Abstract 2341: Sleeping Beauty transposon mutagenesis screen identifies cancer genes of uterine leiomyosarcoma driving sarcomagenesis and lung metastasis

Epithelial-mesenchymal transition (EMT) is thought to contribute to metastasis and chemoresistance in patients with hepatocellular carcinoma (HCC), leading to their poor prognosis. The genes driving EMT in HCC are not yet fully understood, however. Here, we show that mobilization of Sleeping Beauty (SB) transposons in immortalized mouse hepatoblasts induces mesenchymal liver tumors on transplantation to nude mice. These tumors show significant down-regulation of epithelial markers, along with up-regulation of mesenchymal markers and EMT-related transcription factors (EMT-TFs). Sequencing of transposon insertion sites from tumors identified 233 candidate cancer genes (CCGs) that were enriched for genes and cellular processes driving EMT. Subsequent trunk driver analysis identified 23 CCGs that are predicted to function early in tumorigenesis and whose mutation or alteration in patients with HCC is correlated with poor patient survival. Validation of the top trunk drivers identified in the screen, including MET (MET proto-oncogene, receptor tyrosine kinase), GRB2-associated binding protein 1 (GAB1), HECT, UBA, and WWE domain containing 1 (HUWE1), lysine-specific demethylase 6A (KDM6A), and protein-tyrosine phosphatase, nonreceptor-type 12 (PTPN12), showed that deregulation of these genes activates an EMT program in human HCC cells that enhances tumor cell migration. Finally, deregulation of these genes in human HCC was found to confer sorafenib resistance through apoptotic tolerance and reduced proliferation, consistent with recent studies showing that EMT contributes to the chemoresistance of tumor cells. Our unique cell-based transposon mutagenesis screen appears to be an excellent resource for discovering genes involved in EMT in human HCC and potentially for identifying new drug targets.

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Sleeping Beauty Transposon Mutagenesis as a Tool for Gene Discovery in the NOD Mouse Model of Type 1 Diabetes

G3 Genes|Genome|Genetics ◽

10.1534/g3.115.021709 ◽

2015 ◽

Vol 5 (12) ◽

pp. 2903-2911 ◽

Cited By ~ 2

Author(s):

Colleen M. Elso ◽

Edward P. F. Chu ◽

May A. Alsayb ◽

Leanne Mackin ◽

Sean T. Ivory ◽

...

Keyword(s):

Type 1 Diabetes ◽

Mouse Model ◽

Gene Discovery ◽

Sleeping Beauty ◽

Transposon Mutagenesis ◽

Nod Mouse ◽

Sleeping Beauty Transposon

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A simplified transposon mutagenesis method to perform phenotypic forward genetic screens in cultured cells

10.1101/598474 ◽

2019 ◽

Author(s):

Charlotte R. Feddersen ◽

Lexy S. Wadsworth ◽

Eliot Y. Zhu ◽

Hayley R. Vaughn ◽

Andrew P. Voigt ◽

...

Keyword(s):

Cultured Cells ◽

Sequence Data ◽

Sleeping Beauty ◽

Transposon Mutagenesis ◽

Loss Of Function ◽

Genetic Screens ◽

Sleeping Beauty Transposon ◽

Genome Wide ◽

Forward Genetic Screens ◽

The Impact

AbstractThe introduction of genome-wide shRNA and CRISPR libraries has facilitated cell-based screens to identify loss-of-function mutations associated with a phenotype of interest. Approaches to perform analogous gain-of-function screens are less common, although some reports have utilized arrayed viral expression libraries or the CRISPR activation system. However, a variety of technical and logistical challenges make these approaches difficult for many labs to execute. In addition, genome-wide shRNA or CRISPR libraries typically contain of hundreds of thousands of individual engineered elements, and the associated complexity creates issues with replication and reproducibility for these methods. Here we describe a simple, reproducible approach using the Sleeping Beauty transposon system to perform phenotypic cell-based genetic screens. This approach employs only three plasmids to perform unbiased, whole-genome transposon mutagenesis. We also describe a ligation-mediated PCR method that can be used in conjunction with the included software tools to map raw sequence data, identify candidate genes associated with phenotypes of interest, and predict the impact of recurrent transposon insertions on candidate gene function. Finally, we demonstrate the high reproducibility of our approach by having three individuals perform independent replicates of a mutagenesis screen to identify drivers of vemurafenib resistance in cultured melanoma cells. Collectively, our work establishes a facile, adaptable method that can be performed by labs of any size to perform robust, genome-wide screens to identify genes that influence phenotypes of interest.

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Transposon mutagenesis identifies chromatin modifiers cooperating with Ras in thyroid tumorigenesis and detects ATXN7 as a cancer gene

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1702723114 ◽

2017 ◽

Vol 114 (25) ◽

pp. E4951-E4960 ◽

Cited By ~ 8

Author(s):

Cristina Montero-Conde ◽

Luis J. Leandro-Garcia ◽

Xu Chen ◽

Gisele Oler ◽

Sergio Ruiz-Llorente ◽

...

