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The vascular landscape of human cancer
Benjamin M. Kahn, … , Robert B. Faryabi, Ben Z. Stanger
Benjamin M. Kahn, … , Robert B. Faryabi, Ben Z. Stanger
Published December 1, 2020
Citation Information: J Clin Invest. 2021;131(2):e136655. https://doi.org/10.1172/JCI136655.
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Research Article Angiogenesis Oncology Article has an altmetric score of 25

The vascular landscape of human cancer

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Abstract

Tumors depend on a blood supply to deliver oxygen and nutrients, making tumor vasculature an attractive anticancer target. However, only a fraction of patients with cancer benefit from angiogenesis inhibitors. Whether antiangiogenic therapy would be more effective if targeted to individuals with specific tumor characteristics is unknown. To better characterize the tumor vascular environment both within and between cancer types, we developed a standardized metric — the endothelial index (EI) — to estimate vascular density in over 10,000 human tumors, corresponding to 31 solid tumor types, from transcriptome data. We then used this index to compare hyper- and hypovascular tumors, enabling the classification of human tumors into 6 vascular microenvironment signatures (VMSs) based on the expression of a panel of 24 vascular “hub” genes. The EI and VMS correlated with known tumor vascular features and were independently associated with prognosis in certain cancer types. Retrospective testing of clinical trial data identified VMS2 classification as a powerful biomarker for response to bevacizumab. Thus, we believe our studies provide an unbiased picture of human tumor vasculature that may enable more precise deployment of antiangiogenesis therapy.

Authors

Benjamin M. Kahn, Alfredo Lucas, Rohan G. Alur, Maximillian D. Wengyn, Gregory W. Schwartz, Jinyang Li, Kathryn Sun, H. Carlo Maurer, Kenneth P. Olive, Robert B. Faryabi, Ben Z. Stanger

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Figure 4

Signaling pathways and VMSs in cancer.

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Signaling pathways and VMSs in cancer.
(A) The signaling pathways most e...
(A) The signaling pathways most enriched in highly vascular tumors are shown. Bubble plot displays the pathways most significantly enriched in hypervascular tumors (90th percentile EI score) derived from GSEA (comparison of hyper- versus hypovascular tumors across 31 cancer types). All pathways listed as “signaling” were included in the analysis. Cancers are color-coded, and the size of each bubble represents the strength of association between the indicated signaling pathway and vascularity in the indicated cancer type [–log10(FDR)]. (B) Unsupervised clustering of 10,767 solid tumors based on the expression of 24 vascularity network hub genes identified 6 VMSs (VMS1–VMS6). The color displayed for each of the 24 genes in the heatmap represents the gene expression value after normalization by both row (all tumors) and column (col) (all hub genes). Marked over- or underexpression of either VEGFA, CDH1, NOTCH3, or MMP9 was characteristic of individual VMSs. Normalized levels of these genes are displayed as box plots (0 represents the normalized baseline level of this gene across cancers, the center line marks the median, box limits span the IQR, and whiskers extend to 1.5 times the IQR). min, minimum; max, maximum. The expression levels of these genes were compared across all 6 subtypes, and significant differences were detected by Kruskal-Wallis rank-sum test. Significance of the over- or underexpression of these genes in specific subtypes was tested by pairwise multiple comparisons with a Benjamini-Hochberg–adjusted post hoc Conover’s test P value (***P < 0.001).

Copyright © 2025 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

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