A transcriptional ILCness score reveals lobular-like biology and clinical behavior beyond CDH1 mutation status.

Abstract

Invasive lobular carcinoma (ILC) is a distinct histological subtype of breast cancer. However, its molecular basis remains unclear. Although loss-of-function alterations in CDH1 are considered a defining genetic event, substantial biological heterogeneity persists, which cannot be explained by mutation status or histology alone. To address this limitation, we developed continuous transcriptional framework called the ILCness score to quantitatively capture lobular-like tumor biology. Using a rigorously constrained principal component-based approach trained in the METABRIC cohort and fixed without retraining, we enabled the reproducible application of the model across independent datasets and expression platforms. Global transcriptomic analyses demonstrated that invasive ductal carcinoma (IDC) and ILC did not form discrete expression clusters but were distributed along a continuous molecular spectrum. ILCness faithfully captured this continuum, with tumors of mixed histology occupying intermediate positions. Importantly, lobular-like transcriptional programs quantified by ILCness were not redundant with CDH1 mutation status. Across cohorts, higher ILCness was associated with coordinated biological programs, including reduced DNA repair and E2F target activity, as well as context-dependent modulation of epithelial-mesenchymal transition. Within histologically defined IDC, ILCness delineated biologically and clinically distinct subgroups independently of CDH1 mutation status, with divergent survival outcomes and therapeutic response patterns. These findings establish lobular-like breast cancer as a continuous transcriptional state rather than as a discrete entity defined by histology or single-gene alterations. The ILCness score provides a scalable RNA-based framework for integrating molecular heterogeneity with tumor biology and clinical behavior.