摘要
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.
| 源语言 | 英语 |
|---|---|
| 文章编号 | 1012 |
| 期刊 | Nature Communications |
| 卷 | 9 |
| 期 | 1 |
| DOI | |
| 出版状态 | 已出版 - 1 12月 2018 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 3 良好健康与福祉
指纹
探究 'A proteomic landscape of diffuse-type gastric cancer' 的科研主题。它们共同构成独一无二的指纹。引用此
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