Single-cell Sequencing Techniques Research Articles

Migratory Tumor Cells Cooperate with Cancer Associated Fibroblasts in Hormone Receptor-Positive and HER2-Negative Breast Cancer

Hormone receptor-positive and HER2-negative breast cancer (HR+/HER2-BC) is the most common type with a favorable prognosis under endocrine therapy. However, it still demonstrates unpredictable progression and recurrences influenced by high tumoral diversity and microenvironmental status. To address these heterogeneous molecular characteristics of HR+/HER2-BC, we aimed to simultaneously characterize its transcriptomic landscape and genetic architecture at the same resolution. Using advanced single-cell RNA and DNA sequencing techniques together, we defined four distinct tumor subtypes. Notably, the migratory tumor subtype was closely linked to genomic alterations of EGFR, related to the tumor-promoting behavior of IL6-positive inflammatory tumor-associated fibroblast, and contributing to poor prognosis. Our study comprehensively utilizes integrated analysis to uncover the complex dynamics of this breast cancer subtype, highlighting the pivotal role of the migratory tumor subtype in influencing surrounding cells. This sheds light on potential therapeutic targets by offering enhanced insights for HR+/HER2-BC treatment.

A review of single-cell transcriptomics and epigenomics studies in maternal and child health.

Single-cell sequencing technologies enhance our understanding of cellular dynamics throughout pregnancy. We outlined the workflow of single-cell sequencing techniques and reviewed single-cell studies in maternal and child health. We conducted a literature review of single cell studies on maternal and child health using PubMed. We summarized the findings from 16 single-cell atlases of the human and mammalian placenta across gestational stages and 31 single-cell studies on maternal exposures and complications including infection, obesity, diet, gestational diabetes, pre-eclampsia, environmental exposure and preterm birth. Single-cell studies provides insights on novel cell types in placenta and cell type-specific marks associated with maternal exposures and complications.

Single-cell transcriptomics: background, technologies, applications, and challenges.

Single-cell sequencing was developed as a high-throughput tool to elucidate unusual and transient cell states that are barely visible in the bulk. This technology reveals the evolutionary status of cells and differences between populations, helps to identify unique cell subtypes and states, reveals regulatory relationships between genes, targets and molecular mechanisms in disease processes, tumor heterogeneity, the state of the immune environment, etc. However, the high cost and technical limitations of single-cell sequencing initially prevented its widespread application, but with advances in research, numerous new single-cell sequencing techniques have been discovered, lowering the cost barrier. Many single-cell sequencing platforms and bioinformatics methods have recently become commercially available, allowing researchers to make fascinating observations. They are now increasingly being used in various industries. Several protocols have been discovered in this context and each technique has unique characteristics, capabilities and challenges. This review presents the latest advancements in single-cell transcriptomics technologies. This includes single-cell transcriptomics approaches, workflows and statistical approaches to data processing, as well as the potential advances, applications, opportunities and challenges of single-cell transcriptomics technology. You will also get an overview of the entry points for spatial transcriptomics and multi-omics.

CNS Resident Innate Immune Cells: Guardians of CNS Homeostasis.

Although the CNS has been considered for a long time an immune-privileged organ, it is now well known that both the parenchyma and non-parenchymal tissue (meninges, perivascular space, and choroid plexus) are richly populated in resident immune cells. The advent of more powerful tools for multiplex immunophenotyping, such as single-cell RNA sequencing technique and upscale multiparametric flow and mass spectrometry, helped in discriminating between resident and infiltrating cells and, above all, the different spectrum of phenotypes distinguishing border-associated macrophages. Here, we focus our attention on resident innate immune players and their primary role in both CNS homeostasis and pathological neuroinflammation and neurodegeneration, two key interconnected aspects of the immunopathology of multiple sclerosis.

Single-Cell Transcriptome Sequencing Reveals Molecular Expression Differences and Marker Genes in Testes during the Sexual Maturation of Mongolian Horses.

