Abstract 1937: Development of microRNA-based prediction model of Trastuzumab treatment response for HER2-positive breast cancer using FFPE specimens.

Abstract

Abstract [Background and Aim] Although Trastuzumab has been used for HER2(+) breast cancer, the treatment response of Trastuzumab therapy depends on unknown mechanisms among individual cases. In order to avoid unnecessary adverse events and to lighten financial burden, pre-treatment prediction of trastuzumab treatment response would be beneficial for patients. Thus, in this study, we develop a prediction algorithm using microRNA expression profile using formalin-fixed paraffin-embedded (FFPE) specimens of HER2(+) breast cancer. [Materials and Methods] Eighty-three breast cancer patients who underwent trastuzumab-chemo combined therapy before operations were enrolled with written informed consent. FFPE specimens of pre-treatment core needle biopsy samples were collected, and regions containing cancer and adjacent stromal cells were laser-microdissected. Total RNA samples extracted from the microdissected specimens were subjected for microRNA microarray (3D-Gene®, Toray, Japan) analysis. Among these 83 patients, 39 cases had pCR (definition: complete response in IDC regions regardless presence of DCIS without lymph node metastasis), and the other 44 cases did not. According to the pCR/non-pCR information, we develop a prediction model using 35 signature microRNAs by a SVM technique. Prediction accuracy assessed by Leave-one-out validation was AUROC=0.889. The 35 signature microRNAs for trastuzumab treatment response included 7 out of 8 let-7 family members and miR-125a-5p/b-5p, which were downregulated in pCR specimens. [Conclusion] microRNA profile could predict treatment response of trastuzumab-chemo combined therapy for HER2(+) breast cancer, and the developed prediction algorithm might be a useful tool for clinical decision making. Prediction Accuracy Outcome: non-pCR Outcome: pCR total Prediction: non-sensitive 35 6 41 Prediction: sensitive 9 33 42 total 44 39 83 Citation Format: Fumiaki Sato, Zhipeng Wang, Takayuki Ueno, Akira Myomoto, Satoko Takizawa, Feng Ling Pu, Norikazu Masuda, Yoshiki Mikami, Yoshiki Mikami, Kazuharu Shimizu, Shigehira Saji, Masakazu Toi. Development of microRNA-based prediction model of Trastuzumab treatment response for HER2-positive breast cancer using FFPE specimens. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1937. doi:10.1158/1538-7445.AM2013-1937