Mutant KRAS Reprograms Luminal Progenitor Differentiation to Establish a Novel Transformation-Competent Mammary Epithelial Cell State

Background/Objectives: Previous studies reported that basal-like breast cancers may originate from luminal progenitors, suggesting that a classification of this malignancy is not strictly indicative of its cellular origin. Reinforcing this notion, we recently provided experimental evidence in genetically engineered models that basal-like and claudin-low mammary tumors, the two most common triple-negative breast cancer (TNBC) types, can evolve from transformed luminal epithelial cells. The primary objective of this study was to define, at the single-cell level, the earliest molecular changes associated with neoplastic transformation prior to the formation of mammary cancer. Methods: We isolated green fluorescent protein (GFP)-labeled mammary epithelial cells from MMTV-Flp FSF-KrasG12D Rosa26FSF-GFP mice and controls without mutant KRAS by fluorescence-activated cell sorting (FACS) and performed particle-templated instant partition sequencing (PIP-seq). Following hierarchical clustering of the single-cell transcriptomes, as well as differential gene expression and gene ontology analyses, we used Slingshot, TSCAN, and Monocle3 to infer developmental trajectories of luminal epithelial cell states. Results: Based on their single-cell transcriptomes, GFP-expressing mammary epithelial cells were predominantly luminal-type and resolved into 11 transcriptionally distinct cellular states organized into six functional groups. Most notably, mutant KRAS induced a novel oncogenic-permissive state with unique molecular features, including cancer-associated metabolic reprogramming, oncogenic pathway activation, and epithelial-to-mesenchymal cell plasticity. Trajectory inference positioned this KRAS-associated state along an alveolar progenitor differentiation path. Conclusions: The collective results provide new insights into the epithelial states associated with early neoplastic transformation and identify signaling and metabolic programs that may present candidate targets for cancer prevention.