Current chimeric antigen receptor (CAR)-T manufacturing utilizes viral vectors and extensive ex vivo expansion at large central facilities leading to an exhausted CAR-T phenotype, high costs and long vein-to-vein times. While allogeneic CAR-T can reduce delays in patient treatment, they require extensive manipulation of donor cells, severe lymphodepletion and demonstrate short persistence limiting their therapeutic window. The UltraCAR-T® platform is designed to overcome these limitations by utilizing non-viral multigene delivery and a rapid, decentralized manufacturing process without ex vivo activation or expansion of T cells. Patient’s own T cells are collected and manufactured at the medical center and re-infused one day after gene transfer. Here we describe the next generation UltraCAR-T platform that addresses the inhibitory tumor microenvironment by incorporating a novel mechanism for intrinsic downregulation of one or more checkpoint inhibitor (CPI) genes. Our design achieves intrinsic CPI blockade without gene editing and is aimed at avoiding systemic toxicity and the high cost of combining CPI antibodies. Next generation UltraCAR-T cells simultaneously express CAR, membrane bound IL-15 (mbIL15), kill switch, and incorporate intrinsic CPI blockade. To illustrate the ability of this platform, we designed exemplary non-viral transposons to generate UltraCAR-T cells against multiple tumor targets incorporating intrinsic blockade of either one (PD-1) or two (PD-1 and TIGIT) CPI genes. Healthy donor T cells were transfected using the UltraPorator™ electroporation system to manufacture UltraCAR-T cells without ex vivo activation or expansion. The co-expression of CAR, mbIL15 and kill switch was confirmed by flow cytometry and western blot. Activated UltraCAR-T showed significant reduction in CPI gene expression compared to control CAR-T cells lacking the CPI blockade and did not show unintended off-target activity. Downregulation of CPI gene(s) on UltraCAR-T enhanced cytotoxicity and inflammatory cytokine production, especially at low effector to target (E:T) cell ratios, when co-cultured with PD-L1+/CD155+ tumor cells. Single-cell cytokine proteomics showed significant increase in polyfunctionality of UltraCAR-T with intrinsic downregulation of CPI gene(s). In vivo, a single infusion of receptor tyrosine kinase-like orphan receptor 1 (ROR1)-specific UltraCAR-T with intrinsic PD-1 blockade resulted in rapid expansion, an increase in preferred T cell memory (TSCM/TCM) populations, and significantly improved overall survival of ROR1+ PD-L1+ tumor bearing mice. These preclinical data highlight the improved efficacy of incorporating intrinsic CPI blockade in UltraCAR-T cells using non-viral gene delivery and an established rapid, decentralized manufacturing process. Citation Format: Tim Chan, Cheryl Bolinger, Sean Scott, Mengyan Du, Carol Poortman, Byron Koenitzer, Taranjit Athwal, Lindsey Shepard, R. Daniel Slone, Shourik Dutta, Steven Zilko, James M. Dunleavey, Giorgio Zenere, Jacques Plummer, Bernward Klocke, Christian Zinser, Shamim Ahmad, Douglas E. Brough, Rutul R. Shah, Helen Sabzevari. Incorporation of intrinsic checkpoint blockade enhances functionality of multigenic autologous UltraCAR-T® cells manufactured using non-viral gene delivery and rapid manufacturing process [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2821.

Markers in monocytes, precursors of macrophages, which are related to CAD, are largely unknown. Therefore, we aimed to identify genes in monocytes predictive of a new ischemic event in patients with CAD and/or discriminate between stable CAD and acute coronary syndrome. We included 66 patients with stable CAD, of which 24 developed a new ischemic event, and 19 patients with ACS. Circulating CD14+ monocytes were isolated with magnetic beads. RNA sequencing analysis in monocytes of patients with (n = 13) versus without (n = 11) ischemic event at follow-up and in patients with ACS (n = 12) was validated with qPCR (n = 85). MT-COI, STRN and COX10 predicted new ischemic events in CAD patients (power for separation at 1% error rate of 0.97, 0.90 and 0.77 respectively). Low MT-COI and high STRN were also related to shorter time between blood sampling and event. COX10 and ZNF484 together with MT-COI, STRN and WNK1 separated ACS completely from stable CAD patients. RNA expressions in monocytes of MT-COI, COX10, STRN, WNK1 and ZNF484 were independent of cholesterol lowering and antiplatelet treatment. They were independent of troponin T, a marker of myocardial injury. But, COX10 and ZNF484 in human plaques correlated to plaque markers of M1 macrophage polarization, reflecting vascular injury. Expression of MT-COI, COX10, STRN and WNK1, but not that of ZNF484, PBMCs paired with that in monocytes. The prospective study of relation of MT-COI, COX10, STRN, WNK1 and ZNF484 with unstable CAD is warranted.

