Citations

Abstract Background Measurement of cardiac troponin (cTn) using high-sensitivity assays is recommended for the diagnosis of myocardial infarction. We determined sex-specific and uniform 99th percentile upper reference limits (URLs) using the new Elecsys® Troponin T high-sensitivity Gen 6 assay in a global, healthy reference range cohort. Methods Lithium-heparin plasma and serum samples were prospectively collected from apparently healthy individuals aged ≥20 years across 34 global sites in the United States, Europe, China, and Japan. cTnT was measured using the Troponin T high-sensitivity Gen 6 assay on the Cobas® e 801 analyzer. Exclusion criteria were defined according to the 2022 IFCC guidance. Uniform and sex-specific 99th percentile URLs and nonparametric 95% CIs were determined in plasma and serum separately and combined. Results The final study population comprised 4147 participants (52.5% female) with a median (25th–75th percentiles) age of 48.0 (33.0–59.0) years; 45.8%, 47.9%, 5.2%, and 1.1% were White, Asian, Black, and other/unknown, respectively. For sample matrices combined (n = 8294), 81.0% and 99.2% of cTnT values were above the limit of detection in females and males, respectively. Sex-specific 99th percentile URLs (95% CI) were 18 (16–23) ng/L for females and 32 (28–35) ng/L for males; the uniform 99th percentile URL was 27 (24–31) ng/L. URLs were comparable in plasma and serum samples. Conclusions This study determined sex-specific and uniform 99th percentile URLs for the Troponin T high-sensitivity Gen 6 assay that were comparable irrespective of the matrix used in a large, global, healthy reference population.

Abstract Background: Integrin αE (CD103) has been thought to mediate gut-homing Treg retention during GVHD by facilitating E-cadherin interaction on intestinal epithelial cells. However, only a small percentage of natural Tregs express CD103 in peripheral blood (PB). To leverage this mechanism and potentially enhance Treg therapeutic efficacy, we hypothesized that Tregs overexpressing CD103 (CD103high) would show improved gut-homing and GVHD mitigation. Methods: Murine CD4 Tregs were isolated from C57BL/6 (B6) mice via flow sorting and were retrovirally transduced with murine CD103 or truncated epidermal growth factor receptor as a control. Transduced Tregs were then tested in a murine acute GVHD model (B6 → BALB/c). Mouse organs, including small intestine (SI), colon, spleen, PB, axillary (aLN) and mesentric lymph nodes (mLN) were harvested on day 10 post-transplant and analyzed by flow cytometry, multiplex cytokine assay, histopathology, and single-cell RNA sequencing (scRNA-seq). Ex vivo expanded Tregs were subjected to 13C-glucose tracing assay to evaluate glycolytic flux, TCA cycle, and lipid biosynthesis. Results: Despite comparable FoxP3 expression at the end of ex vivo expansion, CD103high Tregs had significantly higher in vitro suppression compared to control Tregs (54% vs. 33% at Treg:Tcon ratio of 1:8, p=0.004). Upon re-stimulation, CD103high Tregs demonstrated increased proliferation compared to control Tregs (3.8 vs 2.8 fold expansion, p <0.0001). Bulk RNA seq on ex vivo expanded CD103high showed upregulation of immuneregulatory and metabolic programs including GTPase signaling and oxidative stress control. These transcriptomic changes suggest that CD103 intrinsically promotes a regulatory phenotype, stress tolerance and metabolic fitness. In vivo, CD103highTregs significantly decreased the severity and mortality of GVHD, compared to control Tregs, as measured by clinical scores, weight loss, and survival (50% vs 0% on day +60, p<0.0001 for three independent experiments combined; n = 24/group). Day 20 histopathology revealed significantly improved colitis scores in mice treated with CD103high Tregs vs controls (9.5 vs. 14.6, p=0.02). While these findings could be partially attributed to CD103 gut-homing function, we observed that CD103high Treg absolute number and frequency were higher not only in the the GI organs and mLN, but also in the spleen, PB, and aLN with similar distribution ratios across different organs (~5-fold higher). In vivo CFSE suppression assay, where CFSE labeled donor T cells were cotransferred with Tregs into B6 Rag1ko mice, demonstrated enhanced suppressive function of CD103high Tregs in the spleen (p=0.02), an effect that could not be accounted for by the conventional gut-homing mechanism attributed to CD103. Plasma cytokine analysis showed significantly elevated IL-10 levels in mice treated with CD103high Tregs (p<0.0001), consistent with increased Treg number and frequency. 13C-glucose tracing assay showed lower palmitate levels in CD103high Tregs, indicating lower de novo lipid synthesis, while glycolysis and TCA cycle tracing were similar. Day 10 scRNA-seq on colon samples revealed seven distinct immune clusters. The neutrophil cluster was absent in CD103high Treg group, suggesting reduced inflammation. Donor-derived dendritic cells (DCs) upregulated genes such as Cstb, and Slamf7, while pro-inflammatory genes including Cd52 and Cd74 were downregulated. STAT5 signaling was upregulated, indicating reprograming of myeloid cells toward an immunoregulatory state. Colon epithelial cells from CD103high Treg-treated mice displayed enhanced stress tolerance, with increased oxidative phosphorylation, fatty acid metabolism, and epithelial repair pathways. CellChat analysis revealed that CD103high Tregs reshaped the intestinal communication landscape, with DCs acting as key signaling hubs through interactions such as Ccl6–Ccr2 and Lgals3–Cd44. Enhanced DC-to-DC and DC-to-T cell communication suggest that CD103high Tregs promote a tolerogenic DC network that modulates downstream immune responses and supports epithelial recovery. Conclusion: Tregs overexpressing CD103 via retroviral transduction significantly improve overall survival and GVHD clinical scores in a murine transplant model. CD103High Tregs orchestrate broad remodeling of cell-cell communication across immune and stromal compartments, promoting an immunoregulatory microenvironment that underlies their protective effects in GVHD.

