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Aberrant expression of viral-like repeat elements is a common feature of epithelial cancers, and the substantial diversity of repeat species provides a distinct view of the cancer transcriptome. Repeatome profiling across ovarian, pancreatic, and colorectal cell lines identifies distinct clustering independent of tissue origin that is seen with coding gene analysis. Deeper analysis of ovarian cancer cell lines demonstrated that human satellite II (HSATII) satellite repeat expression was highly associated with epithelial-mesenchymal transition (EMT) and anticorrelated with IFN-response genes indicative of a more aggressive phenotype. SATII expression--and its correlation with EMT and anticorrelation with IFN-response genes-- was also found in ovarian cancer RNA-Seq data and was associated with significantly shorter survival in a second independent cohort of patients with ovarian cancer. Repeat RNAs were enriched in tumor-derived extracellular vesicles capable of stimulating monocyte-derived macrophages, demonstrating a mechanism that alters the tumor microenvironment with these viral-like sequences. Targeting of HSATII with antisense locked nucleic acids stimulated IFN response and induced MHC I expression in ovarian cancer cell lines, highlighting a potential strategy of modulating the repeatome to reestablish antitumor cell immune surveillance., Introduction Repetitive elements make up approximately 50% of the human genome (1, 2), and their aberrant expression has been described across a wide range ofcancers (3-5). Repeat suppression is achieved [...]

Success of precision neoantigen-based immunotherapies hinges on the selection of immunogenic neoantigens, yet currently neither large-scale datasets nor streamlined methods are available to achieve this goal. Müller et al. present a large experimental dataset resource along with machine learning-based models to classify immunogenic neoantigens. [ABSTRACT FROM AUTHOR]

Author(s): Marta uksza (corresponding author) [1]; Nadeem Riaz [2, 3]; Vladimir Makarov [3, 4]; Vinod P. Balachandran [5, 6, 7]; Matthew D. Hellmann [7, 8, 9]; Alexander Solovyov [10, 11, [...]

With the increasing ability to use high-throughput next-generation sequencing to quantify the diversity of the human T cell receptor (TCR) repertoire, the ability to use TCR sequences to infer antigen-specificity could greatly aid potential diagnostics and therapeutics. Here, we use a machine-learning approach known as Restricted Boltzmann Machine to develop a sequence-based inference approach to identify antigen-specific TCRs. Our approach combines probabilistic models of TCR sequences with clone abundance information to extract TCR sequence motifs central to an antigen-specific response. We use this model to identify patient personalized TCR motifs that respond to individual tumor and infectious disease antigens, and to accurately discriminate specific from non-specific responses. Furthermore, the hidden structure of the model results in an interpretable representation space where TCRs responding to the same antigen cluster, correctly discriminating the response of TCR to different viral epitopes. The model can be used to identify condition specific responding TCRs. We focus on the examples of TCRs reactive to candidate neoantigens and selected epitopes in experiments of stimulated TCR clone expansion. Author summary: Large repertoires of immune cells, such as T cells, are increasingly made available by high-throughput sequencing. Exploiting such datasets to infer how T-cell respond to antigens could help design vaccines and adoptive T-cell therapies. We here propose an approach based on probabilistic machine learning to identify and characterize responding T cells. After learning, this approach is able to distinguish clones that specifically respond to different antigen stimulations. The model parameters and the low-dimensional representations of the T-cell sequences identify sequence motifs underlying T-cell recognition at the molecular level. The approach is illustrated on repertoire data describing in vitro stimulation of T cells by cancer-related neoantigens, as well as on data for common infectious diseases. [ABSTRACT FROM AUTHOR]

