sequencing-based spatial transcriptomics  (Spatial Transcriptomics Inc)

Journal: Nature Communications

Article Title: Spatial transcriptomic analysis drives PET imaging of tight junction protein expression in pancreatic cancer theranostics

doi: 10.1038/s41467-024-54761-6

Figure Lengend Snippet: A Overview of the project. Parts created with BioRender.com. B H&E of PDAC tumor excised from four patients (bottom row) and their corresponding spatial transcriptomic spots (top row) arranged based on increasing CLDN4 expression. The spatial transcriptomes between the PDAC slices were integrated based on canonical correlation analysis (Seurat), clustered, projected on the Uniform Manifold Approximation and Projection (UMAP) dimension in ( C ), and projected onto their histology slices. Scale bar = 3 mm. C Leiden clustering of PDAC transcriptome projected on UMAP space and heatmap of Leiden clusters with genes selected from the PDAC data set of the cancer cell surfaceome with a specification of expression on at least 80% of cells. Scale represents z-score of log-normalized gene counts. Cluster identities were determined with one-sided hypergeometric t tests of all clusters in PDAC with respect to cell type signatures detailed in refs. , , which were derived from scRNA and plotted as a dotplot. D Differential expression of Cluster 1 versus all remaining clusters and versus samples of unaffected pancreas surrounding precancerous IPMN. E Cancer surfaceome score based on average normalized and scaled gene expression of all cells and all cancer cell surfaceome pancreatic cancer genes in each cluster. F Pearson’s correlation similarity matrix of select cancer cell surfaceome genes based on the PDAC spatial transcriptome. G Pearson’s correlation of all spots for S100P vs key markers of interest. H KEGG and REACTOME pathway enrichment of Cluster 1. Each calculation was based on n = 7 samples. For box plots, the center is the median and the lower and upper bound of the box are 25% and 75% of the distribution, respectively. The lower whisker is the lower 25% −1.5 x interquartile range (IQR). The upper whisker is the upper 75% + 1.5 x IQR. Differential expression analysis in ( D ) and ( E ) were based on non-parametric Wilcoxon rank sum test, which is a default setting in Seurat’s FindMarkers function. Gene enrichment analysis in ( H ) was done with 1-sided hypergeometric t test based on clusterProfiler package. Source data are provided as a Source Data file.

Article Snippet: Formalin-fixed, paraffin-embedded (FFPE) human pancreatic cancer tissue sections were placed on spatial transcriptomic slides for spatial transcriptomic sequencing based on the 10x FFPE workflow (10x Genomics, Pleasanton, CA).

Techniques: Expressing, Derivative Assay, Quantitative Proteomics, Gene Expression, Whisker Assay

Journal: Nature Communications

Article Title: Spatial transcriptomic analysis drives PET imaging of tight junction protein expression in pancreatic cancer theranostics

doi: 10.1038/s41467-024-54761-6

Figure Lengend Snippet: A Summary of the IPMN study. B H&E slices of IPMN tumor excised from three patients (bottom two rows) and their corresponding spatial transcriptomic spots (top two rows) arranged based on increasing CLDN4 expression. The spatial transcriptomes between the IPMN slices were merged, clustered, and projected on the Uniform Manifold Approximation and Projection (UMAP) dimension in ( C ) and projected to their H&E slices. Scale bar = 3 mm. C Leiden clustering of IPMN transcriptome projected on UMAP space. Dot plot of one-sided hypergeometric t test results of all clusters in IPMN based on cell type signatures. D Heatmap of Leiden clusters with genes selected from the PDAC cell surfaceome atlas with greater than 80% expression across sequenced PDAC cells. Scale represents z-score of log-normalized gene counts. E – G Differential expression of Cluster 6 ( E ) and Cluster 12 ( F ) versus all remaining clusters and G ) Cluster 12 versus Cluster 6. H Cancer surfaceome score based on average normalized and scaled gene expression of all cells and all cancer cell surfaceome PDAC genes in each cluster. I Pearson’s correlation similarity matrix of select cancer cell surfaceome genes based on the IPMN spatial transcriptome. J Pearson’s correlation of all spots for S100P vs key markers of interest. K KEGG pathway enrichment of Cluster 6 and Cluster 12. Each calculation is based on n = 18 samples. For box plots, the center is the median and the lower and upper bound of the box are 25% and 75% of the distribution, respectively. The lower whisker is the lower 25% − 1.5 x interquartile range (IQR). The upper whisker is the upper 75% + 1.5 x IQR. Differential expression analysis in ( E ), ( F ) and ( G ) were based on non-parametric Wilcoxon rank sum test, which is a default setting in Seurat’s FindMarkers function. Gene enrichment analysis in ( K ) was done with hypergeometric t test based on clusterProfiler package. Source data are provided as a Source Data file.

Article Snippet: Formalin-fixed, paraffin-embedded (FFPE) human pancreatic cancer tissue sections were placed on spatial transcriptomic slides for spatial transcriptomic sequencing based on the 10x FFPE workflow (10x Genomics, Pleasanton, CA).

Techniques: Expressing, Quantitative Proteomics, Gene Expression, Whisker Assay