Temporal genomic analysis of melanoma rejection identifies regulators of tumor immune evasion.

Decreased intra-tumor heterogeneity (ITH) correlates with increased patient survival and immunotherapy response. However, even highly homogenous tumors may display variability in their aggressiveness, and how immunologic-factors impinge on their aggressiveness remains understudied. Here we studied the mechanisms responsible for the immune-escape of murine tumors with low ITH. We compared the temporal growth of homogeneous, genetically-similar single-cell clones that are rejected vs. those that are not-rejected after transplantation in-vivo using single-cell RNA sequencing and immunophenotyping. Non-rejected clones showed high infiltration of tumor-associated-macrophages (TAMs), lower T-cell infiltration, and increased T-cell exhaustion compared to rejected clones. Comparative analysis of rejection-associated gene expression programs, combined with in-vivo CRISPR knockout screens of candidate mediators, identified Mif (macrophage migration inhibitory factor) as a regulator of immune rejection. Mif knockout led to smaller tumors and reversed non-rejection-associated immune composition, particularly, leading to the reduction of immunosuppressive macrophage infiltration. Finally, we validated these results in melanoma patient data.

Large-Scale Immunopeptidome Analysis Reveals Recurrent Posttranslational Splicing of Cancer- and Immune-Associated Genes.

Posttranslational spliced peptides (PTSPs) are a unique class of peptides that have been found to be presented by HLA class-I molecules in cancer. Thus far, no consensus has been reached on the proportion of PTSPs in the immunopeptidome, with estimates ranging from 2% to as high as 45% and stirring significant debate. Furthermore, the role of the HLA class-II pathway in PTSP presentation has been studied only in diabetes. Here, we exploit our large-scale cancer peptidomics database and our newly devised pipeline for filtering spliced peptide predictions to identify recurring spliced peptides, both for HLA class-I and class-II complexes. Our results indicate that HLA class-I-spliced peptides account for a low percentage of the immunopeptidome (less than 3.1%) yet are larger in number relative to other types of identified aberrant peptides. Therefore, spliced peptides significantly contribute to the repertoire of presented peptides in cancer cells. In addition, we identified HLA class-II-bound spliced peptides, but to a lower extent (less than 0.5%). The identified spliced peptides include cancer- and immune-associated genes, such as the MITF oncogene, DAPK1 tumor suppressor, and HLA-E, which were validated using synthetic peptides. The potential immunogenicity of the DAPK1- and HLA-E-derived PTSPs was also confirmed. In addition, a reanalysis of our published mouse single-cell clone immunopeptidome dataset showed that most of the spliced peptides were found repeatedly in a large number of the single-cell clones. Establishing a novel search-scheme for the discovery and evaluation of recurring PTSPs among cancer patients may assist in identifying potential novel targets for immunotherapy.

Combined presentation and immunogenicity analysis reveals a recurrent RAS.Q61K neoantigen in melanoma.

Neoantigens are now recognized drivers of the antitumor immune response. Recurrent neoantigens, shared among groups of patients, have thus become increasingly coveted therapeutic targets. Here, we report on the data-driven identification of a robustly presented, immunogenic neoantigen that is derived from the combination of HLA-A*01:01 and RAS.Q61K. Analysis of large patient cohorts indicated that this combination applies to 3% of patients with melanoma. Using HLA peptidomics, we were able to demonstrate robust endogenous presentation of the neoantigen in 10 tumor samples. We detected specific reactivity to the mutated peptide within tumor-infiltrating lymphocytes (TILs) from 2 unrelated patients, thus confirming its natural immunogenicity. We further investigated the neoantigen-specific clones and their T cell receptors (TCRs) via a combination of TCR sequencing, TCR overexpression, functional assays, and single-cell transcriptomics. Our analysis revealed a diverse repertoire of neoantigen-specific clones with both intra- and interpatient TCR similarities. Moreover, 1 dominant clone proved to cross-react with the highly prevalent RAS.Q61R variant. Transcriptome analysis revealed a high association of TCR clones with specific T cell phenotypes in response to cognate melanoma, with neoantigen-specific cells showing an activated and dysfunctional phenotype. Identification of recurrent neoantigens and their reactive TCRs can promote "off-the-shelf" precision immunotherapies, alleviating limitations of personalized treatments.

