Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence - Huang, Jin; Zhang, Jian-Lin; Ang, Lin; Li, Ming-Cong; Zhao, Min; Wang, Yao; Wu, Qiang (Frontiers in Endocrinology, 2023)
High relapse rates remain a clinical challenge in the management of breast cancer (BC), with distant recurrence being a major driver of patient deterioration. The 'WGCNA' was utilized to establish co-expression networks. Unsupervised clustering was performed with the R package 'ConsensusCluster Plus'. To further screen the key gene signature of residual cancer burden (RCB), multiple knockdown studies were analyzed with the GPSA database. scRNA-seq analysis was conducted through the TISCH database. Molecular docking processes were conducted using Schrodinger software. Our analysis identified 16 RCB-relevant gene signatures influencing DRFS in BC patients following NAC. We then screened GATA3 as the key gene signature of high RCB index using GPSA analysis. A novel molecular subtyping scheme was developed to divide patients into two clusters (C1 and C2) . Patients in cluster C2 had a poorer DRFS than those in cluster C1 (HR: 4.04; 95% CI: 2.60–6.29; log-rank test p < 0.0001). We established a nomogram based on the N stage, RCB class, and molecular subtyping. The ROC curve for 5-year DRFS showed excellent predictive value (AUC=0.91, 95% CI: 0.95–0.86), with a C-index of 0.85 (95% CI: 0.81–0.90). We also provided a comprehensive review of the EDCs exposures that potentially impact the effectiveness of NAC among BC patients. This study established a molecular classification scheme associated with tumor metabolism and cancer cell senescence to predict RCB and DRFS in BC patients after NAC. Furthermore, GATA3 was identified and validated as a key gene associated with BC recurrence.