Serial bone marrow transplantation reveals in vivo expression of the pCLPG retroviral vector

<p>Abstract</p> <p>Background</p> <p>Gene therapy in the hematopoietic system remains promising, though certain aspects of vector design, such as transcriptional control elements, continue to be studied. Our group has developed a retroviral vector where transgene expression is controlled by p53 with the intention of harnessing the dynamic and inducible nature of this tumor suppressor and transcription factor. We present here a test of <it>in vivo </it>expression provided by the p53-responsive vector, pCLPG. For this, we used a model of serial transplantation of transduced bone marrow cells.</p> <p>Results</p> <p>We observed, by flow cytometry, that the eGFP transgene was expressed at higher levels when the pCLPG vector was used as compared to the parental pCL retrovirus, where expression is directed by the native MoMLV LTR. Expression from the pCLPG vector was longer lasting, but did decay along with each sequential transplant. The detection of eGFP-positive cells containing either vector was successful only in the bone marrow compartment and was not observed in peripheral blood, spleen or thymus.</p> <p>Conclusions</p> <p>These findings indicate that the p53-responsive pCLPG retrovirus did offer expression <it>in vivo </it>and at a level that surpassed the non-modified, parental pCL vector. Our results indicate that the pCLPG platform may provide some advantages when applied in the hematopoietic system.</p

Estimated Comparative Integration Hotspots Identify Different Behaviors of Retroviral Gene Transfer Vectors

Integration of retroviral vectors in the human genome follows non random patterns that favor insertional deregulation of gene expression and may cause risks of insertional mutagenesis when used in clinical gene therapy. Understanding how viral vectors integrate into the human genome is a key issue in predicting these risks. We provide a new statistical method to compare retroviral integration patterns. We identified the positions where vectors derived from the Human Immunodeficiency Virus (HIV) and the Moloney Murine Leukemia Virus (MLV) show different integration behaviors in human hematopoietic progenitor cells. Non-parametric density estimation was used to identify candidate comparative hotspots, which were then tested and ranked. We found 100 significative comparative hotspots, distributed throughout the chromosomes. HIV hotspots were wider and contained more genes than MLV ones. A Gene Ontology analysis of HIV targets showed enrichment of genes involved in antigen processing and presentation, reflecting the high HIV integration frequency observed at the MHC locus on chromosome 6. Four histone modifications/variants had a different mean density in comparative hotspots (H2AZ, H3K4me1, H3K4me3, H3K9me1), while gene expression within the comparative hotspots did not differ from background. These findings suggest the existence of epigenetic or nuclear three-dimensional topology contexts guiding retroviral integration to specific chromosome areas

Analyzing the Number of Common Integration Sites of Viral Vectors – New Methods and Computer Programs

Vectors based on γ-retroviruses or lentiviruses have been shown to stably express therapeutical transgenes and effectively cure different hematological diseases. Molecular follow up of the insertional repertoire of gene corrected cells in patients and preclinical animal models revealed different integration preferences in the host genome including clusters of integrations in small genomic areas (CIS; common integrations sites). In the majority, these CIS were found in or near genes, with the potential to influence the clonal fate of the affected cell. To determine whether the observed degree of clustering is statistically compatible with an assumed standard model of spatial distribution of integrants, we have developed various methods and computer programs for γ-retroviral and lentiviral integration site distribution. In particular, we have devised and implemented mathematical and statistical approaches for comparing two experimental samples with different numbers of integration sites with respect to the propensity to form CIS as well as for the analysis of coincidences of integration sites obtained from different blood compartments. The programs and statistical tools described here are available as workspaces in R code and allow the fast detection of excessive clustering of integration sites from any retrovirally transduced sample and thus contribute to the assessment of potential treatment-related risks in preclinical and clinical retroviral gene therapy studies

