Oas1b-dependent Immune Transcriptional Profiles of West Nile Virus Infection in the Collaborative Cross

The oligoadenylate-synthetase (Oas) gene locus provides innate immune resistance to virus infection. In mouse models, variation in the Oas1b gene influences host susceptibility to flavivirus infection. However, the impact of Oas variation on overall innate immune programming and global gene expression among tissues and in different genetic backgrounds has not been defined. We examined how Oas1b acts in spleen and brain tissue to limit West Nile virus (WNV) susceptibility and disease across a range of genetic backgrounds. The laboratory founder strains of the mouse Collaborative Cross (CC) (A/J, C57BL/6J, 129S1/SvImJ, NOD/ShiLtJ, and NZO/HlLtJ) all encode a truncated, defective Oas1b, whereas the three wild-derived inbred founder strains (CAST/EiJ, PWK/PhJ, and WSB/EiJ) encode a full-length OAS1B protein. We assessed disease profiles and transcriptional signatures of F1 hybrids derived from these founder strains. F1 hybrids included wild-type Oas1b (F/F), homozygous null Oas1b (N/N), and heterozygous offspring of both parental combinations (F/N and N/F). These mice were challenged with WNV, and brain and spleen samples were harvested for global gene expression analysis. We found that the Oas1b haplotype played a role in WNV susceptibility and disease metrics, but the presence of a functional Oas1b allele in heterozygous offspring did not absolutely predict protection against disease. Our results indicate that Oas1b status as wild-type or truncated, and overall Oas1b gene dosage, link with novel innate immune gene signatures that impact specific biological pathways for the control of flavivirus infection and immunity through both Oas1b-dependent and independent processes

A framework for highly multiplexed dextramer mapping and prediction of T cell receptor sequences to antigen specificity.

T cell receptor (TCR) antigen-specific recognition is essential for the adaptive immune system. However, building a TCR-antigen interaction map has been challenging due to the staggering diversity of TCRs and antigens. Accordingly, highly multiplexed dextramer-TCR binding assays have been recently developed, but the utility of the ensuing large datasets is limited by the lack of robust computational methods for normalization and interpretation. Here, we present a computational framework comprising a novel method, ICON (Integrative COntext-specific Normalization), for identifying reliable TCR-pMHC (peptide-major histocompatibility complex) interactions and a neural network-based classifier TCRAI that outperforms other state-of-the-art methods for TCR-antigen specificity prediction. We further demonstrated that by combining ICON and TCRAI, we are able to discover novel subgroups of TCRs that bind to a given pMHC via different mechanisms. Our framework facilitates the identification and understanding of TCR-antigen-specific interactions for basic immunological research and clinical immune monitoring

Immune Predictors of Mortality After Ribonucleic Acid Virus Infection

Background Virus infections result in a range of clinical outcomes for the host, from asymptomatic to severe or even lethal disease. Despite global efforts to prevent and treat virus infections to limit morbidity and mortality, the continued emergence and re-emergence of new outbreaks as well as common infections such as influenza persist as a health threat. Challenges to the prevention of severe disease after virus infection include both a paucity of protective vaccines as well as the early identification of individuals with the highest risk that may require supportive treatment. Methods We completed a screen of mice from the Collaborative Cross (CC) that we infected with influenza, severe acute respiratory syndrome-coronavirus, and West Nile virus. Results The CC mice exhibited a range of disease manifestations upon infections, and we used this natural variation to identify strains with mortality after infection and strains exhibiting no mortality. We then used comprehensive preinfection immunophenotyping to identify global baseline immune correlates of protection from mortality to virus infection. Conclusions These data suggest that immune phenotypes might be leveraged to identify humans at highest risk of adverse clinical outcomes upon infection, who may most benefit from intensive clinical interventions, in addition to providing insight for rational vaccine design

Extensive Homeostatic T Cell Phenotypic Variation within the Collaborative Cross

The Collaborative Cross (CC) is a panel of reproducible recombinant inbred mouse strains with high levels of standing genetic variation, affording an unprecedented opportunity to perform experiments in a small animal model containing controlled genetic diversity while allowing for genetic replicates. Here, we advance the utility of this unique mouse resource for immunology research because it allows for both examination and genetic dissection of mechanisms behind adaptive immune states in mice with distinct and defined genetic makeups. This approach is based on quantitative trait locus mapping: identifying genetically variant genome regions associated with phenotypic variance in traits of interest. Furthermore, the CC can be utilized for mouse model development; distinct strains have unique immunophenotypes and immune properties, making them suitable for research on particular diseases and infections. Here, we describe variations in cellular immune phenotypes across F1 crosses of CC strains and reveal quantitative trait loci responsible for several immune phenotypes

