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Applications of RNA Indexes for Precision Oncology in Breast Cancer
Author(s) -
Liming Ma,
Zirui Liang,
Hui Zhou,
LiangHu Qu
Publication year - 2018
Publication title -
genomics proteomics and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.114
H-Index - 49
eISSN - 2210-3244
pISSN - 1672-0229
DOI - 10.1016/j.gpb.2018.03.002
Subject(s) - breast cancer , microrna , transcriptome , computational biology , rna interference , precision medicine , cancer , genomics , subtyping , triple negative breast cancer , bioinformatics , biology , precision oncology , rna , oncology , medicine , computer science , gene , gene expression , genetics , genome , programming language
Precision oncology aims to offer the most appropriate treatments to cancer patients mainly based on their individual genetic information. Genomics has provided numerous valuable data on driver mutations and risk loci; however, it remains a formidable challenge to transform these data into therapeutic agents. Transcriptomics describes the multifarious expression patterns of both mRNAs and non-coding RNAs (ncRNAs), which facilitates the deciphering of genomic codes. In this review, we take breast cancer as an example to demonstrate the applications of these rich RNA resources in precision medicine exploration. These include the use of mRNA profiles in triple-negative breast cancer (TNBC) subtyping to inform corresponding candidate targeted therapies; current advancements and achievements of high-throughput RNA interference (RNAi) screening technologies in breast cancer; and microRNAs as functional signatures for defining cell identities and regulating the biological activities of breast cancer cells. We summarize the benefits of transcriptomic analyses in breast cancer management and propose that unscrambling the core signaling networks of cancer may be an important task of multiple-omic data integration for precision oncology.

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