An Integrated Spatial Multi-Omics Workflow for Sequential RNA and Protein Profiling in FFPE Tumor Tissue

Understanding complex cellular niches, such as tertiary lymphoid structures, requires spatially resolved, multi-omics approaches that link transcriptional states and protein expression levels within individual cells. Here, we present an integrated spatial multi-omics workflow that enables sequential mapping of hundreds of genes via the Xenium In Situ platform and more than 40 protein markers via imaging mass cytometry technology on a single formalin-fixed, paraffin-embedded (FFPE) tissue section. We applied this multi-modal approach to colorectal liver metastases and matched adjacent normal liver tissues. Our results demonstrate that the sequential application of these technologies maintains tissue morphology and the assay's technical sensitivity. Furthermore, high-dimensional data integration was performed through optimized computational coregistration at a single-cell level. Through this approach, we observed a correlation between β-catenin proteomic levels and malignant cell states, characterized immune cell phenotypes in lymphoid aggregates, and identified discrepancies between RNA and protein levels for key checkpoint molecules (PD-L1, TIM-3, and IDO). Overall, this technical framework enables robust profiling of functional cellular states, spatial mapping of chemokine expression, and more sensitive detection of clinically relevant targets missing in single-modality methods.

We present an integrated spatial multi-omics workflow that enables direct comparison of transcript and protein levels within a single FFPE section. This enables detailed profiling of the cellular microenvironment, along with relevant protein biomarkers, for clinical decision-making.