Integrated proteogenomic deep sequencing and analytics accurately identify non-canonical peptides in tumor immunopeptidomes

Nature Communications
Chloe ChongMichal Bassani-Sternberg

Abstract

Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides derived from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single-cell transcriptomics, ribosome profiling, and two MS/MS search tools in combination. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides, including an immunogenic peptide derived from an open reading frame downstream of the melanoma stem cell marker gene ABCB5. These findings hold great promise for the discovery of previously unknown tumor antigens for cancer immunotherapy.

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Methods Mentioned

BETA
RNA-Seq
Ribo-Seq
scRNA-Seq
biopsies
exome sequencing
acetylation
footprinting
Assay
PCR

Software Mentioned

R script
Seurat R package
pLabel
RIboseQC
STRING
Apache Spark
cutdapt
Skyline
MixMHCpred
Bioconductor

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