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- W2774205189 abstract "Abstract We have profiled, for the first time, an evolving human metastatic microenvironment by measuring gene expression, matrisome proteomics, cytokine and chemokine levels, cellularity, extracellular matrix organization, and biomechanical properties, all on the same sample. Using biopsies of high-grade serous ovarian cancer metastases that ranged from minimal to extensive disease, we show how nonmalignant cell densities and cytokine networks evolve with disease progression. Multivariate integration of the different components allowed us to define, for the first time, gene and protein profiles that predict extent of disease and tissue stiffness, while also revealing the complexity and dynamic nature of matrisome remodeling during development of metastases. Although we studied a single metastatic site from one human malignancy, a pattern of expression of 22 matrisome genes distinguished patients with a shorter overall survival in ovarian and 12 other primary solid cancers, suggesting that there may be a common matrix response to human cancer. Significance: Conducting multilevel analysis with data integration on biopsies with a range of disease involvement identifies important features of the evolving tumor microenvironment. The data suggest that despite the large spectrum of genomic alterations, some human malignancies may have a common and potentially targetable matrix response that influences the course of disease. Cancer Discov; 8(3); 304–19. ©2017 AACR. This article is highlighted in the In This Issue feature, p. 253" @default.
- W2774205189 created "2017-12-22" @default.
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- W2774205189 date "2018-03-01" @default.
- W2774205189 modified "2023-10-12" @default.
- W2774205189 title "Deconstruction of a Metastatic Tumor Microenvironment Reveals a Common Matrix Response in Human Cancers" @default.
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- W2774205189 doi "https://doi.org/10.1158/2159-8290.cd-17-0284" @default.
- W2774205189 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5837004" @default.
- W2774205189 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29196464" @default.
- W2774205189 hasPublicationYear "2018" @default.