Original Research ARTICLE
Unveiling the link between inflammation and adaptive immunity in breast cancer
- 1Computational Genomics, Instituto Nacional de Medicina Genómica (INMEGEN), Mexico
- 2University of Chicago, United States
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.
Keywords: Inflammation, breast cancer, Adaptive Immunity, network biology, Tumor immune control
Received: 17 Oct 2018;
Accepted: 10 Jan 2019.
Edited by:Lionel Apetoh, Institut National de la Santé et de la Recherche Médicale (INSERM), France
Reviewed by:Giulio C. Spagnoli, Universität Basel, Switzerland
Dr. Kawaljit Kaur, University of California, Los Angeles, United States
Copyright: © 2019 Velazquez-Caldelas, Alcalá-Corona, Espinal-Enríquez and Hernandez-Lemus. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Enrique Hernandez-Lemus, Instituto Nacional de Medicina Genómica (INMEGEN), Computational Genomics, Mexico City, Mexico, email@example.com