Temporal Genomic Analysis of Homogeneous Tumor Models Reveals Key Regulators of Immune Evasion in Melanoma.

In this study, we find that Mif expression is associated with tumor growth and aggressiveness, specifically in tumors with low heterogeneity. These findings could facilitate the development of new strategies to treat patients with homogeneous, high MIF-expressing tumors that are unresponsive to immune checkpoint therapy.

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.

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.

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.

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

A variety of species of bacteria are known to colonize human tumours, proliferate within them and modulate immune function, which ultimately affects the survival of patients with cancer and their responses to treatment. 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.

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 immunotherapy. 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 IFNγ.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.