Invasive lobular carcinoma (ILC) accounts for 10% to 15% of breast cancers in the United States, 80% of which are estrogen receptor (ER)-positive, with an unusual metastatic pattern of spread to sites such as the serosa, meninges, and ovaries, among others. Lobular cancer presents significant challenges in detection and clinical management given its multifocality and multicentricity at presentation. Despite the unique features of ILC, it is often lumped with hormone receptor-positive invasive ductal cancers (IDC); consequently, ILC screening, treatment, and follow-up strategies are largely based on data from IDC. Despite both being treated as ERpositive breast cancer, querying the Cancer Genome Atlas database shows distinctive molecular aberrations in ILC compared with IDC, such as E-cadherin loss (66% vs. 3%), FOXA1 mutations (7% vs. 2%), and GATA3 mutations (5% vs. 20%).Moreover, compared with patients with IDC, patients with ILC are less likely to undergo breast-conserving surgery, with lower rates of complete response following therapy as these tumors are less chemosensitive. Taken together, this suggests that ILC is biologically distinct, which may influence tumorigenesis and therapeutic strategies. Long-term survival and clinical outcomes in patients with ILC are worse than in stage-and grade-matched patients with IDC; therefore, nuanced criteria are needed to better define treatment goals and protocols tailored to ILC's unique biology. This comprehensive review highlights the histologic and clinicopathologic features that distinguish ILC from IDC, with an in-depth discussion of ILC's molecular alterations and biomarkers, clinical trials and treatment strategies, and future targets for therapy. The Oncologist 2021;25:1-11 Implications for Practice: The majority of invasive lobular breast cancers (ILCs) are hormone receptor (HR)-positive and low grade. Clinically, ILC is treated similar to HR-positive invasive ductal cancer (IDC). However, ILC differs distinctly from IDC in its clinicopathologic characteristics and molecular alterations. ILC also differs in response to systemic therapy, with studies showing ILC as less sensitive to chemotherapy. Patients with ILC have worse clinical outcomes with late recurrences. Despite these differences, clinical trials treat HR-positive breast cancers as a single disease, and there is an unmet need for studies addressing the unique challenges faced by patients diagnosed with ILC.

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Mesothelin is a cell surface associated antigen expressed on mesothelial cells and in some malignant neoplasms. Mesothelin-targeted therapies are in phase I/II clinical trials. The clinicopathologic and prognostic significance of mesothelin expression in triple negative breast carcinomas (TNBC) has not been fully assessed. We evaluated the expression of mesothelin and of basal markers in tissue microarrays of 226 TNBC and 88 non-TNBC and assessed the clinicopathologic features of mesothelin-expressing breast carcinomas. Furthermore, we investigated the impact of mesothelin expression on the disease-free and overall survival of patients with TNBC. We found that mesothelin expression is significantly more frequent in TNBC than in non-TNBC (36% vs 16%, respectively; p = 0.0006), and is significantly correlated with immunoreactivity for basal keratins, but not for EGFR. Mesothelin-positive and mesothelin-negative TNBC were not significantly different by patients’ race, tumor size, histologic grade, tumor subtype, lymphovascular invasion and lymph node metastases. Patients with mesothelin-positive TNBC were older than patients with mesothelin-negative TNBC, developed more distant metastases with a shorter interval, and had significantly lower overall and disease-free survival. Based on our results, patients with mesothelin-positive TNBC could benefit from mesothelin-targeted therapies.

BackgroundNipple adenoma is a very uncommon, benign proliferative process of lactiferous ducts of the nipple. Clinically, it often presents as a palpable nipple nodule, a visible nipple skin erosive lesion, and/or with discharge from the surface of the nipple skin, and is primarily seen in middle-aged women. Resultantly, nipple adenoma can clinically mimic the presentation of mammary Paget’s disease of the nipple. The purpose of our current case report is to present a comprehensive review of the available data on nipple adenoma, as well as provide useful information to health care providers (including dermatologists, breast health specialists, and other health care providers) who evaluate patients with dermatologic conditions of the breast skin for appropriately clinically recognizing, diagnosing, and treating patients with nipple adenoma.Case presentationFifty-three year old Caucasian female presented with a one year history of erythema and induration of the skin of the inferior aspect of the right nipple/areolar region. Skin punch biopsies showed subareolar duct papillomatosis. The patient elected to undergo complete surgical excision with right central breast resection. Final histopathologic evaluation confirmed nipple adenoma. The patient is doing well 31 months after her definitive surgical therapy.ConclusionsSince nipple adenoma represents a benign proliferative process of the nipple, complete surgical excision is curative. However, the coexistence of nipple adenoma and ipsilateral or contralateral breast cancer is well reported in the literature. The potential for a direct causal link or association of nipple adenoma and breast cancer cannot be fully excluded.

In pathology, Immunohistochemical staining (IHC) of tissue sections is regularly used to diagnose and grade malignant tumors. Typically, IHC stain interpretation is rendered by a trained pathologist using a manual method, which consists of counting each positively- and negatively-stained cell under a microscope. The manual enumeration suffers from poor reproducibility even in the hands of expert pathologists. To facilitate this process, we propose a novel method to create artificial datasets with the known ground truth which allows us to analyze the recall, precision, accuracy, and intra- and inter-observer variability in a systematic manner, enabling us to compare different computer analysis approaches. Our method employs a conditional Generative Adversarial Network that uses a database of Ki67 stained tissues of breast cancer patients to generate synthetic digital slides. Our experiments show that synthetic images are indistinguishable from real images. Six readers (three pathologists and three image analysts) tried to differentiate 15 real from 15 synthetic images and the probability that the average reader would be able to correctly classify an image as synthetic or real more than 50% of the time was only 44.7%.