ArticlePloS one2011
Novel molecular and computational methods improve the accuracy of insertion site analysis in Sleeping Beauty-induced tumors.
Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
52 citing papers in PubMed, 81 citations in OpenAlex.
- NetCIS: a network-based common insertion site pipeline for case-control Sleeping Beauty screens.Briefings in bioinformatics · 2026Article
- A forward genetic screen identifies potassium channel essentiality in SHH medulloblastoma maintenance.Developmental cell · 2025Article
- Understanding cancer drug resistance withiScience · 2023Article
- Distinct shared and compartment-enriched oncogenic networks drive primary versus metastatic breast cancer.Nature communications · 2023Article
- Transmicron: accurate prediction of insertion probabilities improves detection of cancer driver genes from transposon mutagenesis screens.Nucleic acids research · 2023Article
- SB Digestor: a tailored driver gene identification tool for dissecting heterogeneous Sleeping Beauty transposon-induced tumors.International journal of biological sciences · 2023Article
- Transposon Mutagenesis Reveals RBMS3 Silencing as a Promoter of Malignant Progression of BRAFV600E-Driven Lung Tumorigenesis.Cancer research · 2022Article
- Single allele loss-of-function mutations select and sculpt conditional cooperative networks in breast cancer.Nature communications · 2021Article
- A Genetic Screen to Identify Gain- and Loss-of-Function Modifications that Enhance T-cell Infiltration into Tumors.Cancer immunology research · 2020Article
- Src-Dependent DBL Family Members Drive Resistance to Vemurafenib in Human Melanoma.Cancer research · 2019Article
- A simplified transposon mutagenesis method to perform phenotypic forward genetic screens in cultured cells.BMC genomics · 2019Article
- Insertional mutagenesis using the Sleeping Beauty transposon system identifies drivers of erythroleukemia in mice.Scientific reports · 2019Article
- Ex Vivo Transposon-Mediated Genetic Screens for Cancer Gene Discovery.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Sleeping Beauty Mouse Models of Cancer: Microenvironmental Influences on Cancer Genetics.Frontiers in oncology · 2019Review
- Molecular profiling of nonalcoholic fatty liver disease-associated hepatocellular carcinoma using SB transposon mutagenesis.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- SB Driver Analysis: a Sleeping Beauty cancer driver analysis framework for identifying and prioritizing experimentally actionable oncogenes and tumor suppressors.Nucleic acids research · 2018Article
- Advances in functional genetic screening with transposons and CRISPR/Cas9 to illuminate cancer biology.Current opinion in genetics & development · 2018Review
- Chronic liver injury alters driver mutation profiles in hepatocellular carcinoma in mice.Hepatology (Baltimore, Md.) · 2018Article
- A Forward Genetic Screen Targeting the Endothelium Reveals a Regulatory Role for the Lipid Kinase Pi4ka in Myelo- and Erythropoiesis.Cell reports · 2018Article
- Linking FOXO3, NCOA3, and TCF7L2 to Ras pathway phenotypes through a genome-wide forward genetic screen in human colorectal cancer cells.Genome medicine · 2018Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
The recent development of the Sleeping Beauty (SB) system has led to the development of novel mouse models of cancer. Unlike spontaneous models, SB causes cancer through the action of mutagenic transposons that are mobilized in the genomes of somatic cells to induce mutations in cancer genes. While previous methods have successfully identified many transposon-tagged mutations in SB-induced tumors, limitations in DNA sequencing technology have prevented a comprehensive analysis of large tumor cohorts. Here we describe a novel method for producing genetic profiles of SB-induced tumors using Illumina sequencing. This method has dramatically increased the number of transposon-induced mutations identified in each tumor sample to reveal a level of genetic complexity much greater than previously appreciated. In addition, Illumina sequencing has allowed us to more precisely determine the depth of sequencing required to obtain a reproducible signature of transposon-induced mutations within tumor samples. The use of Illumina sequencing to characterize SB-induced tumors should significantly reduce sampling error that undoubtedly occurs using previous sequencing methods. As a consequence, the improved accuracy and precision provided by this method will allow candidate cancer genes to be identified with greater confidence. Overall, this method will facilitate ongoing efforts to decipher the genetic complexity of the human cancer genome by providing more accurate comparative information from Sleeping Beauty models of cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.