Abstract Lewy pathology can form over decades in patients with Lewy body diseases, but the causal cellular mechanisms associated with this process remain unclear. This project aims to discover proteins that associate with monomeric and/or oligomeric alpha-synuclein during early stages of the aggregation process. To mimic the aggregation processes, cells expressing a synuclein-biotin ligase fusion protein were treated human recombinant pre-formed fibrils and subjected to BioSITe and mass spectrometry. Using a novel split biotin ligase fused to alpha-synuclein facilitated the identification of proteins specifically associated with multimeric alpha-synuclein. A total of 581 proteins were differentiated into potential interactors of monomeric versus multimeric alpha-synuclein in physiological versus aggregated conditions. The data reveal important phosphorylation mechanisms, connections to insulin processing, and a potential interaction with ALS-associated FUS. Interestingly, we identified that loss of specific interactions may contribute to pathology in patients with sporadic onset of Lewy body diseases. Future studies will validate both true interaction of highlighted proteins with alpha-synuclein, and the impact of such proteins on alpha-synuclein aggregation.

Abstract Motivation Single-cell RNA sequencing (scRNA-seq) has become an important method for characterizing cellular heterogeneity, revealing more biological insights than the bulk RNA-seq. The surge in scRNA-seq data across multiple individuals calls for efficient and statistically powerful methods for differential expression (DE) analysis that addresses individual-level biological variability. Results We introduced DiSC, a method for conducting individual-level DE analysis by extracting multiple distributional characteristics, jointly testing their association with a variable of interest, and using a flexible permutation testing framework to control the false discovery rate (FDR). Our simulation studies demonstrated that DiSC effectively controlled the FDR across various settings and exhibited high statistical power in detecting different types of gene expression changes. Moreover, DiSC is computationally efficient and scalable to the rapidly increasing sample sizes in scRNA-seq studies. When applying DiSC to identify DE genes potentially associated with COVID-19 severity and Alzheimer’s disease across various types of peripheral blood mononuclear cells and neural cells, we found that our method was approximately 100 times faster than other state-of-the-art methods and the results were consistent and supported by existing literature. While DiSC was developed for scRNA-seq data, its robust testing framework can also be applied to other types of single-cell data. We applied DiSC to cytometry by time-of-flight data, DiSC identified significantly more DE markers than traditional methods. Availability and implementation The R software package “SingleCellStat” is freely available on CRAN (https://cran.r-project.org/web/packages/SingleCellStat/index.html) and GitHub (https://github.com/Lujun995/DiSC). The replication code for reproducing the analyses in this study is publicly accessible at https://github.com/Lujun995/DiSC_Replication_Code. The scRNA-seq expression matrix and metadata utilized in our simulations and analyses can be retrieved from https://cells.ucsc.edu/autism/rawMatrix.zip, https://cellxgene.cziscience.com/collections/1ca90a2d-2943-483d-b678-b809bf464c30, and https://covid19.cog.sanger.ac.uk/submissions/release1/haniffa21.processed.h5ad.