COVID-19 can lead to acute respiratory syndrome, which can be due to dysregulated immune signaling. We analyze the distribution of CpG dinucleotides, a pathogen-associated molecular pattern, in the SARS-CoV-2 genome. We characterize CpG content by a CpG force that accounts for statistical constraints acting on the genome at the nucleotidic and amino acid levels. The CpG force, as the CpG content, is overall low compared with other pathogenic betacoronaviruses; however, it widely fluctuates along the genome, with a particularly low value, comparable with the circulating seasonal HKU1, in the spike coding region and a greater value, comparable with SARS and MERS, in the highly expressed nucleocapside coding region (N ORF), whose transcripts are relatively abundant in the cytoplasm of infected cells and present in the 3′UTRs of all subgenomic RNA. This dual nature of CpG content could confer to SARS-CoV-2 the ability to avoid triggering pattern recognition receptors upon entry, while eliciting a stronger response during replication. We then investigate the evolution of synonymous mutations since the outbreak of the COVID-19 pandemic, finding a signature of CpG loss in regions with a greater CpG force. Sequence motifs preceding the CpG-loss-associated loci in the N ORF match recently identified binding patterns of the zinc finger antiviral protein. Using a model of the viral gene evolution under human host pressure, we find that synonymous mutations seem driven in the SARS-CoV-2 genome, and particularly in the N ORF, by the viral codon bias, the transition–transversion bias, and the pressure to lower CpG content. [ABSTRACT FROM AUTHOR]

Recently, gene expression profiling of benign nevi and melanomas characterized two transcriptomic types of melanocytic nevi and primary melanomas (Kunz et al., [4]). I ART4 i mutation was previously founded in metastatic melanoma from GCMN in an adult; I NONO i mutation was founded in primary melanoma arising in GCMN in an eight-year-old child (Lim et al., [5]). Overall, we identified 1,607 differentially expressed genes between CMN and I NRAS i -mutant primary melanoma, including 1,267 upregulated genes and 340 downregulated genes in melanoma (Figure 2a). [Extracted from the article]

Summary: FBXW7 is well characterized as a tumor suppressor in many human cancers including melanoma; however, the mechanisms of tumor‐suppressive function have not been fully elucidated. We leveraged two distinct RNA sequencing datasets: human melanoma cell lines (n = 10) with control versus silenced FBXW7 and a cohort of human melanoma tumor samples (n = 51) to define the transcriptomic fingerprint regulated by FBXW7. Here, we report that loss of FBXW7 enhances a mitochondrial gene transcriptional program that is dependent on MITF in human melanoma and confers poor patient outcomes. MITF is a lineage‐specific master regulator of melanocytes and together with PGC‐1alpha is a marker for melanoma subtypes with dependence for mitochondrial oxidative metabolism. We found that inactivation of FBXW7 elevates MITF protein levels in melanoma cells. In vitro studies examining loss of FBXW7 and MITF alone or in combination showed that FBXW7 is an upstream regulator for the MITF/PGC‐1 signaling. [ABSTRACT FROM AUTHOR]

It has been posited that anti-tumoral innate activation is driven by derepression of endogenous repeats. We compared RNA sequencing protocols to assess repeat transcriptomes in The Cancer Genome Atlas (TCGA). Although poly(A) selection efficiently detects coding genes, most non-coding genes, and limited subsets of repeats, it fails to capture overall repeat expression and co-expression. Alternatively, total RNA expression reveals distinct repeat coexpression subgroups and delivers greater dynamic changes, implying they may serve as better biomarkers of clinical outcomes. We show that endogenous retrovirus expression predicts immunotherapy response better than conventional immune signatures in one cohort yet is not predictive in another. Moreover, we find that global repeat derepression, including the HSATII satellite repeat, correlates with an immunosuppressive phenotype in colorectal and pancreatic tumors and validate in situ. In conclusion, we stress the importance of analyzing the full spectrum of repeat transcription to decode their role in tumor immunity. [ABSTRACT FROM AUTHOR]

Equine influenza viruses (EIVs) of H3N8 subtype are culprits of severe acute respiratory infections in horses, and are still responsible for significant outbreaks worldwide. Adaptability of influenza viruses to a particular host is significantly influenced by their codon usage preference, due to an absolute dependence on the host cellular machinery for their replication. In the present study, we analyzed genome-wide codon usage patterns in 92 EIV strains, including both H3N8 and H7N7 subtypes by computing several codon usage indices and applying multivariate statistical methods. Relative synonymous codon usage (RSCU) analysis disclosed bias of preferred synonymous codons towards A/U-ended codons. The overall codon usage bias in EIVs was slightly lower, and mainly affected by the nucleotide compositional constraints as inferred from the RSCU and effective number of codon (ENc) analysis. Our data suggested that codon usage pattern in EIVs is governed by the interplay of mutation pressure, natural selection from its hosts and undefined factors. The H7N7 subtype was found less fit to its host (horse) in comparison to H3N8, by possessing higher codon bias, lower mutation pressure and much less adaptation to tRNA pool of equine cells. To the best of our knowledge, this is the first report describing the codon usage analysis of the complete genomes of EIVs. The outcome of our study is likely to enhance our understanding of factors involved in viral adaptation, evolution, and fitness towards their hosts. [ABSTRACT FROM AUTHOR]

