4.8 Article

Proteomic Profiling of the ECM of Xenograft Breast Cancer Metastases in Different Organs Reveals Distinct Metastatic Niches

期刊

CANCER RESEARCH
卷 80, 期 7, 页码 1475-1485

出版社

AMER ASSOC CANCER RESEARCH
DOI: 10.1158/0008-5472.CAN-19-2961

关键词

-

类别

资金

  1. Howard Hughes Medical Institute
  2. NIH
  3. Breast Cancer Research Program (BCRP) Innovator Award from the Department of Defense office of the Congressionally Directed Medical Research Programs (CDMRP)
  4. Ludwig Center for Molecular Oncology at the Massachusetts Institute of Technology
  5. NIH Pre-Doctoral Training grant [T32GM007287]
  6. NCI Clinical Proteomic Tumor Analysis Consortium grants [NIH/NCI U24-CA210986, NIH/NCI U01 CA214125]

向作者/读者索取更多资源

Metastasis causes most cancer-related deaths, and one poorly understood aspect of metastatic cancer is the adaptability of cells from a primary tumor to create new niches and survive in multiple, different secondary sites. We used quantitative mass spectrometry to analyze the extracellular matrix (ECM), a critical component of metastatic niches, in metastases to the brain, lungs, liver, and bone marrow, all derived from parental MDA-MB-231 triple-negative breast cancer cells. Tumor and stromal cells cooperated in forming niches; stromal cells produced predominantly core, structural ECM proteins and tumor cells produced a diverse array of ECM-associated proteins, including secreted factors and modulators of the matrix. In addition, tumor and stromal cells together created distinct niches in each tissue. Downregulation of SERPINB1, a protein elevated in brain metastases, led to a reduction in brain metastasis, suggesting that some niche-specific ECM proteins may be involved in metastatic tropism. Significance: Tumor and stromal cells together create distinct ECM niches in breast cancer metastases to various tissues, providing new insight into how tumor cells adapt to survive in different tissue environments.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据