Benign breast tumors may arise on different immunological backgrounds.

Benign breast tumors are a nonthreatening condition defined as abnormal cell growth within the breast without the ability to invade nearby tissue. However, benign lesions hold valuable biological information that can lead us toward better understanding of tumor biology. In this study, we have used two pathway analysis algorithms, Pathifier and gene set variation analysis (GSVA), to identify biological differences between normal breast tissue, benign tumors and malignant tumors in our clinical dataset. Our results revealed that one-third of all pathways that were significantly different between benign and malignant tumors were immune-related pathways, and 227 of them were validated by both methods and in the METABRIC dataset. Furthermore, five of these pathways (all including genes involved in cytokine and interferon signaling) were related to overall survival in cancer patients in both datasets. The cellular moieties that contribute to immune differences in malignant and benign tumors were analyzed using the deconvolution tool, CIBERSORT. The results showed that levels of some immune cells were specifically higher in benign than in malignant tumors, and this was especially the case for resting dendritic cells and follicular T-helper cells. Understanding the distinct immune profiles of benign and malignant breast tumors may aid in developing noninvasive diagnostic methods to differentiate between them in the future.

Age, estrogen, and immune response in breast adenocarcinoma and adjacent normal tissue.

Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. There is a complex relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors. While low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. To characterize the impact of these factors on tumors and the tumor microenvironment, we measured gene expression in 195 breast adenocarcinomas and matched adjacent normal breast tissue samples collected at Akershus University Hospital (AHUS). Age and Body Mass Index (BMI) were independently associated with inflammation in adjacent normal tissue but not tumors. Estrogen Receptor (ER)-negative tumors had elevated macrophage expression compared with matched normal tissue, but ER-positive tumors showed an unexpected decrease in macrophage expression. We found an inverse relationship between the increase in tumor estrogen pathway expression compared with adjacent normal tissue and tumor macrophage score. We validated this finding in 126 breast tumor-normal pairs from the previously published METABRIC cohort. We developed a novel statistic, the Rewiring Coefficient, to quantify the rewiring of gene co-expression networks at the level of individual genes. Differential correlation analysis demonstrated distinct pathways were rewired during tumorigenesis. Our data support an immune suppressive effect of high doses of estrogen signaling in breast tumor microenvironment, suggesting that this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors.