Transposon Mutagenesis Reveals RBMS3 Silencing as a Promoter of Malignant Progression of BRAFV600E-Driven Lung Tumorigenesis.

Mutationally activated BRAF is detected in approximately 7% of human lung adenocarcinomas, with BRAFT1799A serving as a predictive biomarker for treatment of patients with FDA-approved inhibitors of BRAFV600E oncoprotein signaling. In genetically engineered mouse (GEM) models, expression of BRAFV600E in the lung epithelium initiates growth of benign lung tumors that, without additional genetic alterations, rarely progress to malignant lung adenocarcinoma. To identify genes that cooperate with BRAFV600E for malignant progression, we used Sleeping Beauty-mediated transposon mutagenesis, which dramatically accelerated the emergence of lethal lung cancers. Among the genes identified was Rbms3, which encodes an RNA-binding protein previously implicated as a putative tumor suppressor. Silencing of RBMS3 via CRISPR/Cas9 gene editing promoted growth of BRAFV600E lung organoids and promoted development of malignant lung cancers with a distinct micropapillary architecture in BRAFV600E and EGFRL858R GEM models. BRAFV600E/RBMS3Null lung tumors displayed elevated expression of Ctnnb1, Ccnd1, Axin2, Lgr5, and c-Myc mRNAs, suggesting that RBMS3 silencing elevates signaling through the WNT/ß-catenin signaling axis. Although RBMS3 silencing rendered BRAFV600E-driven lung tumors resistant to the effects of dabrafenib plus trametinib, the tumors were sensitive to inhibition of porcupine, an acyltransferase of WNT ligands necessary for their secretion. Analysis of The Cancer Genome Atlas patient samples revealed that chromosome 3p24, which encompasses RBMS3, is frequently lost in non-small cell lung cancer and correlates with poor prognosis. Collectively, these data reveal the role of RBMS3 as a lung cancer suppressor and suggest that RBMS3 silencing may contribute to malignant NSCLC progression. SIGNIFICANCE: Loss of RBMS3 cooperates with BRAFV600E to induce lung tumorigenesis, providing a deeper understanding of the molecular mechanisms underlying mutant BRAF-driven lung cancer and potential strategies to more effectively target this disease.

Transposon mutagenesis identifies cooperating genetic drivers during keratinocyte transformation and cutaneous squamous cell carcinoma progression.

The systematic identification of genetic events driving cellular transformation and tumor progression in the absence of a highly recurrent oncogenic driver mutation is a challenge in cutaneous oncology. In cutaneous squamous cell carcinoma (cuSCC), the high UV-induced mutational burden poses a hurdle to achieve a complete molecular landscape of this disease. Here, we utilized the Sleeping Beauty transposon mutagenesis system to statistically define drivers of keratinocyte transformation and cuSCC progression in vivo in the absence of UV-IR, and identified both known tumor suppressor genes and novel oncogenic drivers of cuSCC. Functional analysis confirms an oncogenic role for the ZMIZ genes, and tumor suppressive roles for KMT2C, CREBBP and NCOA2, in the initiation or progression of human cuSCC. Taken together, our in vivo screen demonstrates an extremely heterogeneous genetic landscape of cuSCC initiation and progression, which can be harnessed to better understand skin oncogenic etiology and prioritize therapeutic candidates.

Promoterless Transposon Mutagenesis Drives Solid Cancers via Tumor Suppressor Inactivation.

A central challenge in cancer genomics is the systematic identification of single and cooperating tumor suppressor gene mutations driving cellular transformation and tumor progression in the absence of oncogenic driver mutation(s). Multiple in vitro and in vivo gene inactivation screens have enhanced our understanding of the tumor suppressor gene landscape in various cancers. However, these studies are limited to single or combination gene effects, specific organs, or require sensitizing mutations. In this study, we developed and utilized a Sleeping Beauty transposon mutagenesis system that functions only as a gene trap to exclusively inactivate tumor suppressor genes. Using whole body transposon mobilization in wild type mice, we observed that cumulative gene inactivation can drive tumorigenesis of solid cancers. We provide a quantitative landscape of the tumor suppressor genes inactivated in these cancers and show that, despite the absence of oncogenic drivers, these genes converge on key biological pathways and processes associated with cancer hallmarks.

