Frequency and phenotype of B cell subpopulations in young and aged HIV-1 infected patients receiving ART

BACKGROUND: Aged individuals respond poorly to vaccination and have a higher risk of contracting infections in comparison to younger individuals; whether age impacts on the composition and function of B cell subpopulations relevant for immune responses is still controversial. It is also not known whether increased age during HIV-1 infection further synergizes with the virus to alter B cell subpopulations. In view of the increased number of HIV-1 infected patients living to high age as a result of anti-retroviral treatment this is an important issue to clarify. RESULTS: In this work we evaluated the distribution of B cell subpopulations in young and aged healthy individuals and HIV-1 infected patients, treated and naïve to treatment. B cell populations were characterized for the expression of inhibitory molecules (PD-1 and FcRL4) and activation markers (CD25 and CD69); the capacity of B cells to respond to activation signals through up-regulation of IL-6 expression was also evaluated. Increased frequencies of activated and tissue-like memory B cells occurring during HIV-1 infection are corrected by prolonged ART therapy. Our findings also reveal that, in spite of prolonged treatment, resting memory B cells in both young and aged HIV-1 infected patients are reduced in number, and all memory B cell subsets show a low level of expression of the activation marker CD25. CONCLUSIONS: The results of our study show that resting memory B cells in ART-treated young and aged HIV-1 infected patients are reduced in number and memory B cell subsets exhibit low expression of the activation marker CD25. Aging per se in the HIV-1 infected population does not worsen impairments initiated by HIV-1 in the memory B cell populations of young individuals. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12977-014-0076-x) contains supplementary material, which is available to authorized users

Immunoglobulin variable-region gene mutational lineage tree analysis: application to autoimmune diseases

Lineage trees have frequently been drawn to illustrate diversification, via somatic hypermutation (SHM), of immunoglobulin variable-region (IGV) genes. In order to extract more information from IGV sequences, we developed a novel mathematical method for analyzing the graphical properties of IgV gene lineage trees, allowing quantification of the differences between the dynamics of SHM and antigen-driven selection in different lymphoid tissues, species, and disease situations. Here, we investigated trees generated from published IGV sequence data from B cell clones participating in autoimmune responses in patients with Myasthenia Gravis (MG), Rheumatoid Arthritis (RA), and Sjögren's Syndrome (SS). At present, as no standards exist for cell sampling and sequence extraction methods, data obtained by different research groups from two studies of the same disease often vary considerably. Nevertheless, based on comparisons of data groups within individual studies, we show here that lineage trees from different individual patients are often similar and can be grouped together, as can trees from two different tissues in the same patient, and even from IgG- and IgA-expressing B cell clones. Additionally, lineage trees from most studies reflect the chronic character of autoimmune diseases

Influence of Treatment With Tumor-Treating Fields on Health-Related Quality of Life of Patients With Newly Diagnosed Glioblastoma: A Secondary Analysis of a Randomized Clinical Trial

Importance Tumor-treating fields (TTFields) therapy improves both progression-free and overall survival in patients with glioblastoma. There is a need to assess the influence of TTFields on patients' health-related quality of life (HRQoL). Objective To examine the association of TTFields therapy with progression-free survival and HRQoL among patients with glioblastoma. Design, Setting, and Participants This secondary analysis of EF-14, a phase 3 randomized clinical trial, compares TTFields and temozolomide or temozolomide alone in 695 patients with glioblastoma after completion of radiochemotherapy. Patients with glioblastoma were randomized 2:1 to combined treatment with TTFields and temozolomide or temozolomide alone. The study was conducted from July 2009 until November 2014, and patients were followed up through December 2016. Interventions Temozolomide, 150 to 200 mg/m2/d, was given for 5 days during each 28-day cycle. TTFields were delivered continuously via 4 transducer arrays placed on the shaved scalp of patients and were connected to a portable medical device. Main Outcomes and Measures Primary study end point was progression-free survival; HRQoL was a predefined secondary end point, measured with questionnaires at baseline and every 3 months thereafter. Mean changes from baseline scores were evaluated, as well as scores over time. Deterioration-free survival and time to deterioration were assessed for each of 9 preselected scales and items. Results Of the 695 patients in the study, 639 (91.9%) completed the baseline HRQoL questionnaire. Of these patients, 437 (68.4%) were men; mean (SD) age, 54.8 (11.5) years. Health-related quality of life did not differ significantly between treatment arms except for itchy skin. Deterioration-free survival was significantly longer with TTFields for global health (4.8 vs 3.3 months; P < .01); physical (5.1 vs 3.7 months; P < .01) and emotional functioning (5.3 vs 3.9 months; P < .01); pain (5.6 vs 3.6 months; P < .01); and leg weakness (5.6 vs 3.9 months; P < .01), likely related to improved progression-free survival. Time to deterioration, reflecting the influence of treatment, did not differ significantly except for itchy skin (TTFields worse; 8.2 vs 14.4 months; P < .001) and pain (TTFields improved; 13.4 vs 12.1 months; P < .01). Role, social, and physical functioning were not affected by TTFields. Conclusions and Relevance The addition of TTFields to standard treatment with temozolomide for patients with glioblastoma results in improved survival without a negative influence on HRQoL except for more itchy skin, an expected consequence from the transducer arrays. Trial Registration clinicaltrials.gov Identifier: NCT00916409

