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Paired CRISPR screens to map gene regulation in cis and trans (ATAC-seq)

ABSTRACT: In this study, we develop a scalable approach that pairs discovery of cis- and trans-acting elements to systematically decipher the gene regulatory network. We explore the regulation of the immune checkpoint PD-L1 under both basal and IFNγ-stimulated contexts. PD-L1 expression on tumor cells serves as a clinically-actionable diagnostic for immune checkpoint blockade therapy across multiple cancer types.

ORGANISM(S): Homo sapiens

PROVIDER: GSE255698 | GEO | 2024/11/28

REPOSITORIES: GEO

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			Action	DRS
		Other
	GSE255698_BxPC3_ATAC_NoIFNy.bw	Other
	GSE255698_BxPC3_ATAC_NoIFNy_peaks.narrowPeak.gz	Bed
	GSE255698_BxPC3_ATAC_PlusIFNy.bw	Other
	GSE255698_BxPC3_ATAC_PlusIFNy_peaks.narrowPeak.gz	Bed

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Paired CRISPR screens to map gene regulation in cis and trans (HiChIP)

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Characterizing the molecular regulation of inhibitory immune checkpoints with multi-modal single-cell screens.

Project description:The expression of inhibitory immune checkpoint molecules such as PD-L1 is frequently observed in human cancers and can lead to the suppression of T-cell mediated immune responses. Here we apply ECCITE-seq, a technology which combines pooled CRISPR screens with single-cell mRNA and surface protein measurements, to explore the molecular networks that regulate PD-L1 expression. We also develop a computational framework, mixscape, that substantially improves the signal-to-noise ratio in single-cell perturbation screens by identifying and removing confounding sources of variation. Applying these tools, we identify and validate regulators of PD-L1, and leverage our multi-modal data to identify both transcriptional and post-transcriptional modes of regulation. In particular, we discover that the kelch-like protein KEAP1 and the transcriptional activator NRF2, mediate levels of PD-L1 upregulation after IFNγ stimulation. Our results identify a novel mechanism for the regulation of immune checkpoints and present a powerful analytical framework for the analysis of multi-modal single-cell perturbation screens.

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