Title |
Extensive rewiring of epithelial-stromal co-expression networks in breast cancer
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Published in |
Genome Biology, June 2015
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DOI | 10.1186/s13059-015-0675-4 |
Pubmed ID | |
Authors |
Eun-Yeong Oh, Stephen M Christensen, Sindhu Ghanta, Jong Cheol Jeong, Octavian Bucur, Benjamin Glass, Laleh Montaser-Kouhsari, Nicholas W Knoblauch, Nicholas Bertos, Sadiq MI Saleh, Benjamin Haibe-Kains, Morag Park, Andrew H Beck |
Abstract |
Epithelial-stromal crosstalk plays a critical role in invasive breast cancer pathogenesis; however, little is known on a systems level about how epithelial-stromal interactions evolve during carcinogenesis. We develop a framework for building genome-wide epithelial-stromal co-expression networks composed of pairwise co-expression relationships between mRNA levels of genes expressed in the epithelium and stroma across a population of patients. We apply this method to laser capture micro-dissection expression profiling datasets in the setting of breast carcinogenesis. Our analysis shows that epithelial-stromal co-expression networks undergo extensive rewiring during carcinogenesis, with the emergence of distinct network hubs in normal breast, and estrogen receptor-positive and estrogen receptor-negative invasive breast cancer, and the emergence of distinct patterns of functional network enrichment. In contrast to normal breast, the strongest epithelial-stromal co-expression relationships in invasive breast cancer mostly represent self-loops, in which the same gene is co-expressed in epithelial and stromal regions. We validate this observation using an independent laser capture micro-dissection dataset and confirm that self-loop interactions are significantly increased in cancer by performing computational image analysis of epithelial and stromal protein expression using images from the Human Protein Atlas. Epithelial-stromal co-expression network analysis represents a new approach for systems-level analyses of spatially localized transcriptomic data. The analysis provides new biological insights into the rewiring of epithelial-stromal co-expression networks and the emergence of epithelial-stromal co-expression self-loops in breast cancer. The approach may facilitate the development of new diagnostics and therapeutics targeting epithelial-stromal interactions in cancer. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 20% |
France | 1 | 20% |
Unknown | 3 | 60% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 40% |
Science communicators (journalists, bloggers, editors) | 1 | 20% |
Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Scientists | 1 | 20% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 3 | 3% |
Sweden | 1 | <1% |
Germany | 1 | <1% |
Brazil | 1 | <1% |
Unknown | 108 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 28 | 25% |
Researcher | 19 | 17% |
Student > Master | 16 | 14% |
Student > Doctoral Student | 9 | 8% |
Professor > Associate Professor | 8 | 7% |
Other | 18 | 16% |
Unknown | 16 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 27 | 24% |
Biochemistry, Genetics and Molecular Biology | 25 | 22% |
Medicine and Dentistry | 17 | 15% |
Computer Science | 13 | 11% |
Engineering | 6 | 5% |
Other | 8 | 7% |
Unknown | 18 | 16% |