In the past decade, single-cell technologies have proliferated and improved from their technically challenging beginnings to become common laboratory methods capable of determining the expression of thousands of genes in thousands of cells simultaneously. The field has progressed by taking the CNS as a primary research subject - the cellular complexity and multiplicity of neuronal cell types provide fertile ground for the increasing power of single-cell methods. Current single-cell RNA sequencing methods can quantify gene expression with sufficient accuracy to finely resolve even subtle differences between cell types and states, thus providing a great tool for studying the molecular and cellular repertoire of the CNS and its disorders. However, single-cell RNA sequencing requires the dissociation of tissue samples, which means that the interrelationships between cells are lost. Spatial transcriptomic methods bypass tissue dissociation and retain this spatial information, thereby allowing gene expression to be assessed across thousands of cells within the context of tissue structural organization. Here, we discuss how single-cell and spatially resolved transcriptomics have been contributing to unravelling the pathomechanisms underlying brain disorders. We focus on three areas where we feel these new technologies have provided particularly useful insights: selective neuronal vulnerability, neuroimmune dysfunction and cell-type-specific treatment response. We also discuss the limitations and future directions of single-cell and spatial RNA sequencing technologies.
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http://dx.doi.org/10.1038/s41582-023-00809-y | DOI Listing |
The intricate development and functionality of the mammalian heart are influenced by the heterogeneous nature of cardiomyocytes (CMs). In this study, single-cell and spatial transcriptomics were utilized to analyze cells from neonatal mouse hearts, resulting in a comprehensive atlas delineating the transcriptional profiles of distinct CM subsets. A continuum of maturation states was elucidated, emphasizing a progressive developmental trajectory rather than discrete stages.
View Article and Find Full Text PDFClin Transl Med
January 2025
Department of General Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background: Thyroid cancer is one of the most common endocrine tumors worldwide, especially among women and the metastatic mechanism of papillary thyroid carcinoma remains poorly understood.
Methods: Thyroid cancer tissue samples were obtained for single-cell RNA-sequencing and spatial transcriptomics, aiming to intratumoral and antimetastatic heterogeneity of advanced PTC. The functions of APOE in PTC cell proliferation and invasion were confirmed through in vivo and in vitro assays.
Cell Rep Med
January 2025
Beijing Neurosurgical Institute, Beijing 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China. Electronic address:
Medulloblastoma (MB), a heterogeneous pediatric brain tumor, poses challenges in the treatment of tumor recurrence and dissemination. To characterize cellular diversity and genetic features, we comprehensively analyzed single-cell/nucleus RNA sequencing (sc/snRNA-seq), single-nucleus assay for transposase-accessible chromatin sequencing (snATAC-seq), and spatial transcriptomics profiles and identified distinct cellular populations in SHH (sonic hedgehog) and Group_3 subgroups, with varying proportions in local recurrence or dissemination. Local recurrence showed higher cycling tumor cell enrichment, whereas disseminated lesions had a relatively notable presence of differentiated subsets.
View Article and Find Full Text PDFJCI Insight
January 2025
Department of Biomedical Engineering, Oregon Health and Science University, Portland, United States of America.
Spatial profiling of tissues promises to elucidate tumor-microenvironment interactions and generate prognostic and predictive biomarkers. We analyzed single-cell, spatial data from three multiplex imaging technologies: cyclic immunofluorescence (CycIF) data we generated from 102 breast cancer patients with clinical follow-up, and publicly available imaging mass cytometry and multiplex ion-beam imaging datasets. Similar single-cell phenotyping results across imaging platforms enabled combined analysis of epithelial phenotypes to delineate prognostic subtypes among estrogen-receptor positive (ER+) patients.
View Article and Find Full Text PDFJ Transl Med
January 2025
Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China.
Background: It is worthwhile to establish a prognostic prediction model based on microenvironment cells (MCs) infiltration and explore new treatment strategies for triple-negative breast cancer (TNBC).
Methods: The xCell algorithm was used to quantify the cellular components of the TNBC microenvironment based on bulk RNA sequencing (bulk RNA-seq) data. The MCs index (MCI) was constructed using the least absolute shrinkage and selection operator Cox (LASSO-Cox) regression analysis.
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