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Tissue stem-progenitor cell frequency has been implicated in tumor risk and progression, but tissue-specific factors linking these associations remain ill-defined. We observed that stiff breast tissue from women with high mammographic density, who exhibit increased lifetime risk for breast cancer, associates with abundant stem-progenitor epithelial cells. Using genetically engineered mouse models of elevated integrin mechanosignaling and collagen density, syngeneic manipulations, and spheroid models, we determined that a stiff matrix and high mechanosignaling increase mammary epithelial stem-progenitor cell frequency and enhance tumor initiation in vivo. Augmented tissue mechanics expand stemness by potentiating extracellular signal-related kinase (ERK) activity to foster progesterone receptor-dependent RANK signaling. Consistently, we detected elevated phosphorylated ERK and progesterone receptors and increased levels of RANK signaling in stiff breast tissue from women with high mammographic density. The findings link fibrosis and mechanosignaling to stem-progenitor cell frequency and breast cancer risk and causally implicate epidermal growth factor receptor-ERK-dependent hormone signaling in this phenotype.

Intratumor heterogeneity associates with poor patient outcome. Stromal stiffening also accompanies cancer. Whether cancers demonstrate stiffness heterogeneity, and if this is linked to tumor cell heterogeneity remains unclear. We developed a method to measure the stiffness heterogeneity in human breast tumors that quantifies the stromal stiffness each cell experiences and permits visual registration with biomarkers of tumor progression. We present Spatially Transformed Inferential Force Map (STIFMap) which exploits computer vision to precisely automate atomic force microscopy (AFM) indentation combined with a trained convolutional neural network to predict stromal elasticity with micron-resolution using collagen morphological features and ground truth AFM data. We registered high-elasticity regions within human breast tumors colocalizing with markers of mechanical activation and an epithelial-to-mesenchymal transition (EMT). The findings highlight the utility of STIFMap to assess mechanical heterogeneity of human tumors across length scales from single cells to whole tissues and implicates stromal stiffness in tumor cell heterogeneity.

Tumors feature elevated sialoglycoprotein content. Sialoglycoproteins promote tumor progression and are linked to immune suppression via the sialic acid-Siglec axis. Understanding factors that increase sialoglycoprotein biosynthesis in tumors could identify approaches to improve patient response to immunotherapy. We quantified higher levels of sialoglycoproteins in the fibrotic regions within human breast tumor tissues. Human breast tumor subtypes, which are more fibrotic, similarly featured increased sialoglycoprotein content. Further analysis revealed the breast cancer cells as the primary cell type synthesizing and secreting the tumor tissue sialoglycoproteins and confirmed that the more aggressive, fibrotic breast cancer subtypes expressed the highest levels of sialoglycoprotein biosynthetic genes. The more aggressive breast cancer subtypes also featured greater infiltration of immunosuppressive SIGLEC7, SIGLEC9, and SIGLEC10-pos myeloid cells, indicating that triple-negative breast tumors had higher expression of both immunosuppressive Siglec receptors and their cognate ligands. The findings link sialoglycoprotein biosynthesis and secretion to tumor fibrosis and aggression in human breast tumors. The data suggest targeting of the sialic acid-Siglec axis may comprise an attractive therapeutic target particularly for the more aggressive HER2+ and triple-negative breast cancer subtypes.

Abnormalities in cell nuclear morphology are a hallmark of cancer. Histological assessment of cell nuclear morphology is frequently used by pathologists to grade ductal carcinoma in situ (DCIS). Objective methods that allow standardization and reproducibility of cell nuclear morphology assessment have potential to improve the criteria needed to predict DCIS progression and recurrence. Aggressive cancers are highly heterogeneous. We asked whether cell nuclear morphology heterogeneity could be incorporated into a metric to classify DCIS. We developed a nuclear heterogeneity image index to objectively, and quantitatively grade DCIS. A whole-tissue cell nuclear morphological analysis, that classified tumors by the worst ten percent in a duct-by-duct manner, identified nuclear size ranges associated with each DCIS grade. Digital image analysis further revealed increasing heterogeneity within ducts or between ducts in tissues of worsening DCIS grade. The findings illustrate how digital image analysis comprises a supplemental tool for pathologists to objectively classify DCIS and in the future, may provide a method to predict patient outcome through analysis of nuclear heterogeneity.

Oestrogen receptor (ER)-positive breast cancer (BC) is generally well responsive to endocrine therapy. Neoadjuvant endocrine therapy (NAET) is increasingly being used for downstaging ER-positive tumours. This study aims to analyse the effect of NAET on a well-characterised cohort of ER-positive BC with particular emphasis on receptor expression. This is a retrospective United Kingdom (UK) multicentre study of 391 patients who received NAET between October 2012 and October 2020. Detailed analyses of the paired pre- and post-NAET morphological changes and hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression were performed. The median duration of NAET was 86 days, with median survival and overall survival rates of 380 days and 93.4%, respectively. A total of 90.3% of cases achieved a pathological partial response, with a significantly higher rate of response in the HER2-low cancers. Following NAET, BC displayed some pathological changes involving the tumour stroma including central scarring and an increase in tumour infiltrating lymphocytes (TILs) and tumour cell morphology. Significant changes associated with the duration of NAET were observed in tumour grade (30.6% of cases), with downgrading identified in 19.3% of tumours (p < 0.001). The conversion of ER status from positive to low or negative was insignificant. The conversion of progesterone receptor (PR) and HER2 status to negative status was observed in 31.3% and 38.1% of cases, respectively (p < 0.001). HER2-low breast cancer decreased from 63% to 37% following NAET in the paired samples. Significant morphological and biomarker changes involving PR and HER2 expression occurred following NAET. The findings support biomarker testing on pre-treatment core biopsies and post-treatment residual carcinoma. [ABSTRACT FROM AUTHOR]