FdDCA : A Novel Fuzzy Deterministic Dendritic Cell Algorithm

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Classification and clinical behavior of blastic plasmacytoid dendritic cell neoplasms according to their maturation-associated immunophenotypic profile

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare subtype of leukemia/lymphoma, whose diagnosis can be difficult to achieve due to its clinical and biological heterogeneity, as well as its overlapping features with other hematologic malignancies. In this study we investigated whether the association between the maturational stage of tumor cells and the clinico-biological and prognostic features of the disease, based on the analysis of 46 BPDCN cases classified into three maturation-associated subgroups on immunophenotypic grounds. Our results show that blasts from cases with an immature plasmacytoid dendritic cell (pDC) phenotype exhibit an uncommon CD56- phenotype, coexisting with CD34+ non-pDC tumor cells, typically in the absence of extramedullary (e.g. skin) disease at presentation. Conversely, patients with a more mature blast cell phenotype more frequently displayed skin/extramedullary involvement and spread into secondary lymphoid tissues. Despite the dismal outcome, acute lymphoblastic leukemia-type therapy (with central nervous system prophylaxis) and/or allogeneic stem cell transplantation appeared to be the only effective therapies. Overall, our findings indicate that the maturational profile of pDC blasts in BPDCN is highly heterogeneous and translates into a wide clinical spectrum -from acute leukemia to mature lymphoma-like behavior-, which may also lead to variable diagnosis and treatment.

Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system, providing the initial detection of pathogenic invaders. Research into this family of cells has revealed that they perform information fusion which directs immune responses. We have derived a Dendritic Cell Algorithm based on the functionality of these cells, by modelling the biological signals and differentiation pathways to build a control mechanism for an artificial immune system. We present algorithmic details in addition to experimental results, when the algorithm was applied to anomaly detection for the detection of port scans. The results show the Dendritic Cell Algorithm is successful at detecting port scans.

The deterministic Dendritic Cell Algorithm

The Dendritic Cell Algorithm is an immune-inspired algorithm originally based on the function of natural dendritic cells. The original instantiation of the algorithm is a highly stochastic algorithm. While the performance of the algorithm is good when applied to large real-time datasets, it is difficult to analyse due to the number of random-based elements. In this paper a deterministic version of the algorithm is proposed, implemented and tested using a port scan dataset to provide a controllable system. This version consists of a controllable amount of parameters, which are experimented with in this paper. In addition the effects are examined of the use of time windows and variation on the number of cells, both which are shown to influence the algorithm. Finally a novel metric for the assessment of the algorithms output is introduced and proves to be a more sensitive metric than the metric used with the original Dendritic Cell Algorithm.

Further exploration of the Dendritic Cell Algorithm: antigen multiplier and time windows

As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DCA, including antigen multiplier and moving time windows, are reported. The real-valued Negative Selection Algorithm (NSA) using constant-sized detectors and the C4.5 decision tree algorithm are used, to conduct a baseline comparison. The results suggest that the DCA is applicable to KDD 99 data set, and the antigen multiplier and moving time windows have the same effect on the DCA for this particular data set. The real-valued NSA with contant-sized detectors is not applicable to the data set. And the C4.5 decision tree algorithm provides a benchmark of the classification performance for this data set.

Exploration of the dendritic cell algorithm with the duration calculus

As one of the newest members in Articial Immune Systems (AIS), the Dendritic Cell Algorithm (DCA) has been applied to a range of problems. These applications mainly belong to the eld of anomaly detection. However, real-time detection, a new challenge to anomaly detection, requires improvement on the real-time capability of the DCA. To assess such capability, formal methods in the research of real-time systems can be employed. The ndings of the assessment can provide guideline for the future development of the algorithm. Therefore, in this paper we use an interval logic based method, named the Duration Calcu- lus (DC), to specify a simplied single-cell model of the DCA. Based on the DC specications with further induction, we nd that each individual cell in the DCA can perform its function as a detector in real-time. Since the DCA can be seen as many such cells operating in parallel, it is potentially capable of performing real-time detection. However, the analysis process of the standard DCA constricts its real-time capability. As a result, we conclude that the analysis process of the standard DCA should be replaced by a real-time analysis component, which can perform periodic analysis for the purpose of real-time detection.

PCA 4 DCA: the application of principal component analysis to the Dendritic Cell Algorithm

As one of the newest members in the field of articial immune systems (AIS), the Dendritic Cell Algorithm (DCA) is based on behavioural models of natural dendritic cells (DCs). Unlike other AIS, the DCA does not rely on training data, instead domain or expert knowledge is required to predetermine the mapping between input signals from a particular instance to the three categories used by the DCA. This data preprocessing phase has received the criticism of having manually over-fitted the data to the algorithm, which is undesirable. Therefore, in this paper we have attempted to ascertain if it is possible to use principal component analysis (PCA) techniques to automatically categorise input data while still generating useful and accurate classication results. The integrated system is tested with a biometrics dataset for the stress recognition of automobile drivers. The experimental results have shown the application of PCA to the DCA for the purpose of automated data preprocessing is successful.

