Expression of type I interferon by splenic macrophages suppresses adaptive immunity during sepsis.

Early during Gram-negative sepsis, excessive release of pro-inflammatory cytokines can cause septic shock that is often followed by a state of immune paralysis characterized by the failure to mount adaptive immunity towards secondary microbial infections. Especially, the early mechanisms responsible for such immune hypo-responsiveness are unclear. Here, we show that TLR4 is the key immune sensing receptor to initiate paralysis of T-cell immunity after bacterial sepsis. Downstream of TLR4, signalling through TRIF but not MyD88 impaired the development of specific T-cell immunity against secondary infections. We identified type I interferon (IFN) released from splenic macrophages as the critical factor causing T-cell immune paralysis. Early during sepsis, type I IFN acted selectively on dendritic cells (DCs) by impairing antigen presentation and secretion of pro-inflammatory cytokines. Our results reveal a novel immune regulatory role for type I IFN in the initiation of septic immune paralysis, which is distinct from its well-known immune stimulatory effects. Moreover, we identify potential molecular targets for therapeutic intervention to overcome impairment of T-cell immunity after sepsis.

Keratin 1 maintains skin integrity and participates in an inflammatory network in skin through interleukin-18.

Keratin 1 (KRT1) and its heterodimer partner keratin 10 (KRT10) are major constituents of the intermediate filament cytoskeleton in suprabasal epidermis. KRT1 mutations cause epidermolytic ichthyosis in humans, characterized by loss of barrier integrity and recurrent erythema. In search of the largely unknown pathomechanisms and the role of keratins in barrier formation and inflammation control, we show here that Krt1 is crucial for maintenance of skin integrity and participates in an inflammatory network in murine keratinocytes. Absence of Krt1 caused a prenatal increase in interleukin-18 (IL-18) and the S100A8 and S100A9 proteins, accompanied by a barrier defect and perinatal lethality. Depletion of IL-18 partially rescued Krt1(-/-) mice. IL-18 release was keratinocyte-autonomous, KRT1 and caspase-1 dependent, supporting an upstream role of KRT1 in the pathology. Finally, transcriptome profiling revealed a Krt1-mediated gene expression signature similar to atopic eczema and psoriasis, but different from Krt5 deficiency and epidermolysis bullosa simplex. Our data suggest a functional link between KRT1 and human inflammatory skin diseases.

Vav1 regulates MHCII expression in murine resting and activated B cells.

Vav1 is a guanine nucleotide exchange factor (GEF) for Rho GTPases, which is exclusively expressed in cells of the hematopoietic system. In addition to its well-documented GEF activity, it was suggested to have other functions due to the presence of multiple domains and nuclear localization signals in its protein structure. Although GEF-dependent and GEF-independent functions of vav have been implicated in T-cell development and T-cell receptor signaling, the role of vav1 in antigen-presenting cells is poorly understood. We found that vav1 is an important regulator of MHCII expression and transport. Microarray analysis of unstimulated bone marrow-derived macrophages revealed a novel role of vav1 in transcriptional regulation of the MHCII locus, possibly by indirect means. Primary immune cells from vav1-deficient mice had a significantly lower constitutive surface expression of MHCII with the strongest impact observed on splenic and peritoneal B cells. Impaired MHCII expression resulted in a diminished capacity for T-cell activation. Using 6-thio-GTP, a specific inhibitor of the GEF function of vav1, we were able to show that the GEF activity is required for MHCII upregulation in B cells after stimulation with LPS. Furthermore, our data show that vav1 not only affects transcription of the MHCII locus but also is an important regulator of MHCII protein transport to the cell surface.

Unique transcriptome signature of mouse microglia.

