Over 150,000 Americans are diagnosed with colorectal cancer (CRC) every year, and annually over 50,000 individuals will die from CRC, necessitating improvements in screening, prognostication, disease management, and therapeutic options. CRC tumors are removed en bloc with surrounding vasculature and lymphatics. Examination of regional lymph nodes at the time of surgical resection is essential for prognostication. Developing alternative approaches to indirectly assess recurrence risk would have utility in cases where lymph node yield is incomplete or inadequate. Spatially dependent, immune cell-specific (e.g., Tumor Infiltrating Lymphocytes- TILs), proteomic, and transcriptomic expression patterns inside and around the tumor - the tumor immune microenvironment (TIME) - can predict nodal/distant metastasis and probe the coordinated immune response from the primary tumor site. The comprehensive characterization of TILs and other immune infiltrates is possible using highly multiplexed spatial omics technologies, such as the GeoMX Digital Spatial Profiler (DSP). In this study, machine learning and differential co-expression analyses helped identify biomarkers from DSP-assayed protein expression patterns inside, at the invasive margin, and away from the tumor, associated with extracellular matrix remodeling (e.g., GZMB, fibronectin), immune suppression (e.g., FOXP3), exhaustion and cytotoxicity (e.g., CD8), PD-L1 expressing dendritic cells, neutrophil proliferation, amongst other concomitant alterations. Further investigation of these biomarkers may reveal independent risk factors of CRC metastasis that can be formulated into low-cost, widely available assays.

The authors have declared no competing interest.

This work was supported by NIH grants R01CA216265, R01CA253976, and P20GM104416 to BC, Dartmouth College Neukom Institute for Computational Science CompX awards to BC, JL and LV, and DCC, DPLM Clinical Genomics and Advanced Technologies EDIT program. JL is supported through NIH subawards P20GM104416 and P20GM130454. The funding bodies above did not have any role in the study design, data collection, analysis and interpretation, or writing of the manuscript.

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Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

IRB of Dartmouth Health gave ethical approval for this work.

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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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Study data can be explored using an Rshiny application, available at the following URL: https://levylab.shinyapps.io/ViewColonDSPResults (user: edit_user, password: cgat2022). Complete set of data produced in the present study are available upon reasonable request to the authors.