Tumor Treating Fields (TTFields) demonstrate antiviral functions in vitro, and safety for application to COVID-19 patients in a pilot clinical study

Coronaviruses are the causative agents of several recent outbreaks, including the COVID-19 pandemic. One therapeutic approach is blocking viral binding to the host receptor. As binding largely depends on electrostatic interactions, we hypothesized possible inhibition of viral infection through application of electric fields, and tested the effectiveness of Tumor Treating Fields (TTFields), a clinically approved cancer treatment based on delivery of electric fields. In preclinical models, TTFields were found to inhibit coronavirus infection and replication, leading to lower viral secretion and higher cell survival, and to formation of progeny virions with lower infectivity, overall demonstrating antiviral activity. In a pilot clinical study (NCT04953234), TTFields therapy was safe for patients with severe COVID-19, also demonstrating preliminary effectiveness data, that correlated with higher device usage

Human NK Cells Differ More in Their KIR2DL1-Dependent Thresholds for HLA-Cw6-Mediated Inhibition than in Their Maximal Killing Capacity

In this study we have addressed the question of how activation and inhibition of human NK cells is regulated by the expression level of MHC class I protein on target cells. Using target cell transfectants sorted to stably express different levels of the MHC class I protein HLA-Cw6, we show that induction of degranulation and that of IFN-γ secretion are not correlated. In contrast, the inhibition of these two processes by MHC class-I occurs at the same level of class I MHC protein. Primary human NK cell clones were found to differ in the amount of target MHC class I protein required for their inhibition, rather than in their maximum killing capacity. Importantly, we show that KIR2DL1 expression determines the thresholds (in terms of MHC I protein levels) required for NK cell inhibition, while the expression of other receptors such as LIR1 is less important. Furthermore, using mathematical models to explore the dynamics of target cell killing, we found that the observed delay in target cell killing is exhibited by a model in which NK cells require some activation or priming, such that each cell can lyse a target cell only after being activated by a first encounter with the same or a different target cell, but not by models which lack this feature

Kinetic modeling reveals a common death niche for newly formed and mature B cells.

B lymphocytes are subject to elimination following strong BCR ligation in the absence of appropriate second signals, and this mechanism mediates substantial cell losses during late differentiation steps in the bone marrow and periphery. Mature B cells may also be eliminated through this mechanism as well as through normal turnover, but the population containing mature cells destined for elimination has not been identified. Herein, we asked whether the transitional 3 (T3) subset, which contains most newly formed cells undergoing anergic death, could also include mature B cells destined for elimination.To interrogate this hypothesis and its implications, we applied mathematical models to previously generated in vivo labeling data. Our analyses reveal that the death rate of T3 B cells is far higher than the death rates of all other splenic B cell subpopulations. Further, the model, in which the T3 pool includes both newly formed and mature primary B cells destined for apoptotic death, shows that this cell loss may account for nearly all mature B cell turnover.This finding has implications for the mechanism of normal mature B cell turnover

Parameter ranges that result from the simulation.

a<p>Rates are per 6 hours.</p>b<p>Models that obey our parameter choice criteria and fit the experimental data.</p

Cell numbers versus time in a simulation of the spleen population model.

<p>These numbers were obtained by a simulation with the parameters set that gave the best fit to the data. Parameter values are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0009497#pone-0009497-t002" target="_blank">Table 2</a>. The steady-state numbers are: T1/2: 1.17×10⁶ cells, T3: 1.43×10⁶ cells, and Mature FO: 2.51×10⁶ cells.</p