We propose a new method for determining the target genes of transcriptional enhancers in specific cells and tissues. It combines global trends across many samples and sample-specific information, and considers the joint effect of multiple enhancers. Our method outperforms existing methods when predicting the target genes of enhancers in unseen samples, as evaluated by independent experimental data. Requiring few types of input data, we are able to apply our method to reconstruct the enhancer-target networks in 935 samples of human primary cells, tissues and cell lines, which constitute by far the largest set of enhancer-target networks. The similarity of these networks from different samples closely follows their cell and tissue lineages. We discover three major co-regulation modes of enhancers and find defense-related genes often simultaneously regulated by multiple enhancers bound by different transcription factors. We also identify differentially methylated enhancers in hepatocellular carcinoma (HCC) and experimentally confirm their altered regulation of HCC-related genes.

ENCODE comprises thousands of functional genomics datasets, and the encyclopedia covers hundreds of cell types, providing a universal annotation for genome interpretation. However, for particular applications, it may be advantageous to use a customized annotation. Here, we develop such a custom annotation by leveraging advanced assays, such as eCLIP, Hi-C, and whole-genome STARR-seq on a number of data-rich ENCODE cell types. A key aspect of this annotation is comprehensive and experimentally derived networks of both transcription factors and RNA-binding proteins (TFs and RBPs). Cancer, a disease of system-wide dysregulation, is an ideal application for such a network-based annotation. Specifically, for cancer-associated cell types, we put regulators into hierarchies and measure their network change (rewiring) during oncogenesis. We also extensively survey TF-RBP crosstalk, highlighting how SUB1, a previously uncharacterized RBP, drives aberrant tumor expression and amplifies the effect of MYC, a well-known oncogenic TF. Furthermore, we show how our annotation allows us to place oncogenic transformations in the context of a broad cell space; here, many normal-to-tumor transitions move towards a stem-like state, while oncogene knockdowns show an opposing trend. Finally, we organize the resource into a coherent workflow to prioritize key elements and variants, in addition to regulators. We showcase the application of this prioritization to somatic burdening, cancer differential expression and GWAS. Targeted validations of the prioritized regulators, elements and variants using siRNA knockdowns, CRISPR-based editing, and luciferase assays demonstrate the value of the ENCODE resource.

Despite the remarkable success and efficacy of immune checkpoint blockade (ICB) therapy against the PD-1/PD-L1 axis, it induces sustained responses in a sizeable minority of cancer patients due to the activation of immunosuppressive factors such as myeloid-derived suppressor cells (MDSCs). Inhibiting the immunosuppressive function of MDSCs is critical for successful cancer ICB therapy. Interestingly, lipid metabolism is a crucial factor in modulating MDSCs function. Fatty acid transport protein 2 (FATP2) conferred the function of PMN-MDSCs in cancer via the upregulation of arachidonic acid metabolism. However, whether regulating lipid accumulation in MDSCs by targeting FATP2 could block MDSCs reactive oxygen species (ROS) production and enhance PD-L1 blockade-mediated tumor immunotherapy remains unexplored. Here we report that FATP2 regulated lipid accumulation, ROS, and immunosuppressive function of MDSCs in tumor-bearing mice. Tumor cells-derived granulocyte macrophage-colony stimulating factor (GM-CSF) induced FATP2 expression in MDSCs by activation of STAT3 signaling pathway. Pharmaceutical blockade of FATP2 expression in MDSCs by lipofermata decreased lipid accumulation, reduced ROS, blocked immunosuppressive activity, and consequently inhibited tumor growth. More importantly, lipofermata inhibition of FATP2 in MDSCs enhanced anti-PD-L1 tumor immunotherapy via the upregulation of CD107a and reduced PD-L1 expression on tumorinfiltrating CD8 + T-cells. Furthermore, the combination therapy blocked MDSC's suppressive role on Tcells thereby enhanced T-cell's ability for the production of IFN-γ. These findings indicate that FATP2 plays a key role in modulating lipid-induced ROS in MDSCs and targeting FATP2 in MDSCs provides a novel therapeutic approach to enhance anti-PD-L1 cancer immunotherapy.

Highlights d Catalytic activity of G9a but not H3K9me2 functions in maintaining DNA methylation d G9a regulates chromatin states and transcription through distinct mechanisms d G9a maintains chromatin loops and TADs boundary strengths d H3K9me2 prevents aberrant CTCF and cohesin binding, particularly at retrotransposons

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