Intrauterine gene transfer (IUGT) offers ontological advantages including immune naiveté mediating tolerance to the vector and transgenic products, and effecting a cure before development of irreversible pathology. Despite proof-of-principle in rodent models, expression efficacy with a therapeutic transgene has yet to be demonstrated in a preclinical nonhuman primate (NHP) model. We aimed to determine the efficacy of human Factor IX (hFIX) expression after adeno-associated-viral (AAV)-mediated IUGT in NHP. We injected 1.0-1.95 × 10(13) vector genomes (vg)/kg of self-complementary (sc) AAV5 and 8 with a LP1-driven hFIX transgene intravenously in 0.9G late gestation NHP fetuses, leading to widespread transduction with liver tropism. Liver-specific hFIX expression was stably maintained between 8 and 112% of normal activity in injected offspring followed up for 2-22 months. AAV8 induced higher hFIX expression (P = 0.005) and milder immune response than AAV5. Random hepatocellular integration was found with no hotspots. Transplacental spread led to low-level maternal tissue transduction, without evidence of immunotoxicity or germline transduction in maternal oocytes. A single intravenous injection of scAAV-LP1-hFIXco to NHP fetuses in late-gestation produced sustained clinically-relevant levels of hFIX with liver-specific expression and a non-neutralizing immune response. These data are encouraging for conditions where gene transfer has the potential to avert perinatal death and long-term irreversible sequelae.
Lentiviral vectors with self-inactivating (SIN) long terminal repeats (LTRs) are promising for safe and sustained transgene expression in dividing as well as quiescent cells. As genome organization and transcription substantially differs between actively dividing and postmitotic cells in vivo, we hypothesized that genomic vector integration preferences might be distinct between these biological states. We performed integration site (IS) analyses on mouse dividing cells (fibroblasts and hematopoietic progenitor cells (HPCs)) transduced ex vivo and postmitotic cells (eye and brain) transduced in vivo. As expected, integration in dividing cells occurred preferably into gene coding regions. In contrast, postmitotic cells showed a close to random frequency of integration into genes and gene spare long interspersed nuclear elements (LINE). Our studies on the potential mechanisms responsible for the detected differences of lentiviral integration suggest that the lowered expression level of Psip1 reduce the integration frequency in vivo into gene coding regions in postmitotic cells. The motif TGGAA might represent one of the factors for preferred lentiviral integration into mouse and rat Satellite DNA. These observations are highly relevant for the correct assessment of preclinical biosafety studies, indicating that lentiviral vectors are well suited for safe and effective clinical gene transfer into postmitotic tissues.
Clonality analysis of viral vector-transduced cell populations represents a convincing approach to dissect the physiology of tissue and organ regeneration, to monitor the fate of individual gene-corrected cells in vivo, and to assess vector biosafety. With the decoding of mammalian genomes and the introduction of next-generation sequencing technologies, the demand for automated bioinformatic analysis tools that can rapidly process and annotate vector integration sites is rising. Here, we provide a publicly accessible, graphical user interface-guided automated bioinformatic high-throughput integration site analysis pipeline. Its performance and key features are illustrated on pyrosequenced linear amplification-mediated PCR products derived from one patient previously enrolled in the first lentiviral vector clinical gene therapy study. Analysis includes trimming of vector genome junctions, alignment of genomic sequence fragments to the host genome for the identification of integration sites, and the annotation of nearby genomic elements. Most importantly, clinically relevant features comprise the determination of identical integration sites with respect to different time points or cell lineages, as well as the retrieval of the most prominent cell clones and common integration sites. The resulting output is summarized in tables within a convenient spreadsheet and can be further processed by researchers without profound bioinformatic knowledge.
Several events of insertional mutagenesis in pre-clinical and clinical gene therapy studies have created intense interest in assessing the genomic insertion profiles of gene therapy vectors. For the construction of such profiles, vector-flanking sequences detected by inverse PCR, linear amplification-mediated-PCR or ligation-mediated-PCR need to be mapped to the host cell's genome and compared to a reference set. Although remarkable progress has been achieved in mapping gene therapy vector insertion sites, public reference sets are lacking, as are the possibilities to quickly detect non-random patterns in experimental data. We developed a tool termed QuickMap, which uniformly maps and analyzes human and murine vector-flanking sequences within seconds (available at www.gtsg.org). Besides information about hits in chromosomes and fragile sites, QuickMap automatically determines insertion frequencies in +/- 250 kb adjacency to genes, cancer genes, pseudogenes, transcription factor and (post-transcriptional) miRNA binding sites, CpG islands and repetitive elements (short interspersed nuclear elements (SINE), long interspersed nuclear elements (LINE), Type II elements and LTR elements). Additionally, all experimental frequencies are compared with the data obtained from a reference set, containing 1 000 000 random integrations ('random set'). Thus, for the first time a tool allowing high-throughput profiling of gene therapy vector insertion sites is available. It provides a basis for large-scale insertion site analyses, which is now urgently needed to discover novel gene therapy vectors with 'safe' insertion profiles.