This study aimed to investigate differences in testicular tissue morphology, gene expression, and marker genes between sexually immature (1-year-old) and sexually mature (10-year-old) Mongolian horses. The purposes of our research were to provide insights into the reproductive physiology of male Mongolian horses and to identify potential markers for sexual maturity. The methods we applied included the transcriptomic profiling of testicular cells using single-cell sequencing techniques. Our results revealed significant differences in tissue morphology and gene expression patterns between the two age groups. Specifically, 25 cell clusters and 10 cell types were identified, including spermatogonial and somatic cells. Differential gene expression analysis highlighted distinct patterns related to cellular infrastructure in sexually immature horses and spermatogenesis in sexually mature horses. Marker genes specific to each stage were also identified, including APOA1, AMH, TAC3, INHA, SPARC, and SOX9 for the sexually immature stage, and PRM1, PRM2, LOC100051500, PRSS37, HMGB4, and H1-9 for the sexually mature stage. These findings contribute to a deeper understanding of testicular development and spermatogenesis in Mongolian horses and have potential applications in equine reproductive biology and breeding programs. In conclusion, this study provides valuable insights into the molecular mechanisms underlying sexual maturity in Mongolian horses.

Recent contributions of single-cell and spatial profiling to the understanding of bladder cancer.

Current risk stratification and treatment decision-making for bladder cancer informed by histopathology as well as molecular diagnostics face limitations. This review summarizes recent advancements in single-cell and spatial omics methodologies for understanding bladder cancer biology and their potential impact on development of novel therapeutic strategies. Single-cell RNA sequencing and spatial omics techniques offer unprecedented insights into various aspects of tumor microenvironment (TME), bladder cancer heterogeneity, cancer stemness, and cellular plasticity. Studies have identified multiple malignant cell subpopulations within tumors, revealing diverse transcriptional states and clonal evolution. Additionally, intratumor heterogeneity has been linked to tumor progression and therapeutic response. Immune cell composition analysis has revealed immunosuppressive features in the TME, impacting treatment response. Furthermore, studies have elucidated the role of cancer-associated fibroblasts and endothelial cells in shaping the tumor immune landscape and response to therapy. Single-cell and spatial omics technologies have revolutionized our understanding of bladder cancer biology, uncovering previously unseen complexities. These methodologies provide valuable insights into tumor heterogeneity and microenvironmental interactions, with implications for therapeutic development. However, challenges remain in translating research findings into clinical practice and implementing personalized treatment strategies. Continued interdisciplinary collaboration and innovation are essential for overcoming these challenges and leveraging the full potential of single-cell and spatial omics in improving bladder cancer diagnosis and treatment.

SEQUENCING OF SINGLE CELLS: APPLICATION AND PERSPECTIVES

Introduction. Sequencing of single cells makes it possible to characterize the cellular and molecular composition of tissues, the state of DNA, RNA and expressed proteins. The «single-cell» sequencing method is gaining increasing popularity in modern biology and medicine. The purpose of the study. Analysis and characterization of single-cell sequencing techniques and their applied significance. Material and methods. The literature search was conducted in the open electronic databases of scientific literature PubMed, Elibrary, bioRxiv and Scopus. The search depth was 27 years. 46 articles were selected for analysis. Results. Single-cell RNA sequencing – scRNA–seq – transcriptomics of individual cells with gene expression profiling. It allows clustering cells by state or type; registering rare genes that are discarded when sequencing a common transcriptome; detect point mutations. Spatial transcriptomics – smFISH and MERFISH – methods for mapping gene expression at the genome level in stationary tissue samples developed in addition to RNA sequencing technologies. With these methods, an image is obtained using fluorescent labels. Spatial sequencing – Slide-seq – allows us to characterize the entire transcriptome of a certain area of the isolated tissue on a slide with a resolution close to one cell. Further research of this analysis is required to reduce its cost and adapt it for more convenient use. Conclusions. The use of single-cell sequencing methods, as well as the study of the epigenome and transcriptome, will help to differentiate cells into various subpopulations, as well as to find new predictive and prognostic targets for therapy.

