LAUSR

Simple Summary We present a meta-analysis of invasive lobular carcinoma (ILC) sequencing data to provide a unified resource for ILC research. A large amount of data has been generated, but remains siloed due to the application of different sequencing approaches and limitations around cohort size and clinical annotation. To enact the goals of precision oncology in the field of lobular breast cancer, a substantive reference point is required, which we present herein. Furthermore, with combined datasets, we were able to define the prognostic significance of relevant clinico-pathology features. Abstract Invasive lobular carcinoma (ILC) is the second most common breast cancer histologic subtype, accounting for approximately 15% of all breast cancers. It is only recently that its unique biology has been assessed in high resolution. Here, we present a meta-analysis of ILC sequencing datasets, to provide a long-awaited ILC-specific resource, and to confirm the prognostic value and strength of association between a number of clinico-pathology features and genomics in this special tumour type. We consider panel (n = 684), whole exome (n = 215) and whole genome sequencing data (n = 48), and review histology of The Cancer Genome Atlas cases to assign grades and determine whether the ILC is of classic type or a variant, such as pleomorphic, prior to performing statistical analyses. We demonstrate evidence of considerable genomic heterogeneity underlying a broadly homogeneous tumour type (typically grade 2, estrogen receptor (ER)-positive); with genomes exhibiting few somatic mutations or structural alterations, genomes with a hypermutator phenotype, and tumours with highly rearranged genomes. We show that while CDH1 (E-cadherin) and PIK3CA mutations do not significantly impact survival, overall survival is significantly poorer for patients with a higher tumour mutation burden; this is also true for grade 3 tumours, and those carrying a somatic TP53 mutation (and these cases were more likely to be ER-negative). Taken together, we have compiled a meta-dataset of ILC with molecular profiling, and our analyses show that the genomic landscape significantly impacts the tumour’s variable natural history and overall survival of ILC patients.