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

Citation data:

Genome medicine, ISSN: 1756-994X, Vol: 8, Issue: 1, Page: 114

Publication Year:
2016
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Repository URL:
https://digitalcommons.dartmouth.edu/facoa/238; https://digitalcommons.dartmouth.edu/facoa/894
PMID:
27788678
DOI:
10.1186/s13073-016-0363-3
PMCID:
PMC5084341
Author(s):
Wang, Yue; Mark, Kenneth . M. K.; Ung, Matthew H; Kettenbach, Arminja; Miller, Todd; Xu, Wei; Cheng, Wenqing Cheng; Xia, Tian; Cheng, Chao
Publisher(s):
Springer Nature
Tags:
Biochemistry, Genetics and Molecular Biology; Medicine; dna-damage; homologous recombination; brca1 promoter; ovarian-cancer; cell-cycle; repair; mutations; brcaness; resistance; rad51; homologous recombination pathway; gene knockdown profiles; cell proliferation; cancer prognosis; neoadjuvant chemotherapy; genomic instability; Genomics; Medicine and Health Sciences; Neoplasms; Genetics; Genetics and Genomics; Life Sciences
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article description
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.