Application of RNAi-induced gene expression profiles for prognostic prediction in breast cancer

Yue Wang, Huazhong University of Science & Technology
Kenneth M. K. Mark, Dartmouth College
Matthew H. Ung, Dartmouth College
Arminja Kettenbach, Dartmouth College
Todd Miller, Dartmouth College
Wei Xu, Huazhong University of Science and Technology
Wenqing Cheng, Huazhong University of Science and Technology
Tian Xia, Huazhong University of Science and Technology
Chao Cheng, Dartmouth College

Abstract

Homologous recombination (HR) is the primary pathway for repairing double-strand DNA breaks implicating in the development of cancer. RNAi-based knockdowns of BRCA1 and RAD51 in this pathway have been performed to investigate the resulting transcriptomic profiles. Here we propose a computational framework to utilize these profiles to calculate a score, named RNA-Interference derived Proliferation Score (RIPS), which reflects cell proliferation ability in individual breast tumors. RIPS is predictive of breast cancer classes, prognosis, genome instability, and neoadjuvant chemosensitivity. This framework directly translates the readout of knockdown experiments into potential clinical applications and generates a robust biomarker in breast cancer.