Monitoring dendritic cells in clinical practice using a new whole blood single-platform TruCOUNT assay

Dendritic cells (DC) from distinct DC subsets are essential contributors to normal human immune responses. Despite this, reliable assays that enable DC to be counted precisely have been slow to evolve. We have now developed a new single-platform flow cytometric assay based on TruCOUN(TM) beads and the whole blood Lyse/No-Wash protocol that allows precise counting of the CD14(-) blood DC subsets: CD11c(+)CD16(-) DC, CD11c(+)CD16(+) DC, CD123(hi) DC, CD1c(+) DC and BDCA-3(+) DC. This assay requires 50 mul of whole blood; does not rely on a hematology blood analyser for the absolute DC counts; allows DC counting in EDTA samples 24 It after collection; and is suitable for cord blood and peripheral blood. The data is highly reproducible with intra-assay and inter-assay coefficients of variation less than 3% and 11%, respectively. This assay does not produce the DC-T lymphocyte conjugates that result in DC counting abnormalities in conventional gradient-density separation procedures. Using the TruCOUNT assay, we established that absolute blood DC counts reduce with age in healthy individuals. In preliminary studies, we found a significantly lower absolute blood CD11c(+)CD16(+) DC count in stage III/IV versus stage I/II breast carcinoma patients and a lower absolute blood CD123(hi) DC count in multiple myeloma patients, compared to age-matched controls. These data indicate that scientific progress in DC counting technology will lead to the global standardization of DC counting and allow clinically meaningful data to be obtained. (C) 2003 Elsevier B.V. All rights reserved.

Hepatitis B surface antigen vector delivers protective cytotoxic T-lymphocyte responses to disease-relevant foreign epitopes

Although hepatitis B surface antigen (HBsAg) per se is highly immunogenic, its use as a vector for the delivery of foreign cytotoxic T-lymphocyte (CTL) epitopes has met with little success because of constraints on HBsAg stability and secretion imposed by the insertion of foreign sequence into critical hydrophobic/amphipathic regions. Using a strategy entailing deletion of DNA encoding HBsAg-specific CTL epitopes and replacement with DNA encoding foreign CTL epitopes, we have derived chimeric HBsAg DNA immunogens which elicited effector and memory CTL responses in vitro, and pathogen- and tumor-protective responses in vivo, when the chimeric HBsAg DNAs were used to immunize mice. We further show that HBsAg DNA recombinant for both respiratory syncytial virus and human papillomavirus CTL epitopes elicited simultaneous responses to both pathogens. These data demonstrate the efficacy of HBsAg DNA as a vector for the delivery of disease-relevant protective CTL responses. They also suggest the applicability of the approach of deriving chimeric HBsAg DNA immunogens simultaneously encoding protective CTL epitopes for multiple diseases. The DNAs we tested formed chimeric HBsAg virus-like particles (VLPs). Thus, our results have implications for the development of vaccination strategies using either chimeric HBsAg DNA or VLP vaccines. HBsAg is the globally administered vaccine for hepatitis B virus infection, inviting its usage as a vector for the delivery of immunogens from other diseases.

Cytotoxic T-lymphocyte epitope vaccination protects against human metapneumovirus infection and disease in mice

Human metapneumovirus (hMPV) has emerged as an important human respiratory pathogen causing upper and lower respiratory tract infections in young children and older adults. In addition, hMPV infection is associated with asthma exacerbation in young children. Recent epidemiological evidence indicates that hMPV may cocircullate with human respiratory syncytial virus (hRSV) and mediate clinical disease similar to that seen with hRSV. Therefore, a vaccine for hMPV is highly desirable. In the present study, we used predictive bioinformatics, peptide immunization, and functional T-cell assays to define hMPV cytotoxic T-lymphocyte (CTL) epitopes recognized by mouse T cells restricted through several major histocompatibility complex class I alleles, including HILA-A*0201. We demonstrate that peptide immunization with hMPV CTL epitopes reduces viral load and immunopathollogy in the lungs of hMPV-challenged mice and enhances the expression of Th1-type cytokines (gamma interferon and interleukin-12 [IL-12]) in lungs and regional lymph nodes. In addition, we show that levels of Th2-type cytolkines (IL-10 and IL-4) are significantly lower in hMPV CTL epitope-vaccinated mice challenged with hMPV. These results demonstrate for the first time the efficacy of an hMPV CTL epitope vaccine in the control of hMPV infection in a murine model.

Comparative gene expression analysis of NKT cell subpopulations

Natural killer T (NKT) cells are a lymphocyte lineage, which has diverse immune regulatory activities in many disease settings. Most previous studies have investigated the functions of this family of cells as a single entity, but more recent evidence highlights the distinct functional and phenotypic properties of NKT cell subpopulations. It is likely that the diverse functions of NKT cells are regulated and coordinated by these different NKT subsets. Little is known about how NKT subsets differ in their interactions with the host. We have undertaken the first microarray analysis comparing the gene expression profiles of activated human NKT cell subpopulations, including CD8(+) NKT cells, which have often been overlooked. We describe the significant gene expression differences among NKT cell subpopulations and some of the molecules likely to confer their distinct functional roles. Several genes not associated previously with NKT cells were shown to be expressed differentially in specific NKT cell subpopulations. Our findings provide new insights into the NKT cell family, which may direct further research toward better manipulation of NKT cells for therapeutic applications.

Improving support vector solutions by selecting a sequence of training subsets

In this paper we demonstrate that it is possible to gradually improve the performance of support vector machine (SVM) classifiers by using a genetic algorithm to select a sequence of training subsets from the available data. Performance improvement is possible because the SVM solution generally lies some distance away from the Bayes optimal in the space of learning parameters. We illustrate performance improvements on a number of benchmark data sets.