Modeling flow cytometry data for cancer vaccine immune monitoring

Flow cytometry (FCM) is widely used in cancer research for diagnosis, detection of minimal residual disease, as well as immune monitoring and profiling following immunotherapy. In all these applications, the challenge is to detect extremely rare cell subsets while avoiding spurious positive events. To achieve this objective, it helps to be able to analyze FCM data using multiple markers simultaneously, since the additional information provided often helps to minimize the number of false positive and false negative events, hence increasing both sensitivity and specificity. However, with manual gating, at most two markers can be examined in a single dot plot, and a sequential strategy is often used. As the sequential strategy discards events that fall outside preceding gates at each stage, the effectiveness of the strategy is difficult to evaluate without laborious and painstaking back-gating. Model-based analysis is a promising computational technique that works using information from all marker dimensions simultaneously, and offers an alternative approach to flow analysis that can usefully complement manual gating in the design of optimal gating strategies. Results from model-based analysis will be illustrated with examples from FCM assays commonly used in cancer immunotherapy laboratories

Viral Load Levels Measured at Set-Point Have Risen Over the Last Decade of the HIV Epidemic in the Netherlands

HIV-1 RNA plasma concentration at viral set-point is associated not only with disease outcome but also with the transmission dynamics of HIV-1. We investigated whether plasma HIV-1 RNA concentration and CD4 cell count at viral set-point have changed over time in the HIV epidemic in the Netherlands.We selected 906 therapy-naïve patients with at least one plasma HIV-1 RNA concentration measured 9 to 27 months after estimated seroconversion. Changes in HIV-1 RNA and CD4 cell count at viral set-point over time were analysed using linear regression models. The ATHENA national observational cohort contributed all patients who seroconverted in or after 1996; the Amsterdam Cohort Studies (ACS) contributed seroconverters before 1996. The mean of the first HIV-1 RNA concentration measured 9-27 months after seroconversion was 4.30 log(10) copies/ml (95% CI 4.17-4.42) for seroconverters from 1984 through 1995 (n = 163); 4.27 (4.16-4.37) for seroconverters 1996-2002 (n = 232), and 4.59 (4.52-4.66) for seroconverters 2003-2007 (n = 511). Compared to patients seroconverting between 2003-2007, the adjusted mean HIV-1 RNA concentration at set-point was 0.28 log(10) copies/ml (95% CI 0.16-0.40; p<0.0001) and 0.26 (0.11-0.41; p = 0.0006) lower for those seroconverting between 1996-2002 and 1984-1995, respectively. Results were robust regardless of type of HIV-1 RNA assay, HIV-1 subtype, and interval between measurement and seroconversion. CD4 cell count at viral set-point declined over calendar time at approximately 5 cells/mm(3)/year.The HIV-1 RNA plasma concentration at viral set-point has increased over the last decade of the HIV epidemic in the Netherlands. This is accompanied by a decreasing CD4 cell count over the period 1984-2007 and may have implications for both the course of the HIV infection and the epidemic

An increased MRP8/14 expression and adhesion, but a decreased migration towards proinflammatory chemokines of type 1 diabetes monocytes

8nonenoneBOUMA G; COPPENS JM; LAM-TSE WK; LUINI W; SINTNICOLAAS K; LEVERING WH; S. SOZZANI; DREXHAGE HA, VERSNEL MA.Bouma, G; Coppens, Jm; LAM TSE, Wk; Luini, W; Sintnicolaas, K; Levering, Wh; Sozzani, Silvano; DREXHAGE HA, VERSNEL M. A