Technological advances have allowed aspects of viral evolution to be explored at unprecedented scales. As a consequence, new quantitative approaches are needed to investigate features of viral evolution that fall outside traditional areas of study, such as antigenic evolution. We examine three areas of viral evolution where tools from disciplines such as statistical physics, topology, and information theory have been used recently as quantitative frameworks for large-scale studies and, in some cases, suggest a novel theoretical approach to a problem. Ongoing interaction among these disciplines with biology is necessary so that experimental researchers can determine which quantitative tools are right for them and quantitative researchers can learn which aspects of viral evolution can be understood and advanced with their approaches. [ABSTRACT FROM AUTHOR]

In this work, we study the first passage statistics of amino acid primary sequences, that is the probability of observing an amino acid for the first time at a certain number of residues away from a fixed amino acid. By using this rich mathematical framework, we are able to capture the background distribution for an organism, and infer lengths at which the first passage has a probability that differs from what is expected. While many features of an organism's genome are due to natural selection, others are related to amino acid chemistry and the environment in which an organism lives, constraining the randomness of genomes upon which selection can further act. We therefore use this approach to infer amino acid correlations, and then study how these correlations vary across a wide range of organisms under a wide range of optimal growth temperatures. We find a nearly universal exponential background distribution, consistent with the idea that most amino acids are globally uncorrelated from other amino acids in genomes. When we are able to extract significant correlations, these correlations are reliably dependent on optimal growth temperature, across phylogenetic boundaries. Some of the correlations we extract, such as the enhanced probability of finding, for the first time, a cysteine three residues away from a cysteine or glutamic acid two residues away from an arginine, likely relate to thermal stability. However, other correlations, likely appearing on alpha helical surfaces, have a less clear physiochemical interpretation and may relate to thermal stability or unusual metabolic properties of organisms that live in a high temperature environment. [ABSTRACT FROM AUTHOR]

Background: The avian influenza A H5N1 virus occasionally infects humans, with high mortality rates. Although all current human infections are from avian-to-human transmission, it has been shown that H5N1 can be evolved to transmit between mammals, and is therefore a pandemic threat. For H5N1 surveillance, it is of interest to identify the avian isolates most likely to infect humans. In this study, we develop a method to identify mutations significantly associated with avian to human transmission. Method: Using protein sequences for the surface glycoprotein hemagglutinin from avian and human H5N1 isolates in China, Egypt, and Indonesia from the years 1996–2011, we used Principle Component Analysis and a Maximum Likelihood Multinomial method to identify mutations associated with avian to human transmission. In each geographic region, transmission bias residues were identified using two signatures: a) significantly different amino-acid frequencies in human isolates compared to avian isolates from the same year, and b) significantly low probability of neutral evolution of the human isolates from the avian viral pool of the previous year. Results: In each geographic region, we find specific transmission bias mutations associated with human infections. These mutations are located in antigenic regions and receptor binding, glycosylation and polybasic cleavage sites of HA. We show that human isolates derive from a limited, subset of the avian pool characterized by geography specific mutations. In Egypt, two of three PCA clusters have very few human isolates but are highly enriched in mutations associated with a vaccine escape mutant H5N1 avian sub-clade that is known to be resistant to the Mexican H5N2 vaccine Furthermore, at these transmission bias associated residues, the mutations characteristic of these two clusters are distinct from those associated with the cluster enriched in human isolates, suggesting that vaccine resistant avian strains are unable to infect humans. Our results are relevant for surveillance and vaccination strategies for human H5N1 infections. [ABSTRACT FROM AUTHOR]

