Abstract
Breast cancer is a complex heterogeneous disease. A clear example is given by the four molecular subtypes: Luminal A, Luminal B, HER2-Enriched and Basal-like. These subtypes give way to different therapeutic approaches to deal with different prognosis. Despite these differences, common hallmark features of cancer can be found, which its origin is traced back to the intricate relationships governing regulatory programs. In our recent work, by constructing RNA-Seq normal tissue and breast cancer gene regulatory networks, we have observed the phenomenon of loss of inter-chromosomal regulation. Our results showed that cis- regulation in breast cancer tissue occurs mostly between neighbour genes. On the contrast, in non-cancerous tissue, gene-gene regulation appears along the whole genome. Here, we extend the aforementioned approach, in order to observe into what extent the loss of trans- regulation occurs in the different intrinsic breast cancer subtypes. A collection of 780 RNA-Seq The Cancer Genome Atlas breast cancer samples were classified using PAM50 algorithm. Differential expression analysis was performed between each subtype and additional 101 normal tissue samples. Gene regulatory networks were inferred for each of the four subtypes and the normal tissue. Circos plots visualization was used to contrast the cis/trans regulation proportion. Finally, power-law regression analyses were fitted to explain the statistical relationship between genes and the distance between genes. Inter and intra-chromosome relationships occur approximately in the same proportion in the healthy network. Meanwhile, the four subtypes present a loss of trans- regulation. The decrease of trans- regulations exhibits different patterns among subtypes. Additionally, the strength of cis- regulatory interactions decays exponentially with the distance in the four subtypes. But, in the non-cancerous phenotype, distance does not influence the strength of the interactions. With this kind of approach, we have been able to integrate gene regulation and physical distance to elaborate a more comprehensive landscape in cancer genomics. Here, we opened the possibility to analyse in a complementary fashion the regulatory program of molecular subtypes of breast cancer. This effort may be complemented with copy number alterations, micro-RNAs or Hi-C data with the aim of providing a multi-omics-based framework to elaborate more specific questions in the era of personalized medicine.
Footnotes
↵* Supplementary materials for this work are available under request.