The higher-order cognitive functions of the human cortex rely on complex cellular structures, with diversity and spatial organization critical for specific functions. However, the molecular features and precise spatial organization of neural cells within the human cortex remain incompletely understood. Subcellular-level spatial transcriptomic sequencing and snRNA-seq offer a unique opportunity to explore and characterize neural cell organization across different cortical regions. Here, we mapped 14 human cortical regions, leading to a single-cell atlas comprising transcriptomic data from 1,121,772 nuclei and spatial profiles from 1,888,306 cells. The atlas reveals distinct expression patterns and spatial arrangements of neural cell types. Glutamatergic neurons show precise laminar patterns, with similar expression in adjacent areas. SST neurons fall into two transcriptional categories, corresponding to superficial and deep layer distributions. The atlas, integrated with functional networks, highlights correlations between neural cell types and cortical functions, uncovering cell-cell interactions and ligand-receptor patterns with regional differences in neuron-glia communication. It also deciphers transcriptomic differences and cellular composition in layer 4 and the stable subplate (layer 6b) across regions. Our findings offer insights into the cellular foundations of complex and intelligent regions within the human cortex.

Atopic dermatitis (AD) is the most common chronic inflammatory skin disease with complex pathogenesis. Using spatial and single-cell transcriptomics of whole skin biopsy and suction blister material, we investigated the cellular and molecular features of the leukocyte-infiltrated area in AD. We identified unique clusters of fibroblasts, dendritic cells, macrophages, and T cells in the lesional AD skin and molecular interactions between these cells. The leukocyte-infiltrated areas in lesional AD skin showed upregulation of COL6A5, COL4A1, TNC, IL32, CCL19 in COL18A1-expressing fibroblasts. Additionally, M2 macrophages expressed CCL13 and CCL18 in the same localization. Ligand–receptor interaction analysis of the spatial transcriptome identified a neighboring infiltration and interaction between activated COL18A1-expressing fibroblasts, activated CCL13- and CCL18-expressing M2 macrophages, CCR7- and LAMP3-expressing DCs, and T cells. As observed in skin lesions, serum levels of TNC and CCL18 were significantly elevated in AD and correlated with clinical disease severity.

In 10X Genomics Visium Spatial Gene Expression (ST), the resolution for distinguishing neighboring cells can be improved using data integration with single-cell/single-nuclei transcriptomics profiles. Besides, depending on the cell type and tissue, nuclei size may vary significantly to an extent that it may exceed the thickness of tissue slices. This may jeopardize capturing full transcriptomics profile of single slice due to the improper/incomplete incision of nuclei during cryosectioning process and this may cause drawbacks in downstream analysis. To monitor the probable consequences, we monitored the effect of consecutive slices data integration (CSDI) on improvement of cell type clustering and annotation through transferring cell labels from a single-nuclei transcriptomics dataset to ST. To do so, two consecutive slices from the orbitofrontal neocortex and temporal neocortex of two post mortem brain samples were obtained and their spatial transcriptomics profiles were retrieved using 10x Genomics Visium Spatial Gene Expression protocol. Using CSDI, not only the number of identified clusters were increased and the inconsistency between the pattern of clusters in consecutive slices was resolved, but the layered-structure of gray matter was unveiled. Besides, only after CSDI the transferred annotations from single-nuclei transcriptomics to ST could match the microscopic results. CSDI can improve the ST clustering and cell type annotation by providing the full signals coming from all cell types of single slice of tissue. The codes in R programming language are publicly available at https://github.com/ElyasMo/ST_snRNA-seq

As pancreatic ductal adenocarcinoma (PDAC) continues to be recalcitrant to therapeutic interventions including poor response to immunotherapy, albeit effective in other solid malignancies, a more nuanced understanding of the immune microenvironment in PDAC is urgently needed. Using a spatially-resolved multimodal single cell approach we unveil a detailed view of the immune micromilieu in PDAC with specific emphasis on the correlation of immune subtypes with patient survival. We substantiate the exhausted phenotype of CD8 T cells and immunosuppressive features of myeloid cells, and highlight immune subpopulations with potentially underappreciated roles in PDAC, particularly CD4 T cell subsets presenting immunosuppressive phenotypes with varying modes of exhaustion. We also demonstrate the dynamic changes associated with transcriptional reprogramming of immune subtypes within adjacent normal tissue and tumor surrounding stroma, and further reveal striking differences between immune phenotypes in PDAC and lung adenocarcinoma, which at least partially explain their differential responsiveness to current immunotherapies and might have implications for the development of novel treatment strategies.

This SuperSeries is composed of the SubSeries listed below.

Heterogeneity of senescent cancer cells have been dissected by Spatial Transcriptomic in human colorectal liver metastasis (CRLM).

We performed spatial transcriptomics of a tumor section from a patient post-treatment with adenoid cystic carcinoma of the lacrimal gland.

Purpose: The 10x Genomics Visium platform allows us to define the spatial topography of gene expression and provides detailed molecular maps that overcome limitations associated with sn/scRNA-seq and microscopy-based spatial transcriptomics methods. The goals of this study are to compare and identify unique transcriptome profiling (RNA-seq) signature between unfavorable and favorable Wilms Tumors and against human fetal kidney. Methods: Human fetal kidney and Wilms tumor spatial topography of gene expression were generated using the 10X Visium platform Results: Using an optimized data analysis workflow, we mapped the reads to the hg38 genome build and grouped the spots into 9 clusters based on gene expression profiles. Conclusion: Our study represents the first implement of Visium technology in human fetal kidney and Wilms Tumor tissue, providing a number of important functional insights about the spatial and molecular definitions of cell populations across human fetal kidney and different subtypes of Wilms Tumor through analyzing gene expression within the intact spatial organization of the human samples.

In this study, we comprehensively charted the cellular landscape of colorectal cancer (CRC) and well-matched liver metastatic CRC using single-cell and spatial transcriptome RNA sequencing. We generated 41892 CD45- non-immune cells and 196473 CD45+ immune cells from 27 samples of 6 CRC patients, and found that CD8_CXCL13 and CD4_CXCL13 subsets increased significantly in liver metastatic samples that exhibited high proliferation ability and tumor-activating characterization, contributing to better prognosis of patients. Distinct fibroblast profiles were observed in primary and liver metastatic tumors. The F3+ fibroblasts enriched in primary tumors contributed to worse overall survival by expressing pro-tumor factors. However, the MCAM+ fibroblasts enriched in liver metastatic tumors might promote generation of CD8_CXCL13 cells through Notch signaling. In summary, we extensively analyzed the transcriptional differences of cell atlas between primary and liver metastatic tumors of CRC by single-cell and spatial transcriptome RNA sequencing, providing different dimensions of the development of liver metastasis in CRC

This SuperSeries is composed of the SubSeries listed below.