Microglial cells can be derived directly from the dissociated brain tissue by sorting procedures, from postnatal glial cultures by mechanic isolation or from pluripotent stem cells by differentiation. The detailed molecular phenotype of microglia from different sources is still unclear. Here, we performed a whole transcriptome analysis of flow cytometry-sorted microglia, primary postnatal cultured microglia, embryonic stem cell derived microglia (ESdM), and other cell types. Microglia and ESdM, both cultured in serum-free medium, were closely related to sorted microglia and showed a unique transcriptome profile, clearly distinct to other myeloid cell types, T cells, astrocytes, and neurons. ESdM and primary cultured microglia showed strong overlap in their transcriptome. Only 143 genes were differentially expressed between both cell types, mainly derived from immune-related genes with a higher activation status of proinflammatory and immune defense genes in primary microglia compared to ESdM. Flow cytometry analysis of cell surface markers CD54, CD74, and CD274 selected from the microarray confirmed the close phenotypic relation between ESdM and primary cultured microglia. Thus, assessment of genome-wide transcriptional regulation demonstrates that microglial cells are unique and clearly distinct from other macrophage cell types.

Intrahepatic IL-8 producing Foxp3⁺CD4⁺ regulatory T cells and fibrogenesis in chronic hepatitis C.

BACKGROUND & AIMS: Regulatory CD4(+) T cells (Tregs) are considered to affect outcomes of HCV infection, because they increase in number during chronic hepatitis C and can suppress T-cell functions. METHODS: Using microarray analysis, in situ immunofluorescence, ELISA, and flowcytometry, we characterised functional differentiation and localisation of adaptive Tregs in patients with chronic hepatitis C. RESULTS: We found substantial upregulation of IL-8 in Foxp3(+)CD4(+) Tregs from chronic hepatitis C. Activated GARP-positive IL-8(+) Tregs were particularly enriched in livers of patients with chronic hepatitis C in close proximity to areas of fibrosis and their numbers were correlated with the stage of fibrosis. Moreover, Tregs induced upregulation of profibrogenic markers TIMP1, MMP2, TGF-beta1, alpha-SMA, collagen, and CCL2 in primary human hepatic stellate cells (HSC). HSC activation, but not Treg suppressor function, was blocked by adding a neutralizing IL-8 antibody. CONCLUSIONS: Our studies identified Foxp3(+)CD4(+) Tregs as an additional intrahepatic source of IL-8 in chronic hepatitis C acting on HSC. Thus, Foxp3(+)CD4(+) Tregs in chronic hepatitis C have acquired differentiation as regulators of fibrogenesis in addition to suppressing local immune responses.

Natural and orthogonal interaction framework for modeling gene-environment interactions with application to lung cancer.

OBJECTIVES: We aimed at extending the Natural and Orthogonal Interaction (NOIA) framework, developed for modeling gene-gene interactions in the analysis of quantitative traits, to allow for reduced genetic models, dichotomous traits, and gene-environment interactions. We evaluate the performance of the NOIA statistical models using simulated data and lung cancer data. METHODS: The NOIA statistical models are developed for additive, dominant, and recessive genetic models as well as for a binary environmental exposure. Using the Kronecker product rule, a NOIA statistical model is built to model gene-environment interactions. By treating the genotypic values as the logarithm of odds, the NOIA statistical models are extended to the analysis of case-control data. RESULTS: Our simulations showed that power for testing associations while allowing for interaction using the NOIA statistical model is much higher than using functional models for most of the scenarios we simulated. When applied to lung cancer data, much smaller p values were obtained using the NOIA statistical model for either the main effects or the SNP-smoking interactions for some of the SNPs tested. CONCLUSION: The NOIA statistical models are usually more powerful than the functional models in detecting main effects and interaction effects for both quantitative traits and binary traits.

Application of T cell-based transcriptomics to identify three candidate biomarkers for monitoring anti-TGFbetaR therapy.

OBJECTIVES: The development of targeted drugs would greatly benefit from the simultaneous identification of biomarkers to determine the aspects of bioactivity, drug safety and efficacy, particularly when affecting receptor-signaling pathways. However, the establishment of appropriate systems to monitor drug-induced events requires an accessible surrogate tissue for functional read out. METHODS: Therefore we present a universal platform based upon T cell-based gene expression profiling for the identification of biomarkers using the antitransforming growth factor beta receptor inhibitor LY2109761 as an example. RESULTS: Our initial screen revealed 12 candidate genes specifically regulated in T cells by the inhibitor. In subsequent in-vitro and in-vivo analyses, the combined monitoring of independent gene regulation of three genes was established in peripheral blood mononuclear cells as novel pharmacodynamic candidate biomarkers for antitransforming growth factor beta receptor based therapies. CONCLUSION: Overall, the proposed concept of biomarker identification can be easily adapted towards other drug candidates for whom gene regulation can be established in cellular components of peripheral blood.

