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: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 ?-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.
Project description:Immune checkpoint inhibitors exhibit limited response rates in patients with triple-negative breast cancer (TNBC), suggesting that additional immune escape mechanisms may exist. Here, we performed two-step customized in vivo CRISPR screens targeting disease-related immune genes using different mouse models with multidimensional immune-deficiency characteristics. In vivo screens characterized gene functions in the different tumor microenvironments and recovered canonical immunotherapy targets such as Ido1. In addition, functional screening and transcriptomic analysis identified Lgals2 as a candidate regulator in TNBC involving immune escape. Mechanistic studies demonstrated that tumor cell-intrinsic Lgals2 induced the increased number of tumor-associated macrophages, as well as the M2-like polarization and proliferation of macrophages through the CSF1/CSF1R axis, which resulted in the immunosuppressive nature of the TNBC microenvironment. Blockade of LGALS2 using an inhibitory antibody successfully arrested tumor growth and reversed the immune suppression. Collectively, our results provide a theoretical basis for LGALS2 as a potential immunotherapy target in TNBC.
