Development of predictive models for the prognosis of triple-negative breast cancer using multiple transcriptomic analyses

Triple-negative breast cancer (TNBC) is a subtype of breast cancer (BC) and constitutes approximately 15-20% of all BC cases. This subtype has the most aggressive behavior and the worst prognosis. Numerous studies have been conducted over the past several decades to address the lack of clinically available treatment options. In particular, potential markers targeting effective treatment options have been actively studied. However, these efforts were hindered by the complex mechanisms of TNBC, and no study has demonstrated a model with a predictive performance exceeding 0.85. This study developed TNBC prognosis predictive models with a predictive performance exceeding 0.94. Applying the nine selected markers to five independent datasets demonstrated their potential as TNBC-specific prognostic markers. Most of these genes (including GPR61, PZP, IGFL1, and AHCTF1) are associated with overall survival (OS) in patients with TNBC. Based on these results, these nine selected genes may serve as prognostic markers for OS in patients with TNBC.