Evolutionary divergence of HLA class I genotype impacts efficacy of cancer immunotherapy

Cytotoxic T cells are of central importance in the immune system's response to disease. They recognize defective cells by binding to peptides presented on the cell surface by MHC class I molecules. Peptide binding to MHC molecules is the single most selective step in the Ag-presentation pathway. Therefore, in the quest for T cell epitopes, the prediction of peptide binding to MHC molecules has attracted widespread attention. In the past, predictors of peptide-MHC interactions have primarily been trained on binding affinity data. Recently, an increasing number of MHC-presented peptides identified by mass spectrometry have been reported containing information about peptide-processing steps in the presentation pathway and the length distribution of naturally presented peptides. In this article, we present NetMHCpan-4.0, a method trained on binding affinity and eluted ligand data leveraging the information from both data types. Large-scale benchmarking of the method demonstrates an increase in predictive performance compared with state-of-the-art methods when it comes to identification of naturally processed ligands, cancer neoantigens, and T cell epitopes.

The interplay between an evolving cancer and the dynamic immune-microenvironment remains unclear. Here, we analyze 258 regions from 88 early-stage untreated non-small cell lung cancers (NSCLCs) using RNAseq and pathology tumor infiltrating lymphocyte estimates. The immune-microenvironment was variable both between and within patients’ tumors. Diverse immune selection pressures were associated with different mechanisms of neoantigen presentation dysfunction restricted to distinct microenvironments. Sparsely infiltrated tumors exhibited evidence for historical immunoediting, with a waning of neoantigen-editing during tumor evolution, or copy number loss of historically clonal neoantigens. Immune-infiltrated tumor regions exhibited ongoing immunoediting, with either HLA LOH or depletion of expressed neoantigens. Promoter hypermethylation of genes harboring neoantigens was identified as an epigenetic mechanism of immunoediting. Our results suggest the immune-microenvironment exerts a strong selection pressure in early stage, untreated NSCLCs, producing multiple routes to immune evasion, which are clinically relevant, forecasting poor disease-free survival in multivariate analysis.

The sequencing of tumors and their matched normals is frequently used to study the genetic composition of cancer. Despite this fact, there remains a dearth of available software tools designed to compare sequences in pairs of samples and identify sites that are likely to be unique to one sample. In this article, we describe the mathematical basis of our SomaticSniper software for comparing tumor and normal pairs. We estimate its sensitivity and precision, and present several common sources of error resulting in miscalls. Binaries are freely available for download at http://gmt.genome.wustl.edu/somatic-sniper/current/, implemented in C and supported on Linux and Mac OS X. delarson@wustl.edu; lding@wustl.edu Supplementary data are available at Bioinformatics online.