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Angiogenesis is a key step in the initiation and progression of an invasive breast cancer. High microvessel density by morphological characterization predicts metastasis and poor survival in women with invasive breast cancers. However, morphologic characterization is subject to variability and only can evaluate a limited portion of an invasive breast cancer. Consequently, breast Magnetic Resonance Imaging (MRI) is currently being evaluated to assess vascularity. Recently, through the new field of radiomics, dynamic contrast enhanced (DCE)-MRI is being used to evaluate vascular density, vascular morphology, and detection of aggressive breast cancer biology. While DCE-MRI is a highly sensitive tool, there are specific features that limit computational evaluation of blood vessels. These include (1) DCE-MRI evaluates gadolinium contrast and does not directly evaluate biology, (2) the resolution of DCE-MRI is insufficient for imaging small blood vessels, and (3) DCE-MRI images are very difficult to co-register. Here we review computational approaches for detection and analysis of blood vessels in DCE-MRI images and present some of the strategies we have developed for co-registry of DCE-MRI images and early detection of vascularization.

During aging in the human mammary gland, luminal epithelial cells lose lineage fidelity by expressing markers normally expressed in myoepithelial cells. We hypothesize that loss of lineage fidelity is a general manifestation of epithelia that are susceptible to cancer initiation. In the present study, we show that histologically normal breast tissue from younger women who are susceptible to breast cancer, as a result of harboring a germline mutation in BRCA1, BRCA2 or PALB2 genes, exhibits hallmarks of accelerated aging. These include proportionately increased luminal epithelial cells that acquired myoepithelial markers, decreased proportions of myoepithelial cells and a basal differentiation bias or failure of differentiation of cKit+ progenitors. High-risk luminal and myoepithelial cells are transcriptionally enriched for genes of the opposite lineage, inflammatory- and cancer-related pathways. We have identified breast-aging hallmarks that reflect a convergent biology of cancer susceptibility, regardless of the specific underlying genetic or age-dependent risk or the associated breast cancer subtype.

Additional file 1. Supplemental information Supporting materials and methods section, including supplementary Figures S1â S8 and Tables S1â S2.

Additional file 1. Supplemental information Supporting materials and methods section, including supplementary Figures S1â S8 and Tables S1â S2.

A growing number of studies have investigated the role of exercise both during and after a breast cancer diagnosis. Observational data suggests that regular endurance exercise is associated with a 20-50% reduction in cancer-specific mortality in women diagnosed with early stage breast cancer, compared to inactive women; however it is unclear whether there is a differential association across breast cancer subtypes. As a pre-requisite to guide future large phase II/III clinical trials, there is a critical need to confirm the biological plausibility of the exercise association in breast cancer patients as well as elucidate the underlying mechanisms of action via utilization of preclinical models. In the present study we investigated the systemic effects of prescribed aerobic training in cancer patients and the direct impact on breast cancer cell subtype phenotypes. In order to test the in vivo significance, we interrogated aerobic training effects on breast cancer progression and tumor biology using syngeneic breast cancer mouse models. Our results suggest that aerobic training may alter the host availability of pro-inflammatory and growth factor cytokines in patients with solid tumors. Modulation of systemic effectors in breast cancer patients compared to controls causes a differential phenotypic response on breast cancer cell subtypes. In vivo, aerobic training has a differential response on breast tumor progression compared to controls that is mediated by Hif1-α and metabolic reprogramming of breast cancer cells.