Proteogenomic analysis prioritises functional single nucleotide variants in cancer samples.

ABSTRACT: Massively parallel DNA sequencing enables the detection of thousands of germline and somatic single nucleotide variants (SNVs) in cancer samples. The functional analysis of these mutations is often carried out through in silico predictions, with further downstream experimental validation rarely performed. Here, we examine the potential of using mass spectrometry-based proteomics data to further annotate the function of SNVs in cancer samples. RNA-seq and whole genome sequencing (WGS) data from Jurkat cells were used to construct a custom database of single amino acid variant (SAAV) containing peptides and identified over 1,000 such peptides in two Jurkat proteomics datasets. The analysis enabled the detection of a truncated form of splicing regulator YTHDC1 at the protein level. To

SUBMITTER: Ma S 

PROVIDER: S-EPMC5707065 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature