Targeting cancer-associated cell surface RNAs with oligonucleotide-drug conjugates enables broad antitumor activity

This dataset contains single-cell transcriptomic and imaging data of cell-surface RNAs (csRNAs) and intracellular RNAs generated using Cell-surface and Intracellular RNAs Co-mapping (CIRCmap), a highly multiplexed in situ profiling approach enabling simultaneous detection of thousands of csRNAs and intracellular RNAs at single-cell resolution. CIRCmap was applied to five cancer and five non-tumorigenic cell types, supporting the identification of cancer-associated csRNAs, characterization of their subcellular trafficking mechanisms, and validation of their potential as targets for oligonucleotide-drug conjugates (ODCs) in cancer therapy. The dataset includes transcriptomic profiles and downstream analysis outputs across 10 cell types, focusing on ancer/non-tumorigenic distinctions and csRNA association with cancer cell states (e.g., M phase). Data Files and Formats 1. Zarr Files (SpatialData Format) Spatially resolved single-cell transcriptomic data of csRNAs and intracellular RNAs for each of the 10 cell types, enabling efficient storage, access, and visualization of spatial transcriptomic arrays. 2. H5AD Files (AnnData Format) Unfiltered: Raw integrated single-cell transcriptomic data of all 10 cell types, including gene expression matrices, cell metadata (type, cancer/non-tumorigenic status), and feature metadata (gene annotations, RNA type designation). Filtered: Quality-controlled integrated dataset (low-quality cells/non-informative genes removed) optimized for downstream differential and co-expression analyses. 3. Countable Text Files Tab-delimited files derived from H5AD files, including raw/normalized count matrices, obs (cell annotations: type,, cell cycle phase), var (gene annotations: csRNA classification, symbols, and PCA/UMAP embedding files for cell clustering visualization. 4. RDS Files Intermediate files compatible with R Seurat framework, containing processed expression data, cell clustering results, and annotations to support further visualization and statistical analysis in R. 5. Imaging Data Raw decoded transcript spot coordinates (per cell line) for spatial mapping of gene expression. Stitched composite images: Flamingo (cell membrane) and DAPI (nucleus) fluorescent staining images of each cell line. Cell segmentation masks: Binary/labeled images derived from Flamingo/DAPI staining, delineating individual cells and nuclei for single-cell transcript extraction.