Dataset Information

Retroviral vector insertion sites associated with dominant hematopoietic clones mark "stemness" pathways.

ABSTRACT: Evidence from model organisms and clinical trials reveals that the random insertion of retrovirus-based vectors in the genome of long-term repopulating hematopoietic cells may increase self-renewal or initiate malignant transformation. Clonal dominance of nonmalignant cells is a particularly interesting phenotype as it may be caused by the dysregulation of genes that affect self-renewal and competitive fitness. We have accumulated 280 retrovirus vector insertion sites (RVISs) from murine long-term studies resulting in benign or malignant clonal dominance. RVISs (22.5%) are located in or near (up to 100 kb [kilobase]) to known proto-oncogenes, 49.6% in signaling genes, and 27.9% in other or unknown genes. The resulting insertional dominance database (IDDb) shows substantial overlaps with the transcriptome of hematopoietic stem/progenitor cells and the retrovirus-tagged cancer gene database (RTCGD). RVISs preferentially marked genes with high expression in hematopoietic stem/progenitor cells, and Gene Ontology revealed an overrepresentation of genes associated with cell-cycle control, apoptosis signaling, and transcriptional regulation, including major "stemness" pathways. The IDDb forms a powerful resource for the identification of genes that stimulate or transform hematopoietic stem/progenitor cells and is an important reference for vector biosafety studies in human gene therapy.

SUBMITTER: Kustikova OS

PROVIDER: S-EPMC1801061 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature

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Retroviral vector insertion sites associated with dominant hematopoietic clones mark "stemness" pathways.

Kustikova Olga S OS Geiger Hartmut H Li Zhixiong Z Brugman Martijn H MH Chambers Stuart M SM Shaw Chad A CA Pike-Overzet Karin K de Ridder Dick D Staal Frank J T FJ von Keudell Gottfried G Cornils Kerstin K Nattamai Kalpana Jekumar KJ Modlich Ute U Wagemaker Gerard G Goodell Margaret A MA Fehse Boris B Baum Christopher C

Blood 20061121 5

Evidence from model organisms and clinical trials reveals that the random insertion of retrovirus-based vectors in the genome of long-term repopulating hematopoietic cells may increase self-renewal or initiate malignant transformation. Clonal dominance of nonmalignant cells is a particularly interesting phenotype as it may be caused by the dysregulation of genes that affect self-renewal and competitive fitness. We have accumulated 280 retrovirus vector insertion sites (RVISs) from murine long-te ...[more]

PMID: 17119121

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Project description:Retroviral insertional mutagenesis screens, which identify genes involved in tumor development in mice, have yielded a substantial number of retroviral integration sites, and this number is expected to grow substantially due to the introduction of high-throughput screening techniques. The data of various retroviral insertional mutagenesis screens are compiled in the publicly available Retroviral Tagged Cancer Gene Database (RTCGD). Integrally analyzing these screens for the presence of common insertion sites (CISs, i.e., regions in the genome that have been hit by viral insertions in multiple independent tumors significantly more than expected by chance) requires an approach that corrects for the increased probability of finding false CISs as the amount of available data increases. Moreover, significance estimates of CISs should be established taking into account both the noise, arising from the random nature of the insertion process, as well as the bias, stemming from preferential insertion sites present in the genome and the data retrieval methodology. We introduce a framework, the kernel convolution (KC) framework, to find CISs in a noisy and biased environment using a predefined significance level while controlling the family-wise error (FWE) (the probability of detecting false CISs). Where previous methods use one, two, or three predetermined fixed scales, our method is capable of operating at any biologically relevant scale. This creates the possibility to analyze the CISs in a scale space by varying the width of the CISs, providing new insights in the behavior of CISs across multiple scales. Our method also features the possibility of including models for background bias. Using simulated data, we evaluate the KC framework using three kernel functions, the Gaussian, triangular, and rectangular kernel function. We applied the Gaussian KC to the data from the combined set of screens in the RTCGD and found that 53% of the CISs do not reach the significance threshold in this combined setting. Still, with the FWE under control, application of our method resulted in the discovery of eight novel CISs, which each have a probability less than 5% of being false detections.

Dataset Information

Retroviral vector insertion sites associated with dominant hematopoietic clones mark "stemness" pathways.

Publications

Retroviral vector insertion sites associated with dominant hematopoietic clones mark "stemness" pathways.

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