Methodology and software to detect viral integration site hot-spots

Abstract

BackgroundModern 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.ResultsWe 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.ConclusionsThe 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.

Dynamics of HSPC Repopulation in Nonhuman Primates Revealed by a Decade-Long Clonal-Tracking Study

“…6). These hot-spots were characterized using a Bayesian change-point (BCP) model that defines VIS hot-spots relatively independently of data set size(Presson et al, 2011). Lentivirus vectors showed distinctive VIS hot-spot patterns that differed from oncogenic MLV vectors.…”

“…Lentivirus vectors showed distinctive VIS hot-spot patterns that differed from oncogenic MLV vectors. Clinical gene-therapy studies with MLV vectors have revealed hot-spots consisting of densely clustered VISs in a small genomic region, typically near the transcription start site of a gene, that often differed across individuals (Deichmann et al, 2007; Presson et al, 2011; Wang et al, 2010). In contrast, the lentivirus vector hot-spots in our test animals consisted of VIS spread across multi-genic, megabase-scale regions (Fig.…”

The role of HTLV-1 clonality, proviral structure, and genomic integration site in adult T-cell leukemia/lymphoma

“…To test the hypothesis that 2 observed HTLV-1 integration sites were present in 1 T-cell clone, we used the Gaussian approximation to the binomial distribution (supplemental Figure 3). To identify clusters of integration sites or genomic hotspots of integration, we used R software developed by Presson et al 23 (http://www. biomedcentral.com/1471-2105/12/367).…”

Mesenchymal Stem/Stromal Cells in Liver Fibrosis: Recent Findings, Old/New Caveats and Future Perspectives

“…However, to reach high gene transfer rate viral vectors are frequently used as technical approach. While retrovirus and lentivirus vectors integrate their genetic material into the host cell genome [135], recombinant adenoviruses would not raise such safety concern; nevertheless, their direct systemic use can trigger potent immune responses against their own proteins instead [72,136]. Interestingly, Treacy et al [137] showed that adenoviral transduction of MSCs did not induce immune responses in vitro or after a single application in vivo.…”