Additional file 2: Table S3. of IL-10 and integrin signaling pathways are associated with head and neck cancer progression

Putative Differential Expression (DE) between HNSCC TCGA Annotated Progressors and NonProgressors (False Discovery Rate (FDR) < 0.05). CTCF binding site annotation was from CTCFBSDB 2.0. (DOCX 489 kb

Additional file 1: Table S1. of IL-10 and integrin signaling pathways are associated with head and neck cancer progression

Demographics for TCGA HNSCC Progressors. Table S2. Demographics for TCGA HNSCC Non-progressors. (DOCX 484 kb

Additional file 3: Table S4. of IL-10 and integrin signaling pathways are associated with head and neck cancer progression

Pathways significantly enriched for differentially expressed (DE) genes between TCGA HNSCC progressors and nonprogressors. FDR = False Discovery Rate. Table S5. Pathways significantly enriched for differentially expressed (DE) genes between TCGA HNSCC progressors and nonprogressors who were assigned radiation treatment. FDR = False Discovery Rate. (DOCX 488 kb

Human CD4 cytotoxic T lymphocytes mediate potent tumor control in humanized immune system mice

Abstract Efficacy of immune checkpoint inhibitors in cancers can be limited by CD8 T cell dysfunction or HLA-I down-regulation. Tumor control mechanisms independent of CD8/HLA-I axis would overcome these limitations. Here, we report potent CD4 T cell-mediated tumor regression and memory responses in humanized immune system (HIS) mice implanted with HT-29 colorectal tumors. The regressing tumors showed increased CD4 cytotoxic T lymphocyte (CTL) infiltration and enhanced tumor HLA-II expression compared to progressing tumors. The intratumoral CD4 T cell subset associated with tumor regression expressed multiple cytotoxic markers and exhibited clonal expansion. Notably, tumor control was abrogated by depletion of CD4 but not CD8 T cells. CD4 T cells derived from tumor-regressing mice exhibited HLA-II-dependent and tumor-specific killing ex vivo. Taken together, our study demonstrates a critical role of human CD4 CTLs in mediating tumor clearance independent of CD8 T cells and provides a platform to study human anti-tumor immunity in vivo

Illuminating biological pathways for drug targeting in head and neck squamous cell carcinoma.

Head and neck squamous cell carcinoma (HNSCC) remains a morbid disease with poor prognosis and treatment that typically leaves patients with permanent damage to critical functions such as eating and talking. Currently only three targeted therapies are FDA approved for use in HNSCC, two of which are recently approved immunotherapies. In this work, we identify biological pathways involved with this disease that could potentially be targeted by current FDA approved cancer drugs and thereby expand the pool of potential therapies for use in HNSCC treatment. We analyzed 508 HNSCC patients with sequencing information from the Genomic Data Commons (GDC) database and assessed which biological pathways were significantly enriched for somatic mutations or copy number alterations. We then further classified pathways as either "light" or "dark" to the current reach of FDA-approved cancer drugs using the Cancer Targetome, a compendium of drug-target information. Light pathways are statistically enriched with somatic mutations (or copy number alterations) and contain one or more targets of current FDA-approved cancer drugs, while dark pathways are enriched with somatic mutations (or copy number alterations) but not currently targeted by FDA-approved cancer drugs. Our analyses indicated that approximately 35-38% of disease-specific pathways are in scope for repurposing of current cancer drugs. We further assess light and dark pathways for subgroups of patient tumor samples according to HPV status. The framework of light and dark pathways for HNSCC-enriched biological pathways allows us to better prioritize targeted therapies for further research in HNSCC based on the HNSCC genetic landscape and FDA-approved cancer drug information. We also highlight the importance in the identification of sub-pathways where targeting and cross targeting of other pathways may be most beneficial to predict positive or negative synergy with potential clinical significance. This framework is ideal for precision drug panel development, as well as identification of highly aberrant, untargeted candidates for future drug development