4.8 Article

A proteomic landscape of diffuse-type gastric cancer

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NATURE COMMUNICATIONS
卷 9, 期 -, 页码 -

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NATURE PORTFOLIO
DOI: 10.1038/s41467-018-03121-2

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资金

  1. National Program on Key Basic Research Project (973 Program) [2014CBA02000, 2014CBA02001, 2014CBA02002, 2014CBA02004, 2012CB910300]
  2. National High-tech R&D Program of China (863 program) [2015AA020108]
  3. National International Cooperation Grant [2014DFB30010, 2014DFA33160, 2012DFB30080]
  4. Beijing Natural Science Foundation [Z131100005213003]
  5. Chinese Ministry of Science and Technology [2016YFA0502500]
  6. National Key Research and Development Program of China [2017YFC1308900, 2017YFA0505102, 2017YFC0908404]
  7. National Natural Science Foundation of China [31270822, 31770886, 31700682]
  8. National Institute of Health (Illuminating Druggable Genome) [U01MH105026]
  9. Shanghai Municipal Science and Technology Major Project [2017SHZDZX01]
  10. State Key Laboratory of Proteomics [SKLP-YA201401]

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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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