Keyword(s):

Genetic Alterations ◽

Sleeping Beauty ◽

Thyroid Tumor ◽

Transposon Mutagenesis ◽

Thyroid Cell ◽

Cancer Gene ◽

Cancer Genes ◽

Thyroid Cancers ◽

Endogenous Expression ◽

Poorly Differentiated

Oncogenic RAS mutations are present in 15–30% of thyroid carcinomas. Endogenous expression of mutant Ras is insufficient to initiate thyroid tumorigenesis in murine models, indicating that additional genetic alterations are required. We used Sleeping Beauty (SB) transposon mutagenesis to identify events that cooperate with HrasG12V in thyroid tumor development. Random genomic integration of SB transposons primarily generated loss-of-function events that significantly increased thyroid tumor penetrance in Tpo-Cre/homozygous FR-HrasG12V mice. The thyroid tumors closely phenocopied the histological features of human RAS-driven, poorly differentiated thyroid cancers. Characterization of transposon insertion sites in the SB-induced tumors identified 45 recurrently mutated candidate cancer genes. These mutation profiles were remarkably concordant with mutated cancer genes identified in a large series of human poorly differentiated and anaplastic thyroid cancers screened by next-generation sequencing using the MSK-IMPACT panel of cancer genes, which we modified to include all SB candidates. The disrupted genes primarily clustered in chromatin remodeling functional nodes and in the PI3K pathway. ATXN7, a component of a multiprotein complex with histone acetylase activity, scored as a significant SB hit. It was recurrently mutated in advanced human cancers and significantly co-occurred with RAS or NF1 mutations. Expression of ATXN7 mutants cooperated with oncogenic RAS to induce thyroid cell proliferation, pointing to ATXN7 as a previously unrecognized cancer gene.

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Abstract 1970: Validation of candidate gastrointestinal cancer genes with ion channel functions, identified from Sleeping Beauty transposon-mediated mutagenesis screens in mice.

10.1158/1538-7445.am2013-1970 ◽

2013 ◽

Author(s):

Bich L. N. Than ◽

M. Gerald O'Sullivan ◽

Tim Starr ◽

David Largaespada ◽

Robert T. Cormier ◽

...

Keyword(s):

Ion Channel ◽

Gastrointestinal Cancer ◽

Sleeping Beauty ◽

Cancer Genes ◽

Sleeping Beauty Transposon

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Sleeping Beauty transposon mutagenesis identifies genes that cooperate with mutant Smad4 in gastric cancer development

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1603223113 ◽

2016 ◽

Vol 113 (14) ◽

pp. E2057-E2065 ◽

Cited By ~ 24

Author(s):

Haruna Takeda ◽

Alistair G. Rust ◽

Jerrold M. Ward ◽

Christopher Chin Kuan Yew ◽

Nancy A. Jenkins ◽

...

Keyword(s):

Gastric Cancer ◽

Large Scale ◽

Molecular Mechanisms ◽

Ldl Receptor ◽

Clinical Importance ◽

Rna Degradation ◽

Sleeping Beauty ◽

Transposon Mutagenesis ◽

Complete List ◽

Cancer Genes

Mutations in SMAD4 predispose to the development of gastrointestinal cancer, which is the third leading cause of cancer-related deaths. To identify genes driving gastric cancer (GC) development, we performed a Sleeping Beauty (SB) transposon mutagenesis screen in the stomach of Smad4+/− mutant mice. This screen identified 59 candidate GC trunk drivers and a much larger number of candidate GC progression genes. Strikingly, 22 SB-identified trunk drivers are known or candidate cancer genes, whereas four SB-identified trunk drivers, including PTEN, SMAD4, RNF43, and NF1, are known human GC trunk drivers. Similar to human GC, pathway analyses identified WNT, TGF-β, and PI3K-PTEN signaling, ubiquitin-mediated proteolysis, adherens junctions, and RNA degradation in addition to genes involved in chromatin modification and organization as highly deregulated pathways in GC. Comparative oncogenomic filtering of the complete list of SB-identified genes showed that they are highly enriched for genes mutated in human GC and identified many candidate human GC genes. Finally, by comparing our complete list of SB-identified genes against the list of mutated genes identified in five large-scale human GC sequencing studies, we identified LDL receptor-related protein 1B (LRP1B) as a previously unidentified human candidate GC tumor suppressor gene. In LRP1B, 129 mutations were found in 462 human GC samples sequenced, and LRP1B is one of the top 10 most deleted genes identified in a panel of 3,312 human cancers. SB mutagenesis has, thus, helped to catalog the cooperative molecular mechanisms driving SMAD4-induced GC growth and discover genes with potential clinical importance in human GC.

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