IRSN-23 Gene Diagnosis Predicts Response to Neoadjuvant Chemotherapy and Refines Breast Cancer Subtype Classification (Prospective Analyses)

Abstract Introduction: This study evaluates the reproducibility of the IRSN-23 model, which classifies patients into highly chemotherapy-sensitive (Gp-R) or less-sensitive (Gp-NR) groups based on immune-related gene expression using DNA microarray analysis, and its impact on breast cancer subtype classification. Methods: Tumor tissues from 146 breast cancer patients receiving preoperative chemotherapy (paclitaxel-FEC) ± trastuzumab at Osaka University Hospital (OUH) were used to classify patients into Gp-R or Gp-NR using IRSN-23. The ability to predict a pathological complete response (pCR) was assessed and the results were validated with independent public datasets (N = 1,282). Results: In the OUH dataset, the pCR rate was significantly higher in the Gp-R group than in the Gp-NR group without trastuzumab (29 versus 1%, P = 1.70E-5). In all validation sets without anti-HER2 therapy, the pCR rate in the Gp-R group was significantly higher than that in the Gp-NR group. The pooled analysis of the validation set showed higher pCR rates in the Gp-R group than in the Gp-NR group, both without (N = 1103, 40 versus 12%, P = 2.02E-26) and with (N = 304, 49 versus 35%, P = 0.017) anti-HER2 therapy. Collaboration analyses of IRSN-23 and OncotypeDx or PAM50 could identify highly chemotherapy-sensitive groups and refine breast cancer subtype classification based on the tumor microenvironment (offensive factor - PAM50 and defensive factor - IRSN-23), and the immune subtype was correlated with a better prognosis after NAC. Conclusions: This study offers prospective analyses of IRSN-23 in predicting chemotherapy efficacy, showing high reproducibility. The findings indicate the clinical value of using IRSN-23 for refining breast cancer subtype classification, with implications for personalized treatment strategies and improved patient outcomes.