Identification of bacteria-derived HLA-bound peptides in melanoma.

A variety of species of bacteria are known to colonize human tumours1-11, proliferate within them and modulate immune function, which ultimately affects the survival of patients with cancer and their responses to treatment12-14. However, it is not known whether antigens derived from intracellular bacteria are presented by the human leukocyte antigen class I and II (HLA-I and HLA-II, respectively) molecules of tumour cells, or whether such antigens elicit a tumour-infiltrating T cell immune response. Here we used 16S rRNA gene sequencing and HLA peptidomics to identify a peptide repertoire derived from intracellular bacteria that was presented on HLA-I and HLA-II molecules in melanoma tumours. Our analysis of 17 melanoma metastases (derived from 9 patients) revealed 248 and 35 unique HLA-I and HLA-II peptides, respectively, that were derived from 41 species of bacteria. We identified recurrent bacterial peptides in tumours from different patients, as well as in different tumours from the same patient. Our study reveals that peptides derived from intracellular bacteria can be presented by tumour cells and elicit immune reactivity, and thus provides insight into a mechanism by which bacteria influence activation of the immune system and responses to therapy.

Anti-tumour immunity induces aberrant peptide presentation in melanoma.

Extensive tumour inflammation, which is reflected by high levels of infiltrating T cells and interferon-γ (IFNγ) signalling, improves the response of patients with melanoma to checkpoint immunotherapy1,2. Many tumours, however, escape by activating cellular pathways that lead to immunosuppression. One such mechanism is the production of tryptophan metabolites along the kynurenine pathway by the enzyme indoleamine 2,3-dioxygenase 1 (IDO1), which is induced by IFNγ3-5. However, clinical trials using inhibition of IDO1 in combination with blockade of the PD1 pathway in patients with melanoma did not improve the efficacy of treatment compared to PD1 pathway blockade alone6,7, pointing to an incomplete understanding of the role of IDO1 and the consequent degradation of tryptophan in mRNA translation and cancer progression. Here we used ribosome profiling in melanoma cells to investigate the effects of prolonged IFNγ treatment on mRNA translation. Notably, we observed accumulations of ribosomes downstream of tryptophan codons, along with their expected stalling at the tryptophan codon. This suggested that ribosomes bypass tryptophan codons in the absence of tryptophan. A detailed examination of these tryptophan-associated accumulations of ribosomes-which we term 'W-bumps'-showed that they were characterized by ribosomal frameshifting events. Consistently, reporter assays combined with proteomic and immunopeptidomic analyses demonstrated the induction of ribosomal frameshifting, and the generation and presentation of aberrant trans-frame peptides at the cell surface after treatment with IFNγ. Priming of naive T cells from healthy donors with aberrant peptides induced peptide-specific T cells. Together, our results suggest that IDO1-mediated depletion of tryptophan, which is induced by IFNγ, has a role in the immune recognition of melanoma cells by contributing to diversification of the peptidome landscape.

PhISCS-BnB: a fast branch and bound algorithm for the perfect tumor phylogeny reconstruction problem.

MOTIVATION: Recent advances in single-cell sequencing (SCS) offer an unprecedented insight into tumor emergence and evolution. Principled approaches to tumor phylogeny reconstruction via SCS data are typically based on general computational methods for solving an integer linear program, or a constraint satisfaction program, which, although guaranteeing convergence to the most likely solution, are very slow. Others based on Monte Carlo Markov Chain or alternative heuristics not only offer no such guarantee, but also are not faster in practice. As a result, novel methods that can scale up to handle the size and noise characteristics of emerging SCS data are highly desirable to fully utilize this technology. RESULTS: We introduce PhISCS-BnB (phylogeny inference using SCS via branch and bound), a branch and bound algorithm to compute the most likely perfect phylogeny on an input genotype matrix extracted from an SCS dataset. PhISCS-BnB not only offers an optimality guarantee, but is also 10-100 times faster than the best available methods on simulated tumor SCS data. We also applied PhISCS-BnB on a recently published large melanoma dataset derived from the sublineages of a cell line involving 20 clones with 2367 mutations, which returned the optimal tumor phylogeny in <4 h. The resulting phylogeny agrees with and extends the published results by providing a more detailed picture on the clonal evolution of the tumor. AVAILABILITY AND IMPLEMENTATION: https://github.com/algo-cancer/PhISCS-BnB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Immunoproteasome expression is associated with better prognosis and response to checkpoint therapies in melanoma.

