Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomic data from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety of tissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10767865 | PMC |
http://dx.doi.org/10.1093/nar/gkad753 | DOI Listing |
Cell
December 2024
Department of Genetics, University of Georgia, Athens, GA, USA. Electronic address:
Cis-regulatory elements (CREs) precisely control spatiotemporal gene expression in cells. Using a spatially resolved single-cell atlas of gene expression with chromatin accessibility across ten soybean tissues, we identified 103 distinct cell types and 303,199 accessible chromatin regions (ACRs). Nearly 40% of the ACRs showed cell-type-specific patterns and were enriched for transcription factor (TF) motifs defining diverse cell identities.
View Article and Find Full Text PDFTalanta
December 2024
Université de Lorraine, CNRS, LIEC, F-54000, Nancy, France.
There is a growing interest in the development of methods for the detection of nanoparticle (NP) toxicity to living organisms based on the analysis of relevant multidimensional data sets. In particular the detection of preliminary signs of NPs toxicity effects would benefit from the selection of data featuring NPs-induced alterations of biological barriers. Accordingly, we present an original Topological Data Analysis (TDA) of the nanomechanical properties of Escherichia coli cell surface, evaluated by multiparametric Atomic Force Microscopy (AFM) after exposure of the cells to increasing concentrations of titanium dioxide nanoparticles (TiONPs).
View Article and Find Full Text PDFRes Sq
December 2024
Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX.
View Article and Find Full Text PDFJ Clin Periodontol
December 2024
Lab of Oral & Craniofacial Innovation (LOCI), Department of Innovation & Technology Research, ADA Science & Research Institute, Gaithersburg, Maryland, USA.
Aims: This narrative review aims to synthesize current knowledge on integrating single-cell genomics technologies with animal models of periodontitis and peri-implantitis.
Review: Single-cell RNA sequencing (scRNAseq) reveals cellular heterogeneity and specific cell roles in periodontitis and peri-implantitis, overcoming the limitations of bulk RNA sequencing. Under controlled conditions and genetic manipulation, animal models facilitate studying disease progression, gene functions and systemic disease links, aiding targeted therapy development.
Nature
December 2024
Department of Genetics, Stanford University, Stanford, CA, USA.
Old age is associated with a decline in cognitive function and an increase in neurodegenerative disease risk. Brain ageing is complex and is accompanied by many cellular changes. Furthermore, the influence that aged cells have on neighbouring cells and how this contributes to tissue decline is unknown.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!