Alfred Au

Tumors are stiff and data suggest that the extracellular matrix stiffening that correlates with experimental mammary malignancy drives tumor invasion and metastasis. Nevertheless, the relationship between tissue and extracellular matrix stiffness and human breast cancer progression and aggression remains unclear. We undertook a biophysical and biochemical assessment of stromal-epithelial interactions in noninvasive, invasive and normal adjacent human breast tissue and in breast cancers of increasingly aggressive subtype. Our analysis revealed that human breast cancer transformation is accompanied by an incremental increase in collagen deposition and a progressive linearization and thickening of interstitial collagen. The linearization of collagen was visualized as an overall increase in tissue birefringence and was most striking at the invasive front of the tumor where the stiffness of the stroma and cellular mechanosignaling were the highest. Amongst breast cancer subtypes we found that the stroma at the invasive region of the more aggressive Basal-like and Her2 tumor subtypes was the most heterogeneous and the stiffest when compared to the less aggressive luminal A and B subtypes. Intriguingly, we quantified the greatest number of infiltrating macrophages and the highest level of TGF beta signaling within the cells at the invasive front. We also established that stroma stiffness and the level of cellular TGF beta signaling positively correlated with each other and with the number of infiltrating tumor-activated macrophages, which was highest in the more aggressive tumor subtypes. These findings indicate that human breast cancer progression and aggression, collagen linearization and stromal stiffening are linked and implicate tissue inflammation and TGF beta.

Retrospective clinical studies have used immune-based biomarkers, alone or in combination, to predict survival outcomes for women with breast cancer (BC); however, the limitations inherent to immunohistochemical analyses prevent comprehensive descriptions of leukocytic infiltrates, as well as evaluation of the functional state of leukocytes in BC stroma. To more fully evaluate this complexity, and to gain insight into immune responses after chemotherapy (CTX), we prospectively evaluated tumor and nonadjacent normal breast tissue from women with BC, who either had or had not received neoadjuvant CTX before surgery. Tissues were evaluated by polychromatic flow cytometry in combination with confocal immunofluorescence and immunohistochemical analysis of tissue sections. These studies revealed that activated T lymphocytes predominate in tumor tissue, whereas myeloid lineage cells are more prominant in "normal" breast tissue. Notably, residual tumors from an unselected group of BC patients treated with neoadjuvant CTX contained increased percentages of infiltrating myeloid cells, accompanied by an increased CD8/CD4 T-cell ratio and higher numbers of granzyme B-expressing cells, compared with tumors removed from patients treated primarily by surgery alone. These data provide an initial evaluation of differences in the immune microenvironment of BC compared with nonadjacent normal tissue and reveal the degree to which CTX may alter the complexity and presence of selective subsets of immune cells in tumors previously treated in the neoadjuvant setting.

Neoadjuvant chemotherapy for breast cancer allows individual tumor response to be assessed depending on molecular subtype, and to judge the impact of response to therapy on recurrence-free survival (RFS). The multicenter I-SPY 1 TRIAL evaluated patients with ≥ 3 cm tumors by using early imaging and molecular signatures, with outcomes of pathologic complete response (pCR) and RFS. The current analysis was performed using data from patients who had molecular profiles and did not receive trastuzumab. The various molecular classifiers tested were highly correlated. Categorization of breast cancer by molecular signatures enhanced the ability of pCR to predict improvement in RFS compared to the population as a whole. In multivariate analysis, the molecular signatures that added to the ability of HR and HER2 receptors, clinical stage, and pCR in predicting RFS included 70-gene signature, wound healing signature, p53 mutation signature, and PAM50 risk of recurrence. The low risk signatures were associated with significantly better prognosis, and also identified additional patients with a good prognosis within the no pCR group, primarily in the hormone receptor positive, HER-2 negative subgroup. The I-SPY 1 population is enriched for tumors with a poor prognosis but is still heterogeneous in terms of rates of pCR and RFS. The ability of pCR to predict RFS is better by subset than it is for the whole group. Molecular markers improve prediction of RFS by identifying additional patients with excellent prognosis within the no pCR group.