Dataset Information

CRISPR screens identify PRMT7 as a therapeutic target to enhance T cell-mediated killing in breast cancer

ABSTRACT: Genome-wide association studies (GWAS) have identified more than 220 loci associated with breast cancer susceptibility, yet identifying effector genes, their modes of action and prioritising therapeutic targets remains a significant challenge. To address this, we performed pooled CRISPR knockout and inhibition screens to identify genes at risk loci that influence cytotoxic T lymphocyte (CTL) killing of MCF7 breast cancer cells in co-culture. These screens uncovered 33 candidate modulating genes, of which we validated six by single gene editing in two cell lines. Deletion of IRF1, ATF7IP, and CASP8 conferred resistance to CTL killing, while disruption of CFLAR, CREBBP and PRMT7 enhanced sensitivity. Analysis of clinical data showed that PRMT7 expression is negatively correlated with CD8+ infiltration and survival in breast cancer patient cohorts. Pharmacological inhibition of PRMT7 sensitized breast cells to CTL killing in vitro, and Prmt7-deficient tumors exhibited reduced growth and increased CD8+ T cell infiltration in immunocompetent mice. Enhanced Prmt7-dependent tumor growth was not observed in immunodeficient mice, implicating Prmt7 in immune evasion. This study underscores the utility of CRISPR screens for high-throughput functional follow-up of GWAS findings and identifies PRMT7 inhibition as a promising therapeutic strategy.

ORGANISM(S): Homo sapiens

PROVIDER: GSE316985 | GEO | 2026/02/18

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Purpose: RNA-sequencing analysis defined a novel role for PRMT7 in melanoma cancer immunotherapy. Methods: PRMT7-deficient cells and control B16.F10 cells treated with mIFN-γ (100ng/ml) for 24 hours. B16.F10 melanoma cells mRNA profiles were generated by deep sequencing, in triplicate using TruSeq Stranded mRNA Sample Prep Kit with TruSeq Unique Dual Indexes (Illumina, Hiseq4000, SR75 platform located at San Diego, CA; UCSD IGM Genomics Facility, La Jolla, CA). Resulting libraries were multiplexed and sequenced with 100 base pair (bp) to a depth of approximately 30 million reads per sample. The sequence reads that passed quality filters were trimmed with Trimmomatic v0.39. STAR v2.7.1a was then used to align the reads to the mouse genome (mm10/GRCm38). Gene expression was quantified across all samples with HOMER v4.11.1, and the normalization was carried out through the regularized logarithm (rlog) transformation of DESeq2 v1.26.0. Differential expression between PRMT7 WT and knockdown samples were calculated through DESeq2 v1.26.0, and the gene expression was considered significantly different if the absolute value of the log-fold-change (LFC) was higher than 2, the base means larger than 10 and the false discovery rate (FDR) less than 0.05. Results: Differential expression analysis between the siLuc and siPRMT7 conditions yielded 185 and 251 genes with statistically significant differences and absolute fold change greater than 2 in the IFN– and IFN+ treatments respectively. Of these, 85% of genes are upregulated in the IFN– treatment, while 72% of genes are downregulated in the IFN+ treatment. Gene ontology analysis using the 185 and 251 lists of differentially expressed genes implies that the downregulated biological processes are enriched for the immune response pathways, while upregulated genes are more involved in the cell cycle process. Altered expression of some genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to better understand PRMT7 function in cancer immunotherapy. Conclusions: Our study represents the first detailed analysis of B16.F10 melanoma transcriptomes without PRMT7 expression, with biologic replicates, generated by RNA-seq technology. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of PRMT7 biologic functions in modulating melanoma transcriptome.

Dataset Information

CRISPR screens identify PRMT7 as a therapeutic target to enhance T cell-mediated killing in breast cancer

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets