Network Modularity and Hierarchical Structure in Breast Cancer Molecular Subtypes
Breast Cancer is the malignant neoplasm with the highest incidence and mortality among women worldwide. It is a heterogeneous and complex disease, its classification in different molecular subtypes is a clear manifestation of this. The recent abundance of genomic data on cancer, make possible to propose theoretical approaches to model the process of genetic regulation. One of these approaches is gene transcriptional networks which represent the regulation and co-expression of genes as well-defined mathematical objects. These complex networks have global topological and dynamic properties. One of these properties is modular structure, which may be related to known or annotated biological processes. In this way, different modular structures in transcription networks can be seen as manifestations of regulatory structures that closely control some biological processes. In this work, we identify modular structures on gene transcriptional networks previously inferred from microarray data of molecular subtypes of breast cancer: luminal A, luminal B, basal, and HER2-enriched. Using a methodology based on the identification of functional modules in transcriptional networks, we analyzed the modules (communities) found in each network to identify particular biological functions (described in the Gene Ontology database) associated to them. We also explored the hierarchical structure of these modules and their functions to identify unique and common characteristics that could allow a better level of description of such molecular subtypes of breast cancer. This approach and its findings are leading us to a better understanding of the molecular cancer subtypes and even contribute to direct experiments and design strategies for their treatment.
KeywordsBreast cancer subtypes Modular structure Gene regulatory networks
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