Abstract

e14657 Background: Spatial multi-omics approaches, including spatial transcriptomics (ST) and spatial proteomics (SP), that elucidate the complex tissue microenvironment (TME) are gaining traction in cancer research studies. However, combining these approaches onto one tissue section remains challenging. ST methods visualize, locate and quantify RNA targets, evaluating the transcriptome of the TME at the subcellular level while SP methods stain and visualize protein biomarkers at the cellular level. Here we show a pipeline that combines these ST and SP methods with Hematoxylin and Eosin (H&E) approach on a single tissue section to achieve single slide multi-omics data with high resolution tissue morphology images. Methods: 5µm formalin-fixed paraffin-embedded sections of human lung cancer samples were placed on a Xenium (10x Genomics, Pleasanton, CA) slides and treated to expose RNA molecules. Probe hybridization was performed with a human lung panel kit containing 289 barcoded DNA padlock probes. Downstream ligation and amplification generated copies of the barcode and thereafter, the Xenium Analyzer performed imaging and data collection. The same tissue section was then stained and imaged in COMET (Lunaphore Technologies SA, Switzerland) using sequential immunofluorescence (seqIF) method to detect 40 protein targets in situ. Serial sections of the specimens were used for direct H&E and seqIF staining for comparative validation. Results: Multi-omics images generated from Xenium and COMET were overlayed, jointly analyzed and interpreted. Staining specificity of the protein targets for the post-Xenium slides remain comparable with the direct COMET-stained slide. 40-plex COMET staining intensity in post-Xenium slide was minimally weaker compared to direct COMET-stained slide. Additionally, H&E staining of the post-Xenium/COMET slide and direct COMET-stained slide were comparable to the direct H&E-stained section, demonstrating discernable tissue landscape features despite a fainter hematoxylin stain. Overall, tissue integrity and cell morphology were well-preserved across the different workflows performed on each section, and the protein targets remain relatively stable for labelling after in situ RNA detection process. Conclusions: We present a pipeline that combines two spatial omics approaches with the diagnostic standard H&E staining on a single tissue section, allowing the same cells to be assessed for their histological, proteomic, and transcriptomic information. A visual comparison of images showed minimal compromise to cellular morphology and protein stability at the end of the pipeline compared to direct staining of serial sections. This pipeline could be potentially generalized to most of the ST and SP approaches, thus advancing multi-omics cancer research and potentially clinical diagnostics in the future.