Integration of single-cell transcriptome and chromatin accessibility and its application on tumor investigation

Abstract The advent of single-cell sequencing techniques has not only revolutionized the investigation of biological processes but also significantly contributed to unraveling cellular heterogeneity at unprecedented levels. Among the various methods, single-cell transcriptome sequencing stands out as the best established, and has been employed in exploring many physiological and pathological activities. The recently developed single-cell epigenetic sequencing techniques, especially chromatin accessibility sequencing, have further deepened our understanding of gene regulatory networks. In this review, we summarize the recent breakthroughs in single-cell transcriptome and chromatin accessibility sequencing methodologies. Additionally, we describe current bioinformatic strategies to integrate data obtained through these single-cell sequencing methods and highlight the application of this analysis strategy on a deeper understanding of tumorigenesis and tumor progression. Finally, we also discuss the challenges and anticipated developments in this field.

Circulating immune cell landscape and T-cell abnormalities in patients with moyamoya disease.

Moyamoya disease (MMD) stands as a prominent cause of stroke among children and adolescents in East Asian populations. Although a growing body of evidence suggests that dysregulated inflammation and autoimmune responses might contribute to the development of MMD, a comprehensive and detailed understanding of the alterations in circulating immune cells associated with MMD remains elusive. In this study, we employed a combination of single-cell RNA sequencing (scRNA-seq), mass cytometry and RNA-sequencing techniques to compare immune cell profiles in peripheral blood samples obtained from patients with MMD and age-matched healthy controls. Our investigation unveiled immune dysfunction in MMD patients, primarily characterized by perturbations in T-cell (TC) subpopulations, including a reduction in effector TCs and an increase in regulatory TCs (Tregs). Additionally, we observed diminished natural killer cells and dendritic cells alongside heightened B cells and monocytes in MMD patients. Notably, within the MMD group, there was an augmented proportion of fragile Tregs, whereas the stable Treg fraction decreased. MMD was also linked to heightened immune activation, as evidenced by elevated expression levels of HLA-DR and p-STAT3. Our findings offer a comprehensive view of the circulating immune cell landscape in MMD patients. Immune dysregulation in patients with MMD was characterized by alterations in T-cell populations, including a decrease in effector T-cells and an increase in regulatory T-cells (Tregs), suggest a potential role for disrupted circulating immunity in the aetiology of MMD.

Clustering single-cell multi-omics data via graph regularized multi-view ensemble learning.

Single-cell clustering plays a crucial role in distinguishing between cell types, facilitating the analysis of cell heterogeneity mechanisms. While many existing clustering methods rely solely on gene expression data obtained from single-cell RNA sequencing techniques to identify cell clusters, the information contained in mono-omic data is often limited, leading to suboptimal clustering performance. The emergence of single-cell multi-omics sequencing technologies enables the integration of multiple omics data for identifying cell clusters, but how to integrate different omics data effectively remains challenging. In addition, designing a clustering method that performs well across various types of multi-omics data poses a persistent challenge due to the data's inherent characteristics. In this paper, we propose a graph-regularized multi-view ensemble clustering (GRMEC-SC) model for single-cell clustering. Our proposed approach can adaptively integrate multiple omics data and leverage insights from multiple base clustering results. We extensively evaluate our method on five multi-omics datasets through a series of rigorous experiments. The results of these experiments demonstrate that our GRMEC-SC model achieves competitive performance across diverse multi-omics datasets with varying characteristics. Implementation of GRMEC-SC, along with examples, can be found on the GitHub repository: https://github.com/polarisChen/GRMEC-SC.

Abstract 1773: Deciphering the roles of germline predisposition variants and somatic mutations on breast cancer cells and the tumor microenvironment