Identification of lung cancer with high sensitivity and specificity by blood testing.

BACKGROUND: Lung cancer is a very frequent and lethal tumor with an identifiable risk population. Cytological analysis and chest X-ray failed to reduce mortality, and CT screenings are still controversially discussed. Recent studies provided first evidence for the potential usefulness of autoantigens as markers for lung cancer. METHODS: We used extended panels of arrayed antigens and determined autoantibody signatures of sera from patients with different kinds of lung cancer, different common non-tumor lung pathologies, and controls without any lung disease by a newly developed computer aided image analysis procedure. The resulting signatures were classified using linear kernel Support Vector Machines and 10-fold cross-validation. RESULTS: The novel approach allowed for discriminating lung cancer patients from controls without any lung disease with a specificity of 97.0%, a sensitivity of 97.9%, and an accuracy of 97.6%. The classification of stage IA/IB tumors and controls yielded a specificity of 97.6%, a sensitivity of 75.9%, and an accuracy of 92.9%. The discrimination of lung cancer patients from patients with non-tumor lung pathologies reached an accuracy of 88.5%. CONCLUSION: We were able to separate lung cancer patients from subjects without any lung disease with high accuracy. Furthermore, lung cancer patients could be separated from patients with other non-tumor lung diseases. These results provide clear evidence that blood-based tests open new avenues for the early diagnosis of lung cancer.

Validation of the "SmoCess-GP" instrument - a short patient questionnaire for assessing the smoking cessation activities of general practitioners: a cross-sectional study.

BACKGROUND: We developed an instrument assessing the extent of smoking cessation activities by general practitioners (GPs) within the Cologne Smoking Study (CoSmoS). The objective of the present study was to examine further psychometric quality of the "SmoCess-GP" instrument (Smoking Cessation by General Practitioners). METHODS: 127 current smokers who had participated in the Cologne Smoking Study (CoSmoS) were included in our analyses. Confirmatory factor analysis (CFA) was conducted to examine the model fit and to retest the single-factor structure of the instrument using the Mplus software. Further construct validity was tested with bivariate analysis using an instrument which measures patients' trust in physicians. RESULTS: CFA supported the unidimensional structure of the instrument. The factor loadings exceed the threshold of > or = 0.50. All indicator reliabilities were higher than 0.30. The composite reliability was 0.86 and the average variance extracted (AVE) resulted in a value of 0.50. The calculation of global fit indices identified a CFI value of 1.00 and for TLI a value of 1.02. The root mean square error of approximation (RMSEA) indicates that 0% of the information is not accounted for by the model. The chi-square value was chi2df = 6 = 4.63 (p = 0.59). Analysis of discriminant validity resulted in a non-significant correlation of r = 0.092 (p = 0.350). CONCLUSIONS: Results indicate preliminary evidence for the construct validity of the "SmoCess-GP" instrument which therefore appears to be a promising tool for analyzing the extent of smoking cessation advice offered by GPs from the patients' perspective. Future research should examine the psychometric properties in a population based sample, further improvements of the instrument and should apply other methods of validation.

Allelic losses on chromosome 6q25 in Hodgkin and Reed Sternberg cells.

We established a molecular cytogenetic approach to identify consistent genetic aberrations in classical Hodgkin lymphoma. Single laser-micromanipulated Hodgkin and Reed Sternberg (H-RS) cells and the respective germ line tissue were PCR-amplified using highly polymorphic microsatellite probes. Loss of heterozygosity and genomic imbalances of the fluorochrome-labeled microsatellites were determined by fragment length analysis. Eleven cases of in classical Hodgkin lymphoma (cHL) were initially screened with 21 microsatellite markers scattered over the entire genome. Loss of heterozygosity was detected in >40% of informative loci in most cases indicating a deletion of a substantial part of the genome of H-RS cells. Allelic losses and imbalances on chromosome 6q were detected in most of these cases. A deletion mapping of 6q was performed in 16 cases of cHL. This detailed analysis of 6q led to the identification of a 3.3-Mbp region around D6S311 flanked by D6S978 and D6S1564 that was altered in 11 of 14 cases of cHL analyzed. In conclusion, allelotyping of single H-RS cells revealed monoallelic chromosomal deletions and genomic imbalances on 6q that might affect genes critically involved in the pathogenesis of H-RS cells.

