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Cited by 377

The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.

Extracellular matrix signatures of human mammary carcinoma identify novel metastasis promoters

Open access
Naba, Alexandra, Clauser, Karl R, Lamar, John M, Carr, Steven A, Hynes, Richard O·2014·eLife

Abstract

The extracellular matrix (ECM) is a major component of tumors and a significant contributor to cancer progression. In this study, we use proteomics to investigate the ECM of human mammary carcinoma xenografts and show that primary tumors of differing metastatic potential differ in ECM composition. Both tumor cells and stromal cells contribute to the tumor matrix and tumors of differing metastatic ability differ in both tumor- and stroma-derived ECM components. We define ECM signatures of poorly and highly metastatic mammary carcinomas and these signatures reveal up-regulation of signaling pathways including TGFβ and VEGF. We further demonstrate that several proteins characteristic of highly metastatic tumors (LTBP3, SNED1, EGLN1, and S100A2) play causal roles in metastasis, albeit at different steps. Finally we show that high expression of LTBP3 and SNED1 correlates with poor outcome for ER − /PR − breast cancer patients. This study thus identifies novel biomarkers that may serve as prognostic and diagnostic tools.

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Metadata

Authors
Naba, A., Clauser, K. R., Lamar, J. M., Carr, S. A., & Hynes, R. O.
Venue
eLife
Published
2014-03-11
Volume
3
Pages
e01308-e01308
ISSN
2050-084X (ISSN-L)
OpenAlex
W2078586977
Cited by
377
References
59
FWCI
11.92
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Extracellular matrix signatures of human mammary carcinoma identify novel metastasis promoters. https://app.cochat.ai/papers/10.7554/elife.01308
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Naba, A., Clauser, K. R., Lamar, J. M., Carr, S. A., & Hynes, R. O. (2014). Extracellular matrix signatures of human mammary carcinoma identify novel metastasis promoters. eLife. https://doi.org/10.7554/elife.01308

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.