Predicting the outcome of immunotherapy treatment in melanoma patients is challenging. Alterations in genes involved in antigen presentation and the interferon gamma (IFNγ) pathway play an important role in the immune response to tumors. We describe here that the overexpression of PSMB8 and PSMB9, two major components of the immunoproteasome, is predictive of better survival and improved response to immune-checkpoint inhibitors of melanoma patients. We study the mechanism underlying this connection by analyzing the antigenic peptide repertoire of cells that overexpress these subunits using HLA peptidomics. We find a higher response of patient-matched tumor infiltrating lymphocytes against antigens diferentially presented after immunoproteasome overexpression. Importantly, we find that PSMB8 and PSMB9 expression levels are much stronger predictors of melanoma patients' immune response to checkpoint inhibitors than the tumors' mutational burden. These results suggest that PSMB8 and PSMB9 expression levels can serve as important biomarkers for stratifying melanoma patients for immune-checkpoint treatment.

UVB-Induced Tumor Heterogeneity Diminishes Immune Response in Melanoma.

Although clonal neo-antigen burden is associated with improved response to immune therapy, the functional basis for this remains unclear. Here we study this question in a novel controlled mouse melanoma model that enables us to explore the effects of intra-tumor heterogeneity (ITH) on tumor aggressiveness and immunity independent of tumor mutational burden. Induction of UVB-derived mutations yields highly aggressive tumors with decreased anti-tumor activity. However, single-cell-derived tumors with reduced ITH are swiftly rejected. Their rejection is accompanied by increased T cell reactivity and a less suppressive microenvironment. Using phylogenetic analyses and mixing experiments of single-cell clones, we dissect two characteristics of ITH: the number of clones forming the tumor and their clonal diversity. Our analysis of melanoma patient tumor data recapitulates our results in terms of overall survival and response to immune checkpoint therapy. These findings highlight the importance of clonal mutations in robust immune surveillance and the need to quantify patient ITH to determine the response to checkpoint blockade.

Author Correction: RGS7 is recurrently mutated in melanoma and promotes migration and invasion of human cancer cells.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Combined Analysis of Antigen Presentation and T-cell Recognition Reveals Restricted Immune Responses in Melanoma.

The quest for tumor-associated antigens (TAA) and neoantigens is a major focus of cancer immunotherapy. Here, we combine a neoantigen prediction pipeline and human leukocyte antigen (HLA) peptidomics to identify TAAs and neoantigens in 16 tumors derived from seven patients with melanoma and characterize their interactions with their tumor-infiltrating lymphocytes (TIL). Our investigation of the antigenic and T-cell landscapes encompassing the TAA and neoantigen signatures, their immune reactivity, and their corresponding T-cell identities provides the first comprehensive analysis of cancer cell T-cell cosignatures, allowing us to discover remarkable antigenic and TIL similarities between metastases from the same patient. Furthermore, we reveal that two neoantigen-specific clonotypes killed 90% of autologous melanoma cells, both in vitro and in vivo, showing that a limited set of neoantigen-specific T cells may play a central role in melanoma tumor rejection. Our findings indicate that combining HLA peptidomics with neoantigen predictions allows robust identification of targetable neoantigens, which could successfully guide personalized cancer immunotherapies.Significance: As neoantigen targeting is becoming more established as a powerful therapeutic approach, investigating these molecules has taken center stage. Here, we show that a limited set of neoantigen-specific T cells mediates tumor rejection, suggesting that identifying just a few antigens and their corresponding T-cell clones could guide personalized immunotherapy. Cancer Discov; 8(11); 1366-75. ©2018 AACR. This article is highlighted in the In This Issue feature, p. 1333.

