Morphological and molecular changes of oestrogen receptor-positive breast cancer following bridging endocrine therapy: a United Kingdom multicentre study.

AIMS: Standard neoadjuvant endocrine therapy (NAET) is used for 6-9 months to downstage hormone-receptor-positive breast cancer. Bridging ET was introduced during the COVID-19 pandemic to delay surgical intervention. There are no data in the literature on the effect of short course therapy on tumour response. We aimed to analyse the effect of bridging ET and validate the previously proposed neoadjuvant ET pathological reporting criteria. METHODS AND RESULTS: This was a multicentre cohort of 256 patients who received bridging ET between March and October 2020. Assessment of paired pre- and post-NAET hormone receptors and HER2 and posttherapy Ki67 expression was done. The median duration of NAET was 45 days. In all, 86% of cases achieved partial pathological response and 9% showed minimal residual disease. Histological response to ET was observed from as early as day 6 posttherapy. Central scarring was noted in 32.8% of cases and lymphocytic infiltrate was seen in 43.4% of cases. Significant changes associated with the duration of ET were observed in tumour grade (21%), with downgrading identified in 12% of tumours (P < 0.001), progesterone receptor (PR) expression with switch to PR-negative status in 26% of cases (P < 0.001), and HER2 status with a switch from HER2-low to HER2-negative status in 32% of cases (P < 0.001). The median patient survival was 475 days, with an overall survival rate of 99.6%. CONCLUSIONS: Changes characteristic of tumour regression and significant changes in PR and HER2 occurred following a short course of NAET. The findings support biomarker testing on pretreatment core biopsies and retesting following therapy.

Mechanosensitive hormone signaling promotes mammary progenitor expansion and breast cancer risk.

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.

A convolutional neural network STIFMap reveals associations between stromal stiffness and EMT in breast cancer.

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.

Immunosuppressive glycoproteins associate with breast tumor fibrosis and aggression.

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.

Derivation of a nuclear heterogeneity image index to grade DCIS.

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.

Characterization of four subtypes in morphologically normal tissue excised proximal and distal to breast cancer.

Widespread mammographic screening programs and improved self-monitoring allow for breast cancer to be detected earlier than ever before. Breast-conserving surgery is a successful treatment for select women. However, up to 40% of women develop local recurrence after surgery despite apparently tumor-free margins. This suggests that morphologically normal breast may harbor early alterations that contribute to increased risk of cancer recurrence. We conducted a comprehensive transcriptomic and proteomic analysis to characterize 57 fresh-frozen tissues from breast cancers and matched histologically normal tissues resected proximal to (<2 cm) and distant from (5-10 cm) the primary tumor, using tissues from cosmetic reduction mammoplasties as baseline. Four distinct transcriptomic subtypes are identified within matched normal tissues: metabolic; immune; matrisome/epithelial-mesenchymal transition, and non-coding enriched. Key components of the subtypes are supported by proteomic and tissue composition analyses. We find that the metabolic subtype is associated with poor prognosis (p < 0.001, HR6.1). Examination of genes representing the metabolic signature identifies several genes able to prognosticate outcome from histologically normal tissues. A subset of these have been reported for their predictive ability in cancer but, to the best of our knowledge, these have not been reported altered in matched normal tissues. This study takes an important first step toward characterizing matched normal tissues resected at pre-defined margins from the primary tumor. Unlocking the predictive potential of unexcised tissue could prove key to driving the realization of personalized medicine for breast cancer patients, allowing for more biologically-driven analyses of tissue margins than morphology alone.

Macrophages induce malignant traits in mammary epithelium via IKKε/TBK1 kinases and the serine biosynthesis pathway.