Abstract While great progress has been made in the understanding and treatment of cancer, tumor heterogeneity remains a diagnostic and prognostic challenge. Single-cell sequencing techniques and high-resolution cellular imaging now afford researchers the ability to investigate the effects of germline variants (especially when compared to somatic mutations) on molecular characteristics of cancer cells and non-cancer cells in the tumor microenvironment (TME). Here, we investigated a breast cancer (BRCA) cohort of over 100 individuals, for which we have generated sc/sn RNA-seq, snATAC-seq, and CODEX imaging data as well as bulk whole exome sequencing and RNA-seq data. We identified 21 BRCA cases carrying pathogenic and likely pathogenic rare germline variants in known cancer predisposition genes, such as BRCA2, BRIP1, ATM, and TP53. These predisposition genes showed diverse expression patterns across stromal and immune cell types, indicating roles in cell types beyond breast epithelia. For cases carrying pathogenic germline variants in such genes, we use snRNA-seq/snATAC-seq to assess gene expression changes and pathway alterations (e.g.,HRD and apoptosis) across all cell types and investigate phenotypic changes associated with pathogenic germline variants in cancer cells compared to stroma and immune cells in the TME. By evaluating chromatin accessibility changes and allele-specific expression, we reveal the connection between epigenetic regulators and differential roles of germline variants across cell types. Finally, the integrated analysis of germline variants and somatic mutations from predisposition genes at single cell resolution broadened our understanding of the role of germline variants in TME during tumorigenesis. Citation Format: Fernanda Martins Rodrigues, Kelsey Gallant, Reyka Jayasinghe, Michael Iglesia, Andrew Houston, Siqi Chen, Preet Lal, Ryan Fields, William Gillanders, Feng Chen, Li Ding. Deciphering the roles of germline predisposition variants and somatic mutations on breast cancer cells and the tumor microenvironment [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 1773.

Antigen/HLA-agnostic strategies for Characterizing Tumor-responsive T cell receptors in PDAC patients via single-cell sequencing and autologous organoid application

Characterization of tumor-responsive T cell receptors (TCRs) is a critical step in personalized TCR-T cell therapy, and remains challenging for pancreatic ductal adenocarcinoma (PDAC). Here we report a proof-of-concept study to identify and validate antitumor TCRs in two representative PDAC patients using ultradeep single-cell TCR/RNA sequencing and autologous organoids, and reveal the phenotypic dynamics of TCR repertoire in different T cell expansions from the same patient. We first performed comparative sequencing on freshly harvested peripheral blood mononuclear cells (PBMCs) and uncultured tumor infiltrating lymphocytes (TILs), followed by reactivity tests of TIL-enriched TCRs with autologous organoids, in which two tumor-responsive TCRs were successfully characterized and the corresponding TILs were mostly tissue-resident memory-like T cells, and partially expressed both naïve and exhausted T cell markers. For the PDAC patient without high-quality TILs, PBMCs were cultured with neoantigen peptide (KRASG12D), organoids, or anti-CD3 antibody in presence, and experienced extensive clonal expansions within ten days. All derived PBMCs were sequenced in parallel (>82,000 cells), and TCRs enriched in both peptide- and organoid-experienced, but not anti-CD3-treated CD8 T cells, were assessed for their reactivity to antigen-presenting cells (APCs) and organoids, in which three neoantigen-reactive TCRs were identified as tumor-responsive, and the corresponding T cells were characterized by mixed transcriptional signatures including but not limited to typical exhausted T cell markers. Together, our study revealed that the combination of ultradeep single-cell sequencing and organoid techniques enabled rapid characterization of tumor-responsive TCRs for developing practical personalized TCR-T therapy in an antigen/human leukocyte antigen (HLA)-agnostic manner.

Harnessing the Transcriptional Signatures of CAR-T-Cells and Leukemia/Lymphoma Using Single-Cell Sequencing Technologies.

Chimeric antigen receptor (CAR)-T-cell therapy has greatly improved outcomes for patients with relapsed or refractory hematological malignancies. However, challenges such as treatment resistance, relapse, and severe toxicity still hinder its widespread clinical application. Traditional transcriptome analysis has provided limited insights into the complex transcriptional landscape of both leukemia cells and engineered CAR-T-cells, as well as their interactions within the tumor microenvironment. However, with the advent of single-cell sequencing techniques, a paradigm shift has occurred, providing robust tools to unravel the complexities of these factors. These techniques enable an unbiased analysis of cellular heterogeneity and molecular patterns. These insights are invaluable for precise receptor design, guiding gene-based T-cell modification, and optimizing manufacturing conditions. Consequently, this review utilizes modern single-cell sequencing techniques to clarify the transcriptional intricacies of leukemia cells and CAR-Ts. The aim of this manuscript is to discuss the potential mechanisms that contribute to the clinical failures of CAR-T immunotherapy. We examine the biological characteristics of CAR-Ts, the mechanisms that govern clinical responses, and the intricacies of adverse events. By exploring these aspects, we hope to gain a deeper understanding of CAR-T therapy, which will ultimately lead to improved clinical outcomes and broader therapeutic applications.

