Decreased progenitor TCF1 + T-cells correlate with COVID-19 disease severity.

COVID-19, caused by SARS-CoV-2, can lead to a severe inflammatory disease characterized by significant lymphopenia. However, the underlying cause for the depletion of T-cells in COVID-19 patients remains incompletely understood. In this study, we assessed the presence of different T-cell subsets in the progression of COVID-19 from mild to severe disease, with a focus on TCF1 expressing progenitor T-cells that are needed to replenish peripheral T-cells during infection. Our results showed a preferential decline in TCF1+ progenitor CD4 and CD8+ T-cells with disease severity. This decline was seen in various TCF1+ subsets including naive, memory and effector-memory cells, and surprisingly, was accompanied by a loss in cell division as seen by a marked decline in Ki67 expression. In addition, TCF1+ T-cells showed a reduction in pro-survival regulator, BcL2, and the appearance of a new population of TCF1 negative caspase-3 expressing cells in peripheral blood from patients with severe disease. The decline in TCF1+ T-cells was also seen in a subgroup of severe patients with vitamin D deficiency. Lastly, we found that sera from severe patients inhibited TCF1 transcription ex vivo which was attenuated by a blocking antibody against the cytokine, interleukin-12 (IL12). Collectively, our findings underscore the potential significance of TCF1+ progenitor T-cells in accounting for the loss of immunity in severe COVID-19 and outline an array of markers that could be used to identify disease progression.

Population PK/PD modelling of meropenem in preterm newborns based on therapeutic drug monitoring data.

Background: Preterm neonates rarely participate in clinical trials, this leads to lack of adequate information on pharmacokinetics for most drugs in this population. Meropenem is used in neonates to treat severe infections, and absence of evidence-based rationale for optimal dosing could result in mismanagement. Aim: The objective of the study was to determine the population pharmacokinetic (PK) parameters of meropenem in preterm infants from therapeutic drug monitoring (TDM) data in real clinical settings and to evaluate pharmacodynamics (PD) indices as well as covariates affecting pharmacokinetics. Materials and methods: Demographic, clinical and TDM data of 66 preterm newborns were included in PK/PD analysis. The NPAG program from the Pmetrics was used for modelling based on peak-trough TDM strategy and one-compartment PK model. Totally, 132 samples were assayed by high-performance liquid chromatography. Meropenem empirical dosage regimens (40-120 mg/kg/day) were administered by 1-3-h IV infusion 2-3 times a day. Regression analysis was used to evaluate covariates (gestation age (GA), postnatal age (PNA), postconceptual age (PCA), body weight (BW), creatinine clearance, etc.) influenced on PK parameters. Results: The mean ± SD (median) values for constant rate of elimination (Kel) and volume of distribution (V) of meropenem were estimated as 0.31 ± 0.13 (0.3) 1/h and 1.2 ± 0.4 (1.2) L with interindividual variability (CV) of 42 and 33%, respectively. The median values for total clearance (CL) and elimination half-life (T1/2) were calculated as 0.22 L/h/kg and 2.33 h with CV = 38.0 and 30.9%. Results of the predictive performance demonstrated that the population model by itself gives poor prediction, while the individualized Bayesian posterior models give much improved quality of prediction. The univariate regression analysis revealed that creatinine clearance, BW and PCA influenced significantly T1/2, meropenem V was mostly correlated with BW and PCA. But not all observed PK variability can be explained by these regression models. Conclusion: A model-based approach in conjunction with TDM data could help to personalize meropenem dosage regimen. The estimated population PK model can be used as Bayesian prior information to estimate individual PK parameter values in the preterm newborns and to obtain predictions of desired PK/PD target once the patient's TDM concentration(s) becomes available.

Effective chimeric antigen receptor T cells against SARS-CoV-2.