Gene transfer of mutant O(6)-methylguanine-DNA-methyltransferase (MGMT(P140K)) into hematopoietic stem cells (HSCs) protects hematopoiesis from alkylating agents and allows efficient in vivo selection of transduced HSCs. However, insertional mutagenesis, high regenerative stress associated with selection, and the genotoxic potential of alkylating drugs represent considerable risk factors for clinical applications of this approach. Therefore, we investigated the long-term effect of MGMT(P140K) gene transfer followed by repetitive, dose-intensive treatment with alkylating agents in a murine serial bone marrow transplant model and assessed clonality of hematopoiesis up to tertiary recipients. The substantial selection pressure resulted in almost completely transduced hematopoiesis in all cohorts. Ligation-mediated PCR and next-generation sequencing identified several repopulating clones carrying vector insertions in distinct genomic regions that were ∼ 9 kb of size (common integration sites). Beside polyclonal reconstitution in the majority of the mice, we also detected monoclonal or oligoclonal repopulation patterns with HSC clones showing vector insertions in the Usp10 or Tubb3 gene. Interestingly, neither Usp10, Tubb3, nor any of the genes located in common integration sites have been linked to clonal expansion in previous preclinical or clinical gene therapy trials. However, a considerable number of these genes are involved in DNA damage response and cell fate decision pathways following cytostatic drug application. Thus, in summary, our study advocates ligation-mediated PCR and next generation sequencing as an effective and reliable method to identify gene products associated with clonal survival in specific experimental settings such as chemoselection using alkylating agents.
Nonintegrating gene delivery vectors have an improved safety profile compared with integrating vectors, but transgene retention is problematic as nonreplicating episomes are progressively and rapidly diluted out through cell division. We have developed an integration-deficient lentiviral vector (IDLV) system generating mitotically stable episomes capable of long-term transgene expression. We found that a transient cell cycle arrest at the time of transduction with IDLVs resulted in 13-45% of Chinese hamster ovary (CHO) cells expressing the transgene for over 100 cell generations in the absence of selection. The use of a scaffold/matrix attachment region did not result in improved episomal retention in this system, and episomes did not form after transduction with adeno-associated viral or minicircle vectors under the same conditions. Investigations into the episomal status of the vector genome using (1) linear amplification-mediated polymerase chain reaction followed by deep sequencing of vector-genome junctions, (2) Southern blotting, and (3) fluorescent in situ hybridization strongly suggest that the vector is not integrated in the vast majority of cells. In conclusion, we have developed an IDLV procedure generating mitotically stable episomes capable of long-term transgene expression. The application of this approach to stem cell populations could significantly improve the safety profile of a range of stem and progenitor cell gene therapies.
Summary Objective: Increasing use of retroviral vector-mediated gene transfer created intense interest to characterize vector integrations on the genomic level. Techniques to determine insertion sites, mainly based on time-consuming manual data processing, are commonly applied. Since a high variability in processing methods hampers further data comparison, there is an urgent need to systematically process the data arising from such analysis. Methods: To allow large-scale and standardized comparison of insertion sites of viral vectors we developed two programs, IntegrationSeqand IntegrationMap. IntegrationSeq can trim sequences, and valid integration sequences get further processed with IntegrationMap for automatic genomic mapping. IntegrationMap retrieves detailed information about whether integrations are located in or close to genes, the name of the gene, the exact localization in the transcriptional units, and further parameters like the distance from the transcription start site to the integration. Results: We validated the method using 259 files originating from integration site analysis (LM-PCR). Sequences processed by IntegrationSeq led to an increased yield of valid integration sequence detection, which were shown to be more sensitive than conventional analysis and 15 times faster, while the specificities are equal. Output files generated by IntegrationMap were found to be 99.8% identical with results retrieved by much slower conventional mapping with the ENSEMBL alignment tool. Conclusion: Using IntegrationSeq and IntegrationMap, a validated, fast and standardized high-throughput analysis of insertion sites can be achieved for the first time.
Gene transfer to hematopoietic stem cells with integrating vectors not only allows sustained correction of monogenic diseases but also tracking of individual clones in vivo. Quantitative real-time PCR (qPCR) has been shown to be an accurate method to quantify individual stem cell clones, yet due to frequently limited amounts of target material (especially in clinical studies), it is not useful for large-scale analyses. To explore whether vector integration site (IS) recovery techniques may be suitable to describe clonal contributions if combined with next-generation sequencing techniques, we designed artificial ISs of different sizes which were mixed to simulate defined clonal situations in clinical settings. We subjected all mixes to either linear amplification–mediated PCR (LAM-PCR) or nonrestrictive LAM-PCR (nrLAM-PCR), both combined with 454 sequencing. We showed that nrLAM-PCR/454-detected clonality allows estimating qPCR-detected clonality in vitro. We then followed the kinetics of two clones detected in a patient enrolled in a clinical gene therapy trial using both, nrLAM-PCR/454 and qPCR and also saw nrLAM-PCR/454 to correlate to qPCR-measured clonal contributions. The method presented here displays a feasible high-throughput strategy to monitor clonality in clinical gene therapy trials is at hand.
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