Liver-primed memory T cells generated under noninflammatory conditions provide anti-infectious immunity.

Development of CD8(+) T cell (CTL) immunity or tolerance is linked to the conditions during T cell priming. Dendritic cells (DCs) matured during inflammation generate effector/memory T cells, whereas immature DCs cause T cell deletion/anergy. We identify a third outcome of T cell priming in absence of inflammation enabled by cross-presenting liver sinusoidal endothelial cells. Such priming generated memory T cells that were spared from deletion by immature DCs. Similar to central memory T cells, liver-primed T cells differentiated into effector CTLs upon antigen re-encounter on matured DCs even after prolonged absence of antigen. Their reactivation required combinatorial signaling through the TCR, CD28, and IL-12R and controlled bacterial and viral infections. Gene expression profiling identified liver-primed T cells as a distinct Neuropilin-1(+) memory population. Generation of liver-primed memory T cells may prevent pathogens that avoid DC maturation by innate immune escape from also escaping adaptive immunity through attrition of the T cell repertoire.

Blood-based miRNA preparation for noninvasive biomarker development.

This chapter describes several methods for the isolation of miRNAs from peripheral whole blood samples or constituent fractions thereof, such as peripheral blood mononuclear cells, plasma, and serum. The methods described here are recently introduced protocols dedicated to the isolation of total RNAs including small RNAs, e.g., miRNeasy Kit and PAXgene Blood miRNA Kit, or alternatively for the enrichment of low-molecular-weight RNA (LMW RNA) fractions including small RNAs, e.g., using the miRNeasy Kit. Furthermore, modifications of classical RNA purification protocols to facilitate the recovery of small RNAs are highlighted.

The association between active participation in a sports club, physical activity and social network on the development of lung cancer in smokers: a case-control study.

BACKGROUND: This study analyses the effect of active participation in a sports club, physical activity and social networks on the development of lung cancer in patients who smoke. Our hypothesis is that study participants who lack social networks and do not actively participate in a sports club are at a greater risk for lung cancer than those who do. METHODS: Data for the study were taken from the Cologne Smoking Study (CoSmoS), a retrospective case-control study examining potential psychosocial risk factors for the development of lung cancer. Our sample consisted of n = 158 participants who had suffered lung cancer (diagnosis in the patient document) and n = 144 control group participants. Both groups had a history of smoking.Data on social networks were collected by asking participants whether they participated in a sports club and about the number of friends and relatives in their social environment. In addition, sociodemographic data (gender, age, education, marital status, residence and religion), physical activity and data on pack years (the cumulative number of cigarettes smoked by an individual, calculated by multiplying the number of cigarettes smoked per day by the number of years the person has smoked divided by 20) were collected to control for potential confounders. Logistic regression was used for the statistical analysis. RESULTS: The results reveal that participants who are physically active are at a lower risk of lung cancer than those who are not (adjusted OR = 0.53*; CI = 0.29-0.97). Older age and lower education seem also to be risk factors for the development of lung cancer. The extent of smoking, furthermore, measured by pack years is statistically significant. Active participation in a sports club, number of friends and relatives had no statistically significant influence on the development of the cancer. CONCLUSIONS: The results of the study suggest that there is a lower risk for physically active participants to develop lung cancer. In the study sample, physical activity seemed to have a greater protective effect than participation in a sports club or social network of friends and relatives. Further studies have to investigate in more detail physical activity and other club participations.

High-resolution transcriptome of human macrophages.

