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

Area of Science:

• Biochemistry
• Bioinformatics
• Genomics

Background:

• Precision oncology relies on quantifying protein variants to identify driver mutations.
• Bottom-up assays, like multiple reaction monitoring mass spectrometry (MRM-MS), use surrogate peptides for protein quantification.
• Selecting appropriate variant-specific peptides is crucial for accurate protein variant analysis.

Purpose of the Study:

• To develop a bioinformatics pipeline for predicting and evaluating variant-specific peptides for MRM-MS assays.
• To enable precise quantification of protein variants to support precision oncology.

Main Methods:

• Developed an R-based bioinformatics pipeline to generate variant protein sequences from Human Genome Variation Society (HGVS) nomenclature.
• Performed in-silico tryptic digestion to identify variant and wild-type peptides.
• Evaluated peptides using 37 criteria to assess suitability as MRM targets, applying it to NCI-GDC and COSMIC mutation data.

Main Results:

• The pipeline successfully identified variant-specific peptides from protein mutations.
• Only 5% of outputted peptides met all 37 stringent criteria, indicating high confidence targets.
• Developed web applications for accessing the pipeline and a database of NCI-GDC derived peptides.

Conclusions:

• The developed pipeline provides a robust method for selecting high-confidence peptides for MRM-MS assay development.
• This tool enhances the ability to quantify protein variants, supporting precision oncology and driver mutation identification.
• The associated web applications facilitate access to the pipeline and curated peptide data.