Methodology and software to detect viral integration site hot-spots

<p>Abstract</p> <p>Background</p> <p>Modern gene therapy methods have limited control over where a therapeutic viral vector inserts into the host genome. Vector integration can activate local gene expression, which can cause cancer if the vector inserts near an oncogene. Viral integration hot-spots or 'common insertion sites' (CIS) are scrutinized to evaluate and predict patient safety. CIS are typically defined by a minimum density of insertions (such as 2-4 within a 30-100 kb region), which unfortunately depends on the total number of observed VIS. This is problematic for comparing hot-spot distributions across data sets and patients, where the VIS numbers may vary.</p> <p>Results</p> <p>We develop two new methods for defining hot-spots that are relatively independent of data set size. Both methods operate on distributions of VIS across consecutive 1 Mb 'bins' of the genome. The first method 'z-threshold' tallies the number of VIS per bin, converts these counts to z-scores, and applies a threshold to define high density bins. The second method 'BCP' applies a Bayesian change-point model to the z-scores to define hot-spots. The novel hot-spot methods are compared with a conventional CIS method using simulated data sets and data sets from five published human studies, including the X-linked ALD (adrenoleukodystrophy), CGD (chronic granulomatous disease) and SCID-X1 (X-linked severe combined immunodeficiency) trials. The BCP analysis of the human X-linked ALD data for two patients separately (774 and 1627 VIS) and combined (2401 VIS) resulted in 5-6 hot-spots covering 0.17-0.251% of the genome and containing 5.56-7.74% of the total VIS. In comparison, the CIS analysis resulted in 12-110 hot-spots covering 0.018-0.246% of the genome and containing 5.81-22.7% of the VIS, corresponding to a greater number of hot-spots as the data set size increased. Our hot-spot methods enable one to evaluate the extent of VIS clustering, and formally compare data sets in terms of hot-spot overlap. Finally, we show that the BCP hot-spots from the repopulating samples coincide with greater gene and CpG island density than the median genome density.</p> <p>Conclusions</p> <p>The z-threshold and BCP methods are useful for comparing hot-spot patterns across data sets of disparate sizes. The methodology and software provided here should enable one to study hot-spot conservation across a variety of VIS data sets and evaluate vector safety for gene therapy trials.</p

Murine Leukemias with Retroviral Insertions at Lmo2 Are Predictive of the Leukemias Induced in SCID-X1 Patients Following Retroviral Gene Therapy

Five X-linked severe combined immunodeficiency patients (SCID-X1) successfully treated with autologous bone marrow stem cells infected ex vivo with an IL2RG-containing retrovirus subsequently developed T-cell leukemia and four contained insertional mutations at LMO2. Genetic evidence also suggests a role for IL2RG in tumor formation, although this remains controversial. Here, we show that the genes and signaling pathways deregulated in murine leukemias with retroviral insertions at Lmo2 are similar to those deregulated in human leukemias with high LMO2 expression and are highly predictive of the leukemias induced in SCID-X1 patients. We also provide additional evidence supporting the notion that IL2RG and LMO2 cooperate in leukemia induction but are not sufficient and require additional cooperating mutations. The highly concordant nature of the genetic events giving rise to mouse and human leukemias with mutations at Lmo2 are an encouraging sign to those wanting to use mice to model human cancer and may help in designing safer methods for retroviral gene therapy

Differential gene expression profile and altered cytokine secretion of thyroid cancer cells in space

