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.

A Mouse Model of Chronic West Nile Virus Disease.

Infection with West Nile virus (WNV) leads to a range of disease outcomes, including chronic infection, though lack of a robust mouse model of chronic WNV infection has precluded identification of the immune events contributing to persistent infection. Using the Collaborative Cross, a population of recombinant inbred mouse strains with high levels of standing genetic variation, we have identified a mouse model of persistent WNV disease, with persistence of viral loads within the brain. Compared to lines exhibiting no disease or marked disease, the F1 cross CC(032x013)F1 displays a strong immunoregulatory signature upon infection that correlates with restraint of the WNV-directed cytolytic response. We hypothesize that this regulatory T cell response sufficiently restrains the immune response such that a chronic infection can be maintained in the CNS. Use of this new mouse model of chronic neuroinvasive virus will be critical in developing improved strategies to prevent prolonged disease in humans.

IL-10 and integrin signaling pathways are associated with head and neck cancer progression.

BACKGROUND: Head and neck cancer is morbid with a poor prognosis that has not significantly improved in the past several decades. The purpose of this study was to identify biological pathways underlying progressive head and neck cancer to inform prognostic and adjuvant strategies. We identified 235 head and neck cancer patients in The Cancer Genome Atlas (TCGA) with sufficient clinical annotation regarding therapeutic treatment and disease progression to identify progressors and non-progressors. We compared primary tumor gene expression and mutational status between these two groups. RESULTS: 105 genes were differentially expressed between progressors and nonprogressors (FDR < 0.05). Pathway analyses revealed deregulation (FDR < 0.05) of multiple pathways related to integrin signaling as well as IL-10 signaling. A number of genes were uniquely mutated in the progressor cohort including increased frequency of truncating mutations in CTCF (P = 0.007). An 11-gene signature derived from a combination of unique mutations and differential expression was identified (PAGE4, SMTNL1, VTN, CA5A, C1orf43, KRTAP19-1, LEP, HRH4, PAGE5, SEZ6L, CREB3). This signature was associated with decreased overall survival (Logrank Test; P = 0.03443). Cox modeling of both key clinical features and the signature was significant (P = 0.032) with the greatest prognostic improvement seen in the model based on nodal extracapsular spread and alcohol use alone (P = 0.004). CONCLUSIONS: Molecular analyses of head and neck cancer tumors that progressed despite treatment, identified IL-10 and integrin pathways to be strongly associated with cancer progression. In addition, we identified an 11-gene signature with implications for patient prognostication. Mutational analysis highlighted a potential role for CTCF, a crucial regulator of long-range chromatin interactions, in head and neck cancer progression.

Microenvironment-dependent growth of Sezary cells in humanized IL-15 mice.

Sezary syndrome (SS) is a rare, aggressive leukemic variant of cutaneous T-cell lymphoma (CTCL) that lacks adequate therapeutic options and representative small-animal models. Here, we demonstrate that IL-15 is a critical CTCL growth factor. Importantly, an immunodeficient knock-in mouse model genetically engineered to express human IL-15 uniquely supported the growth of SS patient samples relative to conventional immunodeficient mouse strains. SS patient-derived xenograft (PDX) models recapacitated key pathological features of the human disease, including skin infiltration and spread of leukemic cells to the periphery, and maintained the dependence on human IL-15 upon serial in vivo passaging. Detailed molecular characterization of the engrafted cells by single-cell transcriptomic analysis revealed congruent neoplastic gene expression signatures but distinct clonal engraftment patterns. Overall, we document an important dependence of Sezary cell survival and proliferation on IL-15 signaling and the utility of immunodeficient humanized IL-15 mice as hosts for SS - and potentially other T and NK cell-derived hematologic malignancies - PDX model generation. Furthermore, these studies advocate the thorough molecular understanding of the resultant PDX models to maximize their translational impact.

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

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.

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.

Natural Product Target Network Reveals Potential for Cancer Combination Therapies.

A body of research demonstrates examples of in vitro and in vivo synergy between natural products and anti-neoplastic drugs for some cancers. However, the underlying biological mechanisms are still elusive. To better understand biological entities targeted by natural products and therefore provide rational evidence for future novel combination therapies for cancer treatment, we assess the targetable space of natural products using public domain compound-target information. When considering pathways from the Reactome database targeted by natural products, we found an increase in coverage of 61% (725 pathways), relative to pathways covered by FDA approved cancer drugs collected in the Cancer Targetome, a resource for evidence-based drug-target interactions. Not only is the coverage of pathways targeted by compounds increased when we include natural products, but coverage of targets within those pathways is also increased. Furthermore, we examined the distribution of cancer driver genes across pathways to assess relevance of natural products to critical cancer therapeutic space. We found 24 pathways enriched for cancer drivers that had no available cancer drug interactions at a potentially clinically relevant binding affinity threshold of < 100nM that had at least one natural product interaction at that same binding threshold. Assessment of network context highlighted the fact that natural products show target family groupings both distinct from and in common with cancer drugs, strengthening the complementary potential for natural products in the cancer therapeutic space. In conclusion, our study provides a foundation for developing novel cancer treatment with the combination of drugs and natural products.

