Machine learning identifies activation of RUNX/AP-1 as drivers of mesenchymal and fibrotic regulatory programs in gastric cancer

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Figure 8.
Figure 8.

Summary of TFs driving GC epigenomic heterogeneity and EMT. (A) Differentially active TFs in Mes-like and Epi-like GC cell lines. (B) DNA CN changes in Mes-like and Epi-like GC cell lines. (C) Mes-like GC has a high correlation of expression and distal enhancer activity with fibroblasts, whereas Epi-like GC is more similar to the stomach. (D) Mes-like GC TF response and chromatin profile are different from that of fibroblasts, despite the shared patterns of expression and chromatin accessibility.

This Article

  1. Genome Res. 34: 680-695

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