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Retroviral insertional mutagenesis identifies RUNX genes involved in chronic myeloid leukemia disease persistence under imatinib treatment.

ABSTRACT: The kinase inhibitor imatinib mesylate targeting the oncoprotein Bcr-Abl has revolutionized the treatment of chronic myeloid leukemia (CML). However, even though imatinib successfully controls the leukemia in chronic phase, it seems not to be able to cure the disease, potentially necessitating lifelong treatment with the inhibitor under constant risk of relapse. On a molecular level, the cause of disease persistence is not well understood. Initial studies implied that innate features of primitive progenitor cancer stem cells may be responsible for the phenomenon. Here, we describe an assay using retroviral insertional mutagenesis (RIM) to identify genes contributing to disease persistence in vivo. We transplanted mice with bone marrow cells retrovirally infected with the Bcr-Abl oncogene and subsequently treated the animals with imatinib to select for leukemic cells in which the proviral integration had affected genes modulating the imatinib response. Southern blot analysis demonstrated clonal outgrowth of cells carrying similar integration sites. Candidate genes located near the proviral insertion sites were identified, among them the transcription factor RUNX3. Proviral integration near the RUNX3 promoter induced RUNX3 expression, and Bcr-Abl-positive cell lines with stable or inducible expression of RUNX1 or RUNX3 were protected from imatinib-induced apoptosis. Furthermore, imatinib treatment selected for RUNX1-expressing cells in vitro and in vivo after infection of primary bone marrow cells with Bcr-Abl and RUNX1. Our results demonstrate the utility of RIM for probing molecular modulators of targeted therapies and suggest a role for members of the RUNX transcription factor family in disease persistence in CML patients.

SUBMITTER: Miething C

PROVIDER: S-EPMC1810334 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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.

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Retroviral insertional mutagenesis identifies RUNX genes involved in chronic myeloid leukemia disease persistence under imatinib treatment.

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