The innate immune response provides a first line of defense against pathogens by targeting generic differential features that are present in foreign organisms but not in the host. These innate responses generate selection forces acting both in pathogens and hosts that further determine their co-evolution. Here we analyze the nucleic acid sequence fingerprints of these selection forces acting in parallel on both host innate immune genes and ssRNA viral genomes. We do this by identifying dinucleotide biases in the coding regions of innate immune response genes in plasmacytoid dendritic cells, and then use this signal to identify other significant host innate immune genes. The persistence of these biases in the orthologous groups of genes in humans and chickens is also examined. We then compare the significant motifs in highly expressed genes of the innate immune system to those in ssRNA viruses and study the evolution of these motifs in the H1N1 influenza genome. We argue that the significant under-represented motif pattern of CpG in an AU context - which is found in both the ssRNA viruses and innate genes, and has decreased throughout the history of H1N1 influenza replication in humans - is immunostimulatory and has been selected against during the co-evolution of viruses and host innate immune genes. This shows how differences in host immune biology can drive the evolution of viruses that jump into species with different immune priorities than the original host. [ABSTRACT FROM AUTHOR]

It is well known that the dinucleotide CpG is under-represented in the genomic DNA of many vertebrates. This is commonly thought to be due to the methylation of cytosine residues in this dinucleotide and the corresponding high rate of deamination of 5-methycytosine, which lowers the frequency of this dinucleotide in DNA. Surprisingly, many singlestranded RNA viruses that replicate in these vertebrate hosts also have a very low presence of CpG dinucleotides in their genomes. Viruses are obligate intracellular parasites and the evolution of a virus is inexorably linked to the nature and fate of its host. One therefore expects that virus and host genomes should have common features. In this work, we compare evolutionary patterns in the genomes of ssRNA viruses and their hosts. In particular, we have analyzed dinucleotide patterns and found that the same patterns are pervasively over- or under-represented in many RNA viruses and their hosts suggesting that many RNA viruses evolve by mimicking some of the features of their host's genes (DNA) and likely also their corresponding mRNAs. When a virus crosses a species barrier into a different host, the pressure to replicate, survive and adapt, leaves a footprint in dinucleotide frequencies. For instance, since human genes seem to be under higher pressure to eliminate CpG dinucleotide motifs than avian genes, this pressure might be reflected in the genomes of human viruses (DNA and RNA viruses) when compared to those of the same viruses replicating in avian hosts. To test this idea we have analyzed the evolution of the influenza virus since 1918. We find that the influenza A virus, which originated from an avian reservoir and has been replicating in humans over many generations, evolves in a direction strongly selected to reduce the frequency of CpG dinucleotides in its genome. Consistent with this observation, we find that the influenza B virus, which has spent much more time in the human population, has adapted to its human host and exhibits an extremely low CpG dinucleotide content. We believe that these observations directly show that the evolution of RNA viral genomes can be shaped by pressures observed in the host genome. As a possible explanation, we suggest that the strong selection pressures acting on these RNA viruses are most likely related to the innate immune response and to nucleotide motifs in the host DNA and RNAs. [ABSTRACT FROM AUTHOR]

An analysis of the semiclassical regime of the quantum-classical transition is given for open, bounded, one-dimensional chaotic dynamical systems. Environmental fluctuations—characteristic of all realistic dynamical systems—suppress the development of a fine structure in classical phase space and damp nonlocal contributions to the semiclassical Wigner function, which would otherwise invalidate the approximation. This dual regularization of the singular nature of the semiclassical limit is demonstrated by a numerical investigation of the chaotic Duffing oscillator. [ABSTRACT FROM AUTHOR]

We examine whether the frequency of amino acids across an organism's proteome is primarily determined by optimization to function or other factors, such as the structure of the genetic code. Considering all available proteins together, we first point out that the frequency of an amino acid in a proteome negatively correlates with its mass, suggesting that the genome preserves a fundamental distribution ruled by simple energetics. Given the universality of such distributions, one can use outliers, cysteine and leucine, to identify amino acids that deviate from this simple rule for functional purposes and examine those functions. We quantify the strength of such selection as the entropic cost outliers pay to defy the mass-frequency relation. Codon degeneracy of an amino acid partially explains the correlation between mass and frequency: light amino acids being typically encoded by highly degenerate codon families, with the exception of arginine. While degeneracy may be a factor in hard wiring the relationship between mass and frequency in proteomes, it does not provide a complete explanation. By examining extremophiles, we are able to show that this law weakens with temperature, likely due to protein stability considerations, thus the environment is essential. [ABSTRACT FROM AUTHOR]

