Analysis of single nuclear chromatin accessibility reveals unique myeloid populations in human pancreatic ductal adenocarcinoma.

BACKGROUND: A better understanding of the pancreatic ductal adenocarcinoma (PDAC) immune microenvironment is critical to developing new treatments and improving outcomes. Myeloid cells are of particular importance for PDAC progression; however, the presence of heterogenous subsets with different ontogeny and impact, along with some fluidity between them, (infiltrating monocytes vs. tissue-resident macrophages; M1 vs. M2) makes characterisation of myeloid populations challenging. Recent advances in single cell sequencing technology provide tools for characterisation of immune cell infiltrates, and open chromatin provides source and function data for myeloid cells to assist in more comprehensive characterisation. Thus, we explore single nuclear assay for transposase accessible chromatin (ATAC) sequencing (snATAC-Seq), a method to analyse open gene promoters and transcription factor binding, as an important means for discerning the myeloid composition in human PDAC tumours. METHODS: Frozen pancreatic tissues (benign or PDAC) were prepared for snATAC-Seq using 10× Chromium technology. Signac was used for preliminary analysis, clustering and differentially accessible chromatin region identification. The genes annotated in promoter regions were used for Gene Ontology (GO) enrichment and cell type annotation. Gene signatures were used for survival analysis with The Cancer Genome Atlas (TCGA)-pancreatic adenocarcinoma (PAAD) dataset. RESULTS: Myeloid cell transcription factor activities were higher in tumour than benign pancreatic samples, enabling us to further stratify tumour myeloid populations. Subcluster analysis revealed eight distinct myeloid populations. GO enrichment demonstrated unique functions for myeloid populations, including interleukin-1b signalling (recruited monocytes) and intracellular protein transport (dendritic cells). The identified gene signature for dendritic cells influenced survival (hazard ratio = .63, p = .03) in the TCGA-PAAD dataset, which was unique to PDAC. CONCLUSIONS: These data suggest snATAC-Seq as a method for analysis of frozen human pancreatic tissues to distinguish myeloid populations. An improved understanding of myeloid cell heterogeneity and function is important for developing new treatment targets in PDAC.

Bifidobacterium affects antitumor efficacy of oncolytic adenovirus in a mouse model of melanoma.

Gut microbiota plays a key role in modulating responses to cancer immunotherapy in melanoma patients. Oncolytic viruses (OVs) represent emerging tools in cancer therapy, inducing a potent immunogenic cancer cell death (ICD) and recruiting immune cells in tumors, poorly infiltrated by T cells. We investigated whether the antitumoral activity of oncolytic adenovirus Ad5D24-CpG (Ad-CpG) was gut microbiota-mediated in a syngeneic mouse model of melanoma and observed that ICD was weakened by vancomycin-mediated perturbation of gut microbiota. Ad-CpG efficacy was increased by oral supplementation with Bifidobacterium, reducing melanoma progression and tumor-infiltrating regulatory T cells. Fecal microbiota was enriched in bacterial species belonging to the Firmicutes phylum in mice treated with both Bifidobacterium and Ad-CpG; furthermore, our data suggest that molecular mimicry between melanoma and Bifidobacterium-derived epitopes may favor activation of cross-reactive T cells and constitutes one of the mechanisms by which gut microbiota modulates OVs response.

Responses of Salmonella biofilms to oxidizing biocides: Evidence of spatial clustering.

The spatial organization of biofilm bacterial communities can be influenced by several factors, including growth conditions and challenge with antimicrobials. Differential survival of clusters of cells within biofilms has been observed. In this work, we present a variety of methods to identify, quantify and statistically analyse clusters of live cells from images of two Salmonella strains with differential biofilm forming capacity exposed to three oxidizing biocides. With a support vector machine approach, we showed spatial separation between the two strains, and, using statistical testing and high-performance computing (HPC), we determined conditions which possess an inherent cluster structure. Our results indicate that there is a relationship between biocide potency and inherent biofilm formation capacity with the tendency to select for spatial clusters of survivors. There was no relationship between positions of clusters of live or dead cells within stressed biofilms. This work identifies an approach to robustly quantify clusters of physiologically distinct cells within biofilms and suggests work to understand how clusters form and survive is needed. SIGNIFICANCE STATEMENT: Control of biofilm growth remains a major challenge and there is considerable uncertainty about how bacteria respond to disinfection within a biofilm and how clustering of cells impacts survival. We have developed a methodological approach to identify and statistically analyse clusters of surviving cells in biofilms after biocide challenge. This approach can be used to understand bacterial behaviour within biofilms under stress and is widely applicable.

Emergence of immune escape at dominant SARS-CoV-2 killer T cell epitope.