Background DNA methylation is one way to encode epigenetic information and plays a crucial role in regulating gene expression during embryonic development. DNA methylation marks are established by the DNA methyltransferases and, recently, a mechanism for active DNA demethylation has emerged involving the ten-eleven translocator proteins and thymine DNA glycosylase (TDG). However, so far it is not clear how these enzymes are recruited to, and regulate DNA methylation at, specific genomic loci. A number of studies imply that sequence-specific transcription factors are involved in targeting DNA methylation and demethylation processes. Oestrogen receptor beta (ERβ) is a ligand-inducible transcription factor regulating gene expression in response to the female sex hormone oestrogen. Previously, we found that ERβ deficiency results in changes in DNA methylation patterns at two gene promoters, implicating an involvement of ERβ in DNA methylation. In this study, we set out to explore this involvement on a genome-wide level, and to investigate the underlying mechanisms of this function. Results Using reduced representation bisulfite sequencing, we compared genome-wide DNA methylation in mouse embryonic fibroblasts derived from wildtype and ERβ knock-out mice, and identified around 8000 differentially methylated positions (DMPs). Validation and further characterisation of selected DMPs showed that differences in methylation correlated with changes in expression of the nearest gene. Additionally, re-introduction of ERβ into the knock-out cells could reverse hypermethylation and reactivate expression of some of the genes. We also show that ERβ is recruited to regions around hypermethylated DMPs. Finally, we demonstrate here that ERβ interacts with TDG and that TDG binds ERβ-dependently to hypermethylated DMPs. Conclusion We provide evidence that ERβ plays a role in regulating DNA methylation at specific genomic loci, likely as the result of its interaction with TDG at these regions. Our findings imply a novel function of ERβ, beyond direct transcriptional control, in regulating DNA methylation at target genes. Further, they shed light on the question how DNA methylation is regulated at specific genomic loci by supporting a concept in which sequence-specific transcription factors can target factors that regulate DNA methylation patterns.

The abuse of anabolic substances in animal husbandry is forbidden within the EU and well controlled by detecting substance residues in different matrices. The application of newly designed drugs or substance cocktails represents big problems. Therefore developing sensitive test methods is important. The analysis of physiological changes caused by the use of anabolic agents on the molecular level, for example, by quantifying gene expression response, is a new approach to develop such screening methods. A novel technology for holistic gene expression analysis is RNA sequencing. In this study, the potential of this high-throughput method for the identification of biomarkers was evaluated. The effect of trenbolone acetate plus estradiol on gene expression in liver from Nguni heifers was analyzed with RNA sequencing. The expression of 40 selected candidate genes was verified via RT-qPCR, whereby 20 of these genes were significantly regulated. To extract the intended information from these regulated genes, biostatistical tools for pattern recognition were applied and resulted in a clear separation of the treatment groups. Those candidate genes could be verified in boars and in calves treated with anabolic substances. These results show the potential of RNA sequencing to screen for biomarker candidates to detect the abuse of anabolics. The verification of these biomarkers in boars and calves leads to the assumption that gene expression biomarkers are independent of breed or even species and that biomarkers, identified in farm animals could also act as potential biomarker candidates to detect the abuse of anabolic substances in human sports.

