Project description:BackgroundGenome-wide association studies (GWAS) have identified > 200 loci associated with breast cancer risk. The majority of candidate causal variants are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association, and identifying the phenotype it mediates, is a major challenge in the interpretation and translation of GWAS.ResultsHere, we show that pooled CRISPR screens are highly effective at identifying GWAS target genes and defining the cancer phenotypes they mediate. Following CRISPR mediated gene activation or suppression, we measure proliferation in 2D, 3D, and in immune-deficient mice, as well as the effect on DNA repair. We perform 60 CRISPR screens and identify 20 genes predicted with high confidence to be GWAS targets that promote cancer by driving proliferation or modulating the DNA damage response in breast cells. We validate the regulation of a subset of these genes by breast cancer risk variants.ConclusionsWe demonstrate that phenotypic CRISPR screens can accurately pinpoint the gene target of a risk locus. In addition to defining gene targets of risk loci associated with increased breast cancer risk, we provide a platform for identifying gene targets and phenotypes mediated by risk variants.
Project description:Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association, and identifying the phenotype it mediates, is a major challenge in the interpretation and translation of GWAS.
Project description:Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association, and identifying the phenotype it mediates, is a major challenge in the interpretation and translation of GWAS.
Project description:Genome-wide association studies (GWAS) have identified >200 loci associated with breast cancer (BC) risk. The majority of candidate causal variants (CCVs) are in non-coding regions and likely modulate cancer risk by regulating gene expression. However, pinpointing the exact target of the association, and identifying the phenotype it mediates, is a major challenge in the interpretation and translation of GWAS.
Project description:Metastasis is the main death reason for triple-negative breast cancer (TNBC). Thus, identifying the driver genes associated with metastasis of TNBC is urgently needed. CRISPR screens have dramatically enhanced genome editing and made it possible to identify genes associated with metastasis. In this study, we identified and explored the crucial role of ras homolog family member V (RhoV) in TNBC metastasis. Here, we performed customized in vivo CRISPR screens targeting metastasis-related genes obtained from transcriptome analysis of TNBC. The regulatory role of RhoV in TNBC was validated using gain- or loss-of-function studies in vitro and in vivo. We further conducted immunoprecipitation and LC-MS/MS to explore the metastasis mechanism of RhoV. In vivo functional screens identified RhoV as a candidate regulator involved in tumor metastasis. RhoV was frequently upregulated in TNBC and correlated with poor survival. Knockdown of RhoV significantly suppressed cell invasion, migration, and metastasis both in vitro and in vivo. In addition, we provided evidence that p-EGFR interacted with RhoV to activate the downstream signal pathway of RhoV, thereby promoting tumor metastasis. We further confirmed that this association was dependent on GRB2 through a specific proline-rich motif in the N-terminus of RhoV. This mechanism of RhoV is unique, as other Rho family proteins lack the proline-rich motif in the N-terminus.
Project description:Cancer genomics studies have identified thousands of putative cancer driver genes1. Development of high-throughput and accurate models to define the functions of these genes is a major challenge. Here we devised a scalable cancer-spheroid model and performed genome-wide CRISPR screens in 2D monolayers and 3D lung-cancer spheroids. CRISPR phenotypes in 3D more accurately recapitulated those of in vivo tumours, and genes with differential sensitivities between 2D and 3D conditions were highly enriched for genes that are mutated in lung cancers. These analyses also revealed drivers that are essential for cancer growth in 3D and in vivo, but not in 2D. Notably, we found that carboxypeptidase D is responsible for removal of a C-terminal RKRR motif2 from the α-chain of the insulin-like growth factor 1 receptor that is critical for receptor activity. Carboxypeptidase D expression correlates with patient outcomes in patients with lung cancer, and loss of carboxypeptidase D reduced tumour growth. Our results reveal key differences between 2D and 3D cancer models, and establish a generalizable strategy for performing CRISPR screens in spheroids to reveal cancer vulnerabilities.