Abstract IA023: Spatial reconstruction and temporal inference of DNA methylation alterations in primary human colorectal cancer

Abstract Phenotypic plasticity is thought to assist immune evasion, metastasis, and therapeutic resistance in tumor evolution. Epigenetic mechanisms such as DNA methylation provide for a more easily acquired and flexible, yet semi-stable adaptation by the tumor cell than hardwired genetic changes. Cancer-associated gain of DNA methylation at promoter CpG islands or distal regulatory elements is associated with transcriptional silencing, whereas loss of DNA methylation is observed at late-replicating, lamina-attached regions of the genome, tracking with cumulative cell divisions. One of the most well-documented genomic features predisposing to DNA hypermethylation is Polycomb Repressive Complex (PRC) occupancy in precursor cells, consistent with an epigenetic block to cellular differentiation as an early or predisposing event in carcinogenesis. A central question is whether this epigenetic switch from reversible PRC repression to more stable DNA hypermethylation occurs before onset of clonal expansion, or whether it represents an ongoing process during tumor evolution. Clonal expansion is a pivotal characteristic of cancer, and is thought to be initiated by a genetic alteration in a key gatekeeper driver gene. However, not all normal cells appear to be susceptible to malignant transformation following such an event. Multiple lines of evidence suggest that epigenetic heterogeneity among normal cells may affect their cancer-initiating potential. We have developed a tumor processing pipeline to deeply and comprehensively map DNA methylation patterns in primary human colorectal cancer (CRC) and adjacent tissues, while preserving spatial information, enabling inference of the temporal order of molecular alterations. We employ a suite of technologies to map the spatial heterogeneity of DNA methylation patterns in primary human CRC. These include a deep single-cell whole-genome bisulfite sequencing technique that improves genomic coverage several-fold over existing published protocols, providing DNA methylation measurements at the majority of CpGs in the genome in individual tumor cells. We have also calibrated and validated an epigenetic clock that allows us to accurately measure the relative replicative history of individual cells. We infer phylogenetic relationships among subclones, and relate these to their spatial distribution in the primary tumor. We find that some tumors have high proportions of PRC-associated clonal hypermethylation, indicating that these hypermethylation events were already present prior to clonal expansion, possibly contributing to susceptibility to malignant transformation in the cell-of-origin, whereas other tumors appear to have active PRC-associated CpG island hypermethylation ongoing during tumor expansion, generating subclonal heterogeneity, which may influence post-therapeutic recurrence potential. Citation Format: Peter W. Laird, Nathan J. Spix, Hsiao-yun Milliron, Manpreet Kalkat, Emily Eugster, David Sokol, Emily Jung, Paula Nolte, Kelly K. Krzyzanowski, Toshinori Hinoue, Hui Shen. Spatial reconstruction and temporal inference of DNA methylation alterations in primary human colorectal cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA023.

Identification and validation of Golgi apparatus-related signature for predicting prognosis and immunotherapy response in breast cancer

BackgroundThe Golgi apparatus plays a pivotal role in various aspects of cancer. This study aims to investigate the predictive value of Golgi apparatus-related genes (GARGs) in breast cancer prognosis and immunotherapy response evaluation.MethodsTranscriptional and clinical data from the TCGA-BRCA cohort and GSE96058 cohort were utilized to construct and validate a prognostic model for breast cancer using Cox regression analysis. Differences in immune landscape, somatic mutations, gene expression, drug sensitivity, and immunotherapy response between different risk groups were assessed. A prognostic nomogram for breast cancer was further developed and evaluated. qPCR and single-cell sequencing analyses were performed to validate the expression of GARGs.ResultsA total of 394 GARGs significantly associated with breast cancer prognosis were identified, leading to the construction of a prognostic risk feature comprising 10 GARGs. This feature effectively stratified breast cancer patients into high-risk and low-risk groups, with the high-risk group exhibiting significantly worse prognosis. Meanwhile, significant differences in clinicopathological features, immune infiltration, drug sensitivity, and immunotherapy response were observed between the high- and low-risk groups. The constructed nomogram incorporating these factors showed superior performance in prognostic assessment for breast cancer patients. Ultimately, the utilization of qPCR and single-cell sequencing techniques substantiated the disparate expression patterns of these prognostic genes in breast cancer.ConclusionOur findings demonstrate that a prognostic risk feature derived from GARGs holds promising application potential for predicting prognosis and evaluating immunotherapy response in breast cancer patients.

