Title
Cell subpopulation deconvolution reveals breast cancer heterogeneity based on DNA methylation signature.
Abstract
Tumour heterogeneity describes the coexistence of divergent tumour cell clones within tumours, which is often caused by underlying epigenetic changes. DNA methylation is commonly regarded as a significant regulator that differs across cells and tissues. In this study, we comprehensively reviewed research progress on estimating of tumour heterogeneity. Bioinformatics-based analysis of DNA methylation has revealed the evolutionary relationships between breast cancer cell lines and tissues. Further analysis of the DNA methylation profiles in 33 breast cancer-related cell lines identified cell line-specific methylation patterns. Next, we reviewed the computational methods in inferring clonal evolution of tumours from different perspectives and then proposed a deconvolution strategy for modelling cell subclonal populations dynamics in breast cancer tissues based on DNA methylation. Further analysis of simulated cancer tissues and real cell lines revealed that this approach exhibits satisfactory performance and relative stability in estimating the composition and proportions of cellular subpopulations. The application of this strategy to breast cancer individuals of the Cancer Genome Atlas's identified different cellular subpopulations with distinct molecular phenotypes. Moreover, the current and potential future applications of this deconvolution strategy to clinical breast cancer research are discussed, and emphasis was placed on the DNA methylation-based recognition of intra-tumour heterogeneity. The wide use of these methods for estimating heterogeneity to further clinical cohorts will improve our understanding of neoplastic progression and the design of therapeutic interventions for treating breast cancer and other malignancies.
Year
DOI
Venue
2017
10.1093/bib/bbw028
BRIEFINGS IN BIOINFORMATICS
Keywords
Field
DocType
breast cancer,cell line,deconvolution,DNA methylation,heterogeneity
Somatic evolution in cancer,Biology,Breast cancer,Methylation,DNA methylation,Cell,Bioinformatics,Cancer,Tumour heterogeneity,Epigenetics
Journal
Volume
Issue
ISSN
18
3
1467-5463
Citations 
PageRank 
References 
0
0.34
14
Authors
9
Name
Order
Citations
PageRank
Yanhua Wen110.70
Yanjun Wei2111.33
Shumei Zhang3111.33
Song Li480.89
Hongbo Liu51426105.95
Fang Wang632.80
Yue Zhao718633.54
Dongwei Zhang800.34
Yan Zhang9487.34