Establishing a human bone marrow single cell reference atlas to study ageing and diseases

T-cell senescence: Unlocking the tumor immune "Dark Box" - A multidimensional analysis from mechanism to tumor immunotherapeutic intervention

Immunosenescence is the dysfunction of the immune system that occurs with age, a process that is complex and characterized by several features, of which T-cell senescence is one of the key manifestations. In the tumor microenvironment, senescent T cells lead to the inability of tumor cells to be effectively eliminated, triggering immunosuppression, which in turn affects the efficacy of immunotherapy. This is a strong indication that T-cell senescence significantly weakens the immune function of the body, making individuals, especially elderly patients with cancer, more vulnerable to cancer attacks. Despite the many challenges, T-cell senescence is important as a potential therapeutic target. This review provides insights into the molecular mechanisms of T-cell senescence and its research advances in patients with cancer, especially in older adults, and systematically analyzes potential intervention strategies, including molecular mechanism-based interventions, the use of immune checkpoint inhibitors, and CAR-T cell therapy. It is hoped that this will establish a theoretical framework for T-cell senescence in the field of tumor immunology and provide a scientific and prospective reference basis for subsequent in-depth research and clinical practice on senescent T cells.

Causal Associations of Inflammatory Cytokines With Osteosarcopenia: Insights From Mendelian Randomization and Single Cell Analysis

Background: Osteosarcopenia, the coexistence of osteoporosis and sarcopenia, poses significant challenges in aging populations due to its dual impact on bone and muscle health. Inflammation, mediated by specific cytokines, is thought to play a crucial role in the development of osteosarcopenia, though the underlying mechanisms are not fully understood. Objective: This study aimed to clarify the causal role of circulating cytokines in the pathogenesis of osteosarcopenia by employing mendelian randomization (MR) and single-cell RNA sequencing (scRNA-seq) to identify cell-specific cytokine expression patterns. The ultimate objective was to uncover potential pathological mechanisms and therapeutic targets for treating osteosarcopenia. Methods: A two-sample MR approach was employed, leveraging publicly available genome-wide association study (GWAS) data from multiple cohorts. A total of 91 circulating cytokines were examined using genetic instruments, and their causal effects on traits related to osteoporosis and sarcopenia were evaluated. Various complementary and sensitivity analyses were performed to ensure robust findings. Additionally, scRNA-seq datasets from human muscle and bone marrow were analyzed to validate the single-cell expression profiles of candidate cytokines. Results: MR analysis identified several cytokines with causal effects on osteosarcopenia traits, including LTA, CD40, CXCL6, CXCL10, DNER (delta and notch-like epidermal growth factor-related receptor), and VEGFA (vascular endothelial growth factor A). LTA and CD40 were protective for both bone and muscle, while VEGFA posed a risk. Other cytokines demonstrated opposite effects on bone and muscle. Single cell analysis revealed distinct expression patterns, with LTA highly expressed in lymphocytes, CD40 in immune cells, and VEGFA in various musculoskeletal cell types. Age-related differences in cytokine expression were also noted, with LTA more highly expressed in younger individuals, and VEGFA in older individuals. Conclusion: This study offers preliminary insights into the inflammatory mechanisms potentially driving osteosarcopenia, identifying key cytokines that may be involved in its pathogenesis. By integrating MR and scRNA-seq data, we highlight potential therapeutic targets, though further research is needed to confirm these findings and their implications for musculoskeletal health.

TimeFlow: A Density-Driven Pseudotime Method for Flow Cytometry Data Analysis

Pseudotime methods order cells undergoing differentiation from the least to the most differentiated. We developed TimeFlow, a new method for computing pseudotime in multi-dimensional flow cytometry datasets. TimeFlow tracks the differentiation path of each cell on a graph by following smooth changes in the cell population density. To compute the probability density function of the cells, it uses a normalizing flow model. We profiled bone marrow samples from three healthy patients using a 20-color antibody panel for flow cytometry and prepared datasets that ranged from 5,000 to 600,000 cells and included monocytes, neutrophils, erythrocytes, and B-cells at various maturation stages. TimeFlow computed fine-grained pseudotime for all the datasets, and the cell orderings were consistent with prior knowledge of human hematopoiesis. Experiments showed its potential in generalizing across patients and unseen cell states. We compared our method to 11 other pseudotime methods using in-house and public datasets and found very good performance for both linear and branching trajectories. TimeFlow's pseudotemporal orderings are useful for modeling the dynamics of cell surface proteins along linear trajectories. The biologically meaningful results in branching trajectories suggest the possibility of future applications with automated cell lineage detection. Code is available at https://github.com/MargaritaLiarou1/TimeFlow and data at https://osf.io/ykue7/.

