IRSN-23 Prospective Analyses

PURPOSE: The IRSN-23 model uses DNA microarray analysis of tumor tissue to personalize patients into highly sensitive chemotherapy (Gp-R) or less sensitive (Gp-NR) based on the expression of immune-related genes. This study assessed the reproducibility of the IRSN-23 in prospective independent validation sets and investigated its clinical significance and impact on breast cancer subtype classification. METHODS: Tumour tissues were collected from 146 breast cancer patients undergoing preoperative chemotherapy (paclitaxel-FEC) ± trastuzumab in Osaka University Hospital (OUH). Patients were classified into Gp-R or Gp-NR using IRSN-23, and the model was examined for its ability to predict the pathological complete response (pCR). RESULTS: In the OUH prospective dataset, the pCR rate was significantly higher in the Gp-R group (29·3% (11/41)) than in the Gp-NR group (1·4% (1/71)) not using trastuzumab (P = 1·70E-5). CONCLUSION: This study provides prospective validation of the IRSN-23 in predicting chemotherapy efficacy, demonstrating a high degree of reproducibility. Fresh frozen tumor samples obtained by vacuum-assisted core biopsy from two hundred and sixty three patients were subjected to RNA extraction and hybridization on Affymetrix microarrays.