This Editorial article was published on Biocompare.
The fact that researchers can now use CRISPR-Cas9 genetic editing to change genes with precision in single cells is reverberating out to the field of disease modeling—with advances that may soon reach therapeutics. Indeed, it may not be an understatement to say that CRISPR is revolutionizing disease modeling by speeding research into mechanisms of a wide range of diseases, as well as drug screening and therapeutics. CRISPR is valuable in studying diseases whose origins stem from mutation(s), but it’s also a powerful tool for disabling or inserting genes of interest when elucidating molecular signaling pathways, for example. Disease models are also valuable tools for preclinical studies on safety and efficacy of therapeutic drug candidates. Here’s a look at current applications of CRISPR tools in disease models.
Tools for editing and drug screening
Disease models can take many formats, including 2D cell cultures, 3D cell cultures (such as spheroids and organoids), organ chip systems, and in vivo animals models. But the early stages of CRISPR applications can be facilitated by tools for verifying editing, automation, and screening.
Molecular Devices provides a wide range of tools that support CRISPR applications. “Whether via high-speed imaging to verify monoclonality with the CloneSelect Imager (CSI), western blots analyzed on the SpectraMax i3x Multi-Mode Microplate Reader, or downstream image analysis via high-content imaging on the ImageXpress HCS.ai High-Content Screening System, scientists can confirm their edits and then track how these mutations alter cellular behavior, signaling pathways, or protein expression,” says Rebecca Kreipke, Senior Workflow Innovation and Solutions Specialist at Molecular Devices. The CSI can assess transfection efficiency, monitor cell confluence, and conduct fluorescence screening. The ability to confirm that CRISPR edits have been successfully performed allows researchers to progress confidently. “Researchers are enabled to more quickly make data-driven decisions about which cell lines to move forward with, whether developing cell and gene therapies or biologically relevant models,” says Kreipke.
Testing drug compounds for therapeutic drugs at large scales is a laborious process for which labs are increasingly turning to automation. Drug screening on high-throughput platforms can make quick work of drug candidates to find the promising few that go on to clinical trials. “Our CellXpress.ai Automated Cell Culture System allows for the automation of the entire cell culture and drug screening workflow,” says Kreipke. “By providing reproducible, assay-ready plates with well-characterized cell lines for experiment after experiment, the CellXpress.ai system relieves valuable scientists of the burden of laborious manual cell culture, as well as improves data quality by ensuring the starting screening material is consistent from experiment to experiment.” The system also provides automated, real-time monitoring of cellular responses to drugs for studying toxicity, off-target effects, and therapeutic efficacy.
Precision cell lines
EditCo Bio uses CRISPR-Cas9 to engineer precise genetic modifications in cell lines used to construct models of genetic diseases, neurodegenerative disorders, and cancer. “For example, we have used CRISPR to introduce clinically relevant KRAS mutations, such as KRAS-G12D or KRAS-G12C, into human pancreatic ductal epithelial cells and lung epithelial cells,” says Montse Morell, Director of Scientific Development at EditCo Bio. “These isogenic models allow researchers to study KRAS-driven tumorigenesis, assess downstream signaling pathways, and evaluate targeted therapies such as KRAS inhibitors.”
The improved ability to replicate mutations associated with diseases allows them to investigate underlying disease mechanisms. “Our KRAS-mutant cell models have enabled researchers to dissect how oncogenic KRAS drives aberrant signaling in the MAPK and PI3K pathways, leading to uncontrolled proliferation and resistance to apoptosis,” Morell says. “These models are also crucial for drug screening, particularly for testing the efficacy of emerging KRAS inhibitors.” Edited cell lines are also used to identify signaling components used by KRAS-mutant cancers. Knocking out or inactivating these signals may render a cancer more vulnerable, boosting the efficacy of cancer treatments.
CRISPR in spheroids and organoids
Disease models are made more powerful by closely replicating in vivo conditions. Recent advances in 3D culture systems—such as spheroids and organoids—offer new possibilities for CRISPR targets. “One major advantage is the ability to introduce disease-specific mutations directly into patient-derived or stem cell-derived organoids, preserving the cellular heterogeneity and microenvironmental cues that are often lost in traditional 2D cultures,” says Morell. “For example, CRISPR-edited intestinal organoids carrying CFTR mutations have been instrumental in cystic fibrosis research, allowing scientists to test small-molecule correctors and modulators in a physiologically relevant system.”
Indeed, the combination of precise CRISPR gene editing with 3D cell cultures are likely to revolutionize disease modeling in multiple ways, according to Kreipke, “including generating more accurate disease models and studying increasingly complex disease mechanisms,” she says. The availability of more biologically relevant models of disease will mean fewer expensive drug failures (thus lowering the costs of drugs that do reach markets), and shorter timelines for drug development, both of which Kreipke notes will be facilitated by CRISPR gene editing of spheroids and organoids. “By using CRISPR to correct a disease-causing mutation in patient-derived cells, researchers can create genetically matched healthy and diseased organoids, reducing variability in experiments,” she says.
CRISPR in liver disease models
DefiniGEN studies monogenic liver diseases using CRISPR and induced pluripotent stem cells (iPSCs). After introducing CRISPR-based mutations into iPSCs, DefiniGEN differentiates them into hepatocytes that form phenotypically relevant models of liver disease. The mutations can then be studied to investigate pathogenic mechanisms, identify therapeutic targets, or screen drug candidates.
For example, DefiniGEN used CRISPR technology to develop a disease model for alpha-1-antitrypsin (A1AT) deficiency. This genetic disorder is caused by impaired production of A1AT, a protease inhibitor that protects the lungs and liver. Mutations in A1AT cause the protein to misfold and accumulate in the endoplasmic reticulum. “Combining the opportunities that iPSC-derived hepatocytes and CRISPR/Cas9 offer, we have developed a cell platform that recapitulates the disease phenotype in a dish, with increased intracellular accumulation of misfolded A1AT in the diseased cells,” says Nikolaos Nikolaou, Head of R&D at DefiniGEN. “DefiniGEN offers this cell model (either as cryopreserved hepatocytes or in-house service) for the large-scale screening of novel therapeutics against A1AT deficiency, including small compounds and RNA-based delivery systems.”
Another powerful characteristic of DefiniGEN’s system is the ability to generate isogenic cell pairs differing in a single genetic change, and to compare disease models derived from each. For example, they can compare liver models created from healthy iPSCs, to those containing liver disease-causing alleles; additionally, they can compare models created from patient-derived iPSCs, to isogenic controls containing disease-correcting alleles. “This allows for the large-scale characterization of the molecular and cellular phenotypes that are driven by the pathological mutation, as well as helping to track population diversity, due to the ability to employ multiple iPSC lines, in a highly controlled manner,” says Nikolaou. “This is of particular importance in drug development, as it provides valuable information on how genetic variation affects drug efficacy early in the therapeutic discovery pipelines.”
Though promising, applying CRISPR technology to organoid disease models can present technical difficulties for researchers to overcome. For example, introducing editing tools into 3D systems is more difficult compared to 2D cultures, and organoid complexity can complicate model reproducibility. But the combination remains promising. With further development of stem cell-derived organoids, their pairing with CRISPR-based genetic editing will be a sharp and powerful instrument for future complex disease modeling.