Abstract Single-cell sequencing technologies provide us with information at the level of individual cells. Combining single-cell RNA-seq and single-cell TCR-seq profiling enables the exploration of cell heterogeneity and T-cell receptor repertoires simultaneously. Integrating both types of data can play a crucial role in enhancing our understanding of T-cell-mediated immunity and, in turn, facilitate the advancement of immunotherapy. Here, we present immunopipe, a comprehensive and flexible pipeline to perform integrated analysis of scRNA-seq and scTCR-seq data. In addition to the command line tool, we provide a user-friendly web interface for pipeline configuration and execution monitoring, benefiting researchers without extensive programming experience. With its comprehensive functionality and ease of use, immunopipe empowers researchers to uncover valuable insights from scRNA-seq and scTCR-seq data, ultimately advancing the understanding of immune responses and immunotherapy development.

ABSTRACT Recent development of single-cell technology across multiple omics platforms has provided new ways to obtain holistic views of cells to study disease pathobiology. Alzheimer’s disease (AD) is the most common form of dementia worldwide, yet the detailed understanding of its cellular and molecular mechanisms remains limited. In this study, we analyzed paired single-cell transcriptomic (scRNA-seq) and chromatin accessibility (scATAC-seq) data from the Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) Consortium to investigate the molecular mechanisms of AD at a cell-subpopulation-specific resolution focusing on glial cells. We benchmarked various multi-omics integration methods using diverse metrics and built an analytic workflow that enabled effective batch correction and cross-modality alignment, creating a unified cell state space. Through integrative analysis of 26 human brain samples, we uncovered AD-associated gene expression and pathway changes in glial subpopulations and highlighted important transcriptomic and epigenomic signatures via functional inference and interpretable machine learning paradigms, discovering the profound involvement of the Solute Carrier proteins (SLC) family genes in multiple glial cell types. We also identified glial cell-specific regulatory programs mediated by key transcription factors such as JUN and FOSL2 in astrocytes, the Zinc Finger (ZNF) family genes in microglia, and the SOX family of transcription factors in oligodendrocytes. Our study provides a comprehensive workflow and a high-resolution view of how glial regulatory programs are disrupted in AD. Our findings offer novel insights into disease-related changes in gene regulation and suggest potential targets for further research and therapy.

Abstract Single-cell RNA sequencing (scRNA-seq) enables high-resolution exploration of cellular diversity and gene regulation, yet analyzing such data remains challenging due to technical and methodological limitations. Existing task-specific deep generative models like Variational Auto-Encoder (VAE) and its variants struggle to incorporate external biological knowledge, while transformer-based foundational large Language Models (LLMs or large LaMs) face limitations in computational cost and applicability to tabular gene expression data. Here, we introduce sciL-aMA (single-cell interpretable Language Model Adapter), a novel representation learning frame-work that bridges these gaps by integrating static gene embeddings from multimodal LLMs with scRNA-seq tabular data through a paired-VAE architecture. Our approach generates context-aware representations for both cells and genes and outperforms state-of-the-art methods in key single-cell downstream tasks, including batch effect correction, cell clustering, and cell-state-specific gene marker and module identification, while maintaining computational efficiency. sciL-aMA offers a computationally efficient, unified framework for comprehensive single-cell data analysis and biologically interpretable gene module discovery. Source code is available at https://github.com/microsoft/sciLaMA