Transcriptional analysis of PRRSV-infected porcine dendritic cell response to Streptococcus suis infection reveals up-regulation of inflammatory-related genes expression

The porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most important swine pathogens and often serves as an entry door for other viral or bacterial pathogens, of which Streptococcus suis is one of the most common. Pre-infection with PRRSV leads to exacerbated disease caused by S. suis infection. Very few studies have assessed the immunological mechanisms underlying this higher susceptibility. Since antigen presenting cells play a major role in the initiation of the immune response, the in vitro transcriptional response of bone marrow-derived dendritic cells (BMDCs) and monocytes in the context of PRRSV and S. suis co-infection was investigated. BMDCs were found to be more permissive than monocytes to PRRSV infection; S. suis phagocytosis by PRRSV-infected BMDCs was found to be impaired, whereas no effect was found on bacterial intracellular survival. Transcription profile analysis, with a major focus on inflammatory genes, following S. suis infection, with and without pre-infection with PRRSV, was then performed. While PRRSV pre-infection had little effect on monocytes response to S. suis infection, a significant expression of several pro-inflammatory molecules was observed in BMDCs pre-infected with PRRSV after a subsequent infection with S. suis. While an additive effect could be observed for CCL4, CCL14, CCL20, and IL-15, a distinct synergistic up-regulatory effect was observed for IL-6, CCL5 and TNF-α after co-infection. This increased pro-inflammatory response by DCs could participate in the exacerbation of the disease observed during PRRSV and S. suis co-infection.

Transcriptional analysis of PRRSV-infected porcine dendritic cell response to Streptococcus suis infection reveals up-regulation of inflammatory-related genes expression

The porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most important swine pathogens and often serves as an entry door for other viral or bacterial pathogens, of which Streptococcus suis is one of the most common. Pre-infection with PRRSV leads to exacerbated disease caused by S. suis infection. Very few studies have assessed the immunological mechanisms underlying this higher susceptibility. Since antigen presenting cells play a major role in the initiation of the immune response, the in vitro transcriptional response of bone marrow-derived dendritic cells (BMDCs) and monocytes in the context of PRRSV and S. suis co-infection was investigated. BMDCs were found to be more permissive than monocytes to PRRSV infection; S. suis phagocytosis by PRRSV-infected BMDCs was found to be impaired, whereas no effect was found on bacterial intracellular survival. Transcription profile analysis, with a major focus on inflammatory genes, following S. suis infection, with and without pre-infection with PRRSV, was then performed. While PRRSV pre-infection had little effect on monocytes response to S. suis infection, a significant expression of several pro-inflammatory molecules was observed in BMDCs pre-infected with PRRSV after a subsequent infection with S. suis. While an additive effect could be observed for CCL4, CCL14, CCL20, and IL-15, a distinct synergistic up-regulatory effect was observed for IL-6, CCL5 and TNF-α after co-infection. This increased pro-inflammatory response by DCs could participate in the exacerbation of the disease observed during PRRSV and S. suis co-infection.

Erythropoietin reduces pathogenic humoral immunity by inhibiting T Follicular Helper cell differentiation and function

A large fraction of organ transplant recipients develop anti-donor antibodies (DSA), with accelerated graft loss and increased mortality. We tested the hypothesis that erythropoietin (EPO) reduces DSA formation by inhibiting T follicular helper (TFH) cells. We measured DSA levels, splenic TFH, TFR cells, germinal center (GC), and class switched B cells, in murine models of allogeneic sensitization, allogeneic transplantation and in parent-to-F1 models of graft versus host disease (GVHD). We quantified the same cell subsets and specific antibodies, upon EPO or vehicle treatment, in wild type mice and animals lacking EPO receptor selectively on T or B cells, immunized with T-independent or T-dependent stimuli. In vitro, we tested the EPO effect on TFH induction. We isolated TFH and TFR cells to perform in vitro assay and clarify their role. EPO reduced DSA levels, GC, class switched B cells, and increased the TFR/TFH ratio in the heart transplanted mice and in two GVHD models. EPO did also reduce TFH and GC B cells in SRBC-immunized mice, while had no effect in TNP-AECM-FICOLL-immunized animals, indicating that EPO inhibits GC B cells by targeting TFH cells. EPO effects were absent in T cells EPOR conditional KO mice, confirming that EPO affects TFH in vivo through EPOR. In vitro, EPO affected TFH induction through an EPO-EPOR-STAT5-dependent pathway. Suppression assay demonstrated that the reduction of IgG antibodies was dependent on TFH cells, sustaining the central role of the subset in this EPO-mediated mechanism. In conclusion, EPO prevents DSA formation in mice through a direct suppression of TFH. Development of DSA is associated with high risk of graft rejection, giving our data a strong rationale for studies testing the hypothesis that EPO administration prevents their formation in organ transplant recipients. Our findings provide a foundation for testing EPO as a treatment of antibody mediated disease processes.