Urea Cycle Dysregulation Generates Clinically Relevant Genomic and Biochemical Signatures.

The urea cycle (UC) is the main pathway by which mammals dispose of waste nitrogen. We find that specific alterations in the expression of most UC enzymes occur in many tumors, leading to a general metabolic hallmark termed "UC dysregulation" (UCD). UCD elicits nitrogen diversion toward carbamoyl-phosphate synthetase2, aspartate transcarbamylase, and dihydrooratase (CAD) activation and enhances pyrimidine synthesis, resulting in detectable changes in nitrogen metabolites in both patient tumors and their bio-fluids. The accompanying excess of pyrimidine versus purine nucleotides results in a genomic signature consisting of transversion mutations at the DNA, RNA, and protein levels. This mutational bias is associated with increased numbers of hydrophobic tumor antigens and a better response to immune checkpoint inhibitors independent of mutational load. Taken together, our findings demonstrate that UCD is a common feature of tumors that profoundly affects carcinogenesis, mutagenesis, and immunotherapy response.

RGS7 is recurrently mutated in melanoma and promotes migration and invasion of human cancer cells.

Analysis of 501 melanoma exomes revealed RGS7, which encodes a GTPase-accelerating protein (GAP), to be a tumor-suppressor gene. RGS7 was mutated in 11% of melanomas and was found to harbor three recurrent mutations (p.R44C, p.E383K and p.R416Q). Structural modeling of the most common recurrent mutation of the three (p.R44C) predicted that it destabilizes the protein due to the loss of an H-bond and salt bridge network between the mutated position and the serine and aspartic acid residues at positions 58 as 61, respectively. We experimentally confirmed this prediction showing that the p.R44C mutant protein is indeed destabilized. We further show RGS7 p.R44C has weaker catalytic activity for its substrate Gαo, thus providing a dual mechanism for its loss of function. Both of these effects are expected to contribute to loss of function of RGS7 resulting in increased anchorage-independent growth, migration and invasion of melanoma cells. By mutating position 56 in the R44C mutant from valine to cysteine, thereby enabling the formation of a disulfide bridge between the two mutated positions, we slightly increased the catalytic activity and reinstated protein stability, leading to the rescue of RGS7's function as a tumor suppressor. Our findings identify RGS7 as a novel melanoma driver and point to the clinical relevance of using strategies to stabilize the protein and, thereby, restore its function.

Genome-wide computational determination of the human metalloproteome.

Accurate prediction of protein function in humans is important for understanding biological processes at the molecular level in biomedicine and drug design. Over a third of proteins are commonly held to bind metal, and ∼10% of human proteins, to bind zinc. Therefore, an initial step in protein function prediction frequently involves predicting metal ion binding. In recent years, methods have been developed to predict a set of residues in 3D space forming the metal-ion binding site, often with a high degree of accuracy. Here, using extensions of these methods, we provide an extensive list of human proteins and their putative metal ion binding site residues, using translated gene sequences derived from the complete, resolved human genome. Under conditions of ∼90% selectivity, over 900 new human putative metal ion binding proteins are identified. A statistical analysis of resolved metal ion binding sites in the human metalloproteome is furnished and the importance of remote homology analysis is demonstrated. As an example, a novel metal-ion binding site involving a complex of a botulinum substrate with its inhibitor is presented. On the basis of the location of the predicted site and the interactions of the contacting residues at the complex interface, we postulate that metal ion binding in this region could influence complex formation and, consequently, the functioning of the protein. Thus, this work provides testable hypotheses about novel functions of known proteins.

First- and second-shell metal binding residues in human proteins are disproportionately associated with disease-related SNPs.