Brexucabtagene autoleucel (brexu-cel), a CD28-costimulated CD19-targeted chimeric antigen receptor T cell (CART19) product, was FDA-approved in 2020 after demonstrating remarkable efficacy in the pivotal ZUMA-2 trial of patients with mantle cell lymphoma (MCL). However, despite the impressive initial activity of CART19 cell therapy in MCL, most patients relapse within the first 3 years following treatment. Myeloid cells, such as monocytes and macrophages, have been demonstrated to be major inhibitors of other immune cells, including T cells. Growing evidence shows that monocytes and macrophages contribute to CART cell failure, although the exact mechanisms are not fully understood. To better understand the mechanisms contributing to CART treatment resistance in MCL, we first utilized brexu-cel products from patients with MCL on the ZUMA-2 trial to uncover their transcriptomic features by single cell RNA sequencing (scRNAseq) analysis. To understand if myeloid cells had negative impacts on clinical outcomes, we then analyzed autologous baseline peripheral blood mononuclear cell (PBMC) samples by scRNAseq. Our analyses of the brexu-cel samples revealed reduced response to IL-1β and its downstream signaling pathway as well as impaired T cell functions in non-responders. Transcriptomic analyses of the autologous baseline monocyte populations showed downregulation of IL-1β production and its associated pathways as well as upregulation of M2 phenotype-associated genes and IL-1 receptor antagonist (IL-1ra) in non-responder monocytes, implying a potential role of myeloid cells in CART resistance through impairment of IL-1 signaling in brexu-cel products. To validate our findings from the ZUMA-2 samples, we further studied the interactions between macrophages, MCL cells, and CART19 cells in preclinical models. First, CD28-costimulated CART19 cells generated from healthy donors were cocultured with JeKo-1, a CD19+ MCL cell line, and freshly isolated monocytes or ex vivo differentiated M2-like macrophages. M2-like macrophages were generated by incubating fresh monocytes with rhGM-CSF followed by coculturing with JeKo-1. CART19 antigen-specific proliferation was significantly inhibited by M2-like macrophages but not fresh monocytes (JeKo-1+CART19 vs JeKo-1+M2+CART19, p=0.00503). Transwell assays indicated that suppression by M2-like macrophages was contact-independent. Cytokine profile analysis of coculture supernatants showed significant elevation of IL-1ra in M2-like macrophage cocultures (JeKo-1+Mono+CART19 vs JeKo-1+M2+CART19, p=0.0292). This led us to hypothesize that M2-like macrophages inhibit CART19 by secreting IL-1ra to block IL-1 signaling in CART19. To test this hypothesis, we interrogated the role of IL-1ra in CART19. CART19 + JeKo-1 cocultures were supplemented with IL-1β + IL-1ra or IL-1β + IL-1ra + IL-1ra neutralizing antibody (neuAb). CART19 proliferation was improved by IL-1β (vehicle control vs IL-1β, p<0.0001). IL-1ra inhibited IL-1β-dependent CART19 proliferation (IL-1β vs IL-1β+IL1ra, p=0.0006), which was restored by IL-1ra neutralization (IL-1β+IL-1ra vs IL-1β+IL-1ra+IL-1ra neuAb, p=0.0215). Next, we assessed the impact of IL-1ra on CART functions in mouse MCL xenografts in the presence of M2-like macrophages. NOD-SCID-γ-/- (NSG) mice were subcutaneously injected with 0.5 million of human macrophages and 1 million of luciferase+ JeKo-1. Mice were then randomized once tumor engraftment was confirmed by bioluminescence imaging (BLI), followed by treatment with 2 million CART19 with 10 mg/kg IL-1ra neuAb or control IgG for 3 weeks. Combination of CART19 cells and IL-1ra neuAb led to improved antitumor activity based on BLI measurements compared to control IgG (IL-1ra neuAb vs control IgG, p=0.0058). Additionally, expression of IL-1RI, receptor of IL-1β and IL-1ra, was measured on T cells after coculturing CART19, JeKo-1, and M2-like macrophages. M2-like macrophages downregulated IL-1RI expression on CART cells, which might potentially desensitize CART response to IL-1β, resulting in further suppression in CART proliferation (JeKo-1+M2+CART19 vs JeKo-1+CART19, p=0.001). Overall, our study elucidates a potential mechanism of IL-1 pathway modulation mediated by myeloid cells in contributing to CART19 failure in MCL.

