Abstract
Immunotherapy is becoming increasingly important in the fight against cancers, using and manipulating the body's immune response to treat tumors. Understanding the immune repertoire-the collection of immunological proteins-of treated and untreated cells is possible at the genomic, but technically difficult at the protein level. Standard protein databases do not include the highly divergent sequences of somatic rearranged immunoglobulin genes, and may lead to miss identifications in a mass spectrometry search. We introduce a novel proteogenomic approach, AbScan, to identify these highly variable antibody peptides, by developing a customized antibody database construction method using RNA-seq reads aligned to immunoglobulin (Ig) genes.AbScan starts by filtering transcript (RNA-seq) reads that match the template for Ig genes. The retained reads are used to construct a repertoire graph using the "split" de Bruijn graph: a graph structure that improves on the standard de Bruijn graph to capture the high diversity of Ig genes in a compact manner. AbScan corrects for sequencing errors, and converts the graph to a format suitable for searching with MS/MS search tools. We used AbScan to create an antibody database from 90 RNA-seq colorectal tumor samples. Next, we used proteogenomic analysis to search MS/MS spectra of matched colorectal samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) against the AbScan generated database. AbScan identified 1,940 distinct antibody peptides. Correlating with previously identified Single Amino-Acid Variants (SAAVs) in the tumor samples, we identified 163 pairs (antibody peptide, SAAV) with significant cooccurrence pattern in the 90 samples. The presence of coexpressed antibody and mutated peptides was correlated with survival time of the individuals. Our results suggest that AbScan (https://github.com/csw407/AbScan.git) is an effective tool for a proteomic exploration of the immune response in cancers.
Highlights
AbScan starts by filtering transcript (RNA-seq) reads that match the template for Ig genes
Analytical Comparison of split” de Bruijn (SdB) and de Bruijn (dB) Graphs—We compared the performance of SdB graphs versus dB graphs using both analytical methods as well as empirical data from simulations
Study—Understanding the immune response to cancer is key to cancer immunotherapy
Summary
AbScan starts by filtering transcript (RNA-seq) reads that match the template for Ig genes. Our initial search of the Clinical Proteomic Tumor Analysis Consortium (CPTAC)1 colorectal tumor samples identified a number of antibody peptide sequences [32]. The SdB graph is used to generate an MS searchable FASTA formatted database, as well as scripts to identify the context of the peptide on the antibody sequence.
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