Macrophages are dynamic cells integrating signals from their microenvironment to develop specific functional responses. Although, microarray-based transcriptional profiling has established transcriptional reprogramming as an important mechanism for signal integration and cell function of macrophages, current knowledge on transcriptional regulation of human macrophages is far from complete. To discover novel marker genes, an area of great need particularly in human macrophage biology but also to generate a much more thorough transcriptome of human M1- and M1-like macrophages, we performed RNA sequencing (RNA-seq) of human macrophages. Using this approach we can now provide a high-resolution transcriptome profile of human macrophages under classical (M1-like) and alternative (M2-like) polarization conditions and demonstrate a dynamic range exceeding observations obtained by previous technologies, resulting in a more comprehensive understanding of the transcriptome of human macrophages. Using this approach, we identify important gene clusters so far not appreciated by standard microarray techniques. In addition, we were able to detect differential promoter usage, alternative transcription start sites, and different coding sequences for 57 gene loci in human macrophages. Moreover, this approach led to the identification of novel M1-associated (CD120b, TLR2, SLAMF7) as well as M2-associated (CD1a, CD1b, CD93, CD226) cell surface markers. Taken together, these data support that high-resolution transcriptome profiling of human macrophages by RNA-seq leads to a better understanding of macrophage function and will form the basis for a better characterization of macrophages in human health and disease.

RNA-stabilized whole blood samples but not peripheral blood mononuclear cells can be stored for prolonged time periods prior to transcriptome analysis.

Microarray-based transcriptome analysis of peripheral blood as surrogate tissue has become an important approach in clinical implementations. However, application of gene expression profiling in routine clinical settings requires careful consideration of the influence of sample handling and RNA isolation methods on gene expression profile outcome. We evaluated the effect of different sample preservation strategies (eg, cryopreservation of peripheral blood mononuclear cells or freezing of PAXgene-stabilized whole blood samples) on gene expression profiles. Expression profiles obtained from cryopreserved peripheral blood mononuclear cells differed substantially from those of their nonfrozen counterpart samples. Furthermore, expression profiles in cryopreserved peripheral blood mononuclear cell samples were found to undergo significant alterations with increasing storage period, whereas long-term freezing of PAXgene RNA stabilized whole blood samples did not significantly affect stability of gene expression profiles. This report describes important technical aspects contributing toward the establishment of robust and reliable guidance for gene expression studies using peripheral blood and provides a promising strategy for reliable implementation in routine handling for diagnostic purposes.

Blood-based gene expression signatures in non-small cell lung cancer.

PURPOSE: Blood-based surrogate markers would be attractive biomarkers for early detection, diagnosis, prognosis, and prediction of therapeutic outcome in cancer. Disease-associated gene expression signatures in peripheral blood mononuclear cells (PBMC) have been described for several cancer types. However, RNA-stabilized whole blood-based technologies would be clinically more applicable and robust. We evaluated the applicability of whole blood-based gene expression profiling for the detection of non-small cell lung cancer (NSCLC). EXPERIMENTAL DESIGN: Expression profiles were generated from PAXgene-stabilized blood samples from three independent groups consisting of NSCLC cases and controls (n = 77, 54, and 102), using the Illumina WG6-VS2 system. RESULTS: Several genes are consistently differentially expressed in whole blood of NSCLC patients and controls. These expression profiles were used to build a diagnostic classifier for NSCLC, which was validated in an independent validation set of NSCLC patients (stages I-IV) and hospital-based controls. The area under the receiver operator curve was calculated to be 0.824 (P < 0.001). In a further independent dataset of stage I NSCLC patients and healthy controls the AUC was 0.977 (P < 0.001). Specificity of the classifier was validated by permutation analysis in both validation cohorts. Genes within the classifier are enriched in immune-associated genes and show specificity for NSCLC. CONCLUSIONS: Our results show that gene expression profiles of whole blood allow for detection of manifest NSCLC. These results prompt further development of gene expression-based biomarker tests in peripheral blood for the diagnosis and early detection of NSCLC.

Re-overcoming barriers in translating biomarkers to clinical practice.