Innovations in Molecular Biology-Cutting-Edge Breakthroughs in Molecular Genetics

The field of molecular biology has experienced significant breakthroughs in recent years, driven by cutting-edge technologies and innovative research strategies. This abstract provides a concise overview of some key advancement that has shaped the landscape of molecular biology. One prominent area of progress involves the CRISPR-Cas9 gene editing system, which has revolutionized genetic manipulation. Researchers have refined and expanded its applications, enabling precise modifications to the genome for therapeutic purposes, functional genomics, and the development of genetically modified organisms. In the realm of nucleic acid sequencing, the advent of third-generation sequencing technologies has enhanced the accuracy and efficiency of deciphering complex genomes. Single-cell sequencing techniques have provided unprecedented insights into cellular heterogeneity, unraveling diverse cell populations within tissues and shedding light on the intricacies of developmental processes and disease progression. The integration of omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics, has propelled systems biology to new heights. This holistic approach allows for a comprehensive understanding of biological systems, unveiling intricate molecular networks and signaling pathways. Advanced computational methods and artificial intelligence applications have played a pivotal role in processing and interpreting the vast amounts of data generated by these high-throughput techniques. Furthermore, the exploration of the microbiome's role in health and disease has gained momentum. Advances in metagenomics have enabled a deeper understanding of microbial communities, their interactions, and their impact on host physiology. The identification of specific microbial signatures associated with various diseases has opened avenues for novel therapeutic interventions and personalized medicine. Conclusion: Recent advances in molecular biology have transformed the field, offering unprecedented opportunities for scientific discovery and medical applications. The integration of cutting-edge technologies and interdisciplinary approaches continues to propel molecular biology forward, paving the way for new insights into the complexities of life at the molecular level

An aging-related immune landscape in the hematopoietic immune system.

Aging is a holistic change that has a major impact on the immune system, and immunosenescence contributes to the overall progression of aging. The bone marrow is the most important hematopoietic immune organ, while the spleen, as the most important extramedullary hematopoietic immune organ, maintains homeostasis of the human hematopoietic immune system (HIS) in cooperation with the bone marrow. However, the overall changes in the HIS during aging have not been described. Here, we describe a hematopoietic immune map of the spleen and bone marrow of young and old mice using single-cell sequencing and flow cytometry techniques. We observed extensive, complex changes in the HIS during aging. Compared with young mice, the immune cells of aged mice showed a marked tendency toward myeloid differentiation, with the neutrophil population accounting for a significant proportion of this response. In this change, hypoxia-inducible factor 1-alpha (Hif1α) was significantly overexpressed, and this enhanced the immune efficacy and inflammatory response of neutrophils. Our research revealed that during the aging process, hematopoietic stem cells undergo significant changes in function and composition, and their polymorphism and differentiation abilities are downregulated. Moreover, we found that the highly responsive CD62L + HSCs were obviously downregulated in aging, suggesting that they may play an important role in the aging process. Overall, aging extensively alters the cellular composition and function of the HIS. These findings could potentially give high-dimensional insights and enable more accurate functional and developmental analyses as well as immune monitoring in HIS aging.

Single-Nucleus ATAC-seq for Mapping Chromatin Accessibility in Individual Cells of Murine Hearts.

