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Importance: The incidence and biochemical consequences of rare tumor subtypes are often hard to study. Fibrolamellar liver cancer (FLC) is one such rare malignancy affecting adolescents and young adults. To better characterize the incidence and biochemical consequences of this disease, we combined a comprehensive analysis of electronic medical record and national payee data and find that FLC incidence is likely 6–8 times higher than previous estimates. By deploying unsupervised learning modes on clinical laboratory data on patients with hyperammonemia, we find that FLC-associated hyperammonemia mirrors metabolic dysregulation in Urea Cycle Disorders. We demonstrate that advanced computational analysis of rich clinical datasets can provide key clinical and biochemical insights into rare cancers.

One hundred years have passed since the discovery of insulin—an achievement that transformed diabetes from a fatal illness into a manageable chronic condition. The decades since that momentous achievement have brought ever more rapid innovation and advancement in diabetes research and clinical care. To celebrate the important work of the past century and help to chart a course for its continuation into the next, the Canadian Institutes of Health Research’s Institute of Nutrition, Metabolism and Diabetes and the U.S. National Institutes of Health’s National Institute of Diabetes and Digestive and Kidney Diseases recently held a joint international symposium, bringing together a cohort of researchers with diverse interests and backgrounds from both countries and beyond to discuss their collective quest to better understand the heterogeneity of diabetes and thus gain insights to inform new directions in diabetes treatment and prevention. This article summarizes the proceedings of that symposium, which spanned cutting-edge research into various aspects of islet biology, the heterogeneity of diabetic phenotypes, and the current state of and future prospects for precision medicine in diabetes.

Background. Current lipid-lowering drugs often leave significant residual risk for adverse outcomes. Identification of previously approved drugs for new indications, drug repurposing, may provide a cost effective alternative to de novo drug developing.Objectives. We combined clinical, transcriptomic, computational, and experimental strategies to explore lipid-lowering and plaque-stabilizing effects of atypical antidepressant trazodone.Methods. First, a connectivity mapping strategy was used to match rosuvastatin gene expression signature derived from a clinical trial of 85 patients with to the expression patterns of 1,309 different small molecules to discover a similarity between the rosuvastatin and trazodone gene expression signatures. Then, we assessed the lipid-lowering ability of trazodone in vitro using HepG2 cells and in vivo using molecular imaging of rabbit atherosclerotic lesions. In addition, we analyzed electronic medical records of patients from three large medical centers who had a prescription for trazodone and lipid laboratory measurements available.Results. Trazodone significantly reduced cholesterol levels in the HepG2 human hepatocyte model, decreased atherosclerotic plaque burden in a rabbit model and lowered low-density lipoprotein (LDL) cholesterol levels in patients.Conclusion. Our results indicate that trazodone may be a promising candidate for adjunctive lipid lowering therapy. It may provide significant benefits to patients with hyperlipidemia, including lipid level reduction and formation of a more favorable atherosclerotic plaque morphology. Patients diagnosed with major depressive disorder requiring better lipid control would benefit the most from the for adjunctive lipid lowering therapy.

By linking “real-word” patient data mined from electronic medical records to the results of clinical genomic testing, we can analyze the impact of the rapid expansion in tumor molecular profiling on the management of cancer patients over the past several years. Theoretically, the widespread adoption of comprehensive molecular characterization of patient tumors using next-generation sequencing panels provides new opportunities for advances in precision oncology. For patients, identification of specific alterations can potentially lead to new therapeutic options from an ever-widening array of targeted agents. For example, the recent FDA approval in 2017 of pembrolizumab for patients with unresectable or metastatic, microsatellite instability-high (MSI-H) or mismatch repair deficient (dMMR) solid tumors is the first example of an FDA approval agnostic with regards to the tumor site of origin. The availability of this novel treatment option has likely led to more frequent use of tumor molecular profiling in the clinical setting, and in the future, we can expect similar examples of treatment strategies that favor specific genomic perturbations over the tumor site of origin. However, despite their ever-expanding use in the clinical setting, the overall impact of genomic testing remains unclear, and evidence demonstrating improvement in patient outcomes is lacking. In this study, we present the development of a database that combines clinical genomic results from our internal next-generation sequencing panel, as well as commercially available external clinical genomic panels, with a variety of data points from our institution’s electronic medical record (EMR). This data set allows us to measure the utility of genomic tumor testing for the management of cancer patients. We analyze the magnitude of positive impact for various tumor types, identify barriers to efficient use of genomic tumor testing, and assess for disparities in the utilization of testing. Patient survival data relative to the clinical action of obtaining tumor molecular profiling can also be measured. We find that a small fraction of patients dies before results return and any action can be taken, especially in cases of pancreatic cancer, suggesting that molecular profiling should be considered earlier in the course of disease for certain cancer types. Combining information on patient outcomes from “real-world” EMR data with clinical genomic testing provides the additional opportunity of identifying exceptional responders or non-responders with greater efficiency, which can lead to the discovery of new therapeutic targets and treatments as well as the identification of novel biomarkers for response or resistance to therapy. Citation Format: Debajyoti Datta, Atul Butte, Theodore Goldstein. Linking clinical molecular profiles of tumors to the electronic medical record [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1695.