We studied the prevalent cytotoxic CD8 T cell response mounted against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike glycoprotein269-277 epitope (sequence YLQPRTFLL) via the most frequent human leukocyte antigen (HLA) class I worldwide, HLA A∗02. The Spike P272L mutation that has arisen in at least 112 different SARS-CoV-2 lineages to date, including in lineages classified as "variants of concern," was not recognized by the large CD8 T cell response seen across cohorts of HLA A∗02+ convalescent patients and individuals vaccinated against SARS-CoV-2, despite these responses comprising of over 175 different individual T cell receptors. Viral escape at prevalent T cell epitopes restricted by high frequency HLAs may be particularly problematic when vaccine immunity is focused on a single protein such as SARS-CoV-2 Spike, providing a strong argument for inclusion of multiple viral proteins in next generation vaccines and highlighting the need for monitoring T cell escape in new SARS-CoV-2 variants.

Viral Molecular Mimicry Influences the Antitumor Immune Response in Murine and Human Melanoma.

Molecular mimicry is one of the leading mechanisms by which infectious agents can induce autoimmunity. Whether a similar mechanism triggers an antitumor immune response is unexplored, and the role of antiviral T cells infiltrating the tumor has remained anecdotal. To address these questions, we first developed a bioinformatic tool to identify tumor peptides with high similarity to viral epitopes. Using peptides identified by this tool, we demonstrated that, in mice, preexisting immunity toward specific viral epitopes enhanced the efficacy of cancer immunotherapy via molecular mimicry in different settings. To understand whether this mechanism could partly explain immunotherapy responsiveness in humans, we analyzed a cohort of patients with melanoma undergoing anti-PD1 treatment who had a high IgG titer for cytomegalovirus (CMV). In this cohort of patients, we showed that high levels of CMV-specific antibodies were associated with prolonged progression-free survival and found that, in some cases, peripheral blood mononuclear cells (PBMC) could cross-react with both melanoma and CMV homologous peptides. Finally, T-cell receptor sequencing revealed expansion of the same CD8+ T-cell clones when PBMCs were expanded with tumor or homologous viral peptides. In conclusion, we have demonstrated that preexisting immunity and molecular mimicry could influence the response to immunotherapies. In addition, we have developed a free online tool that can identify tumor antigens and neoantigens highly similar to pathogen antigens to exploit molecular mimicry and cross-reactive T cells in cancer vaccine development.

Macrophage and Neutrophil Interactions in the Pancreatic Tumor Microenvironment Drive the Pathogenesis of Pancreatic Cancer.

Despite modest improvements in survival in recent years, pancreatic adenocarcinoma remains a deadly disease with a 5-year survival rate of only 9%. These poor outcomes are driven by failure of early detection, treatment resistance, and propensity for early metastatic spread. Uncovering innovative therapeutic modalities to target the resistance mechanisms that make pancreatic cancer largely incurable are urgently needed. In this review, we discuss the immune composition of pancreatic tumors, including the counterintuitive fact that there is a significant inflammatory immune infiltrate in pancreatic cancer yet anti-tumor mechanisms are subverted and immune behaviors are suppressed. Here, we emphasize how immune cell interactions generate tumor progression and treatment resistance. We narrow in on tumor macrophage (TAM) spatial arrangement, polarity/function, recruitment, and origin to introduce a concept where interactions with tumor neutrophils (TAN) perpetuate the microenvironment. The sequelae of macrophage and neutrophil activities contributes to tumor remodeling, fibrosis, hypoxia, and progression. We also discuss immune mechanisms driving resistance to standard of care modalities. Finally, we describe a cadre of treatment targets, including those intended to overcome TAM and TAN recruitment and function, to circumvent barriers presented by immune infiltration in pancreatic adenocarcinoma.

Molecular Rules Underpinning Enhanced Affinity Binding of Human T Cell Receptors Engineered for Immunotherapy.

Immuno-oncology approaches that utilize T cell receptors (TCRs) are becoming highly attractive because of their potential to target virtually all cellular proteins, including cancer-specific epitopes, via the recognition of peptide-human leukocyte antigen (pHLA) complexes presented at the cell surface. However, because natural TCRs generally recognize cancer-derived pHLAs with very weak affinities, efforts have been made to enhance their binding strength, in some cases by several million-fold. In this study, we investigated the mechanisms underpinning human TCR affinity enhancement by comparing the crystal structures of engineered enhanced affinity TCRs with those of their wild-type progenitors. Additionally, we performed molecular dynamics simulations to better understand the energetic mechanisms driving the affinity enhancements. These data demonstrate that supra-physiological binding affinities can be achieved without altering native TCR-pHLA binding modes via relatively subtle modifications to the interface contacts, often driven through the addition of buried hydrophobic residues. Individual energetic components of the TCR-pHLA interaction governing affinity enhancements were distinct and highly variable for each TCR, often resulting from additive, or knock-on, effects beyond the mutated residues. This comprehensive analysis of affinity-enhanced TCRs has important implications for the future rational design of engineered TCRs as efficacious and safe drugs for cancer treatment.

