Abstract 5072: Multi-omic, multi-scale characterisation of colorectal cancer defines spatiotemporal patterns of recurrence

Abstract Aim: Patients who undergo intended curative resection of colorectal cancer (CRC) have a 20-25% chance of metachronous recurrence, the site and timing of which are unpredictable and resistant to current treatment. The biological basis for such heterogeneous disease behavior remains to be elucidated. Bulk transcriptomic profiling and subsequently single-cell RNAseq have provided insight in the epithelial subtypes and immune microenvironment. Recently spatially resolved transcriptomic assessment allow molecular profiling of tissue while preserving tissue architecture. Utilizing ST technology we sought to perform deep characterization of a large cohort of patients with primary CRC with the intention to decipher the biological determinants of spatio-temporal patterns of recurrence. Methods: 750 patients who underwent resection of CRC with mature follow up were studied. Bulk transcriptomic, genomic and multiplex immune characterization was performed using a TMA format. Of these, 28 patients were assessed using single cell spatial transcriptomics (Nanostring CosMx Spatial Molecular Imager (SMI, 1000plex gene panel) ), 120 tumors underwent regional whole transcriptome profiling of epithelium and TME (Nanostring GeoMx Digital Spatial Profiler using FFPE tissue). We used image analysis and bioinformatics to integrate these complex datasets in over 120000 single-cells in the context of their spatial tissue architecture and clinicopatholgical outcome and recurrence data. Results: Using the CosMx SMI we characterized cells with complete topographic detail and defined 2 unique epithelial cell states defined. Each epithelial state had distinct spatial properties including cell size and morphology, average distance to nearest lymphocyte, neighboring cell types and stromal neighborhood. This epithelial signature was integrated in GeoMx samples and were found to predict recurrence (p0. 05). The Epithelial, Fibroblast and Immune GeoMx transcriptomic compartments were expanded and grouped using unsupervised clustering. Each compartment demonstrated groups of patients where specific spatially derived signatures could predict site and time of recurrence (p0. 05). Conclusions: By maintaining the tissue structure, we have directly measured cellular interactions and captured cells commonly missed during dissociative studies whilst defining novel molecular subtypes of CRC with clinical relevance. Novel platforms such as CosMx allow deeper characterization of unique cell types and cellular interactions that may pave the way for novel therapeutics and precision medicine for patients with CRC. Citation Format: Colin Stuart Wood, Joao Da Silva Filho, Andrew Cameron, Assya Legrini, Holly Leslie, Tengyu Zhang, Yoana Doncheva, Claire Kennedy-Dietrich, Matthias Marti, Joanne Edwards, Paul Horgan, Campbell Roxburgh, Colin Steele, Nigel Jamieson. Multi-omic, multi-scale characterisation of colorectal cancer defines spatiotemporal patterns of recurrence abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 5072.