neoepiscope improves neoepitope prediction with multivariant phasing

MOTIVATION

The vast majority of tools for neoepitope prediction from DNA sequencing of complementary tumor and normal patient samples do not consider germline context or the potential for the co-occurrence of two or more somatic variants on the same mRNA transcript. Without consideration of these phenomena, existing approaches are likely to produce both false-positive and false-negative results, resulting in an inaccurate and incomplete picture of the cancer neoepitope landscape. We developed neoepiscope chiefly to address this issue for single nucleotide variants (SNVs) and insertions/deletions (indels).

RESULTS

Herein, we illustrate how germline and somatic variant phasing affects neoepitope prediction across multiple datasets. We estimate that up to ∼5% of neoepitopes arising from SNVs and indels may require variant phasing for their accurate assessment. neoepiscope is performant, flexible and supports several major histocompatibility complex binding affinity prediction tools.

AVAILABILITY AND IMPLEMENTATION

neoepiscope is available on GitHub at https://github.com/pdxgx/neoepiscope under the MIT license. Scripts for reproducing results described in the text are available at https://github.com/pdxgx/neoepiscope-paper under the MIT license. Additional data from this study, including summaries of variant phasing incidence and benchmarking wallclock times, are available in Supplementary Files 1, 2 and 3. Supplementary File 1 contains Supplementary Table 1, Supplementary Figures 1 and 2, and descriptions of Supplementary Tables 2-8. Supplementary File 2 contains Supplementary Tables 2-6 and 8. Supplementary File 3 contains Supplementary Table 7. Raw sequencing data used for the analyses in this manuscript are available from the Sequence Read Archive under accessions PRJNA278450, PRJNA312948, PRJNA307199, PRJNA343789, PRJNA357321, PRJNA293912, PRJNA369259, PRJNA305077, PRJNA306070, PRJNA82745 and PRJNA324705; from the European Genome-phenome Archive under accessions EGAD00001004352 and EGAD00001002731; and by direct request to the authors.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1-3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10-18.

Population-level distribution and putative immunogenicity of cancer neoepitopes

Background

Tumor neoantigens are drivers of cancer immunotherapy response; however, current prediction tools produce many candidates requiring further prioritization. Additional filtration criteria and population-level understanding may assist with prioritization. Herein, we show neoepitope immunogenicity is related to measures of peptide novelty and report population-level behavior of these and other metrics.

Methods

We propose four peptide novelty metrics to refine predicted neoantigenicity: tumor vs. paired normal peptide binding affinity difference, tumor vs. paired normal peptide sequence similarity, tumor vs. closest human peptide sequence similarity, and tumor vs. closest microbial peptide sequence similarity. We apply these metrics to neoepitopes predicted from somatic missense mutations in The Cancer Genome Atlas (TCGA) and a cohort of melanoma patients, and to a group of peptides with neoepitope-specific immune response data using an extension of pVAC-Seq (Hundal et al., pVAC-Seq: a genome-guided in silico approach to identifying tumor neoantigens. Genome Med 8:11, 2016).

Results

We show neoepitope burden varies across TCGA diseases and HLA alleles, with surprisingly low repetition of neoepitope sequences across patients or neoepitope preferences among sets of HLA alleles. Only 20.3% of predicted neoepitopes across TCGA patients displayed novel binding change based on our binding affinity difference criteria. Similarity of amino acid sequence was typically high between paired tumor-normal epitopes, but in 24.6% of cases, neoepitopes were more similar to other human peptides, or bacterial (56.8% of cases) or viral peptides (15.5% of cases), than their paired normal counterparts. Applied to peptides with neoepitope-specific immune response, a linear model incorporating neoepitope binding affinity, protein sequence similarity between neoepitopes and their closest viral peptides, and paired binding affinity difference was able to predict immunogenicity (AUROC = 0.66).

Conclusions

Our proposed prioritization criteria emphasize neoepitope novelty and refine patient neoepitope predictions for focus on biologically meaningful candidate neoantigens. We have demonstrated that neoepitopes should be considered not only with respect to their paired normal epitope, but to the entire human proteome, and bacterial and viral peptides, with potential implications for neoepitope immunogenicity and personalized vaccines for cancer treatment. We conclude that putative neoantigens are highly variable across individuals as a function of cancer genetics and personalized HLA repertoire, while the overall behavior of filtration criteria reflects predictable patterns.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4325-6) contains supplementary material, which is available to authorized users.

Evidence of a broad histamine footprint on the human exercise transcriptome

KEY POINTS

Histamine is a primordial signalling molecule, capable of activating cells in an autocrine or paracrine fashion via specific cell surface receptors, in a variety of pathways that probably predate its more recent role in innate and adaptive immunity. Although histamine is normally associated with pathological conditions or allergic and anaphylactic reactions, it may contribute beneficially to the normal changes that occur within skeletal muscle during the recovery from exercise. We show that the human response to exercise includes an altered expression of thousands of protein-coding genes, and much of this response appears to be driven by histamine. Histamine may be an important molecular transducer contributing to many of the adaptations that accompany chronic exercise training.

ABSTRACT

Histamine is a primordial signalling molecule, capable of activating cells in an autocrine or paracrine fashion via specific cell surface receptors. In humans, aerobic exercise is followed by a post-exercise activation of histamine H1 and H2 receptors localized to the previously exercised muscle. This could trigger a broad range of cellular adaptations in response to exercise. Thus, we exploited RNA sequencing to explore the effects of H1 and H2 receptor blockade on the exercise transcriptome in human skeletal muscle tissue harvested from the vastus lateralis. We found that exercise exerts a profound influence on the human transcriptome, causing the differential expression of more than 3000 protein-coding genes. The influence of histamine blockade post-exercise was notable for 795 genes that were differentially expressed between the control and blockade condition, which represents >25% of the number responding to exercise. The broad histamine footprint on the human exercise transcriptome crosses many cellular functions, including inflammation, vascular function, metabolism, and cellular maintenance.

midlife crisis encodes a conserved zinc-finger protein required to maintain neuronal differentiation in Drosophila

Stem cells generate progeny that undergo terminal differentiation. The initiation and maintenance of the differentiated status is crucial for tissue development, function and homeostasis. Drosophila neural stem cells (neuroblasts) are a model for stem cell self-renewal and differentiation; they divide asymmetrically to self-renew and generate the neurons and glia of the CNS. Here we report the identification of midlife crisis (mdlc; CG4973) as a gene required for the maintenance of neuronal differentiation and for neuroblast proliferation in Drosophila. mdlc encodes a ubiquitously expressed zinc-finger-containing protein with conserved orthologs from yeast to humans that are reported to have a role in RNA splicing. Using clonal analysis, we demonstrate that mdlc mutant neurons initiate but fail to complete differentiation, as judged by the loss of the pro-differentiation transcription factor Prospero, followed by derepression of the neuroblast factors Deadpan, Asense and Cyclin E. RNA-seq shows that loss of Mdlc decreases pros transcript levels and results in aberrant pros splicing. Importantly, misexpression of the full-length human ortholog, RNF113A, completely rescues all CNS defects in mdlc mutants. We conclude that Mdlc plays an essential role in maintaining neuronal differentiation, raising the possibility that RNF113A regulates neuronal differentiation in the human CNS.