Flow cytometry and mass cytometry are used to diagnose diseases and to predict clinical outcomes. Here, we propose a novel strategy to predict clinical outcomes using cytometry data without cell gating (CytoDx; accessible at github.com/hzc363/CytoDx). CytoDx is able to predict the response to influenza vaccine using heterogeneous datasets, demonstrating that it is not only accurate but also robust to batch effects and cytometry platforms.

Flow cytometry has been used to analyze cell populations with a certain condition, but because of the limitations of a single flow cytometry experiment, results only present a small portion of cell populations. Meta-analysis has been used to compare and contrast multiple datasets in hopes of discovering new insights. Scientists can then identify more cell populations linked to the condition. Therefore, we are developing a method to standardize and analyze multiple flow cytometry datasets.

Bio-medical knowledge, including immunology-related knowledge, evolves and changes over time. Examining such changes, along with other immune-related patterns and trends may reflect changes in the field and may assist in detecting new and un-addressed areas of research. We have recently developed a cytokine-centered knowledgebase focusing on the role of cytokines in diagnostics and therapeutics and their association with immune cell types and a variety of different diseases. As a part of its initial development, the knowledgebase was extensively populated with information extracted from relevant biomedical literature. Here, we present interesting cytokine-, cell- and disease-related trends found in the literature (and captured in our knowledgebase). For example, the association of Rheumatoid Arthritis (RA) with tumor necrosis factor alpha (TNFa) has increased over time; on the other hand, at the same time, there was a dramatic decrease in the number of publications linking RA with Interleukin 1 indicating a shift in the focus of RA-cytokine related research. Such changes over time in immune-related topics as well as the association of cytokines and diseases across different tissue types, age groups and ethnic groups demonstrates the usefulness of the knowledgebase in capturing immune-related patterns and focusing at possibly useful avenues of research.

Several independent studies been conducted to understand the genetic and environmental factors influencing the cause of atopic dermatitis, which is an inflammatory skin disorder. To leverage the power of combining the studies we downloaded seven publicly available datasets on atopic dermatitis from ImmPort data portal (https://immport.niaid.nih.gov/). These studies include wide range of molecular and cellular measurements like ELISA, flow and complete blood count (CBC) across multiple cohort and various sample types. We have taken the meta-analysis approach to understand the factors influencing the disease phenotype by integrating the datasets measured under different conditions to find the associations between independent and combined effects. The molecular and cellular measurements were normalized such that data is comparable across studies. We have found a strong association of certain inflammatory cytokines in atopic dermatitis patients under specific conditions, and perturbations in certain cell types of these patients. We also evaluate the influence of gender, age and vaccine response in atopic dermatitis patients with respect to healthy controls.

To date, our understanding of a normal immune system is far behind that of other healthy organ systems. One reason for this is the lack of a widespread adoption of standardization in the lab techniques, especially flow cytometry. Here we demonstrate the use of the Immunology Database and Analysis Portal (immport.niaid.nih.gov) as a source of publicly available flow cytometry files from hundreds of participants in several clinical trials, to study immune cells from the blood of healthy individuals. To characterize well-defined cells in a normal immune system, we used an unbiased, gate-free method to compare data from different cytometers and antibody staining panels, based on the distribution of fluorescence intensity of the markers. In order to perform the meta-analyses, the marker information from each file was obtained in an automated fashion and their nomenclature was made consistent. Various transformation and normalization strategies were applied and evaluated to make the flow cytometry data comparable across studies. Initial promising results were observed for the cell-surface markers used to define T and B cells in general, and some specific subsets including regulatory T cells as well as plasmablasts. We found high concordance in normal individuals from two studies performed at different times measured within the same facility. The extension of this approach to studies of healthy individuals across facilities promises to give insights towards the normal immune system.

