Dataset Information

Replication-incompetent gammaretroviral and lentiviral vector-based insertional mutagenesis screens identify prostate cancer progression genes.

ABSTRACT: Replication-incompetent gammaretroviral (?RV) and lentiviral (LV) vectors have both been used in insertional mutagenesis screens to identify cancer drivers. In this approach the vectors stably integrate in the host cell genome and induce cancers by dysregulating nearby genes. The cells that contain a retroviral vector provirus in or near a proto-oncogene or tumor suppressor are preferentially enriched in a tumor. ?RV and LV vectors have different integration profiles and genotoxic potential, making them potentially complementary tools for insertional mutagenesis screens. We performed screens using both ?RV and LV vectors to identify driver genes that mediate progression of androgen-independent prostate cancer (AIPC) using a xenotransplant mouse model. Vector transduced LNCaP cells were injected orthotopically into the prostate gland of immunodeficient mice. Mice that developed tumors were castrated to create an androgen-deficient environment and metastatic tumors that developed were analyzed. A high-throughput modified genomic sequencing PCR (MGS-PCR) approach identified the positions of vector integrations in these metastatic tumors. OR2A14, FER1L6, TAOK3, MAN1A2, MBNL2, SERBP1, PLEKHA2, SPTAN1, ADAMTS1, SLC30A5, ABCC1, SLC7A1 and SLC25A24 were identified as candidate prostate cancer (PC) progression genes. TAOK3 and ABCC1 expression in PC patients predicted the risk of recurrence after androgen deprivation therapy. Our data shows that ?RV and LV vectors are complementary approaches to identify cancer driver genes which may be promising potential biomarkers and therapeutic targets.

SUBMITTER: Bii VM

PROVIDER: S-EPMC5884640 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Replication-incompetent gammaretroviral and lentiviral vector-based insertional mutagenesis screens identify prostate cancer progression genes.

Bii Victor M VM Collins Casey P CP Hocum Jonah D JD Trobridge Grant D GD

Oncotarget 20180215 21

Replication-incompetent gammaretroviral (γRV) and lentiviral (LV) vectors have both been used in insertional mutagenesis screens to identify cancer drivers. In this approach the vectors stably integrate in the host cell genome and induce cancers by dysregulating nearby genes. The cells that contain a retroviral vector provirus in or near a proto-oncogene or tumor suppressor are preferentially enriched in a tumor. γRV and LV vectors have different integration profiles and genotoxic potential, mak ...[more]

PMID: 29643985

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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

Replication-incompetent gammaretroviral and lentiviral vector-based insertional mutagenesis screens identify prostate cancer progression genes.

Publications

Replication-incompetent gammaretroviral and lentiviral vector-based insertional mutagenesis screens identify prostate cancer progression genes.

Similar Datasets

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