During the last decade a wide range of single-cell and single-nucleus next-generation sequencing techniques have been developed, which revolutionized detection of rare cell populations, enabling creation of comprehensive cell atlases of complex organs and tissues. State-of-the-art methods do not only allow classical transcriptomics of individual cells but also comprise a number of epigenetic approaches, including assessment of chromatin accessibility by single-nucleus Assay for Transposase Accessible Chromatin ATAC-seq (snATAC-seq). The snATAC-seq assay detects "open chromatin," a term for low nucleosome occupancy of genomic regions, which is a prerequisite for effective transcription factor binding. Information about open chromatin at the single-nucleus level helps to recognize epigenetic changes, sometimes before transcription of respective genes occurs. snATAC-seq detects cellular heterogeneity in otherwise still transcriptionally and/or morphologically homogeneous cell populations. Chromatin accessibility assays may be used to detect epigenetic changes in cardiac lineages during heart development, chromatin landscape changes during aging, and epigenetic alterations in heart diseases. Here, we provide an optimized protocol for snATAC-seq of murine hearts. We describe isolation of single nuclei from snap-frozen hearts, provide hints for preparation of libraries suitable for snATAC-seq next-generation sequencing (NGS) using the Chromium 10× platform, and give general recommendations for downstream analysis using conventional bioinformatic pipelines and packages. The protocol should serve as a beginner's guide to generate high-quality snATAC-seq datasets and to perform chromatin accessibility analysis of individual heart-derived cell nuclei.

Fibroblasts under pressure: cardiac fibroblast responses to hypertension and antihypertensive therapies.

Approximately 50% of Americans have hypertension, which significantly increases the risk of heart failure. In response to increased peripheral resistance in hypertension, intensified mechanical stretch in the myocardium induces cardiomyocyte hypertrophy and fibroblast activation to withstand increased pressure overload. This changes the structure and function of the heart, leading to pathological cardiac remodeling and eventual progression to heart failure. In the presence of hypertensive stimuli, cardiac fibroblasts activate and differentiate to myofibroblast phenotype capable of enhanced extracellular matrix secretion in coordination with other cell types, mainly cardiomyocytes. Both systemic and local renin-angiotensin-aldosterone system activation lead to increased angiotensin II stimulation of fibroblasts. Angiotensin II directly activates fibrotic signaling such as transforming growth factor β/SMAD and mitogen-activated protein kinase (MAPK) signaling to produce extracellular matrix comprised of collagens and matricellular proteins. With the advent of single-cell RNA sequencing techniques, heterogeneity in fibroblast populations has been identified in the left ventricle in models of hypertension and pressure overload. The various clusters of fibroblasts reveal a range of phenotypes and activation states. Select antihypertensive therapies have been shown to be effective in limiting fibrosis, with some having direct actions on cardiac fibroblasts. The present review focuses on the fibroblast-specific changes that occur in response to hypertension and pressure overload, the knowledge gained from single-cell analyses, and the effect of antihypertensive therapies. Understanding the dynamics of hypertensive fibroblast populations and their similarities and differences by sex is crucial for the advent of new targets and personalized medicine.

Unraveling the tumor immune microenvironment of lung adenocarcinoma using single-cell RNA sequencing.

Tumor immune microenvironment (TIME) and its indications for lung cancer patient prognosis and therapeutic response have become new hotspots in cancer research in recent years. Tumor cells, immune cells, various regulatory factors, and their interactions in the TIME have been suggested to commonly influence lung cancer development and therapeutic outcome. The heterogeneity of TIME is composed of dynamic immune-related components, including various cancer cells, immune cells, cytokine/chemokine environments, cytotoxic activity, or immunosuppressive factors. The specific composition of cell subtypes may facilitate or hamper the response to immunotherapy and influence patient prognosis. Various markers have been found to stratify the patient prognosis or predict the therapeutic outcome. In this article, we systematically reviewed the recent advancement of TIME studies in lung adenocarcinoma (LUAD) using single-cell RNA sequencing (scRNA-seq) techniques, with specific focuses on the roles of TIME in LUAD development, TIME heterogeneity, indications of TIME in patient prognosis and therapeutic response during immunotherapy and drug resistance. The main findings in TIME heterogeneity and relevant markers or models for prognosis stratification and response prediction have been summarized. We hope that this review provides an overview of TIME status in LUAD and an inspiration for future development of strategies and biomarkers in LUAD treatment.