ABSTRACT
Transcription factors (TFs) regulate gene programs, thereby controlling diverse cellular processes and cell states. To comprehensively understand TFs and the programs they control, we created a barcoded library of all annotated human TF splice isoforms (>3,500) and applied it to build a TF Atlas charting expression profiles of human embryonic stem cells (hESCs) overexpressing each TF at single-cell resolution. We mapped TF-induced expression profiles to reference cell types and validated candidate TFs for generation of diverse cell types, spanning all three germ layers and trophoblasts. Targeted screens with subsets of the library allowed us to create a tailored cellular disease model and integrate mRNA expression and chromatin accessibility data to identify downstream regulators. Finally, we characterized the effects of combinatorial TF overexpression by developing and validating a strategy for predicting combinations of TFs that produce target expression profiles matching reference cell types to accelerate cellular engineering efforts.
Subject(s)
Cell Differentiation , Transcription Factors , Humans , Chromatin , Gene Expression Regulation , Human Embryonic Stem Cells/metabolism , Transcription Factors/metabolism , Atlases as TopicABSTRACT
The cellular processes that govern tumor resistance to immunotherapy remain poorly understood. To gain insight into these processes, here we perform a genome-scale CRISPR activation screen for genes that enable human melanoma cells to evade cytotoxic T cell killing. Overexpression of four top candidate genes (CD274 (PD-L1), MCL1, JUNB, and B3GNT2) conferred resistance in diverse cancer cell types and mouse xenografts. By investigating the resistance mechanisms, we find that MCL1 and JUNB modulate the mitochondrial apoptosis pathway. JUNB encodes a transcription factor that downregulates FasL and TRAIL receptors, upregulates the MCL1 relative BCL2A1, and activates the NF-κB pathway. B3GNT2 encodes a poly-N-acetyllactosamine synthase that targets >10 ligands and receptors to disrupt interactions between tumor and T cells and reduce T cell activation. Inhibition of candidate genes sensitized tumor models to T cell cytotoxicity. Our results demonstrate that systematic gain-of-function screening can elucidate resistance pathways and identify potential targets for cancer immunotherapy.
