Suyan Tian

Integrative Responses to IL-17 and TNF-α in Human Keratinocytes Account for Key Inflammatory Pathogenic Circuits in Psoriasis

Psoriasis is a complex inflammatory disease mediated by tumor necrosis factor (TNF)-α and cytokines secreted by specialized T-cell populations, e.g., IL-17, IL-22, and IFN-γ. The mechanisms by which innate and adaptive immune cytokines regulate inflammation in psoriasis are not completely understood. We sought to investigate the effects of TNF-α and IL-17 on keratinocyte (KC) gene profile, to identify genes that might be coregulated by these cytokines and determine how synergistically activated genes relate to the psoriasis transcriptome. Primary KCs were stimulated with IL-17 or TNF-α alone, or in combination. KC responses were assessed by gene array analysis, followed by reverse transcriptase-PCR confirmation for significant genes. We identified 160 genes that were synergistically upregulated by IL-17 and TNF-α, and 196 genes in which the two cytokines had at least an additive effect. Synergistically upregulated genes included some of the highest expressed genes in psoriatic skin with an impressive correlation between IL-17/TNF-α-induced genes and the psoriasis gene signature. KCs may be key drivers of pathogenic inflammation in psoriasis through integrating responses to TNF-α and IL-17. Our data predict that psoriasis therapy with either TNF or IL-17 antagonists will produce greater modulation of the synergistic/additive gene set, which consists of the most highly expressed genes in psoriasis skin lesions.

Meta-Analysis Derived (MAD) Transcriptome of Psoriasis Defines the “Core” Pathogenesis of Disease

The cause of psoriasis, a common chronic inflammatory skin disease, is not fully understood. Microarray experiments have been widely used in recent years to identify genes associated with psoriasis pathology, by comparing expression levels of lesional (LS) with adjacent non-lesional (NL) skin. It is commonly observed that the differentially expressed genes (DEGs) differ greatly across experiments, due to variations introduced in the microarray experiment pipeline. Therefore, a statistically based meta-analytic approach, which combines the results of individual studies, is warranted. In this study, a meta-analysis was conducted on 5 microarray data sets, including 193 LS and NL pairs. We termed this the Meta-Analysis Derived (MAD) transcriptome. In “MAD-5” transcriptome, 677 genes were up-regulated and 443 were down-regulated in LS skin compared to NL skin. This represents a much larger set than the intersection of DEGs of these 5 studies, which consisted of 100 DEGs. We also analyzed 3 of the studies conducted on the Affymetrix hgu133plus2 chips and found a greater number of DEGs (1084 up- and 748 down-regulated). Top canonical pathways over-represented in the MAD transcriptome include Atherosclerosis Signaling and Fatty Acid Metabolism, while several “new” genes identified are involved in Cardiovascular Development and Lipid Metabolism. These findings highlight the relationship between psoriasis and systemic manifestations such as the metabolic syndrome and cardiovascular disease. Then, the Meta Threshold Gradient Descent Regularization (MTGDR) algorithm was used to select potential markers distinguishing LS and NL skin. The resulting set (20 genes) contained many genes that were part of the residual disease genomic profile (RDGP) or “molecular scar” after successful treatment, and also genes subject to differential methylation in LS tissues. To conclude, this MAD transcriptome yielded a reference list of reliable psoriasis DEGs, and represents a robust pool of candidates for further discovery of pathogenesis and treatment evaluation.

Multiple interferon stimulated genes synergize with the zinc finger antiviral protein to mediate anti-alphavirus activity

The zinc finger antiviral protein (ZAP) is a host factor that mediates inhibition of viruses in the Filoviridae, Retroviridae and Togaviridae families. We previously demonstrated that ZAP blocks replication of Sindbis virus (SINV), the prototype Alphavirus in the Togaviridae family at an early step prior to translation of the incoming genome and that synergy between ZAP and one or more interferon stimulated genes (ISGs) resulted in maximal inhibitory activity. The present study aimed to identify those ISGs that synergize with ZAP to mediate Alphavirus inhibition. Using a library of lentiviruses individually expressing more than 350 ISGs, we screened for inhibitory activity in interferon defective cells with or without ZAP overexpression. Confirmatory tests of the 23 ISGs demonstrating the largest infection reduction in combination with ZAP revealed that 16 were synergistic. Confirmatory tests of all potentially synergistic ISGs revealed 15 additional ISGs with a statistically significant synergistic effect in combination with ZAP. These 31 ISGs are candidates for further mechanistic studies. The number and diversity of the identified ZAP-synergistic ISGs lead us to speculate that ZAP may play an important role in priming the cell for optimal ISG function.