In recent years, gene fusions have gained significant recognition as biomarkers. They can assist treatment decisions, are seldom found in normal tissue and are detectable through Next-generation sequencing (NGS) of the transcriptome (RNA-seq). To transform the data provided by the sequencer into robust gene fusion detection several analysis steps are needed. Usually the first step is to map the sequenced transcript fragments (RNA-seq) to a reference genome. One standard application of this approach is to estimate expression and detect variants within known genes, e.g. SNPs and indels. In case of gene fusions, however, completely novel gene structures have to be detected. Here, we describe the detection of such gene fusion events based on our comprehensive transcript annotation (ElDorado). To demonstrate the utility of our approach, we extract gene fusion candidates from eight breast cancer cell lines, which we compare to experimentally verified gene fusions. We discuss several gene fusion events, like BCAS3-BCAS4 that was only detected in the breast cancer cell line MCF7. As supporting evidence we show that gene fusions occur more frequently in copy number enriched regions (CNV analysis). In addition, we present the Transcriptome Viewer (TViewer) a tool that allows to interactively visualize gene fusions. Finally, we support detected gene fusions through literature mining based annotations and network analyses. In conclusion, we present a platform that allows detecting gene fusions and supporting them through literature knowledge as well as rich visualization capabilities. This enables scientists to better understand molecular processes, biological functions and disease associations, which will ultimately lead to better biomedical knowledge for the development of biomarkers for diagnostics and therapies.

Background: MYC is a key transcription factor involved in central cellular processes such as regulation of the cell cycle, histone acetylation and ribosomal biogenesis. It is overexpressed in the majority of human tumors including aggressive B-cell lymphoma. Especially Burkitt lymphoma (BL) is a highlight example for MYC overexpression due to a chromosomal translocation involving the c-MYC gene. However, no genome-wide analysis of MYC-binding sites by chromatin immunoprecipitation (ChIP) followed by next generation sequencing (ChIP-Seq) has been conducted in BL so far.Methodology/Principal Findings: ChIP-Seq was performed on 5 BL cell lines with a MYC-specific antibody giving rise to 7,054 MYC-binding sites after bioinformatics analysis of a total of approx. 19 million sequence reads. In line with previous findings, binding sites accumulate in gene sets known to be involved in the cell cycle, ribosomal biogenesis, histone acetyltransferase and methyltransferase complexes demonstrating a regulatory role of MYC in these processes. Unexpectedly, MYC-binding sites also accumulate in many B-cell relevant genes. To assess the functional consequences of MYC binding, the ChIP-Seq data were supplemented with siRNA-mediated knock-downs of MYC in BL cell lines followed by gene expression profiling. Interestingly, amongst others, genes involved in the B-cell function were up-regulated in response to MYC silencing.Conclusion/Significance: The 7,054 MYC-binding sites identified by our ChIP-Seq approach greatly extend the knowledge regarding MYC binding in BL and shed further light on the enormous complexity of the MYC regulatory network. Especially our observations that (i) many B-cell relevant genes are targeted by MYC and (ii) that MYC down-regulation leads to an upregulation of B-cell genes highlight an interesting aspect of BL biology.

Luminal-like breast tumor cells express estrogen receptor alpha (ERalpha), a member of the nuclear receptor family of ligand-activated transcription factors that controls their proliferation, survival, and functional status. To identify the molecular determinants of this hormone-responsive tumor phenotype, a comprehensive genome-wide analysis was performed in estrogen stimulated MCF-7 and ZR-75.1 cells by integrating time-course mRNA expression profiling with global mapping of genomic ERalpha binding sites by chromatin immunoprecipitation coupled to massively parallel sequencing, microRNA expression profiling, and in silico analysis of transcription units and receptor binding regions identified. All 1270 genes that were found to respond to 17beta-estradiol in both cell lines cluster in 33 highly concordant groups, each of which showed defined kinetics of RNA changes. This hormone-responsive gene set includes several direct targets of ERalpha and is organized in a gene regulation cascade, stemming from ligand-activated receptor and reaching a large number of downstream targets via AP-2gamma, B-cell activating transcription factor, E2F1 and 2, E74-like factor 3, GTF2IRD1, hairy and enhancer of split homologue-1, MYB, SMAD3, RARalpha, and RXRalpha transcription factors. MicroRNAs are also integral components of this gene regulation network because miR-107, miR-424, miR-570, miR-618, and miR-760 are regulated by 17beta-estradiol along with other microRNAs that can target a significant number of transcripts belonging to one or more estrogen-responsive gene clusters.