Minimize Off-Target Effects With Precision Genome Editing
By Life Science Connect Editorial Staff
The possibilities of gene therapies to combat genetic diseases such as cancer and autoimmune disorders are ever-expanding, offering new therapeutic possibilities to treat patients with chronic conditions. Though genome editing holds immense promise for treating genetic diseases, off-target effects remain a significant concern. As a drug sponsor, it is critical to familiarize yourself with the potential negative impacts of off-target effects in gene editing while exploring different strategies for mitigating said effects. As you assess the appropriate tools to ensure the safety and efficacy of your gene therapy, consider what risk mitigation strategies and gene editing technologies are available to you and how best to implement them.
What Is An Off-Target Effect?
An on-target effect is the intended gene edit for therapeutic benefit; the opposite, an off-target effect, occurs when an unintended part of the genome is targeted and can lead to detrimental biological impacts. When making an ex vivo gene edit on a cell, off-target effects are not of high risk. However, when making an in vivo gene edit that targets your cell of interest, there is a risk of inadvertently altering the genome, which can potentially impact safety and/or efficacy. For researchers, the goal is to better understand how an off-target effect impacts overall gene expression and the biological properties of a cell.
In the FDA guidance released in January 2024 — Human Gene Therapy Products Incorporating Human Genome Editing —the health authority made a number of recommendations to help facilitate the development of gene therapies and reduce the associated risks of genome editing. This included guidelines that are common for any drug product, including characterizing identity, sterility, and purity of your drug product to limit unknowns as much as possible, but there were a variety of specific considerations as well. One recommendation specified that all aspects of the drug product, including carrier, cell type, and gene editing components like the type of gene editing technology, the enzyme used, and the guide RNAs, should be considered during development.
The FDA also advised assessing how the preclinical animal model relates to the targeted clinical populations, i.e., what similarities and differences are present in the two different genomes, as well as how much gene editing is needed to obtain the intended therapeutic effect, i.e., the therapeutic editing threshold. This relates to the durability of your gene editor of choice, including how long it lingers in the cell and its activity. Finally, in terms of manufacturing considerations for ex vivo gene therapies, the FDA recommended considering the timing of your gene editing step within the manufacturing process and ensuring scalability across your studies. Ideally, the FDA is looking for well-characterized pathways as well as clear safety and efficacy endpoints.
What Strategies Are Available For Reducing The Off-Target Effects Of Genome Editing?
Reducing off-target effects starts with screening and understanding your gene of interest (GOI), which begins with identifying every protospacer adjacent motif (PAM) sequence with your GOI and then generating guides to each of those sequences. From there, you can screen them to identify the best editors. Once you identify multiple editors, there are various tools available to look for off-target effects and then rank the editors by the severity of the off-target effects they generate.
Reducing off-target effects requires the development of strategies that can predict and detect them. There are currently several prediction software applications that can be used in silico to identify potential off-target effects, such as CasOT, Cas-OFFinder, FlashFry, and FLASH. These tools offer distinct advantages, including the ability to rapidly detect potential off-target effects. Other applications such as CCTOP and CROP can provide a score for the number of potential off-target effects. DeepCRISPR is another application, an algorithm, that considers epigenetic features when finding off-target effects. Different tools can be useful to answer distinct questions. These tools analyze guide RNA sequences that direct the enzyme to the target location in the genome and predict off-target locations. One challenge associated with prediction software is that the intranuclear environment is highly complex. While software may be focused on a 2D environment encompassed of the guide RNA and what it can bind to, sponsors must also consider the 3D epigenetic environment.
To supplement these predictive technologies, researchers can use experimental strategies that include cell-free and cell-based approaches as well as in vivo detection of off-target effects. With cell-based strategies, a sequence is inserted into double-stranded break sites that can then be enriched for deep sequences. Other experimental technologies consider larger structural changes such as chromosomal rearrangements and translocations.
At Caribou Biosciences, their team developed the chRDNA genome editing technology using a CRISPR hybrid of RNA and DNA. This proprietary tool aims to improve the precision of genome edits and significantly reduce off-target editing by adding DNA residues into the backbone of the chRNA guides, which detunes their affinity and thus limits off-target effects.
How Does CRISPR Compare To Other Gene Editing Tools?
CRISPR-Cas9 is a gene editing technology that uses a guide RNA to match a desired target gene and Cas9, which is an endonuclease that causes a double-stranded DNA break and allows modifications to the genome.1 When compared to ZFNs and TALENs, two older gene editing technologies, CRISPR offers a number of benefits, including target specificity, efficiency, and the ability to introduce multiple mutations in multiple genes at the same time.2 According to Chief Scientific Officer at Caribou Biosciences, Steve Kanner’s experience, “All technologies differ in terms of their capability of inserting a gene. We’ve found that the best one in our hands to date for gene insertion is CRISPR-Cas12a, [potentially because of its ability to] generate overhangs rather than blunt ends.”
From Life Sciences Management Consultant at Accenture, Eric Clark’s perspective, “When I was doing my PhD, everyone switched over to CRISPR to answer research questions. It is much more efficient. That’s not to say that there aren’t uses for other gene editing tools, but CRISPR has proven to be much more cost-effective.” CRISPR can target any area with a PAM site, making it a popular and versatile tool. To make it even more effective, directed evolution experiments are being conducted to develop mutations in certain domains and identify new, more efficient types of Cas enzymes.
What Is The Right Gene Editing Tool For My Project?
The gene editing tool best suited for you depends on your target outcomes. ZFNs, TALENs, and CRISPR-Cas9 can all be used for different types of gene editing, but the requisite work associated with each system differs, as do their capabilities. To identify the most appropriate tool for your project, determine your objectives: are you planning to do a gene insertion, correction, or knock out? Once your path forward is well-defined, you can determine which approach best aligns with your goals.
References
- Redman, M., King, A., Watson, C., & King, D. (2016). What is CRISPR/Cas9?. Archives of disease in childhood. Education and practice edition, 101(4), 213–215. https://doi.org/10.1136/archdischild-2016-310459
- Pros and cons of ZFNs, Talens, and CRISPR/Cas . The Jackson Laboratory. (n.d.). https://www.jax.org/news-and-insights/jax-blog/2014/march/pros-and-cons-of-znfs-talens-and-crispr-cas
Interested in learning more about how to reduce off-target effects in genome editing? Watch a webinar on the topic here.