Flow cytometry is a widely applied approach for exploratory immune profiling and biomarker discovery in cancer and other diseases. However, flow cytometry is limited by the number of parameters that can be simultaneously analyzed, severely restricting its utility. Recently, the advent of mass cytometry (CyTOF) has enabled high dimensional and unbiased examination of the immune system, allowing simultaneous interrogation of a large number of parameters. This is important for deep interrogation of immune responses and particularly when sample sizes are limited (such as in tumors). Our goal was to compare the accuracy and reproducibility of CyTOF against flow cytometry as a reliable analytic tool for human PBMC and tumor tissues for cancer clinical trials. We developed a 40+ parameter CyTOF panel and demonstrate that compared to flow cytometry, CyTOF yields analogous quantification of cell lineages in conjunction with markers of cell differentiation, function, activation, and exhaustion for use with fresh and viably frozen PBMC or tumor tissues. Further, we provide a protocol that enables reliable quantification by CyTOF down to low numbers of input human cells, an approach that is particularly important when cell numbers are limiting. Thus, we validate CyTOF as an accurate approach to perform high dimensional analysis in human tumor tissue and to utilize low cell numbers for subsequent immunologic studies and cancer clinical trials.

It remains unknown how fine particulate matter (PM2.5) constituents affect differently the fractional concentration of exhaled nitric oxide (FeNO, a biomarker of airway inflammation) and the DNA methylation of its encoding gene (NOS2A). We aimed to investigate the short-term effects of PM2.5 constituents on NOS2A methylation and FeNO. We designed a longitudinal study among chronic obstructive pulmonary disease (COPD) patients with six repeated health measurements in Shanghai, China. We applied linear mixed-effect models to evaluate the associations. We observed that the inverse association between PM2.5 and methylation at position 1 was limited within 24 h, and the positive association between PM2.5 and FeNO was the strongest at lag 1 day. Organic carbon, element carbon, NO3(-) and NH4(+) were robustly and significantly associated with decreased methylation and elevated FeNO. An interquartile range increase in total PM2.5 and the four constituents was associated with decreases of 1.19, 1.63, 1.62, 1.17, and 1.14 in percent methylation of NOS2A, respectively, and increases of 13.30%,16.93%, 8.97%, 18.26%, and 11.42% in FeNO, respectively. Our results indicated that organic carbon, element carbon, NO3(-) and NH4(+) might be mainly responsible for the effects of PM2.5 on the decreased NOS2A DNA methylation and elevated FeNO in COPD patients.

Bacille Calmette–Guérin (BCG), an attenuated strain of Mycobacterium bovis, is the only vaccine available for tuberculosis (TB) control. However, BCG is not an ideal vaccine and has two major limitations: BCG exhibits highly variable effectiveness against the development of TB both in pediatric and adult populations and can cause disseminated BCG disease in immunocompromised individuals. BCG comprises a number of substrains that are genetically distinct. Whether and how these genetic differences affect BCG efficacy remains largely unknown. In this study, we performed comparative analyses of the virulence and efficacy of 13 BCG strains, representing different genetic lineages, in SCID and BALB/c mice. Our results show that BCG strains of the DU2 group IV (BCG-Phipps, BCG-Frappier, BCG-Pasteur, and BCG-Tice) exhibit the highest levels of virulence, and BCG strains of the DU2 group II (BCG-Sweden, BCG-Birkhaug) are among the least virulent group. These distinct levels of virulence may be explained by strain-specific duplications and deletions of genomic DNA. There appears to be a general trend that more virulent BCG strains are also more effective in protection against Mycobacterium tuberculosis challenge. Our findings have important implications for current BCG vaccine programs and for future TB vaccine development.

Limited evidence is available on the effects of various fine particulate matter (PM) constituents on blood inflammation and coagulation. We examined the associations between 10 constituents and 10 circulating biomarkers in a panel of 28 urban residents with four repeated measurements in Shanghai, China. Based on the linear mixed-effect models, we fitted the single-constituent models, the constituent-PM joint models, and the constituent-residual models to evaluate the associations between PM constituents and eight inflammatory biomarkers (fibrinogen, C-reactive protein, monocyte chemoattractant protein-1, tumor necrosis factor-α, interleukin-1b, intercellular adhesion molecule-1, P-selectin, vascular cell adhesion molecule-1) and two coagulation biomarkers (plasminogen activator inhibitor-1 and soluble CD40 ligand). We found robust associations of organic carbon (OC), elemental carbon (EC), nitrate (NO), and ammonium (NH) with at least 1 of 8 inflammatory markers. On average, an interquartile range increase in the four constituents corresponded to increments of 50%, 37%, 25%, and 26% in inflammatory biomarkers, respectively. Only sulfate (SO) or NH was robustly associated with coagulation markers (corresponding increments: 23% and 20%). Our results provided evidence that some constituents in PM (OC, EC, NO, SO, and NH) might play crucial roles in inducing systematic inflammation and coagulation, but their roles varied by the selected biomarkers.