Protein structure serves as a key determinant for revealing the molecular basis of human disease. Metal ions are among the most frequently bound heterogroups in proteins affecting structure and function. We analyzed the relationship between single nucleotide polymorphisms (SNPs) associated with human disease and metal binding sites in proteins on a database scale, using structural models and predictive tools. A match was identified for 586 disease-associated SNPs (dSNPs) located at 135 predicted metal binding sites and associated with 126 diverse diseases. For 104 diseases, a metal is known to bind at the predicted site in the homologue; for 22, the analysis gives a first indication for metal involvement in the disease. As second-shell residues play an important part in metal ion binding, our analysis included protein space up to 4.5 Å from metal binding sites. The ratio of disease-associated versus nondisease-associated SNPs (dSNP/ndSNP) for first-shell residues is 7.4 and for second-shell residues, 3.1. In addition, over 13% of all dSNPs were found to be associated with first- and second-shell residues, although these residues occupy only about 3% of protein space. These results show a disproportionate association of dSNPs and metal binding sites over a wide variety of diseases.

Critical sensitivity effect in an interferometer sensor.

We report the observation of anomalous behavior in the spectral sensitivity response in a specially designed waveguided interferometer sensor. Approaching a definite critical point, the sensitivity increases nonlinearly. Furthermore, at the critical wavelength a new effect of splitting or bifurcation of a minimum dip is observed. The value of the splitting is suggested as an advantageous measure for sensing.

Prediction of 3D metal binding sites from translated gene sequences based on remote-homology templates.

Database-scale analysis was performed to determine whether structural models, based on remote homologues, are effective in predicting 3D transition metal binding sites in proteins directly from translated gene sequences. The extent by which side chain modeling alone reduces sensitivity and selectivity is shown to be <10%. Surprisingly, selectivity was not dependent on the level of sequence homology between template and target, or on the presence of a metal ion in the structural template. Applying a modification of the CHED algorithm (Babor et al., Proteins 2008;70:208-217) and machine learning filters, a selectivity of approximately 90% was achieved for protein sequences using unrelated structural templates over a sequence identity range of 18-100%. Below approximately 18% identity, the number of analyzable target-template pairs and predictability of metal binding sites falls off sharply. A full third of structural templates were found to have target partners only in the remote homology range of 18-30%. In this range, nonmetal-binding templates are calculated to be the majority and serve to predict with 50% sensitivity at the geometric level. Overall, sensitivity at the geometric level for targets having templates in the 18-30% sequence identity range is 73%, with an average of one false positive site per true site. Protein sequences described as "unknown" in the UniProt database and composed largely of unidentified genome project sequences were studied and metal binding sites predicted. A web server for prediction of metal binding sites from protein sequence is provided.

Critical sensitivity in hetero-modal interferometric sensor using spectral interrogation.

This paper reports on the finding of a critical working point in the sensitivity of hetero-modal interferometric optical sensors using spectral interrogation. At this point the theoretical sensitivity approaches infinity and the practical sensitivity will depend only on the measurement accuracy and noise sources present. If the critical condition is attained at a point of minimal power transfer, a phenomenon of splitting or bifurcation of the minimum dip is expected as sensing occurs. The conditions for attainment of these critical effects are discussed.

Principles of transcriptional control in the metabolic network of Saccharomyces cerevisiae.

Cellular networks are subject to extensive regulation, which modifies the availability and efficiency of connections between components in response to external conditions. Thus far, studies of large-scale networks have focused on their connectivity, but have not considered how the modulation of this connectivity might also determine network properties. To address this issue, we analyzed how the coordinated expression of enzymes shapes the metabolic network of Saccharomyces cerevisiae. By integrating large-scale expression data with the structural description of the metabolic network, we systematically characterized the transcriptional regulation of metabolic pathways. The analysis revealed recurrent patterns, which may represent design principles of metabolic gene regulation. First, we find that transcription regulation biases metabolic flow toward linearity by coexpressing only distinct branches at metabolic branchpoints. Second, individual isozymes were often separately coregulated with distinct processes, providing a means of reducing crosstalk between pathways using a common reaction. Finally, transcriptional regulation defined a hierarchical organization of metabolic pathways into groups of varying expression coherence. These results emphasize the utility of incorporating regulatory information when analyzing properties of large-scale cellular networks.