Cellular Immune Suppression in Paraneoplastic Neurologic Syndromes Targeting Intracellular Antigens

BACKGROUND Tumor treatment is the mainstay of therapy for paraneoplastic neurologic disorders (PNDs), but it is only effective in some cases and other treatment options are limited. OBJECTIVE To evaluate the short-term use of a combination of prednisone and tacrolimus for acute neurologic worsening in PND in which intracellular antigens are targeted. DESIGN Retrospective single-center case series of patients with PND treated with tacrolimus. SETTING The Rockefeller University Hospital, a research hospital in New York, New York. PATIENTS Twenty-six patients with PND with high titer (≥1:1000) anti-HuD, anti-Yo, or anti-CRMP5 autoantibodies were enrolled. Patients were referred from Memorial Sloan Kettering Cancer Center or self-referred. Two patients discontinued intervention owing to adverse events. INTERVENTIONS Patients were treated with tacrolimus, 0.15-0.30 mg/kg per day, in 2 divided oral doses with 60 mg per day of oral prednisone, tapered off during 1 to 4 weeks. MAIN OUTCOME MEASURES The primary outcome measure was median survival. Neurologic examinations before and after treatment as well as adverse events are described. RESULTS Median survival time was 52 months from time of diagnosis. Some patients experienced neurologic improvement that was functionally meaningful. The incidence of adverse events was similar to that generally reported with tacrolimus. CONCLUSIONS A short course of prednisone and tacrolimus to target central nervous system T cells in patients with PND with acute neurologic decline in which intracellular antigens are targeted was well tolerated and warrants further study. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00378326.

Test of IL28B Polymorphisms in Chronic Hepatitis C Patients Treated with PegIFN and Ribavirin Depends on HCV Genotypes: Results from a Meta-Analysis

Background Many studies have been published on the association between single nucleotide polymorphisms (SNP) near the IL28B gene and response to the combined treatments of pegylated-interferon (PegIFN) and ribavirin (RBV) in chronic HCV-infected patients, but without identical conclusions. The aim of this study was to assess impact of the IL28B polymorphisms on the effect of HCV standard treatment using meta-analysis based method. Methods Association studies between polymorphisms of rs12979860 or rs8099917 and response to PegIFN/RBV treatment in chronic HCV patients were retrieved from PubMed. Data of qualified studies on sustained virological response (SVR) in different genotypes were extracted and analyzed using meta-analysis method in Stata 10 software. Results Thirty-four papers, containing 46 independent studies, were included in the analysis. In the HCV G1/4 patients without treatment history, individuals carrying rs12979860 CC genotype were more likely to achieve SVR (OR 3.97, 95%CI 3.29–4.80) compared to those carrying CT/TT genotypes. Similar results were observed in the HCV G1/4 patients with unsuccessful or unknown treatment history (OR 3.76, 95%CI 2.67–5.28) or in the patients co-infected with human immunodeficiency virus (OR 5.20, 95%CI 3.04–8.90). However, associations could not be observed in HCV G2/3 patients. For rs8099917, similar results were obtained for genotype TT compared to genotypes TG/GG, indicating that TT genotype was significantly associated with better treatment response in patients infected with genotype 1 or 4 HCV, but not genotype 2 or 3 HCV. Conclusion Polymorphisms of rs12979860 and rs8099917 near IL28B only associate with the treatment response to PegIFN/RBV in patients infected with HCV genotype 1 or 4 but not with genotype 2 or 3, irrespective of the previous treatment history or HIV co-infected status. Therefore, identification of IL28B genotypes is necessary only in patients infected with relatively difficult-to-treat genotype 1 or 4 HCV.

Increased expression of interleukin-17 pathway genes in nonlesional skin of moderate-to-severe psoriasis vulgaris

Psoriasis vulgaris is an inflammatory immune‐mediated disease, with lesional skin characterized by sharply demarcated, erythematous scaly plaques. Uninvolved psoriatic skin appears clinically similar to normal skin. However, it has been hypothesized that inflammatory cytokines, e.g. interleukin (IL)‐17, may affect any organ or tissue having a vascular supply; thus, distant uninvolved skin could be exposed to increased circulating IL‐17.

Harnessing Naturally Occurring Tumor Immunity: A Clinical Vaccine Trial in Prostate Cancer

Background Studies of patients with paraneoplastic neurologic disorders (PND) have revealed that apoptotic tumor serves as a potential potent trigger for the initiation of naturally occurring tumor immunity. The purpose of this study was to assess the feasibility, safety, and immunogenicity of an apoptotic tumor-autologous dendritic cell (DC) vaccine. Methods and Findings We have modeled PND tumor immunity in a clinical trial in which apoptotic allogeneic prostate tumor cells were used to generate an apoptotic tumor-autologous dendritic cell vaccine. Twenty-four prostate cancer patients were immunized in a Phase I, randomized, single-blind, placebo-controlled study to assess the safety and immunogenicity of this vaccine. Vaccinations were safe and well tolerated. Importantly, we also found that the vaccine was immunogenic, inducing delayed type hypersensitivity (DTH) responses and CD4+ and CD8+ T cell proliferation, with no effect on FoxP3+ regulatory T cells. A statistically significant increase in T cell proliferation responses to prostate tumor cells in vitro (p = 0.002), decrease in prostate specific antigen (PSA) slope (p = 0.016), and a two-fold increase in PSA doubling time (p = 0.003) were identified when we compared data before and after vaccination. Conclusions An apoptotic cancer cell vaccine modeled on naturally occurring tumor immune responses in PND patients provides a safe and immunogenic tumor vaccine. (ClinicalTrials.gov number NCT00289341). Trial Registration ClinicalTrials.gov NCT00289341