Targeting senescent stemlike subpopulations in Philadelphia chromosome-like acute lymphoblastic leukemia

ABSTRACT

Philadelphia chromosome-like B-cell acute lymphoblastic leukemia (Ph-like ALL) is driven by genetic alterations that induce constitutive kinase signaling and is associated with chemoresistance and high relapse risk in children and adults. Preclinical studies in the most common CRLF2-rearranged/JAK pathway-activated Ph-like ALL subtype have revealed variable responses to JAK inhibitor-based therapies, suggesting incomplete oncogene addiction and highlighting a need to elucidate alternative biologic dependencies and therapeutic vulnerabilities, whereas the ABL-class Ph-like ALL subtype seems preferentially sensitive to SRC/ABL- or PDGFRB-targeting inhibitors. Which patients may be responsive vs resistant to tyrosine kinase inhibitor (TKI)-based precision medicine approaches remains a critical knowledge gap. Using bulk and single-cell multiomics analyses, we profiled residual cells from CRLF2-rearranged or ABL1-rearranged Ph-like ALL patient-derived xenograft models treated in vivo with targeted inhibitors to identify TKI-resistant subpopulations and potential mechanisms of therapeutic escape. We detected a specific MYC dependency in Ph-like ALL cells and defined a new leukemia cell subpopulation with senescence-associated stem cell-like features regulated by AP-1 transcription factors. This dormant ALL subpopulation was effectively eradicated by dual pharmacologic inhibition of BCL-2 and JAK/STAT or SRC/ABL pathways, a clinically relevant therapeutic strategy. Single cell-derived molecular signatures of this senescence and stem/progenitor-like subpopulation further predicted poor clinical outcomes associated with other high-risk genetic subtypes of childhood B-ALL and thus may have broader prognostic applicability beyond Ph-like ALL.

Mapping the spatial atlas of the human bone tissue integrating spatial and single-cell transcriptomics

Bone is a multifaceted tissue requiring orchestrated interplays of diverse cells within specialized microenvironments. Although significant progress has been made in understanding cellular and molecular mechanisms of component cells of bone, revealing their spatial organization and interactions in native bone tissue microenvironment is crucial for advancing precision medicine, as they govern fundamental signaling pathways and functional dependencies among various bone cells. In this study, we present the first integrative high-resolution map of human bone and bone marrow, using spatial and single-cell transcriptomics profiling from femoral tissue. This multi-modal approach discovered a novel bone formation-specialized niche enriched with osteoblastic lineage cells and fibroblasts and unveiled critical cell-cell communications and co-localization patterns between osteoblastic lineage cells and other cells. Furthermore, we discovered a novel spatial gradient of cellular composition, gene expression and signaling pathway activities radiating from the trabecular bone. This comprehensive atlas delineates the intricate bone cellular architecture and illuminates key molecular processes and dependencies among cells that coordinate bone metabolism. In sum, our study provides an essential reference for the field of bone biology and lays the foundation for advanced mechanistic studies and precision medicine approaches in bone-related disorders.

Similar, but not the same: multiomics comparison of human valve interstitial cells and osteoblast osteogenic differentiation expanded with an estimation of data-dependent and data-independent PASEF proteomics

Osteogenic differentiation is crucial in normal bone formation and pathological calcification, such as calcific aortic valve disease (CAVD). Understanding the proteomic and transcriptomic landscapes underlying this differentiation can unveil potential therapeutic targets for CAVD. In this study, we employed RNA sequencing transcriptomics and proteomics on a timsTOF Pro platform to explore the multiomics profiles of valve interstitial cells (VICs) and osteoblasts during osteogenic differentiation. For proteomics, we utilized 3 data acquisition/analysis techniques: data-dependent acquisition (DDA)-parallel accumulation serial fragmentation (PASEF) and data-independent acquisition (DIA)-PASEF with a classic library-based (DIA) and machine learning-based library-free search (DIA-ML). Using RNA sequencing data as a biological reference, we compared these 3 analytical techniques in the context of actual biological experiments. We use this comprehensive dataset to reveal distinct proteomic and transcriptomic profiles between VICs and osteoblasts, highlighting specific biological processes in their osteogenic differentiation pathways. The study identified potential therapeutic targets specific for VICs osteogenic differentiation in CAVD, including the MAOA and ERK1/2 pathway. From a technical perspective, we found that DIA-based methods demonstrate even higher superiority against DDA for more sophisticated human primary cell cultures than it was shown before on HeLa samples. While the classic library-based DIA approach has proved to be a gold standard for shotgun proteomics research, the DIA-ML offers significant advantages with a relatively minor compromise in data reliability, making it the method of choice for routine proteomics.

