Combining functional genomics strategies identifies modular heterogeneity of breast cancer intrinsic subtypes

BioData Mining
Nima PouladiJason H Moore

Abstract

The discovery of breast cancer subtypes and subsequent development of treatments aimed at them has allowed for a great reduction in the mortality of breast cancer. But despite this progress, tumors with similar characteristics that belong to the same subtype continue to respond differently to the same treatment. Five subtypes of breast cancer, namely intrinsic subtypes, have been characterized to date based on their gene expression profiles. Among other characteristics, subtypes vary in their degree of intra-subtype heterogeneity. It is not clear, however, whether this heterogeneity is shared across all tumor traits. It is also unclear whether individual traits can be highly heterogeneous among a majority of homogeneous traits. We employ network theory to uncover gene modules and accordingly consider them as tumor traits, which capture shared biological processes among the subtypes. We then use the β-diversity metric from ecology to quantify the heterogeneity in these gene modules. In doing so, we show that breast cancer heterogeneity is contained in gene modules and that this modular heterogeneity increases monotonically across the subtypes. We identify a core of two modules that are shared among all subtypes which contain nuc...Continue Reading

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Citations

Nov 10, 2016·Oncotarget·Asha A NairKrishna R Kalari

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Methods Mentioned

BETA
dissection

Software Mentioned

WGCNA
R library vegan
R
limma
R ( Weighted Gene Co - Expression Network Analysis )

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