Data Reproducibility for the Development of Safer Gene Therapies
App Note / Case Study
Published: August 16, 2023
Immunogenicity is a key consideration in the development of safe gene therapy products. In fact, certain product components can cause unintended immune responses with life-threatening implications if not addressed.
Reproducible quantitation of gene expression can help researchers investigate potential sources of vector-induced immunotoxicity. Hence, data reproducibility is a cornerstone of safe therapeutic development.
This application note highlights a robust and reliable qPCR-based approach to reproducible data generation with significant insights for vector design.
Download this application note to discover:
Potential sources of immunotoxicity in gene therapy products
How gene expression data can inform vector design
Ways to minimize experimental error and support data concordance
Importance of data reproducibility for development of safe gene therapies Gene expression analysis Introduction After decades of research, viral-based vectors have now become an integral part of clinically approved gene therapies. Delivering and inserting genes into the host genome are natural behaviors of viruses and are cornerstones of gene therapy. However, viral infection can also provoke deleterious immune responses. In gene therapy, a virusinduced immune reaction can interfere with gene transfer, destroy the functional transgene product, eliminate transduced cells, or even threaten the life of the gene therapy recipient. [1,2,3] Consequently, evading unintended immune responses is a primary obstacle in ensuring the safety as well as the efficacy of gene therapies. Understanding the interplay among gene therapy vector components and deleterious immune responses may be especially important in developing safer gene therapies. Immune response in gene therapy Several studies have revealed that many components of gene therapy can cause or influence both innate and adaptive immune responses. [1,4] Immunogenic factors may include the route of vector administration, the target tissue, specific vector components, the viral strain, capsid structure, viral DNA or RNA, vector dose, viral-encoded proteins, impurities, the transgene product itself, or downstream effects. The first immune response, occurring within a few hours following vector transfer, is the innate immune secretion of inflammatory cytokines around the therapeutic administration site. If the innate reaction is too aggressive, adverse effects can occur ranging from mild flu-like symptoms to multiple-organ failure. Within a few days after vector administration, the innate immune response gives way to the adaptive immune response.  The adaptive immune response leads to long-term immunity, which can present multiple safety challenges for gene therapy. Recombinant adeno-associated virus (rAAV) vectors comprising viral capsid proteins, the vector DNA expression cassette, and products generated by it can themselves be immunogenic due to their interaction with toll-like receptors (TLRs), which recognize specific conserved signatures (pathogen-associated molecular pattens, PAMPs).  Different TLRs recognize specific PAMPs. For example, TLR2 recognizes ligands on rAAV capsids at the cell membrane, and TLR3, TLR7, TLR8, and TLR9 sense the AAV genome at different stages of transcription. An immune response launched by TLRs can block expression of the therapeutic transgene and present risks of adverse immune reactions.  Engineering rAAV vectors with altered genetic sequences to modify TLR PAMPs may offer approaches to mitigate TLR-initiated immune response and advance understanding of gene therapy safety. In this application note we: • Introduce the importance of reproducible quantitation of gene expression to investigate potential sources of vector-induced immunotoxicity in gene therapy • Demonstrate reproducibility of measuring gene expression across multiple Applied Biosystems™ QuantStudio™ 7 Pro Real-Time Systems using the Applied Biosystems™ TaqMan® Array Human Inflammation Panel • Demonstrate reproducibility of measuring gene expression from well-to-well and across multiple 96-well plates and across multiple 384-well Applied Biosystems™ TaqMan® Array CardsGene expression analysis to investigate immune response Due to the paramount importance of ensuring safety across multiple populations and the complexity of developing a new gene therapy product, gene therapy studies can grow into large collaborations among multiple research teams in different geographic areas. For example, in October 2021, the US FDA, US NIH, ten pharmaceutical companies, and five non-profit organizations partnered to accelerate development of gene therapies for rare diseases  When even gathering enough data for a comprehensive study requires such extraordinary efforts, experimental reproducibility across all sites is essential for the researchers to trust the results. Robust and reliable technologies must be used to generate study data that provides researchers with confidence to draw conclusions. Here, using quantitative real-time PCR (qPCR) to evaluate the expression of 90 inflammation-associated genes and six reference genes, we show how this genetic technology can be used to investigate immune responses. Gene expression analysis using qPCR is a reliable, sensitive, and reproducible approach to quantify transgene expression and investigate the potential sources of immunotoxicity in gene therapy such as viral genes, adventitious contaminants, therapy-induced tissue damage, and off-target activity. The data presented here show excellent well-towell and instrument-to-instrument data concordance in the QuantStudio 7 Pro Real-Time PCR System, demonstrating the robustness of the platform and the assays. Methods We tested the reproducibility of measuring gene expression on the QuantStudio 7 Pro Real-Time PCR System using the TaqMan Array Human Inflammation Panel. This panel consists of 96 TaqMan Assays that encompass the 90 inflammation-associated and six reference (housekeeping) genes pre-spotted and dried down into either 96-well plates or 384-well TaqMan Array Cards. In separate preparations, we synthesized cDNA from 10 ng and 100 ng of universal human reference (UHR) RNA using Invitrogen™ SuperScript™ VILO™ Master Mix. 384-well TaqMan Array Cards were spotted in quadruplicate so that four samples could be run simultaneously. PCR was done using Applied Biosystems™ TaqMan® Fast Advanced™ Master Mix and cycled according to standard protocols. Analysis of resulting Cq values was performed using Applied Biosystems™ QuantStudio™ Design and Analysis Software using default baseline calling values. Further analysis was performed in Microsoft™ Excel™ or SAS JMP™ software.
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