An unmet clinical need in solid tumor cancers is the ability to harness the intrinsic spatial information in primary tumors that can be exploited to optimize prognostics, diagnostics and therapeutic strategies for precision medicine. We have developed a transformational spatial analytics (SpAn) computational and systems biology platform that predicts clinical outcomes and captures emergent spatial biology that can potentially inform therapeutic strategies. Here we apply SpAn to primary tumor tissue samples from a cohort of 432 chemo-naïve colorectal cancer (CRC) patients iteratively labeled with a highly multiplexed (hyperplexed) panel of fifty-five fluorescently tagged antibodies. SpAn predicted the 5-year risk of CRC recurrence with a mean area under the ROC curve of 88.5% (SE of 0.1%), significantly better than current state-of-the-art methods. SpAn also inferred the emergent network biology of the tumor spatial domains revealing a synergistic role of known features from CRC consensus molecular subtypes that will enhance precision medicine.
MainColorectal Cancer (CRC) is the second most common type of cancer and the third leading cause of cancer-related deaths worldwide. 1 This multi-factorial disease like other carcinomas, develops and progresses through the selection of epithelial clones with the potential to confer malignant phenotypes in the context of a reciprocally coevolving tumor microenvironment (TME) comprising immune and stromal cells. 2-4 CRC patients are staged using the well-established tumor-nodemetastases (TNM) classification. 5,6 However, there is significant variability in patient outcomes within each stage. For example, CRC will recur in up to 30% of Stage II patients despite complete tumor resection, no residual tumor burden and no signs of metastasis. 7 In contrast, more advanced CRC has been known to show stability or indeed even to spontaneously regress. 7,8 The intrinsic plasticity of the TME underlying this variability in outcome is controlled by complex network biology emerging from the spatial organization of diverse cell types within the TME and their heterogeneous states of activation. 3,[9][10][11] The important role of the TME in CRC progression and recurrence has recently been highlighted by the identification of four consensus molecular subtypes (CMS) 12,13 , functional studies defining the critical role of stromal cells in determining overall survival, 14 and the development of Immunoscore® 14 which quantifies tumorinfiltrating T-lymphocytes in different regions of the tumor and associates their infiltration with CRC recurrence. 15,16 However the TME can be further harnessed to significantly improve CRC prognosis through the identification of biomarkers mechanistically linked to disease progression and the development of novel therapeutic strategies.Deeper understanding of the TME may arise from imaging methods capable of labeling > 7 cellular and tissue components in the same sample (hyperplexed 17 (HxIF) fluorescence and other imaging modalities). [17][18][19][20][21] To...