Pan-cancer analysis connects tumor matrisome to immune response

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Pan-cancer analysis connects tumor matrisome to immune response
Title:
Pan-cancer analysis connects tumor matrisome to immune response
Journal Title:
Precision Oncology
Keywords:
Publication Date:
22 May 2019
Citation:
Lim, S.B., Chua, M.L.K., Yeong, J.P.S. et al. Pan-cancer analysis connects tumor matrisome to immune response. npj Precis. Onc. 3, 15 (2019). https://doi.org/10.1038/s41698-019-0087-0
Abstract:
Recent sequencing efforts unveil genomic landscapes of tumor microenvironment. A key compartment in this niche is the extracellular matrix (ECM) and its related components – matrisome. Yet, little is known about the extent to which matrisome pattern is conserved in progressive tumors across diverse cancer types. Using integrative genomic approaches, we conducted multi-platform assessment of a measure of deregulated matrisome associated with tumor progression, termed as tumor matrisome index (TMI), in over 30,000 patient-derived samples. Combined quantitative analyses of genomics and proteomics reveal that TMI is closely associated with mutational load, tumor pathology, and predicts survival across different malignancies. Interestingly, we observed an enrichment of specific tumor-infiltrating immune cell populations, along with signatures predictive of resistance to immune checkpoint blockade immunotherapy, and clinically targetable immune checkpoints in TMIhigh tumors. B7-H3 emerged as a particularly promising target for anti-tumor immunity in these tumors. Here, we show that matrisomal abnormalities could represent a potential clinically useful biomarker for prognostication and prediction of immunotherapy response.
License type:
http://creativecommons.org/licenses/by/4.0/
Funding Info:
We acknowledge support provided by the National Research Foundation, Prime Minister’s Office, Singapore under its Research Centre for Excellence, and Mechanobiology Institute at NUS. W.-T.L. is supported by the National Medical Research Council (NMRC/CSA/040/2012 and NMRC/CSA-INV/0025/2017). S.B.L. is supported by NUS Graduate School for Integrative Sciences and Engineering (NGS), Daewoong Foundation, and MOGAM Science Scholarship Foundation.
Description:
ISSN:
2397-768X
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