Pan-cancer analysis of expressed somatic nucleotide variants in long intergenic non-coding RNA

Travers Ching^1,2, Lana X. Garmire^1,2

¹Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at Manoa
²Epidemiology Program, University of Hawaii Cancer Center

Pacific Symposium on Biocomputing 23:512-523(2018)

© 2018 World Scientific
Open Access chapter published by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution (CC BY) 4.0 License.

Abstract

Long intergenic non-coding RNAs have been shown to play important roles in cancer. However, because lincRNAs are a relatively new class of RNAs compared to protein-coding mRNAs, the mutational landscape of lincRNAs has not been as extensively studied. Here we characterize expressed somatic nucleotide variants within lincRNAs using 12 cancer RNA-Seq datasets in TCGA. We build machine-learning models to discriminate somatic variants from germline variants within lincRNA regions (AUC 0.987). We build another model to differentiate lincRNA somatic mutations from background regions (AUC 0.72) and find several molecular features that are strongly associated with lincRNA mutations, including copy number variation, conservation, substitution type and histone marker features.