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Cell Rep. 2016 Nov 15;17(8):2075-2086. doi: 10.1016/j.celrep.2016.10.057.

Epigenomic Deconvolution of Breast Tumors Reveals Metabolic Coupling between Constituent Cell Types.

Author information

1
Molecular and Human Genetics Department, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA; Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA. Electronic address: onuchic@bcm.edu.
2
Department of Pharmacology and Chemical Biology, Magee Womens Research Institute, University of Pittsburgh Cancer Institute, 204 Craft Avenue, B705, Pittsburgh, PA 15213, USA.
3
RainDance Technologies, Inc., 749 Middlesex Turnpike, Billerica, MA 01821, USA.
4
Molecular and Human Genetics Department, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.
5
Department of Obstetrics and Gynecology, Mayo Clinic College of Medicine, 200 1st Street SW, Rochester, MN 55905, USA.
6
Division of Nephrology and Hypertension, Mayo Clinic, 200 1st Street SW, Rochester, MN 55905, USA.
7
Molecular and Human Genetics Department, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA; Program in Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA. Electronic address: amilosav@bcm.edu.

Abstract

Cancer progression depends on both cell-intrinsic processes and interactions between different cell types. However, large-scale assessment of cell type composition and molecular profiles of individual cell types within tumors remains challenging. To address this, we developed epigenomic deconvolution (EDec), an in silico method that infers cell type composition of complex tissues as well as DNA methylation and gene transcription profiles of constituent cell types. By applying EDec to The Cancer Genome Atlas (TCGA) breast tumors, we detect changes in immune cell infiltration related to patient prognosis, and a striking change in stromal fibroblast-to-adipocyte ratio across breast cancer subtypes. Furthermore, we show that a less adipose stroma tends to display lower levels of mitochondrial activity and to be associated with cancerous cells with higher levels of oxidative metabolism. These findings highlight the role of stromal composition in the metabolic coupling between distinct cell types within tumors.

KEYWORDS:

DNA methylation; Warburg effect; breast cancer; cancer; cell type composition; deconvolution; gene expression; heterotypic interaction; metabolic coupling; metabolism

PMID:
27851969
PMCID:
PMC5115176
DOI:
10.1016/j.celrep.2016.10.057
[Indexed for MEDLINE]
Free PMC Article

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