This study focuses on the effects of short-term [22 s, parabolic flight campaign (PFC)] and long-term (10 d, Shenzhou 8 space mission) real microgravity on changes in cytokine secretion and gene expression patterns in poorly differentiated thyroid cancer cells. FTC-133 cells were cultured in space and on a random positioning machine (RPM) for 10 d, to evaluate differences between real and simulated microgravity. Multianalyte profiling was used to evaluate 128 secreted cytokines. Microarray analysis revealed 63 significantly regulated transcripts after 22 s of microgravity during a PFC and 2881 after 10 d on the RPM or in space. Genes in several biological processes, including apoptosis (n=182), cytoskeleton (n=80), adhesion/extracellular matrix (n=98), proliferation (n=184), stress response (n=268), migration (n=63), angiogenesis (n=39), and signal transduction (n=429), were differentially expressed. Genes and proteins involved in the regulation of cancer cell proliferation and metastasis, such as IL6, IL8, IL15, OPN, VEGFA, VEGFD, FGF17, MMP2, MMP3, TIMP1, PRKAA, and PRKACA, were similarly regulated under RPM and spaceflight conditions. The resulting effect was mostly antiproliferative. Gene expression during the PFC was often regulated in the opposite direction. In summary, microgravity is an invaluable tool for exploring new targets in anticancer therapy and can be simulated in some aspects in ground-based facilities.Ma, X., Pietsch, J., Wehland, M., Schulz, H., Saar, K., Hubner, N., Bauer, J., Braun, M., Schwarzwalder, A., Segerer, J., Birlem, M., Horn, A., Hemmersbach, R., Wa ss er, K., Grosse, J., Infanger, M., Grimm, D. Differential gene expression profile and altered cytokine secretion of thyroid cancer cells in space

Transcriptional Enhancers Induce Insertional Gene Deregulation Independently From the Vector Type and Design

The integration characteristics of retroviral (RV) vectors increase the probability of interfering with the regulation of cellular genes, and account for a tangible risk of insertional mutagenesis in treated patients. To assess the potential genotoxic risk of conventional or self-inactivating (SIN) γ-RV and lentiviral (LV) vectors independently from the biological consequences of the insertion event, we developed a quantitative assay based on real-time reverse transcriptase—PCR on low-density arrays to evaluate alterations of gene expression in individual primary T-cell clones. We show that the Moloney leukemia virus long terminal repeat (LTR) enhancer has the strongest activity in both a γ-RV and a LV vector context, while an internal cellular promoter induces deregulation of gene expression less frequently, at a shorter range and to a lower extent in both vector types. Downregulation of gene expression was observed only in the context of LV vectors. This study indicates that insertional gene activation is determined by the characteristics of the transcriptional regulatory elements carried by the vector, and is largely independent from the vector type or design

Comprehensive genomic access to vector integration in clinical gene therapy.

Retroviral vectors have induced subtle clonal skewing in many gene therapy patients and severe clonal proliferation and leukemia in some of them, emphasizing the need for comprehensive integration site analyses to assess the biosafety and genomic pharmacokinetics of vectors and clonal fate of gene-modified cells in vivo. Integration site analyses such as linear amplification-mediated PCR (LAM-PCR) require a restriction digest generating unevenly small fragments of the genome. Here we show that each restriction motif allows for identification of only a fraction of all genomic integrants, hampering the understanding and prediction of biological consequences after vector insertion. We developed a model to define genomic access to the viral integration site that provides optimal restriction motif combinations and minimizes the percentage of nonaccessible insertion loci. We introduce a new nonrestrictive LAM-PCR approach that has superior capabilities for comprehensive unbiased integration site retrieval in preclinical and clinical samples independent of restriction motifs and amplification inefficienc

Insertion Sites in Engrafted Cells Cluster Within a Limited Repertoire of Genomic Areas After Gammaretroviral Vector Gene Therapy

Vector-associated side effects in clinical gene therapy have provided insights into the molecular mechanisms of hematopoietic regulation in vivo. Surprisingly, many retrovirus insertion sites (RIS) present in engrafted cells have been found to cluster nonrandomly in close association with specific genes. Our data demonstrate that these genes directly influence the in vivo fate of hematopoietic cell clones. Analysis of insertions thus far has been limited to individual clinical studies. Here, we studied >7,000 insertions retrieved from various studies. More than 40% of all insertions found in engrafted gene-modified cells were clustered in the same genomic areas covering only 0.36% of the genome. Gene classification analyses displayed significant overrepresentation of genes associated with hematopoietic functions and relevance for cell growth and survival in vivo. The similarity of insertion distributions indicates that vector insertions in repopulating cells cluster in predictable patterns. Thus, insertion analyses of preclinical in vitro and murine in vivo studies as well as vector insertion repertoires in clinical trials yielded concerted results and mark a small number of interesting genomic loci and genes that warrants further investigation of the biological consequences of vector insertions