The recent arrival of high-resolution spatial transcriptomics (ST) technologies is generating a veritable revolution in life sciences, enabling biomolecules to be measured in their native spatial context. By integrating morphology and molecular biology, ST technologies offer the potential of improving the understanding of tissue biology and disease and may also provide meaningful clinical insights. This review describes the main ST technologies currently available and the computational analysis for data interpretation and visualization, and illustrate their scientific and potential medical interest in the context of kidney disease. Finally, we discuss the perspectives and challenges of these booming new technologies.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.ajpath.2024.06.012 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Exploring the role of metabolic pathways in TNBC immunotherapy: insights from single-cell and spatial transcriptomics.
Front Endocrinol (Lausanne)
January 2025
The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
The article provides an overview of the current understanding of the interplay between metabolic pathways and immune function in the context of triple-negative breast cancer (TNBC). It highlights recent advancements in single-cell and spatial transcriptomics technologies, which have revolutionized the analysis of tumor heterogeneity and the immune microenvironment in TNBC. The review emphasizes the crucial role of metabolic reprogramming in modulating immune cell function, discussing how specific metabolic pathways, such as glycolysis, lipid metabolism, and amino acid metabolism, can directly impact the activity and phenotypes of various immune cell populations within the TNBC tumor microenvironment.
View Article and Find Full Text PDFMapping the topography of spatial gene expression with interpretable deep learning.
Nat Methods
January 2025
Department of Computer Science, Princeton University, Princeton, NJ, USA.
Spatially resolved transcriptomics technologies provide high-throughput measurements of gene expression in a tissue slice, but the sparsity of these data complicates analysis of spatial gene expression patterns. We address this issue by deriving a topographic map of a tissue slice-analogous to a map of elevation in a landscape-using a quantity called the isodepth. Contours of constant isodepths enclose domains with distinct cell type composition, while gradients of the isodepth indicate spatial directions of maximum change in expression.
View Article and Find Full Text PDFHighly multiplexed spatial transcriptomics in bacteria.
Science
January 2025
Program in Cellular and Molecular Medicine, Boston Children's Hospital, Boston, MA, USA.
Single-cell decisions made in complex environments underlie many bacterial phenomena. Image-based transcriptomics approaches offer an avenue to study such behaviors, yet these approaches have been hindered by the massive density of bacterial messenger RNA. To overcome this challenge, we combined 1000-fold volumetric expansion with multiplexed error-robust fluorescence in situ hybridization (MERFISH) to create bacterial-MERFISH.
View Article and Find Full Text PDFSpatially resolved transcriptomics of benign and malignant peripheral nerve sheath tumors.
Neuro Oncol
January 2025
Department of Neurosurgery, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg.
Background: Peripheral nerve sheath tumors (PNSTs) encompass entities with different cellular differentiation and degrees of malignancy. Spatial heterogeneity complicates diagnosis and grading of PNSTs in some cases. In malignant PNST (MPNST) for example, single cell sequencing data has shown dissimilar differentiation states of tumor cells.
View Article and Find Full Text PDFNovel Integration of Spatial and Single-Cell Omics Data Sets Enables Deeper Insights into IPF Pathogenesis.
Proteomes
January 2025
Research & Development, AbbVie Bioresearch Center, Worcester, MA 01605, USA.
Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease characterized by repetitive alveolar injuries with excessive deposition of extracellular matrix (ECM) proteins. A crucial need in understanding IPF pathogenesis is identifying cell types associated with histopathological regions, particularly local fibrosis centers known as fibroblast foci. To address this, we integrated published spatial transcriptomics and single-cell RNA sequencing (scRNA-seq) transcriptomics and adopted the Query method and the Overlap method to determine cell type enrichments in histopathological regions.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!