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.

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.

Dose-Dependent Regulation of Alternative Splicing by MBNL Proteins Reveals Biomarkers for Myotonic Dystrophy.

Alternative splicing is a regulated process that results in expression of specific mRNA and protein isoforms. Alternative splicing factors determine the relative abundance of each isoform. Here we focus on MBNL1, a splicing factor misregulated in the disease myotonic dystrophy. By altering the concentration of MBNL1 in cells across a broad dynamic range, we show that different splicing events require different amounts of MBNL1 for half-maximal response, and respond more or less steeply to MBNL1. Motifs around MBNL1 exon 5 were studied to assess how cis-elements mediate the MBNL1 dose-dependent splicing response. A framework was developed to estimate MBNL concentration using splicing responses alone, validated in the cell-based model, and applied to myotonic dystrophy patient muscle. Using this framework, we evaluated the ability of individual and combinations of splicing events to predict functional MBNL concentration in human biopsies, as well as their performance as biomarkers to assay mild, moderate, and severe cases of DM.

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.

Actinomycin D Specifically Reduces Expanded CUG Repeat RNA in Myotonic Dystrophy Models.

Myotonic dystrophy type 1 (DM1) is an inherited disease characterized by the inability to relax contracted muscles. Affected individuals carry large CTG expansions that are toxic when transcribed. One possible treatment approach is to reduce or eliminate transcription of CTG repeats. Actinomycin D (ActD) is a potent transcription inhibitor and FDA-approved chemotherapeutic that binds GC-rich DNA with high affinity. Here, we report that ActD decreased CUG transcript levels in a dose-dependent manner in DM1 cell and mouse models at significantly lower concentrations (nanomolar) compared to its use as a general transcription inhibitor or chemotherapeutic. ActD also significantly reversed DM1-associated splicing defects in a DM1 mouse model, and did so within the currently approved human treatment range. RNA-seq analyses showed that low concentrations of ActD did not globally inhibit transcription in a DM1 mouse model. These results indicate that transcription inhibition of CTG expansions is a promising treatment approach for DM1.

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.