Single-cell transcriptomic analysis in two patients with rare systemic autoinflammatory diseases treated with anti-TNF therapy

Hua, Yichao; Wu, Na; Miao, Junke; Shen, Min

doi:10.3389/fimmu.2023.1091336

Cited by 3 publications

(2 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1000121) and Chromium Single Cell G Chip Kit (catalog no. 1000120), the cell suspension (300 to 600 cells/μl determined by Countstar) was loaded onto the Chromium single-cell controller (10x Genomics) to generate single-cell gel beads in the emulsion according to the manufacturer’s protocol ( 59 ). In short, single cells were suspended in phosphate-buffered saline (PBS) containing 0.04% bovine serum albumin.…”

Section: Methodsmentioning

confidence: 99%

Identification of an anaplastic subtype of prostate cancer amenable to therapies targeting SP1 or translation elongation

Zou,

Li,

Zhang

et al. 2024

Sci. Adv.

View full text Add to dashboard Cite

Histopathological heterogeneity is a hallmark of prostate cancer (PCa). Using spatial and parallel single-nucleus transcriptomics, we report an androgen receptor (AR)–positive but neuroendocrine-null primary PCa subtype with morphologic and molecular characteristics of small cell carcinoma. Such small cell–like PCa (SCLPC) is clinically aggressive with low AR, but high stemness and proliferation, activity. Molecular characterization prioritizes protein translation, represented by up-regulation of many ribosomal protein genes, and SP1, a transcriptional factor that drives SCLPC phenotype and overexpresses in castration-resistant PCa (CRPC), as two potential therapeutic targets in AR-indifferent CRPC. An SP1-specific inhibitor, plicamycin, effectively suppresses CRPC growth in vivo. Homoharringtonine, a Food And Drug Administration–approved translation elongation inhibitor, impedes CRPC progression in preclinical models and patients with CRPC. We construct an SCLPC-specific signature capable of stratifying patients for drug selectivity. Our studies reveal the existence of SCLPC in admixed PCa pathology, which may mediate tumor relapse, and establish SP1 and translation elongation as actionable therapeutic targets for CRPC.

show abstract

Section: Methodsmentioning

confidence: 99%

Identification of an anaplastic subtype of prostate cancer amenable to therapies targeting SP1 or translation elongation

Zou,

Li,

Zhang

et al. 2024

Sci. Adv.

View full text Add to dashboard Cite

show abstract

“…In a subsequent study by Hua et al (2023), SeuratExtend was utilized to decipher complex immune responses in patients with rare systemic autoinflammatory diseases (SAIDs) undergoing anti-TNF therapy (Hua et al 2023). The package facilitated detailed transcriptomic profiling of peripheral blood mononuclear cells (PBMCs) and polymorphonuclear neutrophils (PMNs).…”

Section: Comprehensive Tutorials and Interactive Learning Resourcesmentioning

confidence: 99%

SeuratExtend: Streamlining Single-Cell RNA-Seq Analysis Through an Integrated and Intuitive Framework

Hua,

Weng,

Zhao

et al. 2024

Preprint

View full text Add to dashboard Cite

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity, but the rapid expansion of analytical tools has proven to be both a blessing and a curse, presenting researchers with significant challenges. Here, we present SeuratExtend, a comprehensive R package built upon the widely adopted Seurat framework, which streamlines scRNA-seq data analysis by integrating essential tools and databases. SeuratExtend offers a user-friendly and intuitive interface for performing a wide range of analyses, including functional enrichment, trajectory inference, gene regulatory network reconstruction, and denoising. The package seamlessly integrates multiple databases, such as Gene Ontology and Reactome, and incorporates popular Python tools like scVelo, Palantir, and SCENIC through a unified R interface. SeuratExtend enhances data visualization with optimized plotting functions and carefully curated color schemes, ensuring both aesthetic appeal and scientific rigor. We demonstrate SeuratExtend’s performance through case studies investigating tumor-associated high-endothelial venules and autoinflammatory diseases, and showcase its novel applications in pathway-Level analysis and cluster annotation. SeuratExtend empowers researchers to harness the full potential of scRNA-seq data, making complex analyses accessible to a wider audience. The package, along with comprehensive documentation and tutorials, is freely available at GitHub, providing a valuable resource for the single-cell genomics community.Practitioner PointsSeuratExtend streamlines scRNA-seq workflows by integrating R and Python tools, multiple databases (e.g., GO, Reactome), and comprehensive functional analysis capabilities within the Seurat framework, enabling efficient, multi-faceted analysis in a single environment.Advanced visualization features, including optimized plotting functions and professional color schemes, enhance the clarity and impact of scRNA-seq data presentation.A novel clustering approach using pathway enrichment score-cell matrices offers new insights into cellular heterogeneity and functional characteristics, complementing traditional gene expression-based analyses.

show abstract

RNA Sequencing in Disease Diagnosis

Smail,

Montgomery

2024

Annual Review of Genomics and Human Genetics

View full text Add to dashboard Cite

RNA sequencing (RNA-seq) enables the accurate measurement of multiple transcriptomic phenotypes for modeling the impacts of disease variants. Advances in technologies, experimental protocols, and analysis strategies are rapidly expanding the application of RNA-seq to identify disease biomarkers, tissue- and cell-type-specific impacts, and the spatial localization of disease-associated mechanisms. Ongoing international efforts to construct biobank-scale transcriptomic repositories with matched genomic data across diverse population groups are further increasing the utility of RNA-seq approaches by providing large-scale normative reference resources. The availability of these resources, combined with improved computational analysis pipelines, has enabled the detection of aberrant transcriptomic phenotypes underlying rare diseases. Further expansion of these resources, across both somatic and developmental tissues, is expected to soon provide unprecedented insights to resolve disease origin, mechanism of action, and causal gene contributions, suggesting the continued high utility of RNA-seq in disease diagnosis. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 25 is August 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

show abstract

Single-cell transcriptomic analysis in two patients with rare systemic autoinflammatory diseases treated with anti-TNF therapy

Cited by 3 publications

References 45 publications

Identification of an anaplastic subtype of prostate cancer amenable to therapies targeting SP1 or translation elongation

Identification of an anaplastic subtype of prostate cancer amenable to therapies targeting SP1 or translation elongation

SeuratExtend: Streamlining Single-Cell RNA-Seq Analysis Through an Integrated and Intuitive Framework

RNA Sequencing in Disease Diagnosis

Contact Info

Product

Resources

About