Title |
Identification of Interacting Stromal Axes in Triple-Negative Breast Cancer
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Published in |
Cancer Research, August 2017
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DOI | 10.1158/0008-5472.can-16-3427 |
Pubmed ID | |
Authors |
Sadiq M.I. Saleh, Nicholas Bertos, Tina Gruosso, Mathieu Gigoux, Margarita Souleimanova, Hong Zhao, Atilla Omeroglu, Michael T. Hallett, Morag Park |
Abstract |
Triple-negative breast cancer (TNBC) is a molecularly heterogeneous cancer that is difficult to treat. Despite the role it may play in tumor progression and response to therapy, microenvironmental (stromal) heterogeneity in TNBC has not been well characterized. To address this challenge, we investigated the transcriptome of tumor-associated stroma isolated from TNBC (n=57). We identified four stromal axes enriched for T cells (T), B cells (B), epithelial markers (E), or desmoplasia (D). Our analysis method (STROMA4) assigns a score along each stromal axis for each patient, and then combined the axis scores to subtype patients. Analysis of these subtypes revealed that prognostic capacity of the B, T and E scores was governed by the D score. When compared to a previously published TNBC subtyping scheme, the STROMA4 method better captured tumor heterogeneity and predicted patient benefit from therapy with increased sensitivity. This approach produces a simple ontology that captures TNBC heterogeneity and informs how tumor-associated properties interact to affect prognosis. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Canada | 2 | 25% |
Norway | 1 | 13% |
Unknown | 5 | 63% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 6 | 75% |
Scientists | 2 | 25% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 46 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 9 | 20% |
Student > Bachelor | 6 | 13% |
Student > Master | 5 | 11% |
Student > Postgraduate | 4 | 9% |
Researcher | 3 | 7% |
Other | 6 | 13% |
Unknown | 13 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 11 | 24% |
Biochemistry, Genetics and Molecular Biology | 9 | 20% |
Agricultural and Biological Sciences | 7 | 15% |
Immunology and Microbiology | 2 | 4% |
Nursing and Health Professions | 1 | 2% |
Other | 2 | 4% |
Unknown | 14 | 30% |