Hierarchical-TGDR: Combining biological hierarchy with a regularization method for multi-class classification of lung cancer samples via high-throughput gene-expression data

Regularization methods that simultaneously select a small set of the most relevant features and build a classifier using the selected features have gained much attention recently in problems of classification of “omics” data. In many multi-class classification problems, which are of practical importance, the classes are naturally endowed with a hierarchical structure. However, such natural hierarchical structure is often ignored. Here, we use an existing regularization algorithm, Threshold Gradient Descent Regularization, in a hierarchical fashion, which takes advantage of natural biological structure to specifically tackle multi-class classification of microarray data. We apply this approach to one of the tasks presented by the sbv IMPROVER Diagnostic Signature Challenge: the Lung Cancer Sub-Challenge. Gene expression data from non-small cell lung carcinoma were used to classify tumors into adenocarcinoma and squamous cell carcinoma subtypes, and their clinical stages (I and II). Genetic and transcriptomic differences between AC and SCC have been reported, indicating a potentially different pathological mechanism of differentiation and invasion. The results from this analysis show that hierarchical-TGDR outperforms pairwise TGDRs in terms of predictive performance, and is substantially more parsimonious. In conclusion, the hierarchical-TGDR approach trains classifiers in a top-down fashion by considering the naturally existing structure within the data, reducing the number of pairwise-TGDRs to be trained. It also highlights different mechanisms of “invasion” in the two subtypes. This work suggests that incorporating known biological information into classification algorithms, such as data hierarchies, can improve the discriminative performance and biological interpretation of this classifier.

Dendritic cells loaded with FK506 kill T cells in an antigen-specific manner and prevent autoimmunity in vivo

FK506 (Tacrolimus) is a potent inhibitor of calcineurin that blocks IL2 production and is widely used to prevent transplant rejection and treat autoimmunity. FK506 treatment of dendritic cells (FKDC) limits their capacity to stimulate T cell responses. FK506 does not prevent DC survival, maturation, or costimulatory molecule expression, suggesting that the limited capacity of FKDC to stimulate T cells may be due to inhibition of calcineurin signaling in the DC. Instead, we demonstrate that DC inhibit T cells by sequestering FK506 and continuously releasing the drug over several days. T cells encountering FKDC proliferate but fail to upregulate the survival factor bcl-xl and die, and IL2 restores both bcl-xl and survival. In mice, FKDC act in an antigen-specific manner to inhibit T-cell mediated autoimmune arthritis. This establishes that DCs can act as a cellular drug delivery system to target antigen specific T cells. DOI: http://dx.doi.org/10.7554/eLife.00105.001

Multi-TGDR: A Regularization Method for Multi-Class Classification in Microarray Experiments

Background As microarray technology has become mature and popular, the selection and use of a small number of relevant genes for accurate classification of samples has arisen as a hot topic in the circles of biostatistics and bioinformatics. However, most of the developed algorithms lack the ability to handle multiple classes, arguably a common application. Here, we propose an extension to an existing regularization algorithm, called Threshold Gradient Descent Regularization (TGDR), to specifically tackle multi-class classification of microarray data. When there are several microarray experiments addressing the same/similar objectives, one option is to use a meta-analysis version of TGDR (Meta-TGDR), which considers the classification task as a combination of classifiers with the same structure/model while allowing the parameters to vary across studies. However, the original Meta-TGDR extension did not offer a solution to the prediction on independent samples. Here, we propose an explicit method to estimate the overall coefficients of the biomarkers selected by Meta-TGDR. This extension permits broader applicability and allows a comparison between the predictive performance of Meta-TGDR and TGDR using an independent testing set. Results Using real-world applications, we demonstrated the proposed multi-TGDR framework works well and the number of selected genes is less than the sum of all individualized binary TGDRs. Additionally, Meta-TGDR and TGDR on the batch-effect adjusted pooled data approximately provided same results. By adding Bagging procedure in each application, the stability and good predictive performance are warranted. Conclusions Compared with Meta-TGDR, TGDR is less computing time intensive, and requires no samples of all classes in each study. On the adjusted data, it has approximate same predictive performance with Meta-TGDR. Thus, it is highly recommended.