Noninvasive Assessment of Epidermal Genomic Markers of UV Exposure in Skin.

The measurement of UV-induced DNA damage as a dosimeter of exposure and predictor of skin cancer risk has been proposed by multiple groups. Although UV-induced mutations and adducts are present in normal-appearing UV-exposed epidermis, sampling normal nonlesional skin requires noninvasive methods to extract epidermal DNA for analysis. Here, we demonstrate the feasibility of such an approach, termed surfactant-based tissue acquisition for molecular profiling. Sampling in patients was performed using a felt-tip pen soaked in a mixture of surfactants (Brij-30/N-decyl-N,N-dimethyl-3-ammonio-1-propanesulfonate). In mice, we show that the epidermis can be selectively removed without scarring, with complete healing within 2 weeks. We exposed hairless mice to low-dose UV radiation over a period of 3 months and serially sampled them through up to 2 months following the cessation of UV exposure, observing a progressive increase in a UV signature mutational burden. To test whether surfactant-based tissue acquisition for molecular profiling could be applied to human patients, samples were collected from sun-exposed and sun-protected areas, which were then subjected to high-depth targeted exome sequencing. Extensive UV-driven mosaicism and substantially increased mutational loads in sun-exposed versus sun-protected areas were observed, suggesting that genomic measures, as an integrated readout of DNA damage, repair, and clonal expansion, may be informative markers of UV exposure.

SB Driver Analysis: a Sleeping Beauty cancer driver analysis framework for identifying and prioritizing experimentally actionable oncogenes and tumor suppressors.

Cancer driver prioritization for functional analysis of potential actionable therapeutic targets is a significant challenge. Meta-analyses of mutated genes across different human cancer types for driver prioritization has reaffirmed the role of major players in cancer, including KRAS, TP53 and EGFR, but has had limited success in prioritizing genes with non-recurrent mutations in specific cancer types. Sleeping Beauty (SB) insertional mutagenesis is a powerful experimental gene discovery framework to define driver genes in mouse models of human cancers. Meta-analyses of SB datasets across multiple tumor types is a potentially informative approach to prioritize drivers, and complements efforts in human cancers. Here, we report the development of SB Driver Analysis, an in-silico method for defining cancer driver genes that positively contribute to tumor initiation and progression from population-level SB insertion data sets. We demonstrate that SB Driver Analysis computationally prioritizes drivers and defines distinct driver classes from end-stage tumors that predict their putative functions during tumorigenesis. SB Driver Analysis greatly enhances our ability to analyze, interpret and prioritize drivers from SB cancer datasets and will continue to substantially increase our understanding of the genetic basis of cancer.

SBCDDB: Sleeping Beauty Cancer Driver Database for gene discovery in mouse models of human cancers.

Large-scale oncogenomic studies have identified few frequently mutated cancer drivers and hundreds of infrequently mutated drivers. Defining the biological context for rare driving events is fundamentally important to increasing our understanding of the druggable pathways in cancer. Sleeping Beauty (SB) insertional mutagenesis is a powerful gene discovery tool used to model human cancers in mice. Our lab and others have published a number of studies that identify cancer drivers from these models using various statistical and computational approaches. Here, we have integrated SB data from primary tumor models into an analysis and reporting framework, the Sleeping Beauty Cancer Driver DataBase (SBCDDB, http://sbcddb.moffitt.org), which identifies drivers in individual tumors or tumor populations. Unique to this effort, the SBCDDB utilizes a single, scalable, statistical analysis method that enables data to be grouped by different biological properties. This allows for SB drivers to be evaluated (and re-evaluated) under different contexts. The SBCDDB provides visual representations highlighting the spatial attributes of transposon mutagenesis and couples this functionality with analysis of gene sets, enabling users to interrogate relationships between drivers. The SBCDDB is a powerful resource for comparative oncogenomic analyses with human cancer genomics datasets for driver prioritization.