Abstract Introduction: Single-cell RNA-sequencing (scRNA-seq) pairing with single-cell T-Cell-Receptor-sequencing (scTCR-seq) enables profiling of gene expression and TCR repertoires in individual T cells, elevating our understanding of T-cell-mediated immunity. Here, we present immunopipe, a comprehensive and flexible pipeline (https://github.com/pwwang/immunopipe) for analyzing the paired data. Besides the command-line tool, it offers a user-friendly web interface that allows users with varying programming expertise to configure, initiate, and monitor the pipeline. By combining extensive functionality with ease of use, immunopipe empowers users to unlock valuable insights from the data, which notably advances our understanding of immune response and fosters the development of innovative immunotherapies. Results: Immunopipe is a comprehensive analytical pipeline for scRNA-seq and scTCR-seq data, offering various modules leveraging existing tools and novel methods to ensure data quality and enable downstream analytics. It performs quality control for scRNA-seq data, clusters cells based on gene expression to facilitate the identification of cell populations and provides insights into T-cell heterogeneity and functional diversity through T-cell selection and clustering. Enrichment analysis identifies markers and pathways for T-cell characterization. Our automated T-cell annotation tool annotates cell types accurately and hierarchically. For scTCR-seq data, immunopipe analyzes TCR clones, including clonality, diversity, gene usage, and repertoire overlap. Clone residency analysis examines the presence of clones across samples. Integrative analyses combine scRNA-seq and scTCR-seq data, providing a comprehensive understanding of the cellular landscape. Immunopipe incorporates diverse cell group information to analyze T-cell populations, which enables granular perspectives of the data for comprehensive insights. Immunopipe offers a flexible platform, allowing users to customize the analyses as needed. It supports both core and optional analyses through configuration, where users have control over the adjustable parameters. The pipeline relies on cell grouping information that can be referenced from metadata or modified to generate new variables for analysis and data filtering. Immunopipe can be executed locally or on scheduler platforms, and a docker image is provided for compatibility and simplified installation. It also offers a web interface that facilitates configuration, execution monitoring, and access to results. Conclusion: Immunopipe is a flexible and user-friendly pipeline for analyzing scRNA-seq and scTCR-seq data. It empowers researchers to gain valuable insights that could enhance the understanding of immune responses and facilitate the development of innovative immunotherapies. Citation Format: Panwen Wang, Haidong Dong, Yue Yu, Shuwen Zhang, Zhifu Sun, Jean-Pierre A. Kocher, Junwen Wang, Lin Yi, Ying Li. Immunopipe: A comprehensive and flexible scRNA-seq and scTCR-seq data analysis pipeline [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4959.

Abstract ZC3H18 is a multifunctional regulator of gene expression that is lost in a subset of high-grade serous ovarian cancers (HGSOC). Our prior studies have established that the loss of ZC3H18 diminishes BRCA1 levels, leading to the disruption of homologous recombination DNA repair (HR) and heightened sensitivity of HGSOC cells to PARP inhibitors. Here we show an additional facet to ZC3H18's impact, showing that its loss also induces a reprogramming of energy metabolism in HGSOC. Our findings demonstrate that the depletion of ZC3H18 results in reduced mRNA and protein levels of the NAD+-biosynthetic enzyme, NMNAT1, in HGSOC cells. Mechanistic studies uncovered that ZC3H18 occupies the NMNAT1 promoter, facilitating NMNAT1 transcription by recruiting CDK12 onto the promoter. Consistent with this mechanism, loss of ZC3H18 led to a reduction in CDK12 levels on the NMNAT1 promoter, diminishing NMNAT1 abundance and subsequently causing a decline in cellular NAD levels. These observations unveil a previously unknown role for ZC3H18 in HGSOC, shedding light on its involvement in the regulation of energy metabolism. Importantly, our findings provide valuable insights into potential therapeutic pathways that leverage the metabolic changes linked to ZC3H18 deficiency. Citation Format: Benjamin Wilson, Natalie Wilson, Xianfeng Chen, Shuwen Zhang, Chen Wang, Larry M. Karnitz, Scott H. Kaufmann, Arun Kanakkanthara. ZC3H18: A novel regulator of NAD+ metabolism in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4447.