Abstract

Inflammation has been recognized as an important driver in the development and growth of malignancies. Inflammatory signaling in cancer emerges from the combinatorial interaction of several deregulated pathways. Pathway deregulation is often driven by changes in the underlying gene regulatory networks. Confronted with such complex scenario, it can be argued that a closer analysis of the structure of such regulatory networks will shed some light on how gene deregulation led to sustained inflammation in cancer. Here, we inferred an inflammation-associated gene regulatory network from 641 breast cancer and 78 healthy samples. A modular structure analysis of the regulatory network was carried out, revealing a hierarchical modular structure. Modules show significant overrepresentation score p-values for biological processes unveiling a definite association between inflammatory processes and adaptive immunity. Other modules are enriched for T-cell activation, differentiation of CD8+ lymphocytes and immune cell migration, thus reinforcing the aforementioned association. These analyses suggest that in breast cancer tumors, the balance between antitumor response and immune tolerance involving CD8+ T cells is tipped in favor of the tumor. One possible mechanism is the induction of tolerance and anergization of these cells by persistent antigen exposure.

Highlights

  • Breast cancer is the most frequently diagnosed malignancy in women worldwide [1]

  • We found a hierarchical modular structure in transcriptional networks associated to inflammatory response, where genes tend to be connected to others with similar differential expression patterns: overexpressed genes are more connected between them, as well as underexpressed ones

  • The Inflammation-associated Gene Regulatory Network (IGRN) contains the top 10,000 interactions ordered by mutual information (MI) value; this IGRN has 942 genes with three connected components that contain more than 10 genes (Figures 2A–C and Supplementary File 1)

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Summary

Introduction

Breast cancer is the most frequently diagnosed malignancy in women worldwide [1]. Given its prevalence, a great effort has been made to understand the mechanisms that lead to its development including genetic analysis, mutation status for known oncogenes ad tumor suppresors, expression status of known associated receptors like ER and ERBB2 (HER2), as well as transcriptomic assays as exemplified in Cancer Genome Atlas Network [2]. Breast cancer tumors appear to be highly heterogeneous in all these aspects, a shared set of characteristics are recognizable during tumor development, which are widely known as the hallmarks of cancer [3, 4]. In this view, cancerous phenotypes result from a complex of interacting biological processes or pathways that are subverted in favor of tumor survival, growth and invasion. The effects of inflammation include changes in tissue properties like blood vessel

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