Transposon mutagenesis identifies genes that cooperate with mutant Pten in breast cancer progression.

Triple-negative breast cancer (TNBC) has the worst prognosis of any breast cancer subtype. To better understand the genetic forces driving TNBC, we performed a transposon mutagenesis screen in a phosphatase and tensin homolog (Pten) mutant mice and identified 12 candidate trunk drivers and a much larger number of progression genes. Validation studies identified eight TNBC tumor suppressor genes, including the GATA-like transcriptional repressor TRPS1 Down-regulation of TRPS1 in TNBC cells promoted epithelial-to-mesenchymal transition (EMT) by deregulating multiple EMT pathway genes, in addition to increasing the expression of SERPINE1 and SERPINB2 and the subsequent migration, invasion, and metastasis of tumor cells. Transposon mutagenesis has thus provided a better understanding of the genetic forces driving TNBC and discovered genes with potential clinical importance in TNBC.

Analyzing tumor heterogeneity and driver genes in single myeloid leukemia cells with SBCapSeq.

A central challenge in oncology is how to kill tumors containing heterogeneous cell populations defined by different combinations of mutated genes. Identifying these mutated genes and understanding how they cooperate requires single-cell analysis, but current single-cell analytic methods, such as PCR-based strategies or whole-exome sequencing, are biased, lack sequencing depth or are cost prohibitive. Transposon-based mutagenesis allows the identification of early cancer drivers, but current sequencing methods have limitations that prevent single-cell analysis. We report a liquid-phase, capture-based sequencing and bioinformatics pipeline, Sleeping Beauty (SB) capture hybridization sequencing (SBCapSeq), that facilitates sequencing of transposon insertion sites from single tumor cells in a SB mouse model of myeloid leukemia (ML). SBCapSeq analysis of just 26 cells from one tumor revealed the tumor's major clonal subpopulations, enabled detection of clonal insertion events not detected by other sequencing methods and led to the identification of dominant subclones, each containing a unique pair of interacting gene drivers along with three to six cooperating cancer genes with SB-driven expression changes.

Mutant p53 accumulates in cycling and proliferating cells in the normal tissues of p53 R172H mutant mice.

The tumour suppressor p53 is regulated primarily at the protein level. In normal tissues its levels are maintained at a very low level by the action of specific E3 ligases and the ubiquitin proteosome pathway. The mutant p53 protein contributes to transformation, metastasis and drug resistance. High levels of mutant p53 can be found in tumours and the accumulation of mutant p53 has previously been reported in pathologically normal cells in human skin. We show for the first time that similarly elevated levels of mutant p53 can be detected in apparently normal cells in a mutant p53 knock-in mouse model. In fact, in the small intestine, mutant p53 spontaneously accumulates in a manner dependent on gene dosage and cell type. Mutant p53 protein is regulated similarly to wild type p53, which can accumulate rapidly after induction by ionising radiation or Mdm2 inhibitors, however, the clearance of mutant p53 protein is much slower than wild type p53. The accumulation of the protein in the murine small intestine is limited to the cycling, crypt base columnar cells and proliferative zone and is lost as the cells differentiate and exit the cell cycle. Loss of Mdm2 results in even higher levels of p53 expression but p53 is still restricted to proliferating cells in the small intestine. Therefore, the small intestine of these p53 mutant mice is an experimental system in which we can dissect the molecular pathways leading to p53 accumulation, which has important implications for cancer prevention and therapy.

Transposon mutagenesis identifies genetic drivers of Braf(V600E) melanoma.