CD4+ T Cells Recognize Conserved Influenza A Epitopes through Shared Patterns of V-Gene Usage and Complementary Biochemical Features.

T cell recognition of peptides presented by human leukocyte antigens (HLAs) is mediated by the highly variable T cell receptor (TCR). Despite this built-in TCR variability, individuals can mount immune responses against viral epitopes by using identical or highly related TCRs expressed on CD8+ T cells. Characterization of these TCRs has extended our understanding of the molecular mechanisms that govern the recognition of peptide-HLA. However, few examples exist for CD4+ T cells. Here, we investigate CD4+ T cell responses to the internal proteins of the influenza A virus that correlate with protective immunity. We identify five internal epitopes that are commonly recognized by CD4+ T cells in five HLA-DR1+ subjects and show conservation across viral strains and zoonotic reservoirs. TCR repertoire analysis demonstrates several shared gene usage biases underpinned by complementary biochemical features evident in a structural comparison. These epitopes are attractive targets for vaccination and other T cell therapies.

GPU-Accelerated Discovery of Pathogen-Derived Molecular Mimics of a T-Cell Insulin Epitope.

The strong links between (Human Leukocyte Antigen) HLA, infection and autoimmunity combine to implicate T-cells as primary triggers of autoimmune disease (AD). T-cell crossreactivity between microbially-derived peptides and self-peptides has been shown to break tolerance and trigger AD in experimental animal models. Detailed examination of the potential for T-cell crossreactivity to trigger human AD will require means of predicting which peptides might be recognised by autoimmune T-cell receptors (TCRs). Recent developments in high throughput sequencing and bioinformatics mean that it is now possible to link individual TCRs to specific pathologies for the first time. Deconvolution of TCR function requires knowledge of TCR specificity. Positional Scanning Combinatorial Peptide Libraries (PS-CPLs) can be used to predict HLA-restriction and define antigenic peptides derived from self and pathogen proteins. In silico search of the known terrestrial proteome with a prediction algorithm that ranks potential antigens in order of recognition likelihood requires complex, large-scale computations over several days that are infeasible on a personal computer. We decreased the time required for peptide searching to under 30 min using multiple blocks on graphics processing units (GPUs). This time-efficient, cost-effective hardware accelerator was used to screen bacterial and fungal human pathogens for peptide sequences predicted to activate a T-cell clone, InsB4, that was isolated from a patient with type 1 diabetes and recognised the insulin B-derived epitope HLVEALYLV in the context of disease-risk allele HLA A*0201. InsB4 was shown to kill HLA A*0201+ human insulin producing ß-cells demonstrating that T-cells with this specificity might contribute to disease. The GPU-accelerated algorithm and multispecies pathogen proteomic databases were validated to discover pathogen-derived peptide sequences that acted as super-agonists for the InsB4 T-cell clone. Peptide-MHC tetramer binding and surface plasmon resonance were used to confirm that the InsB4 TCR bound to the highest-ranked peptide agonists derived from infectious bacteria and fungi. Adoption of GPU-accelerated prediction of T-cell agonists has the capacity to revolutionise our understanding of AD by identifying potential targets for autoimmune T-cells. This approach has further potential for dissecting T-cell responses to infectious disease and cancer.

Induction of influenza-specific local CD8 T-cells in the respiratory tract after aerosol delivery of vaccine antigen or virus in the Babraham inbred pig.

There is increasing evidence that induction of local immune responses is a key component of effective vaccines. For respiratory pathogens, for example tuberculosis and influenza, aerosol delivery is being actively explored as a method to administer vaccine antigens. Current animal models used to study respiratory pathogens suffer from anatomical disparity with humans. The pig is a natural and important host of influenza viruses and is physiologically more comparable to humans than other animal models in terms of size, respiratory tract biology and volume. It may also be an important vector in the birds to human infection cycle. A major drawback of the current pig model is the inability to analyze antigen-specific CD8+ T-cell responses, which are critical to respiratory immunity. Here we address this knowledge gap using an established in-bred pig model with a high degree of genetic identity between individuals, including the MHC (Swine Leukocyte Antigen (SLA)) locus. We developed a toolset that included long-term in vitro pig T-cell culture and cloning and identification of novel immunodominant influenza-derived T-cell epitopes. We also generated structures of the two SLA class I molecules found in these animals presenting the immunodominant epitopes. These structures allowed definition of the primary anchor points for epitopes in the SLA binding groove and established SLA binding motifs that were used to successfully predict other influenza-derived peptide sequences capable of stimulating T-cells. Peptide-SLA tetramers were constructed and used to track influenza-specific T-cells ex vivo in blood, the lungs and draining lymph nodes. Aerosol immunization with attenuated single cycle influenza viruses (S-FLU) induced large numbers of CD8+ T-cells specific for conserved NP peptides in the respiratory tract. Collectively, these data substantially increase the utility of pigs as an effective model for studying protective local cellular immunity against respiratory pathogens.