Co-modulation analysis of gene regulation in breast cancer reveals complex interplay between ESR1 and ERBB2 genes
Journal
BMC Genomics
Journal Volume
16
Journal Issue
7
Date Issued
2015
Author(s)
Abstract
Background: Gene regulation is dynamic across cellular conditions and disease subtypes. From the aspect of regulation under modulation, regulation strength between a pair of genes can be modulated by (dependent on) expression abundance of another gene (modulator gene). Previous studies have demonstrated the involvement of genes modulated by single modulator genes in cancers, including breast cancer. However, analysis of multi-modulator co-modulation that can further delineate the landscape of complex gene regulation is, to our knowledge, unexplored previously. In the present study we aim to explore the joint effects of multiple modulator genes in modulating global gene regulation and dissect the biological functions in breast cancer. Results: To carry out the analysis, we proposed the Covariability-based Multiple Regression (CoMRe) method. The method is mainly built on a multiple regression model that takes expression levels of multiple modulators as inputs and regulation strength between genes as output. Pairs of genes were divided into groups based on their co-modulation patterns. Analyzing gene expression profiles from 286 breast cancer patients, CoMRe investigated ten candidate modulator genes that interacted and jointly determined global gene regulation. Among the candidate modulators, ESR1, ERBB2, and ADAM12 were found modulating the most numbers of gene pairs. The largest group of gene pairs was composed of ones that were modulated by merely ESR1. Functional annotation revealed that the group was significantly related to tumorigenesis and estrogen signaling in breast cancer. ESR1-ERBB2 co-modulation was the largest group modulated by more than one modulators. Similarly, the group was functionally associated with hormone stimulus, suggesting that functions of the two modulators are performed, at least partially, through modulation. The findings were validated in majorities of patients (> 99%) of two independent breast cancer datasets. Conclusions: We have showed CoMRe is a robust method to discover critical modulators in gene regulatory networks, and it is capable of achieving reproducible and biologically meaningful results. Our data reveal that gene regulatory networks modulated by single modulator or co-modulated by multiple modulators play important roles in breast cancer. Findings of this report illuminate complex and dynamic gene regulation under modulation and its involvement in breast cancer. © 2015 Chiu et al.; licensee BioMed Central Ltd.
SDGs
Other Subjects
epidermal growth factor receptor 2; estrogen; estrogen receptor alpha; Ki 67 antigen; macrophage migration inhibition factor; protein p53; RANTES; somatomedin C; ADAM protein; ADAM12 protein; ADAM12 protein, human; ERBB2IP protein, human; estrogen receptor alpha; estrogen receptor alpha, human; membrane protein; signal transducing adaptor protein; ADAM12 gene; algorithm; Article; breast cancer; carcinogenesis; CCL5 gene; controlled study; covariability based multiple regression method; ERBB2 gene; ESR1 gene; gene; gene control; gene expression profiling; gene interaction; gene regulatory network; human; IGF1 gene; major clinical study; MIF gene; MKI67 gene; oncogene myc; RECK gene; signal transduction; TP53 gene; algorithm; biological model; breast tumor; female; gene expression regulation; genetic database; genetics; procedures; ADAM Proteins; ADAM12 Protein; Adaptor Proteins, Signal Transducing; Algorithms; Breast Neoplasms; Databases, Genetic; Estrogen Receptor alpha; Female; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Humans; Membrane Proteins; Models, Genetic
Publisher
BioMed Central Ltd.
Type
journal article