Current therapies to treat coronavirus disease 2019 (COVID-19) involve vaccines against the spike protein S1 of SARS-CoV-2. Here, we outline an alternative approach involving chimeric antigen receptors (CARs) in T cells (CAR-Ts). CAR-T recognition of the SARS-CoV-2 receptor-binding domain (RBD) peptide induced ribosomal protein S6 phosphorylation, the increased expression of activation antigen, CD69 and effectors, interferon-γ, granzyme B, perforin, and Fas-ligand on overlapping subsets of CAR-Ts. CAR-Ts further showed potent in vitro killing of target cells loaded with RBD, S1 peptide, or expressing the S1 protein. The efficacy of killing varied with different sized hinge regions, whereas time-lapse microscopy showed CAR-T cluster formation around RBD-expressing targets. Cytolysis of targets was mediated primarily by the GZMB/perforin pathway. Lastly, we showed in vivo killing of S1-expressing cells by our SARS-CoV-2 CAR-Ts in mice. The successful generation of SARS-CoV-2 CAR-Ts represents a living vaccine approach for the treatment of COVID-19.

Hydroxychloroquine (HCQ) decreases the benefit of anti-PD-1 immune checkpoint blockade in tumor immunotherapy.

Immunotherapy using checkpoint blockade (ICB) with antibodies such as anti-PD-1 has revolutionised the treatment of many cancers. Despite its use to treat COVID-19 patients and autoimmune diseases such as systemic lupus erythematosus and rheumatoid arthritis, the effect of hydroxychloroquine (HCQ) on cancer immunotherapy has not been examined. In this study, remarkably, we find that HCQ alone, or in combination with azithromycin (AZ), at doses used to treat patients, decreased the therapeutic benefit of anti-PD-1 in cancer immunotherapy. No deleterious effect was seen on untreated tumors. Mechanistically, HCQ and HCQ/AZ inhibited PD-L1 expression on tumor cells, while specifically targeting the anti-PD-1 induced increase in progenitor CD8+CD44+PD-1+TCF1+ tumor infiltrating T cells (TILs) and the generation of CD8+CD44+PD-1+ effectors. Surprisingly, it also impaired the appearance of a subset of terminally exhausted CD8+ TILs. No effect was seen on the presence of CD4+ T cells, FoxP3+ regulatory T cells (Tregs), thymic subsets, B cells, antibody production, myeloid cells, or the vasculature of mice. This study indicates for the first time that HCQ and HCQ/AZ negatively impact the ability of anti-PD-1 checkpoint blockade to promote tumor rejection.

Programmed cell death 1 ligand (PD-L1) on T cells generates Treg suppression from memory.

A recent study shows that programmed cell death 1 ligand (PD-L1) on activated T cells promotes their conversion to suppressive inducible regulatory T cells (iTregs), preferentially from among memory T cells. This new mechanism may normally protect against autoimmunity but is dysregulated in rheumatoid arthritis.

A side-by-side comparison of T cell reactivity to fifty-nine Mycobacterium tuberculosis antigens in diverse populations from five continents.

We compared T cell recognition of 59 prevalently recognized Mycobacterium tuberculosis (MTB) antigens in individuals latently infected with MTB (LTBI), and uninfected individuals with previous BCG vaccination, from nine locations and populations with different HLA distribution, MTB exposure rates, and standards of TB care. This comparison revealed similar response magnitudes in diverse LTBI and BCG-vaccinated cohorts and significant correlation between responses in LTBIs from the USA and other locations. Many antigens were uniformly recognized, suggesting suitability for inclusion in vaccines targeting diverse populations. Several antigens were similarly immunodominant in LTBI and BCG cohorts, suggesting applicability for vaccines aimed at boosting BCG responses. The panel of MTB antigens will be valuable for characterizing MTB-specific CD4 T cell responses irrespective of ethnicity, infecting MTB strains and BCG vaccination status. Our results illustrate how a comparative analysis can provide insight into the relative immunogenicity of existing and novel vaccine candidates in LTBIs.