PROJECT SUMMARY/ABSTRACT Differences in colorectal cancer (CRC) incidence and mortality rates are appreciable and continue to exist across population groups in the United States. By studying population groups with varying cancer rates, we enhance the statistical power to identify the molecular characteristics and contributing factors driving these differences, ultimately aiming to meaningfully reduce morbidity and mortality. We propose a CRC tumor molecular profiling strategy that will provide novel insights and take full advantage of the existing infrastructure of our Translational Research Program in Cancer Differences across Populations (TRPCDP) with its available biospecimens from highly annotated CRC patients. Specifically, novel spatial proteomic analyses enable deep characterization of the tumor microenvironment and immune response which in other cancers has been shown to be of high translational relevance. Few studies though have applied this powerful approach to CRC or to advance our understanding of differences in cancer outcomes across population groups. This project will complete the following specific aims: Aim 1. Discover novel colorectal tumor-tissue based spatially resolved prognostic biomarkers using the PhenoCycler platform (n=840); Aim 2. Discover colorectal tumor tissue based spatially resolved predictors of response to both first-line CRC therapy (n=840) and immunotherapy (n=100); Aim 3. Develop and validate predictors of treatment response and CRC-specific mortality. This aim will use 70% of samples for discovery, and 30% for validation. Our optimized panel to predict risk of CRC-specific mortality will be translated into a multiplex immunofluorescence (mIF) ~8 biomarker assay (using the Vectra Polaris platform) and its performance will be evaluated on our 30% validation set. The results of this work will have short-term potential translational impacts through improving the identification of: 1) patients at high risk of dying from CRC who may benefit from advanced monitoring or alternative first-line treatments, including the development of the first version of a potentially clinically useful mIF assay; and 2) predictors of treatment response that can guide clinical decision making, treatment selection, and patient stratification. Our comprehensive evaluations of tumoral immune response and mechanism of immune evasion may have longer-term potential translational impact as these evaluations could inform the development of novel therapeutic approaches that could be particularly relevant for certain population groups. We anticipate that through identifying new treatment strategies and improving risk prediction across different patient population groups, this project will have a positive impact on reducing existing differences in CRC outcomes.