Abstract
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.
S. A. Alcalá-Corona, G. de Anda-Jáuregui, J. Espinal-Enriquez and E. Hernández-Lemus—Equal Contributors.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Alcalá-Corona, S.A., Velázquez-Caldelas, T.E., Espinal-Enríquez, J., Hernández-Lemus, E.: Community structure reveals biologically functional modules in MEF2C transcriptional regulatory network. Front. Physiol. 7, 184 (2016)
Alcalá-Corona, S.A., De Anda Jáuregui, G., Espinal-Enríquez, J., Hernández-Lemus, E.: Network modularity in breast cancer molecular subtypes. Front. Physiol. 8, 915 (2017)
Alcalá-Corona, S.A., De Anda Jáuregui, G., Espinal-Enríquez, J., Hernández-Lemus, E.: The hierarchical network structure of HER2+ breast cancer. Submitted to Front. Physiol. Sect. Syst. Biol. (2018). (in Press)
Gene Ontology Consortium. Gene ontology consortium: going forward. Nucleic Acids Res. 43, D1049–D1056 (2015)
de Anda-Jáuregui, G., Mejía-Pedroza, R.A., Espinal-Enríquez, J., Hernández-Lemus, E.: Crosstalk events in the estrogen signaling pathway may affect tamoxifen efficacy in breast cancer molecular subtypes. Comput. Biol. Chem. 59, 42–54 (2015)
de Anda-Jáuregui, G., Velázquez-Caldelas, T.E., Espinal-Enríquez, J., Hernández-Lemus, E.: Transcriptional network architecture of breast cancer molecular subtypes. Front. Physiol. 7, 568 (2016)
Fortunato, S.: Community detection in graphs. Phys. Rep. 486(3–5), 75–174 (2010)
Fortunato, S., Hric, D.: Community detection in networks: a user guide. Phys. Rep. 659, 1–44 (2016)
Margolin, A.A., Wang, K., Lim, W.K., Kustagi, M., Nemenman, I., Califano, A.: Reverse engineering cellular networks. Nat. Protoc. 1, 662–671 (2006)
Parker, J.S., Mullins, M., Cheang, M.C.U., Leung, S., Voduc, D., Vickery, T., Davies, S., Fauron, C., He, X., Hu, Z., et al.: Supervised risk predictor of breast cancer based on intrinsic subtypes. J. Clin. Oncol. 27(8), 1160 (2009)
Ravasz, E., Somera, A.L., Mongru, D.A., Oltvai, Z.N., Barabasi, A.L.: Hierarchical organization of modularity in metabolic networks. Science (New York, N.Y.) 297, 1551–1555 (2002)
Rosvall, M., Bergstrom, C.T.: Maps of random walks on complex networks reveal community structure. Proc. Natl. Acad. Sci. 105(4), 1118–1123 (2008)
Rosvall, M., Bergstrom, C.T.: Mapping change in large networks. PLoS ONE 5(1), e8694 (2010)
Sole, R.V., Valverde, S.: Spontaneous emergence of modularity in cellular networks. J. R. Soc. Interface 5, 129–133 (2008)
Solé, R.V., Valverde, S., Rodriguez-Caso, C.: Modularity in biological networks. In: Biological Networks (2006)
Tripathi, S., Moutari, S., Dehmer, M., Emmert-Streib, F.: Comparison of module detection algorithms in protein networks and investigation of the biological meaning of predicted modules. BMC Bioinform. 17, 129 (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this paper
Cite this paper
Alcalá-Corona, S.A., de Anda-Jáuregui, G., Espinal-Enriquez, J., Tovar, H., Hernández-Lemus, E. (2018). Network Modularity and Hierarchical Structure in Breast Cancer Molecular Subtypes. In: Morales, A., Gershenson, C., Braha, D., Minai, A., Bar-Yam, Y. (eds) Unifying Themes in Complex Systems IX. ICCS 2018. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-319-96661-8_36
Download citation
DOI: https://doi.org/10.1007/978-3-319-96661-8_36
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-96660-1
Online ISBN: 978-3-319-96661-8
eBook Packages: Physics and AstronomyPhysics and Astronomy (R0)