A proteogenomic approach for protein-level evidence of genomic variants in cancer cells.

Jeonghun Yeom,Hee-Sung Ahn,Cheolju Lee,Seon-Young Kim,Byungho Lim,Mohammad Humayun Kabir

doi:10.1038/srep35305

Abstract

Variations in protein coding sequence may sometimes play important roles in cancer development. However, since variants may not express into proteins due to various cellular quality control systems, it is important to get protein-level evidence of the genomic variations. We present a proteogenomic strategy getting protein-level evidence of genomic variants, which we call sequential targeted LC-MS/MS based on prediction of peptide pI and Retention time (STaLPIR). Our approach shows improved peptide identification, and has the potential for the unbiased analysis of variant sequence as well as corresponding reference sequence. Integrated analysis of DNA, mRNA and protein suggests that protein expression level of the nonsynonymous variant is regulated either before or after translation, according to influence of the variant on protein function. In conclusion, our data provides an excellent approach getting direct evidence for the expression of variant protein forms from genome sequence data.

Highlights

Variations in protein coding sequence may sometimes play important roles in cancer development
As a proof-of-concept, we present an analysis of nonsynonymous variants at the protein level by using our STaLPIR method on gastric cancer cells
We expected that the lesser heterogeneous properties of cancer cell lines compared to primary tumors might facilitate straightforward interpretation of proteogenomic data

Summary

Introduction

Variations in protein coding sequence may sometimes play important roles in cancer development. We present a proteogenomic strategy getting protein-level evidence of genomic variants, which we call sequential targeted LC-MS/ MS based on prediction of peptide pI and Retention time (STaLPIR). Our data provides an excellent approach getting direct evidence for the expression of variant protein forms from genome sequence data. Proteogenomics provides protein-level evidence of predicted genes and helps to improve genome annotations using integrated information of Exon/RNA sequencing and proteomic data[1–4]. The purpose of the present research is to suggest a new strategy of proteogenomics for getting protein-level evidence of genomic variations. As a proof-of-concept, we present an analysis of nonsynonymous variants at the protein level by using our STaLPIR method on gastric cancer cells. Our results provide significant information for understanding the expression of variant genes from DNA to protein, and lay a foundation for future work to treat mutant proteins that might occur in various cancers

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