Enabling Variant Proteogenomic Assay Development Through a Peptide Target Selection Pipeline and Web Application

PROTEOMICS, vol. 26, pp. 64–72

Abstract

The quantification of key protein variants can guide precision oncology to enable better identification of driver mutations. Bottom-up assays infer parent protein levels through the quantification of surrogate peptides. Assay methods designed for absolute quantification of protein variants, such as multiple reaction monitoring mass spectrometry (MRM-MS), can achieve quantitation with high precision and specificity. Bottom-up approaches rely on proper selection of suitable surrogate proteogenotypic peptide targets to quantify protein variants of interest. To this end, we developed an R-based bioinformatics pipeline to predict and evaluate variant-specific peptides. The workflow generates variant protein sequences from wild-type sequences and mutations encoded in the Human Genome Variation Society (HGVS) recommended nomenclature, performs in-silico tryptic digestion, and identifies both variant and corresponding wild-type peptides. Each peptide is evaluated by 37 selection criteria to determine suitability as MRM targets. To assess the strictness of these criteria, we applied all protein-altering mutations from the NCI-Genomic Data Commons (GDC) and COSMIC to our pipeline. Of the peptides outputted, 5% satisfied all defined criteria, representing the highest confidence candidates for assay development. We developed a database and web application from NCI-GDC generated peptides for searching, filtering, and downloading. Another web application was developed to provide access to our pipeline.

Authors 5

1. Constantinos Blidjios

   McGill University

   Affiliation as printed

   Department of Oncology McGill University Montreal Quebec Canada

2. Pallab Bhowmick

   Jewish General Hospital

   Affiliation as printed

   Segal Cancer Proteomics Centre Jewish General Hospital Montreal Quebec Canada

3. Vincent R. Richard

   Jewish General Hospital

   Affiliation as printed

   Segal Cancer Proteomics Centre Jewish General Hospital Montreal Quebec Canada

4. Yassene Mohammed Aachen Center for Proteomics and Metabolomics Leiden University Medical Center Leiden The Netherlands

   Leiden University Medical Center · Jewish General Hospital

   Affiliation as printed

   Center For Proteomics and Metabolomics Leiden University Medical Center Leiden the Netherlands

   Segal Cancer Proteomics Centre Jewish General Hospital Montreal Quebec Canada

5. Christoph H. Borchers corresponding

   Jewish General Hospital · McGill University

   Affiliation as printed

   Department of Pathology McGill University Montreal Quebec Canada

   Division of Experimental Medicine McGill University Montreal Quebec Canada

   Gerald Bronfman Department of Oncology Jewish General Hospital Montreal Quebec Canada

   Segal Cancer Proteomics Centre Jewish General Hospital Montreal Quebec Canada