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.

Induction of anaplastic lymphoma kinase (ALK) as a novel mechanism of EGFR inhibitor resistance in head and neck squamous cell carcinoma patient-derived models.

Head and neck squamous cell carcinoma (HNSCC) currently only has one FDA-approved cancer intrinsic targeted therapy, the epidermal growth factor receptor (EGFR) inhibitor cetuximab, to which only approximately 10% of tumors are sensitive. In order to extend therapy options, we subjected patient-derived HNSCC cells to small-molecule inhibitor and siRNA screens, first, to find effective combination therapies with an EGFR inhibitor, and second, to determine a potential mechanistic basis for repurposing the FDA approved agents for HNSCC. The combinations of EGFR inhibitor with anaplastic lymphoma kinase (ALK) inhibitors demonstrated synergy at the highest ratio in our cohort, 4/8 HNSCC patients' derived tumor cells, and this corresponded with an effectiveness of siRNA targeting ALK combined with the EGFR inhibitor gefitinib. Co-targeting EGFR and ALK decreased HNSCC cell number and colony formation ability and increased annexin V staining. Because ALK expression is low and ALK fusions are infrequent in HNSCC, we hypothesized that gefitinib treatment could induce ALK expression. We show that ALK expression was induced in HNSCC patient-derived cells both in 2D and 3D patient-derived cell culture models, and in patient-derived xenografts in mice. Four different ALK inhibitors, including two (ceritinib and brigatinib) FDA approved for lung cancer, were effective in combination with gefitinib. Together, we identified induction of ALK by EGFR inhibitor as a novel mechanism potentially relevant to resistance to EGFR inhibitor, a high ratio of response of HNSCC patient-derived tumor cells to a combination of ALK and EGFR inhibitors, and applicability of repurposing ALK inhibitors to HNSCC that lack ALK aberrations.

Stand and Move at Work.

Cardiovascular disease and diabetes are epidemic in the United States, and efforts to shift this trend have been largely ineffective. The greatest challenge that health care practitioners face is inspiring the lifestyle changes necessary to prevent or reverse these conditions. New evidence suggests that minimal activity, such as simply standing up periodically and moving around can reduce biomarkers of cardiovascular disease and diabetes. Given the challenge and temporary nature of inspiring habitually sedentary individuals to take on intensive exercise routines, this is an exciting prospect. With this new information, the question becomes: "How do we inspire individuals and populations to get up and move?" Dr. Matthew Buman and his group at Arizona State University are addressing this question through researching methods to inspire individuals and groups to stand at move at work. In support of Dr. Buman's work, we have leveraged subject generated postural data gathered by his group to create a pipeline that processes and analyzes the patterns of subject movement with the prompts they received in order to identify the most effective prompt that elicits standing and moving behavior. The pipeline helps researchers in his group visualize their data in an interactive way and to help inform statistical analyses. In future directions, this pipeline structure can be adopted by various aspects of clinical work such as diagnosis, selection of treatment options, monitoring for changes in a patient's conditions over time, evaluating efficacy of different treatment options, and promoting shared decision-making between providers and patients. They can range from novel ways to visualize PGD to help clinicians and patients identify important and actionable trends, to novel computational solutions, to using these data together with the traditional EHR data to provide clinical decision support that may or may not include visual presentations. Importantly, in this challenge, our focus is on integrating PGD with EHR to improve care within the clinical context, rather than on using these data outside of traditional care settings to promote health and wellness.

Evidence-Based Precision Oncology with the Cancer Targetome.

A core tenet of precision oncology is the rational choice of drugs to interact with patient-specific biological targets of interest, but it is currently difficult for researchers to obtain consistent and well-supported target information for pharmaceutical drugs. We review current drug-target interaction resources and critically assess how supporting evidence is handled. We introduce the concept of a unified Cancer Targetome to aggregate drug-target interactions in an evidence-based framework. We discuss current unmet needs and the implications for evidence-based clinical omics. The focus of this review is precision oncology but the discussion is highly relevant to targeted therapies in any area.

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.

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.