Development of a Cell line Classifier for Precision Subtyping of Triple-Negative Breast Cancer

State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China

^* Corresponding author: haohuang@seu.edu.cn

Abstract

Triple-negative breast cancer (TNBC) exhibits marked clinical diversity and an absence of established targeted therapies, largely driven by heterogeneous tumor phenotypes and transcriptional profiles across subtypes. This biological variability complicates therapeutic strategies and underscores the unmet need for refined molecular classification systems. While molecular insights into TNBC pathogenesis have expanded, clinical applications remain constrained by insufficiently validated stratification tools. To address this gap, we developed an RNA-seq based classifier specifically optimized for TNBC cell lines, designed to enable refined subtype stratification and mechanistic exploration of molecular drivers.