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Pertel, T.

Publications and source records attributed to Pertel, T..

2 recordsLinked to original sources

Latent human herpesvirus 6 is reactivated in chimeric antigen receptor T cells

Cell therapies have yielded durable clinical benefits for patients with cancer, but the risks associated with the development of therapies from manipulated human cells are still being understood. For example, we currently lack a comprehensive understanding of the mechanisms of neurotoxicity observed in patients receiving T cell therapies, including recent reports of encephalitis caused by human herpesvirus 6 (HHV-6) reactivation1. Here, via petabase-scale viral RNA data mining, we examine the landscape of human latent viral reactivation and demonstrate that HHV-6B can become reactivated in human CD4+ T cells in standard in vitro cultures. Using single-cell sequencing, we identify a rare population of HHV-6 super-expressors (~1 in 300-10,000 cells) that possess high viral transcriptional activity in chimeric antigen receptor (CAR) T cell culture before spreading to infect other cells in vitro. Through the analysis of single-cell sequencing data from patients receiving cell therapy products that are FDA-approved2 or used in clinical studies3,4, we identify the presence of CAR+, HHV-6 super-expressor T cells in vivo. Together, our study implicates cell therapy products as a source of lytic HHV-6 reported in clinical trials1,5-7 and has broad implications for the design, production, and monitoring of cell therapies.

immunology↗

Single Cell-type Integrative Network Modeling IdentifiedNovel Microglial-specific Targets for the Phagosome inAlzheimer's disease

SummaryLate-Onset Alzheimer’s Disease (LOAD) results from a complex pathological process influenced by genetic variation, aging and environment factors. Genetic susceptibility factors indicate that myeloid cells such as microglia play a significant role in the onset of LOAD. Here, we developed a computational systems biology approach to construct probabilistic causal and predictive network models of genetic regulatory programs of microglial cells under LOAD diagnosis by integrating two independent brain transcriptome and genome-wide genotype datasets from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) and Mayo Clinic (MAYO) studies in the AMP-AD consortium. From this network model, we identified and replicated novel microglial-specific master regulators predicted to modulate network states associated with LOAD. We experimentally validated three microglial master regulators (FCER1G, HCK and LAPTM5) in primary human microglia-like cells (MDMi) by demonstrating the molecular impact these master regulators have on modulating downstream genomic targets identified by our top-down/bottom-up method and the causal relations among the three key drivers. These master regulators are involved in phagocytosis, a process associated with LOAD. Thus, we propose three new master regulator (key driver) genes that emerged from our network analyses as robust candidates for further evaluation in LOAD therapeutic development efforts.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