Thymic epithelial cell loss results in age-related thymic involution and immune deficiency. We investigated mechanisms of TEC loss during chronological aging (6 weeks, 7 months, 15 months) of normal C57BL6/J mice. Aged TEC showed replicative senescence with increased apoptosis, decreased proliferation, decreased telomerase activity and shortened telomere length. A subpopulation of aged TEC expressed Fas in response to pro-inflammatory cytokines (TNFα,IL-1β) made by aged thymocytes. Fas signaling and caspase-8 activation were induced by FasL selectively expressed by aged intrathymic memory T cells. Combined pharmacological inhibition of Caspase-8 and TEC growth stimulation by KGF restored thymopoiesis to neonatal levels. Aged TEC differentially expressed a 175-gene set predicted to be dually regulated by two transcription factors, NF-κB and HNF4α, which are activated by inflammatory cytokines and fatty acids, respectively. NF-κB and HNF4α signaling in aged TEC was confirmed by ChIP assays demonstrating binding to promoters of age-related genes, gene reporter assays, and synergistic induction of TEC apoptosis by inflammatory cytokines and fatty acids. TEC aging is mediated by the convergence of different TFs responsive to inflammatory and metabolic signals on shared promoters. Thymic regeneration in aging will require mitigation of the effects of non-autonomous inflammatory and metabolic signals, e.g., from infection and obesity, which drive TEC death and thymic involution.

The identification of cell populations from flow cytometry has rarely been mapped in a multi-dimensional space. Instead, the focus is typically limited to a small number of pre-specified cell types already described in the literature. We propose to re-conceptualize the flow cytometry panel as a discovery tool to disentangle complex flow data into the simplest, most clinically relevant cell types. We present a combinatorial method to enumerate all possible immunophenotypes within a flow panel from a clinical trial study. We applied this approach to 11,000 raw flow cytometry files from a multi-panel flow experiment in a ragweed allergy clinical trial (ImmPort:SDY1), available from the publicly accessible, NIAID-funded Immunology Database and Analysis portal (ImmPort; immport.niaid.nih.gov). Files were processed through an automated pipeline that applied ImmPort’s FLOCK autogating tool to segregate cell populations based on the expression of individual surface markers. This yielded roughly 59,000 unique cell populations. Unsupervised hierarchical clustering revealed cell populations that were highly correlated with treatment conditions, based on the Pearson similarity measure. From these results we identified a subset of monocytes with positive expression for CD23 that were correlated with clinical outcome. We believe this approach can help identify the minimal set of markers needed to characterize functionally distinct cell populations associated with clinical outcome.

Neonates are highly susceptible to severe infection by a variety of intracellular pathogens, including M. tuberculosis and T. gondii. A large body of evidence suggests that a limitation in T helper 1 (Th1) responses accounts for much of this susceptibility. Our lab has previously defined a number of limitations in neonatal naive CD4+ T cells obtained from umbilical cord blood that restrict Th1 generation in vitro. These include decreased expression by naive CD4+ T cells of CD40 ligand and IFN-γ. Unexpectedly, we have also observed increased calcium flux in neonatal cells in response to CD3 mAb cross-linking. Because of the diverse molecular differences between neonatal and adult naive CD4+ T cells, we investigated differences in microRNA expression. miR-181a, which has been shown to regulate calcium flux positively in murine T cells, was expressed at higher levels in neonatal naive CD4+ T cells, consistent with increased calcium flux. Its predicted mRNA targets are expressed at lower levels in neonatal naive CD4+ T cells by gene set enrichment analysis (GSEA). Others have shown that over-expression of miR-181a results in increased phosphorylation of Erk1/2 after CD3 mAb crosslinking, and we are examining the activity of the Erk pathway in neonatal and adult naive CD4+ T cells. Also in progress are studies using a stable, lentiviral system to determine the effects of miR-181a over-expression and knockdown in human CD4 T cells focusing on validated murine mRNA targets.

