data analysis indicates that in addition to finding activated kinase pathways in DGC, large-scale phosphoproteomics could be used to classify DGCs into subtypes that are associated with distinct clinical outcomes as well as nomination of kinase targets that may be inhibited for cancer treatments. [Display omitted] •A phosphoproteomic landscape of diffuse-type gastric cancer (DGC) was depicted•DGC could be classified into three subtypes based on phosphorylation data•A bioinformatics workflow was used to identify 16 kinases as potential drug targets•A patient-specific strategy for nomination of kinases was proposed Biological Sciences; Cancer Systems Biology; Proteomics; Systems Biology
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These authors contributed equally
ISSN:2589-0042
2589-0042
DOI:10.1016/j.isci.2019.11.003