Modeling of clear cell sarcoma of the kidney of the pediatric age

Clear cell sarcoma of the kidney (CCSK) is the second most common pediatric renal tumor, characterized in 90% of cases by the presence of internal tandem duplications (ITDs) localized at the last exon of BCOR gene. BCOR protein constitute a core component of the non-canonical Polycomb Repressive Complex1 (PRC1.1), which performs a fundamental silencing activity. ITDs in the last BCOR exon at the level of PUFD domain have been identified in many tumor subtypes and could affect PCGF1 binding and the subsequent PRC1.1 activity, although the exact oncogenic mechanism of ITD remains poorly understood. This project has the objective of investigating the molecular mechanisms underlying the oncogenesis of CCSK, approaching the study with different methodologies. A first model in HEK-293 allowed to obtain important informations about BCOR functionality, suggesting that the presence of ITD generates an altered activity which is very different from a loss-of-function. It has also been observed that BCOR function within the PRC1.1 complex varies with different ITDs. Moreover, it allowed the identification of molecular signatures evoked by the presence of BCOR-ITD, including its role in extracellular matrix interactions and invasiveness promotion. The parallel analysis of WTS data from 8 CCSK cases permitted the identification of a peculiar signature for metastatic CCSKs, highlighting a 20-fold overexpression of FGF3. This factor promoted a significant increase in invasive ability in the cellular model. In order to study BCOR-ITD effects over cell stemness and differentiation, an inducible model is being obtained in H1 cells. This way, it will be possible to study the functionality of BCOR-ITD in a context more similar to the origin of CCSKs, evaluating both the specific interactome and phenotypic consequences caused by the mutation.

Effect of antiretroviral therapy on apoptosis markers and morphology in peripheral lymph nodes of HIV-infected individuals.

BACKGROUND: CD4+ T cell depletion and destruction and the involution of the lymphoid tissue are hallmarks of HIV infection. Although the underlying mechanisms are still unclear, apoptosis appears to play a central role. The objective of this study was to investigate the effect of antiretroviral therapy on the lymph node tissue, particularly with respect to morphology and apoptosis. PATIENTS AND METHODS: Between 1997 and 1999, two inguinal lymph nodes were excised from 31 previously untreated individuals who were in an early stage of HIV infection, the first one prior to treatment and the second after 16 to 20 months of treatment. Paraffin sections were investigated for lymph node architecture, distribution of cellular and viral markers, apoptosis, and expression of apoptotic key molecules which indirectly reflect apoptotic processes. RESULTS: After 16-20 months of antiretroviral therapy, a significant decrease in highly activated HIV-driven immune response was observed in the lymph node tissue as a marked reduction in follicular hyperplasia, a normalization of the follicular dendritic cell network, a significant increase in the number of CD4+ T cells, and a significant decrease in the number of CD8+ T cells. The expression of several proapoptotic (Fas, TRAIL, and active caspase 3) and antiapoptotic (Bcl-2 and IL-7Ralpha) molecules that were reconstituted in the tissues during therapy resembled their expression in lymph nodes of HIV-negative individuals. Limitations of the study are (a) the lack of untreated patients in the late stages, (b) for ethical reasons, the lack of a control group with untreated patients, and (c) for methodological reasons, the restriction of sequential measurements of apotpotic markers to one-third of the patients. CONCLUSION: Antiretroviral therapy initiated in the early stages in HIV infection may halt the irreversible destruction of the lymph node tissue and may partially normalize apoptotic processes.

Abnormal development of secondary lymphoid tissues in lymphotoxin β-deficient mice

The tumor necrosis factor (TNF) family cytokines lymphotoxin (LT) α and LTβ form heterotrimers that are expressed on the surface of activated lymphocytes and natural killer cells; LTα homotrimers can be secreted as well. Mice with a disrupted LTα gene lack lymph nodes (LN), Peyer’s patches (PP), and follicular dendritic cell (FDC) networks and reveal profound defects of the splenic architecture. However, it is unclear which of these abnormalities is the result of the absence in LTα homotrimers or LTαβ heterotrimers. To distinguish between these two possibilities, a mouse strain deficient in LTβ was created employing Cre/loxP-mediated gene targeting. Mice deficient in LTβ reveal severe defects in organogenesis of the lymphoid system similar to those of LTα−/− mice, except that mesenteric and cervical LN are present in most LTβ-deficient mice. Both LTβ- and LTα-deficient mice show significant lymphocytosis in the circulation and peritoneal cavity and lymphocytic infiltrations in lungs and liver. After immunization, PNA-positive B cell clusters were detected in the splenic white pulp of LTβ-deficient mice, but FDC networks were severely underdeveloped. Collectively, these results indicate that LTα can signal independently from LTβ in the formation of PNA-positive foci in the spleen, and especially in the development of mesenteric and cervical LN.

Characterization of a human synovial cell antigen: VCAM-1 and inflammatory arthritis

The contribution of synovial cells to the pathogenesis of rheumatoid arthritis (RA) is only partly understood. Monoclonal antibody (mAb) 1D5 is one of very few mAb ever raised against RA synovial cells in order to study the biology of these cells. Studies on the expression pattern and structural features of the 1D5 Ag suggest that 1D5 recognizes human vascular cell adhesion molecule-1 (VCAM-1), which is an intercellular adhesion molecule. Vascular cell adhesion molecule-1 may be involved in a number of crucial intercellular interactions in RA.