Highlights d A single-cell EC atlas of healthy murine tissues d This study provides an interactive webtool for comparative analyses and data exploration d Characterization of inter-and intra-tissue EC heterogeneity d Discovery tool for characterization of ECs in other datasets

Colon cancer is a clinically diverse disease. This heterogeneity makes it difficult to determine which patients will benefit most from adjuvant therapy and impedes the development of new targeted agents. More insight into the biological diversity of colon cancers, especially in relation to clinical features, is therefore needed. We demonstrate, using an unsupervised classification strategy involving over 1,100 individuals with colon cancer, that three main molecularly distinct subtypes can be recognized. Two subtypes have been previously identified and are well characterized (chromosomal-instable and microsatellite-instable cancers). The third subtype is largely microsatellite stable and contains relatively more CpG island methylator phenotype-positive carcinomas but cannot be identified on the basis of characteristic mutations. We provide evidence that this subtype relates to sessile-serrated adenomas, which show highly similar gene expression profiles, including upregulation of genes involved in matrix remodeling and epithelial-mesenchymal transition. The identification of this subtype is crucial, as it has a very unfavorable prognosis and, moreover, is refractory to epidermal growth factor receptor-targeted therapy.

Highlights d We single-cell RNA-sequenced 56,771 endothelial cells (ECs) from human, mouse, and cultured lung tumor models d Tip ECs were resolved into migratory and basementmembrane remodeling phenotypes d Capillary and venous ECs expressed immunoregulatory gene signatures d Integrated analysis identified collagen modification as an angiogenic pathway

Highlights d Single-cell RNA-seq reveals EC heterogeneity in choroidal neovascularization d ECs display metabolic transcriptome heterogeneity in the cell cycle and quiescence d Data integration with a genome-scale metabolic model identifies angiogenic targets d SQLE and ALDH18A1 are validated as metabolic angiogenic candidates

In the original article, the surname of co-author Wouter Everaerts was spelled incorrectly as "Everaert." It appears correctly in this Correction, and the error has been corrected online.