IMPORTANCE OF THE FIELD: Recently, there has been growing evidence for the concept of personalized medicine as the implementation of genomic and molecular information in the delivery of healthcare. In parallel, the identification of biomarkers has become of enormous significance as a prerequisite for individualized intervention regimens. AREAS COVERED IN THIS REVIEW: Biomarkers are developed to improve prevention, diagnosis or therapeutic outcome of a given disease. Although each application reveals distinct developmental strategies, evidence-based approval of new biomarkers is important for the success of new drugs, diagnostic tests or recommendations in preventive medicine. Current hurdles to bringing biomarkers into clinical practice are reviewed, thereby focusing on adequate approaches to overcome these limitations in the future. WHAT THE READER WILL GAIN: The reader will get an introduction to strategies resolving actual barriers in clinical biomarker development. TAKE HOME MESSAGE: The identification of evidence-based biomarkers is crucial for the success of individualized therapeutic approaches. Developmental strategies have to be adapted to clinical need, thereby focusing on biomarker validation in clinical settings as well as on the establishment of standardized biomarker test systems for routine application. Consortia have been established bringing together representatives of government, academia and industry to improve future biomarker development.

Prediction and prognosis: impact of gene expression profiling in personalized treatment of breast cancer patients.

Breast cancer is a complex disease, whose heterogeneity is increasingly recognized. Despite considerable improvement in breast cancer treatment and survival, a significant proportion of patients seems to be over- or undertreated. To date, single clinicopathological parameters show limited success in predicting the likelihood of survival or response to endocrine therapy and chemotherapy. Consequently, new gene expression based prognostic and predictive tests are emerging that promise an improvement in predicting survival and therapy response. Initial evidence has emerged that this leads to allocation of fewer patients into high-risk groups allowing a reduction of chemotherapy treatment. Moreover, pattern-based approaches have also been developed to predict response to endocrine therapy or particular chemotherapy regimens. Irrespective of current pitfalls such as lack of validation and standardization, these pattern-based biomarkers will prove useful for clinical decision making in the near future, especially if more patients get access to this form of personalized medicine.

The influence of occupational stress factors on the nicotine dependence: a cross sectional study.

OBJECTIVE: This study analyses the association between occupational stress factors and nicotine dependence. Our hypothesis is that occupational stress factors increase nicotine dependence. METHODS: Data were taken from the Cologne Smoking Study, a case-control study that examines which genetic/psychosocial factors lead to a higher risk for smokers to suffer from cardiac infarction, lung cancer and/or to become addicted to nicotine. Our sample consisted of N = 197 currently smoking and employed participants. Nicotine dependence was measured using the Fagerström Test for Nicotine Dependence (FTND). The extent of the stress factors experienced at work was assessed using the Effort-Reward Imbalance scale (ERI). Logistic regression was used for the statistical analysis. RESULTS: Contrary to our hypothesis, the results show that occupational stress factors are actually associated with lower levels of nicotine dependence (N = 197; adjusted OR = 0.439; p = .059). CONCLUSIONS: One possible explanation for the study's findings is that the participants have a heavy workload and can only smoke in their spare time. Another reason may be workplace smoking bans. Furthermore, the Fagerström Test for Nicotine Dependence is unable to examine nicotine dependence during working hours.

Bead array-based microrna expression profiling of peripheral blood and the impact of different RNA isolation approaches.

Blood-based mRNA expression profiling has already become an important issue in clinical applications. More recently, the characterization of the small RNA transcriptome offers additional avenues for diagnostic approaches. However, when applying miRNA expression profiling in routine clinical settings, the method of RNA preservation and the manner of RNA extraction as well as the reliability of the miRNA profiling procedure have to be carefully considered. Here we evaluate a recently introduced bead array-based technology as a robust method for the generation of blood-based human miRNA expression profiles. Importantly the comparison of different RNA extraction strategies resulted in dissimilar profiles depending on the RNA extraction method as well as on the underlying source. Expression profiles obtained from peripheral mononuclear cells (PBMCs) substantially differed from those of whole blood samples, whereby both sources per se yielded reproducible and reliable results. Expression profiles were also distinct when using either fresh or frozen PBMCs. Moreover RNA size fractioning resulted in discriminative miRNA expression profiles compared with total RNA based profiles. This study outlines important steps toward the establishment of a robust strategy for blood-based miRNA profiling and provides a reliable strategy for its implementation in routine handling for diagnostic purposes.