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      CRISPR-Cas9–mediated gene knockout in intestinal tumor organoids provides functional validation for colorectal cancer driver genes

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          Abstract

          Colorectal cancer (CRC) is the third leading cause of cancer-related deaths worldwide. Several genome sequencing studies have provided comprehensive CRC genomic datasets. Likewise, in our previous study, we performed genome-wide Sleeping Beauty transposon-based mutagenesis screening in mice and provided comprehensive datasets of candidate CRC driver genes. However, functional validation for most candidate CRC driver genes, which were commonly identified from both human and mice, has not been performed. Here, we describe a platform for functionally validating CRC driver genes that utilizes CRISPR-Cas9 in mouse intestinal tumor organoids and human CRC-derived organoids in xenograft mouse models. We used genetically defined benign tumor-derived organoids carrying 2 frequent gene mutations ( Apc and Kras mutations), which act in the early stage of CRC development, so that we could clearly evaluate the tumorigenic ability of the mutation in a single gene. These studies showed that Acvr1b, Acvr2a, and Arid2 could function as tumor suppressor genes (TSGs) in CRC and uncovered a role for Trp53 in tumor metastasis. We also showed that co-occurrent mutations in receptors for activin and transforming growth factor-β (TGF-β) synergistically promote tumorigenesis, and shed light on the role of activin receptors in CRC. This experimental system can also be applied to mouse intestinal organoids carrying other sensitizing mutations as well as organoids derived from other organs, which could further contribute to identification of novel cancer driver genes and new drug targets.

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          Most cited references26

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            Genome-wide recessive genetic screening in mammalian cells with a lentiviral CRISPR-guide RNA library.

            Identification of genes influencing a phenotype of interest is frequently achieved through genetic screening by RNA interference (RNAi) or knockouts. However, RNAi may only achieve partial depletion of gene activity, and knockout-based screens are difficult in diploid mammalian cells. Here we took advantage of the efficiency and high throughput of genome editing based on type II, clustered, regularly interspaced, short palindromic repeats (CRISPR)-CRISPR-associated (Cas) systems to introduce genome-wide targeted mutations in mouse embryonic stem cells (ESCs). We designed 87,897 guide RNAs (gRNAs) targeting 19,150 mouse protein-coding genes and used a lentiviral vector to express these gRNAs in ESCs that constitutively express Cas9. Screening the resulting ESC mutant libraries for resistance to either Clostridium septicum alpha-toxin or 6-thioguanine identified 27 known and 4 previously unknown genes implicated in these phenotypes. Our results demonstrate the potential for efficient loss-of-function screening using the CRISPR-Cas9 system.
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              Modeling colorectal cancer using CRISPR-Cas9-mediated engineering of human intestinal organoids.

              Human colorectal tumors bear recurrent mutations in genes encoding proteins operative in the WNT, MAPK, TGF-β, TP53 and PI3K pathways. Although these pathways influence intestinal stem cell niche signaling, the extent to which mutations in these pathways contribute to human colorectal carcinogenesis remains unclear. Here we use the CRISPR-Cas9 genome-editing system to introduce multiple such mutations into organoids derived from normal human intestinal epithelium. By modulating the culture conditions to mimic that of the intestinal niche, we selected isogenic organoids harboring mutations in the tumor suppressor genes APC, SMAD4 and TP53, and in the oncogenes KRAS and/or PIK3CA. Organoids engineered to express all five mutations grew independently of niche factors in vitro, and they formed tumors after implantation under the kidney subcapsule in mice. Although they formed micrometastases containing dormant tumor-initiating cells after injection into the spleen of mice, they failed to colonize in the liver. In contrast, engineered organoids derived from chromosome-instable human adenomas formed macrometastatic colonies. These results suggest that 'driver' pathway mutations enable stem cell maintenance in the hostile tumor microenvironment, but that additional molecular lesions are required for invasive behavior.
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                Author and article information

                Journal
                Proceedings of the National Academy of Sciences
                Proc Natl Acad Sci USA
                Proceedings of the National Academy of Sciences
                0027-8424
                1091-6490
                July 30 2019
                July 30 2019
                July 30 2019
                July 12 2019
                : 116
                : 31
                : 15635-15644
                Article
                10.1073/pnas.1904714116
                6681705
                31300537
                4f2c1e15-feb7-49cf-a868-2ee85d595616
                © 2019

                Free to read

                https://www.pnas.org/site/aboutpnas/licenses.xhtml

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