Abstract

   Recent advancements in spatial transcriptomics technologies have
   significantly enhanced resolution and throughput, underscoring an
   urgent need for systematic benchmarking. Here, we generate serial
   tissue sections from colon adenocarcinoma, hepatocellular carcinoma,
   and ovarian cancer samples for systematic evaluation. Using these
   uniformly processed samples, we generate spatial transcriptomics data
   across four high-throughput platforms with subcellular resolution:
   Stereo-seq v1.3, Visium HD FFPE, CosMx 6K, and Xenium 5K. To establish
   ground truth datasets, we profile proteins on tissue sections adjacent
   to all platforms using CODEX and perform single-cell RNA sequencing on
   the same samples. Leveraging manual nuclear segmentation and detailed
   annotations, we systematically assess each platform’s performance
   across capture sensitivity, specificity, diffusion control, cell
   segmentation, cell annotation, spatial clustering, and concordance with
   adjacent CODEX. The uniformly generated and processed multi-omics
   dataset could advance computational method development and biological
   discoveries. The dataset is accessible via SPATCH, a user-friendly web
   server for visualization and download.

   Subject terms: RNA sequencing, Cancer microenvironment
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   This study benchmarks four cutting-edge spatial transcriptomics
   platforms using human tumour tissues, performs multi-metric evaluation
   with multi-omics references, and presents the SPATCH portal for