SUMMARY
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 reveals 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 imaging shows that seemingly localized 2D features such as tertiary lymphoid structures are commonly interconnected 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.
Competing Interest Statement
PKS is a co-founder and member of the BOD of Glencoe Software, a member of the BOD for Applied Biomath, and a member of the SAB for RareCyte, NanoString, and Montai Health; he holds equity in Glencoe, Applied Biomath, and RareCyte. PKS is a consultant for Merck and the Sorger lab has received research funding from Novartis and Merck in the past five years. YC is a consultant for RareCyte. Sorger declares that none of these relationships have influenced the content of this manuscript. The other authors declare no outside interests.
Footnotes
↵# lead contact at peter_sorger{at}hms.harvard.edu
A key concern mentioned by the reviewers and in the editorial cover letter was that the emphasis of our original paper was perceived to be primarily methodological rather than biological. This was certainly not our intention; therefore, we have restructured the paper so that the key point about spatial power is fully described in a single figure (Figure 2) and all subsequent figures describe specific results (the five points listed below) that derive from our findings about whole slide vs. TMA vs. 3D imaging. We do not believe that we have removed any critical methodological points. Instead, we have rebalanced the results and the STAR methods between the main and supplementary materials to make the text more accessible to general readers. We hope the editors and reviewers agree that the new manuscript is much improved in this regard.
https://www.tissue-atlas.org/atlas-datasets/lin-wang-coy-2021/