Immune system function generally degrades with age and is associated with increased risk of infection and disease. Though differences between young and old have been noted in many immune system components, no system wide understanding of how these disparate observation act together exists to date, nor how they relate to genes found to associated with increased longevity, many of which are immune related. Here we characterize the immune system of 29 young and old individuals by concurrently measuring from peripheral blood, immune cell subset frequency, serum cytokines, gene expression and individual cellular responses to cytokine stimuli by pathway specific phospho-protein abundance. We identify age-dependent changes in STAT signaling baseline and in response to stimulation by a panel of 7 different cytokines, particularly prominent in CD8 and CD4 T cells, but also in monocytes and B-cells. The observed differences in cellular responses are not due to adaptation to higher level of cytokine stimuli but rather to an inert inability to mount a full response, many times augmented by a higher base line phosphorylation level in the elderly. We construct an immune network spanning multiple biological layers and identify co-occurring modules which link longevity associated genes with these cellular immune phenotypes. We quantify the contributions of these modules to the observed reduction in cellular response to stimuli in the elderly and suggest a common responsible mechanism.

Blood is a complex tissue made up of many cell-types, each with its own functional attributes and molecular signature. Yet, the proportions of any given cell-type in the blood can vary markedly, even between normal individuals. This results in a significant loss of sensitivity in gene expression studies of blood cells and great difficulty in identifying the cellular source of any perturbations. Ideally, one would like to perform differential expression analysis between patient groups for each of the cell-types within a tissue but this is impractical and prohibitively expensive. Here we present a statistical methodology which, given microarray data from two groups of biological samples and the relative cell-type frequencies of each sample, estimates in a virtual manner the gene expression data for each cell-type at a group level, and uses these to identify differentially expressed genes at a cell-type specific level between groups. To validate the utility of csSAM, we apply our method to whole blood gene expression measurements of stable and acute rejection renal transplant patients. csSAM was able to identify hundreds of genes that were upregulated in monocytes of the acute rejection patients, as well as in other cell-types, that were undetectable at the whole blood level. Our methodology is widely applicable and enables the analysis of gene expression in complex tissues at a much higher resolution than previously possible.

Wiskott-Aldrich Syndrome (WAS) is an X-linked recessive immunodeficiency disorder with eczema, thrombocytopenia and high susceptibility to opportunistic and pyogenic infections. The gene product of the WAS locus, WAS protein (WASP), is expressed in a hematopoietic-specific fashion and regulates cytoskeletal actin reorganization via Cdc42 and Arp2/3 interactions. Non-random inactivation of the X chromosome carrying the defective WASP gene in all peripheral blood cells from obligate female carriers of WAS suggests a selective advantage of hematopoietic stem cells or immature progenitor cells expressing the intact WASP gene. Because such progenitor cells are dependent on the Kit receptor/Kit ligand (KL) pathway, we tested whether or not WASP plays a role in signaling responses through Kit. WASP and interacting proteins WIP and Arp2/3 were strongly phosphorylated in response to KL stimulation of Mo7e cells. Time kinetics revealed onset of tyrosine phosphorylation of WASP as early as 1 min and a maximum at 5 min after KL stimulation. Although real-time KL-induced actin reorganization and KL-mediated spreading of bone marrow-derived mast cells (BMMC) on fibronectin-coated surfaces were grossly normal, KL-induced formation of filopodia was significantly decreased in number and size in the absence of WASP. In addition, KL-induced calcium-flux in BMMCs was aberrant in the absence of WASP suggesting that KL-dependent calcium signals and cytoskeletal rearrangement are linked through WASP. When BMMC cultures were established from WASP heterozygous female mice using KL as a growth factor, the cultures initially contained a mixture of WASP positive and negative populations. KL-driven differentiation into mature BMMCs eventually resulted in homogenous WASP positive cultures derived from the WASP positive progenitors. Thus, WASP expression conferred a selective advantage to the development of Kit-dependent hematopoiesis consistent with the selective advantage of WASP positive blood cells observed in WAS heterozygous female humans. Finally, KL-mediated gene expression in BMMCs derived from WASP negative mice or WT controls was compared and revealed in summary that at least 30% of all changes are WASP-dependent. The results indicate that WASP is downstream of Kit signaling and necessary for Kit-mediated filopodia formation, cell survival and gene expression.