Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer

Advanced solid cancers are complex assemblies of tumor, immune, and stromal cells characterized by high intratumoral variation. We use highly multiplexed tissue imaging, 3D reconstruction, spatial statistics, and machine learning to identify cell types and states underlying morphological features of known diagnostic and prognostic significance in colorectal cancer. Quantitation of these features in high-plex marker space re-veals recurrent transitions from one tumor morphology to the next, some of which are coincident with long-range gradients in the expression of oncogenes and epigenetic regulators. At the tumor invasive margin, where tumor, normal, and immune cells compete, T cell suppression involves multiple cell types and 3D im-aging shows that seemingly localized 2D features such as tertiary lymphoid structures are commonly inter-connected and have graded molecular properties. Thus, while cancer genetics emphasizes the importance of discrete changes in tumor state, whole-specimen imaging reveals large-scale morphological and molecular gradients analogous to those in developing tissues.

Automated summary

We used advanced imaging techniques, 3D reconstruction, spatial statistics, and machine learning to identify cell types and states associated with diagnostic and prognostic features in colorectal cancer. We found that at the tumor invasive margin, T cell suppression involves multiple cell types and that seemingly localized features such as tertiary lymphoid structures are interconnected and have graded molecular properties. These findings challenge the notion that discrete changes in tumor state are most important, demonstrating the presence of large-scale morphological and molecular gradients.