EACR: Cancer Genomics, Multiomics and Computational Biology

Spatial biology techniques have revolutionized our approach towards the study of the tumor microenvironment (TME) and its complex cellular interplay. While multiplex immunofluorescence methods have enabled precise spatial profiling of TME cellular players, in situ, hybridization technologies have provided complementary information on signaling and immune activation statuses. Here, we used a novel multiomics approach that combines these two biological inputs by integrating RNAscope™ and sequential immunofluorescence (seqIF™) protocols to achieve same-section co-detection of RNA and protein targets. The combined workflow is fully automated on COMET™, an advanced tissue staining and imaging platform. The instrument ensures maximum efficiency and reproducibility of the assays through precise control over temperature and reagent distribution. The integrated multiomics protocol allows up to three RNAscope™ detection cycles combined with twelve seqIF™ cycles, for a final 12-plex RNA + 24-plex protein panel. We first showed the capacity of the COMET™ platform to automate the RNAscope™ protocol. We demonstrated its sensitivity and specificity by analyzing positive and negative control genes on HeLa cell pellets, highlighting the flexibility of sample selection. To illustrate the potential of multiomics in unraveling the complexity of the TME, we designed a panel of 12-RNA-targeting probes for key biomarkers of tumor-infiltrating lymphocytes and combined it with a 24-antibody panel for the detection of protein biomarkers, selected to enable the single-cell profiling of different players within the TME. Our results highlight the potential of spatial multiomics technologies in enhancing the efficiency of investigations of immune cell behavior and, generally, the understanding of cellular interplay in the TME. Their full automation on a platform like COMET™ will accelerate analysis and increase robustness by minimizing user intervention and ultimately helping in the development of prognostic and predictive biomarkers, in the refinement of cancer diagnoses, and in the selection of new personalized therapies.