Summary To guide the design of immunotherapy strategies for patients with early stage lung tumors, we developed a multiscale immune profiling strategy to map the immune landscape of early lung adenocarcinoma lesions to search for tumor-driven immune changes. Utilizing a barcoding method that allows a simultaneous single-cell analysis of the tumor, non-involved lung, and blood cells, we provide a detailed immune cell atlas of early lung tumors. We show that stage I lung adenocarcinoma lesions already harbor significantly altered T cell and NK cell compartments. Moreover, we identified changes in tumor-infiltrating myeloid cell (TIM) subsets that likely compromise anti-tumor T cell immunity. Paired single-cell analyses thus offer valuable knowledge of tumor-driven immune changes, providing a powerful tool for the rational design of immune therapies. Video Abstract [ABSTRACT FROM AUTHOR]

Aberrant expression of repeat RNAs in pancreatic ductal adenocarcinoma (PDAC) mimics viral-like responses with implications on tumor cell state and the response of the surrounding microenvironment. To better understand the relationship of repeat RNAs in human PDAC, we performed spatial molecular imaging at single-cell resolution in 46 primary tumors, revealing correlations of high repeat RNA expression with alterations in epithelial state in PDAC cells and myofibroblast phenotype in cancer-associated fibroblasts (CAFs). This loss of cellular identity is observed with dosing of extracellular vesicles (EVs) and individual repeat RNAs of PDAC and CAF cell culture models pointing to cell-cell intercommunication of these viral-like elements. Differences in PDAC and CAF responses are driven by distinct innate immune signaling through interferon regulatory factor 3 (IRF3). The cell-context-specific viral-like responses to repeat RNAs provide a mechanism for modulation of cellular plasticity in diverse cell types in the PDAC microenvironment., Competing Interests: Declaration of interests D.T.T. and B.D.G. are co-founders with equity and consulting fees from ROME Therapeutics, a company developing drugs targeting repetitive elements, but this work was not supported by ROME Therapeutics. D.T.T. received in kind research support and a speaking honorarium from NanoString Technologies, and in kind research support from ACD-Biotechne, which was used in this work. M.J.A. is a co-founder of, owns equity in, and receives consulting fees from SeQure Dx, unrelated to this work. M.J.A. receives consulting fees from Chroma Medicine, unrelated to this work. P.D., N.S., B.M.H., K.N., S.E.C., T.K.K., Y.C., and Y.K. are or were employees of NanoString Technologies. D.T.T. has received consulting fees from PanTher Therapeutics, AstraZeneca, Sonata Therapeutics, Moderna, abrdn, Astellas, and Leica Biosystems Imaging; is a founder and has equity in PanTher Therapeutics and TellBio, Inc.; and is on the scientific advisory board with equity for ImproveBio, Inc., which are not related to this work. D.T.T. receives research support from Sanofi, AVA LifeScience GmbH, and Incyte, which was not used in this work. B.D.G. is a consultant or received honoraria for Darwin Health, Merck, PMV Pharma, Merck, Bristol-Meyers Squibb, and Chugai Pharmaceuticals and has research funding from Bristol-Meyers Squibb., (Copyright © 2024 Elsevier Inc. All rights reserved.)

T cells are the central drivers of many inflammatory diseases, but the repertoire of tissue-resident T cells at sites of pathology in human organs remains poorly understood. We examined the site-specificity of T cell receptor (TCR) repertoires across tissues (5 to 18 tissues per patient) in prospectively collected autopsies of patients with and without graft-versus-host disease (GVHD), a potentially lethal tissue-targeting complication of allogeneic hematopoietic cell transplantation, and in mouse models of GVHD. Anatomic similarity between tissues was a key determinant of TCR repertoire composition within patients, independent of disease or transplant status. The T cells recovered from peripheral blood and spleens in patients and mice captured a limited portion of the TCR repertoire detected in tissues. Whereas few T cell clones were shared across patients, motif-based clustering revealed shared repertoire signatures across patients in a tissue-specific fashion. T cells at disease sites had a tissue-resident phenotype and were of donor origin based on single-cell chimerism analysis. These data demonstrate the complex composition of T cell populations that persist in human tissues at the end stage of an inflammatory disorder after lymphocyte-directed therapy. These findings also underscore the importance of studying T cell in tissues rather than blood for tissue-based pathologies and suggest the tissue-specific nature of both the endogenous and posttransplant T cell landscape.