During obesity, macrophages infiltrate the breast tissue leading to low-grade chronic inflammation, a factor considered responsible for the higher risk of breast cancer associated with obesity. Here, we formally demonstrate that breast epithelial cells acquire malignant properties when exposed to medium conditioned by macrophages derived from human healthy donors. These effects were mediated by the breast cancer oncogene IKKε and its downstream target-the serine biosynthesis pathway as demonstrated by genetic or pharmacological tools. Furthermore, amlexanox, an FDA-approved drug targeting IKKε and its homologue TBK1, delayed in vivo tumour formation in a combined genetic mouse model of breast cancer and high-fat diet-induced obesity/inflammation. Finally, in human breast cancer tissues, we validated the link between inflammation-IKKε and alteration of cellular metabolism. Altogether, we identified a pathway connecting obesity-driven inflammation to breast cancer and a potential therapeutic strategy to reduce the risk of breast cancer associated with obesity.

Lobular Breast Cancer: A Review.

Invasive lobular carcinoma accounts for 5%-15% of all invasive breast cancers, with a marked increase in incidence rates over the past two decades. Distinctive biological hallmarks of invasive lobular carcinoma include the loss of cell adhesion molecule E-cadherin leading to cells with a discohesive morphology, proliferating into single-file strands and estrogen receptor positivity. These key molecular features can make diagnosis difficult, as invasive lobular carcinoma is challenging to detect both physically and with current standard imaging. Treatment of invasive lobular carcinoma strongly favors endocrine therapy due to low chemosensitivity and lower rates of pathological response as a result. This review will summarize the distinct biological and molecular features of invasive lobular carcinoma, focusing on the diagnostic challenges faced and the subsequent surgical and medical management strategies. Prospective therapeutic options will also be explored, highlighting how furthering our understanding of the unique biology of lobular breast carcinoma is essential in guiding and informing the treatment of patients in the future.

Stromal characteristics may hold the key to mammographic density: the evidence to date.

There is strong epidemiological data indicating a role for increased mammographic density (MD) in predisposing to breast cancer, however, the biological mechanisms underlying this phenomenon are less well understood. Recently, studies of human breast tissues have started to characterise the features of mammographically dense breasts, and a number of in-vitro and in-vivo studies have explored the potential mechanisms through which dense breast tissue may exert this tumourigenic risk. This article aims to review both the pathological and biological evidence implicating a key role for the breast stromal compartment in MD, how this may be modified and the clinical significance of these findings. The epidemiological context will be briefly discussed but will not be covered in detail.

Redefining the R1 resection for pancreatic ductal adenocarcinoma: tumour lymph nodal burden and lymph node ratio are the only prognostic factors associated with survival.

INTRODUCTION: The presence of positive nodal disease (LND) and the number of lymph nodes involved (LNB) are known to be significant prognostic markers for resected adenocarcinoma of the pancreas. In addition, the ratio of the number of involved nodes to the number of nodes resected known as the lymph node ratio (LNR) is emerging as an important prognostic marker. The role of the resection margin (RM) as presently defined (R1 ≤ 1 mm) is unclear as results differ based on the dataset. The aim of this study was to assess the impact of nodal disease and a redefined RM on outcome. MATERIAL AND METHODS: Retrospective analysis of pancreatic head resections for adenocarcinomas from 2003-2009. The RM was re-analysed based on tumour clearance and categorized into: histopathological evidence of a tumour; ≤ 0.5 mm, ≤ 1 mm, ≤ 1.5 mm, or ≤ 2.0 mm of the actual surgical resection margin. The impact of histopathological variables on cancer-specific survival (CSS) and disease-free survival (DFS) was analysed. RESULTS: LND, LNB and LNR were independent prognostic markers for CSS (P = 0.048, 0.003, 0.016) but, did not influence DFS. A LNR < 0.143 was associated with a higher CSS [38.16 ± 4.69 versus 20.59 ± 2.20 months, P = 0.0042, hazard ratio (HR) 3.74 (95% confidence interval (CI) 1.52-9.23)]. An R1 RM was not associated with CSS or DFS on multivariate analysis, irrespective of the distance. LNB and LNR maintained independent significance irrespective of the size of the RM. CONCLUSION: LNB and LNR are the only prognostic factors for CSS in patients with pancreatic head adenocarcinoma, but do not predict recurrence. Microscopic RMs does not seem to influence the outcome even when redefined. Further prospective studies are indicated to substantiate these findings.