Network Modularity in Breast Cancer Molecular Subtypes

Alcalá-Corona, Sergio Antonio; Anda-Jáuregui, Guillermo de; Espinal-Enríquez, Jesús; Hernández‐Lemus, Enrique

doi:10.3389/fphys.2017.00915

Cited by 46 publications

(42 citation statements)

References 85 publications

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“…Breast cancer transcriptional networks also exhibit modular structures, as it has been previously reported (Alcalá-Corona et al, 2017 ). The HER2+ molecular subtype is no exception.…”

Section: Resultssupporting

confidence: 69%

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The Hierarchical Modular Structure of HER2+ Breast Cancer Network

et al. 2018

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HER2-enriched breast cancer is a complex disease characterized by the overexpression of the ERBB2 amplicon. While the effects of this genomic aberration on the pathology have been studied, genome-wide deregulation patterns in this subtype of cancer are also observed. A novel approach to the study of this malignant neoplasy is the use of transcriptional networks. These networks generally exhibit modular structures, which in turn may be associated to biological processes. This modular regulation of biological functions may also exhibit a hierarchical structure, with deeper levels of modular organization accounting for more specific functional regulation. In this work, we identified the most probable (maximum likelihood) model of the hierarchical modular structure of the HER2-enriched transcriptional network as reconstructed from gene expression data, and analyzed the statistical associations of modules and submodules to biological functions. We found modular structures, independent from direct ERBB2 amplicon regulation, involved in different biological functions such as signaling, immunity, and cellular morphology. Higher resolution submodules were identified in more specific functions, such as micro-RNA regulation and the activation of viral-like immune response. We propose the approach presented here as one that may help to unveil mechanisms involved in the development of the pathology.

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“…Breast cancer transcriptional networks also exhibit modular structures, as it has been previously reported (Alcalá-Corona et al, 2017 ). The HER2+ molecular subtype is no exception.…”

Section: Resultssupporting

confidence: 69%

“…Previously, we have shown that modular structures in transcriptional networks are usually associated with biological features (Alcalá-Corona et al, 2016 , 2017 ). Here we show that new insights on the biological features of HER2+ breast cancer may be revealed by exploring the functionality related to different layers of modularity.…”

Section: Resultsmentioning

confidence: 96%

The Hierarchical Modular Structure of HER2+ Breast Cancer Network

et al. 2018

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“…Transcriptional profiles are the basis of the classification into the main four molecular subtypes: Luminal A, Luminal B, Her2-enriched and Basal. Our group has shown that co-expression networks of breast cancer molecular subtypes are different in terms of their modularity [34] and network architecture [35]. Here, it is shown that the cis-/trans-proportion imbalance is another feature that characterizes each network (Table I, Figure 3).…”

Section: Discussionmentioning

confidence: 79%

Gene co-expression is distance-dependent in breast cancer

García-Cortés

Anda-Jáuregui²,

Fresno³

et al. 2018

Preprint

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Breast carcinomas are characterized by anomalous gene regulatory programs. As is well known, gene expression programs are able to shape phenotypes. Hence, the understanding of gene co-expression may shed light on the underlying mechanisms behind the transcriptional regulatory programs affecting tumor development and evolution. For instance, in breast cancer, there is a clear loss of inter-chromosomal (trans-) co-expression, compared with healthy tissue. At the same time cis-(intrachromosomal) interactions are favored in breast tumors. In order to have a deeper understanding of regulatory phenomena in cancer, here, we constructed Gene Coexpression Networks by using 848 RNA-seq whole-genome samples corresponding to the four breast cancer molecular subtypes, as well as healthy tissue. We quantify the cis-/trans-co-expression imbalance in all phenotypes. Additionally, we measured the association between co-expression and physical distance between genes, and characterized the proportion of intra/inter-cytoband interactions per phenotype. We confirmed loss of trans-co-expression in all molecular subtypes. We also observed that gene cis-co-expression decays abruptly with distance in all tumors in contrast with healthy tissue. We observed co-expressed gene hotspots, that tend to be connected at cytoband regions, and coincide accurately with already known copy number altered regions, such as Chr17q12, or Chr8q24.3 for all subtypes. Our methodology recovered different alterations already reported for specific breast cancer subtypes, showing how co-expression network approaches might help to capture distinct events that modify the cell regulatory program.

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“…Our group has found that representing the transcriptional program of breast cancer molecular subtypes as co-expression networks, it is possible by to capture the differences found between each cancer manifestation [15]. We have also shown how genes with coordinated expression patterns are found associated to each cancer subtype, and through these, it is possible to identify and associate functional perturbations to molecular subtypes [1,2].…”

Section: Introductionmentioning

confidence: 96%

Highly-connected, non-redundant microRNAs functional control in breast cancer molecular subtypes

Anda-Jáuregui¹,

Espinal-Enríquez²,

Hernández‐Lemus³

2019

Preprint

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Transcriptional patterns are altered in breast cancer. These alterations capture the heterogeneity of breast cancer, leading to the emergence of molecular subtypes. Network biology approaches to study gene co-expression are able to capture the differences between breast cancer subtypes. Network biology approaches may be extended to include other co-expression patterns, like those found between genes and non-coding RNA: such as mi-croRNAs (miRs). Commodore miRs are microRNAs that, based on their connectivity and redundancy in co-expression networks, have been proposed as potential control elements of biological functions. In this work, we reconstructed miR-gene co-expression networks for each breast cancer molecular subtype. We identified Commodore miRs in three out of four molecular subtypes. We found that in each subtype, each cdre-miR had a different set of associated genes, as well as a different set of associated biological functions. We used a systematic literature validation strategy, and identified that the associated biological functions to these cdre-miRs are hallmarks of cancer.

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Network Modularity in Breast Cancer Molecular Subtypes

Cited by 46 publications

References 85 publications

The Hierarchical Modular Structure of HER2+ Breast Cancer Network

The Hierarchical Modular Structure of HER2+ Breast Cancer Network

Gene co-expression is distance-dependent in breast cancer

Highly-connected, non-redundant microRNAs functional control in breast cancer molecular subtypes

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