Rediscovering publicly available single-cell data with the DISCO platform

Single-cell RNA sequencing (scRNA-seq) has emerged as the key technique for studying transcriptomics at the single-cell level. In our previous work, we presented the DISCO database (https://www.immunesinglecell.org/) that integrates publicly available human scRNA-seq data. We now introduce an enhanced version of DISCO, which has expanded fourfold to include >100 million cells from >17 thousand samples. It provides uniformly realigned read count tables, curated metadata, integrated tissue and phenotype specific atlases, and harmonized cell type annotations. It also hosts a single-cell enhanced knowledgebase of cell type ontology and gene signatures relating to cell types and phenotypes. Lastly, it offers a suite of tools for data retrieval, integration, annotation, and mapping, allowing users to construct customized atlases and perform integrated analysis with their own data. These tools are also available in a standalone R package for offline analysis.

A global view of altered ligand-receptor interactions in bone marrow aging based on single-cell sequencing

Altered cell-cell communication is a hallmark of aging, but its impact on bone marrow aging remains poorly understood. Based on a common and effective pipeline and single-cell transcriptome sequencing, we detected 384,124 interactions including 2575 ligand-receptor pairs and 16 non-adherent bone marrow cell types in old and young mouse and identified a total of 5560 significantly different interactions, which were then verified by flow cytometry and quantitative real-time PCR. These differential ligand-receptor interactions exhibited enrichment for the senescence-associated secretory phenotypes. Further validation demonstrated supplementing specific extracellular ligands could modify the senescent signs of hematopoietic stem cells derived from old mouse. Our work provides an effective procedure to detect the ligand-receptor interactions based on single-cell sequencing, which contributes to understand mechanisms and provides a potential strategy for intervention of bone marrow aging.

Clonal hematopoiesis and its impact on the aging osteo-hematopoietic niche

Clonal hematopoiesis (CH) defines a premalignant state predominantly found in older persons that increases the risk of developing hematologic malignancies and age-related inflammatory diseases. However, the risk for malignant transformation or non-malignant disorders is variable and difficult to predict, and defining the clinical relevance of specific candidate driver mutations in individual carriers has proved to be challenging. In addition to the cell-intrinsic mechanisms, mutant cells rely on and alter cell-extrinsic factors from the bone marrow (BM) niche, which complicates the prediction of a mutant cell's fate in a shifting pre-malignant microenvironment. Therefore, identifying the insidious and potentially broad impact of driver mutations on supportive niches and immune function in CH aims to understand the subtle differences that enable driver mutations to yield different clinical outcomes. Here, we review the changes in the aging BM niche and the emerging evidence supporting the concept that CH can progressively alter components of the local BM microenvironment. These alterations may have profound implications for the functionality of the osteo-hematopoietic niche and overall bone health, consequently fostering a conducive environment for the continued development and progression of CH. We also provide an overview of the latest technology developments to study the spatiotemporal dependencies in the CH BM niche, ideally in the context of longitudinal studies following CH over time. Finally, we discuss aspects of CH carrier management in clinical practice, based on work from our group and others.

Human skeletal muscle aging atlas

Skeletal muscle aging is a key contributor to age-related frailty and sarcopenia with substantial implications for global health. Here we profiled 90,902 single cells and 92,259 single nuclei from 17 donors to map the aging process in the adult human intercostal muscle, identifying cellular changes in each muscle compartment. We found that distinct subsets of muscle stem cells exhibit decreased ribosome biogenesis genes and increased CCL2 expression, causing different aging phenotypes. Our atlas also highlights an expansion of nuclei associated with the neuromuscular junction, which may reflect re-innervation, and outlines how the loss of fast-twitch myofibers is mitigated through regeneration and upregulation of fast-type markers in slow-twitch myofibers with age. Furthermore, we document the function of aging muscle microenvironment in immune cell attraction. Overall, we present a comprehensive human skeletal muscle aging resource ( https://www.muscleageingcellatlas.org/ ) together with an in-house mouse muscle atlas to study common features of muscle aging across species.

Multimodal profiling reveals tissue-directed signatures of human immune cells altered with age

The immune system comprises multiple cell lineages and heterogeneous subsets found in blood and tissues throughout the body. While human immune responses differ between sites and over age, the underlying sources of variation remain unclear as most studies are limited to peripheral blood. Here, we took a systems approach to comprehensively profile RNA and surface protein expression of over 1.25 million immune cells isolated from blood, lymphoid organs, and mucosal tissues of 24 organ donors aged 20-75 years. We applied a multimodal classifier to annotate the major immune cell lineages (T cells, B cells, innate lymphoid cells, and myeloid cells) and their corresponding subsets across the body, leveraging probabilistic modeling to define bases for immune variations across donors, tissue, and age. We identified dominant tissue-specific effects on immune cell composition and function across lineages for lymphoid sites, intestines, and blood-rich tissues. Age-associated effects were intrinsic to both lineage and site as manifested by macrophages in mucosal sites, B cells in lymphoid organs, and T and NK cells in blood-rich sites. Our results reveal tissue-specific signatures of immune homeostasis throughout the body and across different ages. This information provides a basis for defining the transcriptional underpinnings of immune variation and potential associations with disease-associated immune pathologies across the human lifespan.