Although nearly half of human melanomas harbor oncogenic BRAF(V600E) mutations, the genetic events that cooperate with these mutations to drive melanogenesis are still largely unknown. Here we show that Sleeping Beauty (SB) transposon-mediated mutagenesis drives melanoma progression in Braf(V600E) mutant mice and identify 1,232 recurrently mutated candidate cancer genes (CCGs) from 70 SB-driven melanomas. CCGs are enriched in Wnt, PI3K, MAPK and netrin signaling pathway components and are more highly connected to one another than predicted by chance, indicating that SB targets cooperative genetic networks in melanoma. Human orthologs of >500 CCGs are enriched for mutations in human melanoma or showed statistically significant clinical associations between RNA abundance and survival of patients with metastatic melanoma. We also functionally validate CEP350 as a new tumor-suppressor gene in human melanoma. SB mutagenesis has thus helped to catalog the cooperative molecular mechanisms driving BRAF(V600E) melanoma and discover new genes with potential clinical importance in human melanoma.

Transposon mutagenesis identifies genes and evolutionary forces driving gastrointestinal tract tumor progression.

To provide a more comprehensive understanding of the genes and evolutionary forces driving colorectal cancer (CRC) progression, we performed Sleeping Beauty (SB) transposon mutagenesis screens in mice carrying sensitizing mutations in genes that act at different stages of tumor progression. This approach allowed us to identify a set of genes that appear to be highly relevant for CRC and to provide a better understanding of the evolutionary forces and systems properties of CRC. We also identified six genes driving malignant tumor progression and a new human CRC tumor-suppressor gene, ZNF292, that might also function in other types of cancer. Our comprehensive CRC data set provides a resource with which to develop new therapies for treating CRC.

Sleeping Beauty mutagenesis: exploiting forward genetic screens for cancer gene discovery.

Sleeping Beauty (SB) is a powerful insertional mutagen used in somatic forward genetic screens to identify novel candidate cancer genes. In the past two years, SB has become widely adopted to model human pancreatic, hepatocellular, colorectal and neurological cancers to identify loci that participate in tumor initiation, progression and metastasis. Oncogenomic approaches have directly linked hundreds of genes identified by SB with human cancers, many with prognostic implications. These SB candidate cancer genes are aiding to prioritize punitive human cancer genes for follow-up studies and as possible biomarkers or therapeutic targets. This review highlights recent advances in SB cancer gene discovery, approaches to validate candidate cancer genes, and efforts to integrate SB data across all tumor types to prioritize drug development and tumor specificity.

Transposon insertional mutagenesis models of cancer.

Transposon-based insertional mutagenesis in the mouse provides a powerful approach for identifying new cancer genes. Transposon insertions in cancer genes are selected during tumor development because of their positive effect on tumor growth, and the transposon insertion sites in tumors thus serve as tags for identifying new cancer genes. Direct comparisons of transposon-mutated genes in mouse tumors with mutated genes in human tumors can lend insight into the genes and signaling pathways that drive tumorigenesis. This is critical for prioritizing genes for further study, either for their efficacy as biomarkers or drug targets. In this article, we will introduce DNA transposon-based systems used for gene discovery in mice and discuss their application to identify candidate cancer genes in light of recently published tumor studies.

MelanomaDB: A Web Tool for Integrative Analysis of Melanoma Genomic Information to Identify Disease-Associated Molecular Pathways.

Despite on-going research, metastatic melanoma survival rates remain low and treatment options are limited. Researchers can now access a rapidly growing amount of molecular and clinical information about melanoma. This information is becoming difficult to assemble and interpret due to its dispersed nature, yet as it grows it becomes increasingly valuable for understanding melanoma. Integration of this information into a comprehensive resource to aid rational experimental design and patient stratification is needed. As an initial step in this direction, we have assembled a web-accessible melanoma database, MelanomaDB, which incorporates clinical and molecular data from publically available sources, which will be regularly updated as new information becomes available. This database allows complex links to be drawn between many different aspects of melanoma biology: genetic changes (e.g., mutations) in individual melanomas revealed by DNA sequencing, associations between gene expression and patient survival, data concerning drug targets, biomarkers, druggability, and clinical trials, as well as our own statistical analysis of relationships between molecular pathways and clinical parameters that have been produced using these data sets. The database is freely available at http://genesetdb.auckland.ac.nz/melanomadb/about.html. A subset of the information in the database can also be accessed through a freely available web application in the Illumina genomic cloud computing platform BaseSpace at http://www.biomatters.com/apps/melanoma-profiler-for-research. The MelanomaDB database illustrates dysregulation of specific signaling pathways across 310 exome-sequenced melanomas and in individual tumors and identifies the distribution of somatic variants in melanoma. We suggest that MelanomaDB can provide a context in which to interpret the tumor molecular profiles of individual melanoma patients relative to biological information and available drug therapies.

