Atlas of Lobular Breast Cancer Models: Challenges and Strategic Directions

Simple Summary: Invasive lobular breast cancer (ILC) is the second most common histological subtype of invasive breast cancer, which is noted to have a unique microscopic appearance. The understanding of ILC biology is advancing through the evolution of various experimental models, with the ultimate aim to discover new therapeutic strategies. In this review, we summarize the critical developments in the modeling of ILC. We provide a comprehensive overview of well-established ILC models and discuss different approaches for modeling the disease. We highlight the potential opportunities, the challenges, and the recent advances that have contributed to a better understanding of ILC and envisage the future of ILC modeling.Invasive lobular carcinoma (ILC) accounts for up to 15% of all breast cancer (BC) cases and responds well to endocrine treatment when estrogen receptor alpha-positive (ER+) yet differs in many biological aspects from other ER+ BC subtypes. Up to 30% of patients with ILC will develop late-onset metastatic disease up to ten years after initial tumor diagnosis and may experience failure of systemic therapy. Unfortunately, preclinical models to study ILC progression and predict the efficacy of novel therapeutics are scarce. Here, we review the current advances in ILC modeling, including cell lines and organotypic models, genetically engineered mouse models, and patient-derived xenografts. We also underscore four critical challenges that can be addressed using ILC models: drug resistance, lobular tumor microenvironment, tumor dormancy, and metastasis. Finally, we highlight the advantages of shared experimental ILC resources and provide essential considerations from the perspective of the European Lobular Breast Cancer Consortium (ELBCC), which is devoted to better understanding and translating the molecular cues that underpin ILC to clinical diagnosis and intervention. This review will guide investigators who are considering the implementation of ILC models in their research programs.