New approaches to vector design could boost the efficacy of gene therapy and reducing dosages, while the identification of robust, predictive biomarkers could help determine patients mostly likely to respond.Credit: Getty Images
Genetic research has the power to completely change the treatment of certain conditions. Take haemophilia B: Patients with this condition don’t produce functional Factor IX (FIX), a clotting protein. In severe cases, patients can experience spontaneous bleeding in muscles, joints and the central nervous system. Treatment used to require regular injections of FIX preparations, but it’s now possible to use gene therapy to empower the patient’s cells to express their own protein.
The turning point came in 2014, when researchers at University College London and St Jude’s Children’s Research Hospital, in Memphis, reported that they had achieved sustained expression of FIX, albeit at very low levels.1 It was what researchers had been waiting for since the first publication of the human genome: gene therapy for a genetic condition. But seven years on, gene therapy hasn’t become as widely used as many had hoped. Currently, it’s only available for a limited number of conditions and, even in those cases, not all the kinks have been ironed out.
In a study of gene therapy for X-linked myotubular myopathy, patients required high doses of the adeno-associated viral (AAV) vector to ensure that enough genetic material could reach the skeletal muscle cells. But AAV has a natural affinity for liver cells, and three clinical trial participants with pre-existing liver conditions died when given the high dose.
“The minute investigators push the envelope and aim for very high doses, the chance of liver inflammation increases,” says Thierry VandenDriessche, director of the Department of Gene Therapy and Regenerative Medicine at the Vrije Universiteit Brussel in Belgium.
Challenges also remain with haemophilia B. VandenDriessche and other researchers have been able to lower the dose of delivery vector by using an overactive variant of the FIX gene, named FIX Padua—after the city in which it was identified.2 This reduced the risk of liver inflammation, but other unexpected problems have come to light. A recent clinical trial of a specific type of AAV vector expressing FIX Padua found that, in seven out of eight patients, FIX expression was lost within a few months.3 This hadn’t been a problem in animal models, and appeared to be related to an immune response triggered by the vector.
Such cases illustrate the importance of translational research when moving from discovery to practice. If gene therapy is to become widespread, scientists need a better fundamental understanding of what makes it successful. Improvements include a more efficient delivery vector and biomarkers to predict short- and long-term efficacy along with side effect profiles. Pairing gene therapy research with a wider drug development platform and broad preclinical expertise could help avoid some of these issues—and offer opportunities for improvement.
Improving the delivery vectors
Viruses are common gene delivery vectors. They can readily infect cells and deliver their genetic cargo. For successful gene therapy, vectors need to selectively target the right cells and tissues, and the transgene needs to be expressed at the right levels. It’s a delicate balance, and difficult to achieve.
“I have seen gene therapy fail miserably,” says Friedrich Scheiflinger, Head of Gene Therapy at Evotec, a drug discovery alliance and development partnership company, referring to the early days of gene therapy, 20 years ago. “Vectors got much better,” he continues. “The regulatory elements have improved, and therapies are better targeted.”
Scheiflinger and his colleagues have been developing gene therapy product candidates for years, initially at Baxter, later at Takeda and now at Evotec’s Gene Therapy group in Orth an der Donau, Austria.
One research area they’re pursuing is the development of better vectors. “We take on projects that deal with improving the gene therapy technology,” says Hanspeter Rottensteiner, Evotec’s Head of In Vitro Gene Therapy. This involves a range of preclinical work, such as investigating where vectors end up in the body, comparing candidate vectors and overseeing animal studies. For this type of work, Scheiflinger and Rottensteiner often collaborate with partners on specific gene therapy programmes.
For example, while still at Takeda, they worked with VandenDriessche and his colleague Marinee Chuah to further optimize the vector for FIX.4 VandenDriessche and Chuah’s research had previously identified a small stretch of nucleotides that increases gene expression, specifically in hepatocytes.5 The idea was to combine this ‘turbocharger’ element with FIX Padua, packaged into an AAV, to achieve the required FIX activity with a minimal vector dose.6 The work is still in the preclinical stage, but the goal is to minimize side effects such as liver inflammation or an overactive immune response. As VandenDriessche puts it, “Let’s try to adapt the vector to the patient, and not adapt the patient to the vector.”
Biomarkers reveal patient responses
Scheiflinger and Rottensteiner have learned that one of the keys to the development of effective gene therapies is a multidisciplinary approach. They note that insights in genetic vector design need to be coupled with biomarkers that predict the clinical response and potential adverse effects. Evotec has developed methods that use unbiased platforms, such as RNAseq or global proteomics, and machine learning tools to discover such biomarkers. In cases when target organs cannot be analysed directly, researchers can evaluate more accessible specimens, such as blood or cerebrospinal fluids.
By applying those methods already in the preclinical phase and comparing outcomes from animal models that did and did not receive gene therapy, Evotec can help reveal biomarkers linked to treatment outcomes. That knowledge could aid the discovery of predictive factors that could make gene therapy safer, more customized and more predictable. For example, it would be useful to be able to identify patients with pre-existing liver conditions who could be prone to negative side effects from gene therapy.
Evotec has developed workflows based on high-throughput RNAseq and global proteomics that enable its scientists to generate large molecular databases from preclinical and clinical studies. Combining these databases with Evotec’s data analytics platform, PanHunter, empowers researchers to identify novel targets and to investigate disease mechanisms and drug modes of action.
By integrating with Evotec’s broader technologies and deep biology expertise, the gene therapy team can not only develop new vectors, but also look more broadly at whether the vector is likely to succeed. It’s a powerful drug discovery platform that, Rottensteiner says, enables a lot of preclinical work to happen “under one roof”.
As research progresses, Scheiflinger and Rottensteiner are confident that by taking a multidisciplinary approach, the benefits of gene therapy can be increased, and its risks reduced, making it a more feasible treatment option for many conditions, particularly rare diseases.
“To be able to serve a large group of patients, and provide a longer duration of treatment at an effective level, will still take quite a lot of work,” says Scheiflinger. “But with a couple of products on the market and hundreds in development, we have come a long way in the last 20 years.”