Using targeted transgenic reporter mice to study promoter-specific p53 transcriptional activity.

The p53 transcription factor modulates gene expression programs that induce cell cycle arrest, senescence, or apoptosis, thereby preventing tumorigenesis. However, the mechanisms by which these fates are selected are unclear. Our objective is to understand p53 target gene selection and, thus, enable its optimal manipulation for cancer therapy. We have generated targeted transgenic reporter mice in which EGFP expression is driven by p53 transcriptional activity at a response element from either the p21 or Puma promoter, which induces cell cycle arrest/senescence and apoptosis, respectively. We demonstrate that we could monitor p53 activity in vitro and in vivo and detect variations in p53 activity depending on the response element, tissue type, and stimulus, thereby validating our reporter system and illustrating its utility for preclinical drug studies. Our results also show that the sequence of the p53 response element itself is sufficient to strongly influence p53 target gene selection. Finally, we use our reporter system to provide evidence for p53 transcriptional activity during early embryogenesis, showing that p53 is active as early as embryonic day 3.5 and that p53 activity becomes restricted to embryonic tissue by embryonic day 6.5. The data from this study demonstrate that these reporter mice could serve as powerful tools to answer questions related to basic biology of the p53 pathway, as well as cancer therapy and drug discovery.

Defective sister-chromatid cohesion, aneuploidy and cancer predisposition in a mouse model of type II Rothmund-Thomson syndrome.

Type II Rothmund-Thomson syndrome (Type II RTS) is a rare autosomal recessive genetic disorder characterized by a congenital skin rash, birth defects of the skeleton, genomic instability and cancer predisposition. It is caused by mutations in the RECQL4 gene and thus represents one of the three cancer-prone genetic diseases that are caused by mutations in a RecQ helicase-encoding gene. Genomic instability has been suspected as a major underlying cause of this disease, and analyses of Type II RTS patient-derived cells demonstrate unusually high frequencies of chromosomal aberrations, suggesting the involvement of chromosomal instability. However, the nature of the instability induced by RECQL4 mutations has not been clearly defined. We created a viable Recql4 mutant mouse model. These mice exhibit a distinctive skin abnormality, birth defects of the skeletal system, genomic instability and increased cancer susceptibility in a sensitized genetic background. Thus, they provide a useful model for studying Type II RTS. In addition, we demonstrate that cells from these mutant mice have high frequencies of premature centromere separation and aneuploidy. Thus, our observations provide evidence for a previously unsuspected role for Recql4 in sister-chromatid cohesion, and suggest that the chromosomal instability may be the underlying cause of cancer predisposition and birth defects in these mutant mice.

Association between the phenylethanolamine N-methyltransferase gene and multiple sclerosis.

Phenylethanolamine N-methyltransferase (PNMT), the terminal enzyme of the catecholamine biosynthesis pathway, catalyzes the conversion of norepinephrine (NE) to epinephrine (EPI). PNMT is a candidate gene for multiple sclerosis (MS) for two reasons. PNMT is known to map to a region identified in two genome screens for MS and it directly regulates the amounts of NE and EPI, both of which play a significant role in the modulation of the innate immune response. The frequencies of two promoter polymorphisms of the PNMT gene showed genetic association in a case-control study of 108 patients with MS and 774 ethnically and age-matched control subjects. In subjects with MS, significant differences in the frequency of the GG genotype at the G-387A marker and the AA genotype at the G-182A marker were observed. Additionally, when both markers were combined and evaluated, highly significant differences between the polymorphism distributions in patients with MS and control subjects were detected. The data suggest that these promoter polymorphisms of the PNMT gene, both independently and cumulatively, show association with MS.