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

Transmicron: accurate prediction of insertion probabilities improves detection of cancer driver genes from transposon mutagenesis screens

Transposon screens are powerful in vivo assays used to identify loci driving carcinogenesis. These loci are identified as Common Insertion Sites (CISs), i.e. regions with more transposon insertions than expected by chance. However, the identification of CISs is affected by biases in the insertion behaviour of transposon systems. Here, we introduce Transmicron, a novel method that differs from previous methods by (i) modelling neutral insertion rates based on chromatin accessibility, transcriptional activity and sequence context and (ii) estimating oncogenic selection for each genomic region using Poisson regression to model insertion counts while controlling for neutral insertion rates. To assess the benefits of our approach, we generated a dataset applying two different transposon systems under comparable conditions. Benchmarking for enrichment of known cancer genes showed improved performance of Transmicron against state-of-the-art methods. Modelling neutral insertion rates allowed for better control of false positives and stronger agreement of the results between transposon systems. Moreover, using Poisson regression to consider intra-sample and inter-sample information proved beneficial in small and moderately-sized datasets. Transmicron is open-source and freely available. Overall, this study contributes to the understanding of transposon biology and introduces a novel approach to use this knowledge for discovering cancer driver genes.

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.

Non-melanoma skin cancers, the most common cancers in the US, are caused by UV skin exposure. Nearly 1 million cases of cutaneous squamous cell carcinoma (cuSCC) are diagnosed in the US each year. While most cuSCCs are highly treatable, more than twice as many individuals die from this disease as from melanoma. The high burden of UV-induced DNA damage in human skin poses a challenge for identifying initiating and cooperating mutations that promote cuSCC development and for defining potential therapeutic targets. Here, we describe a genetic screen in mice using a DNA transposon system to mutagenize the genome of keratinocytes and drive squamous cell carcinoma in the absence of UV. By sequencing where the transposons selectively integrated in the genomes of normal skin, skin with pre-cancerous lesions and skin with fully developed cuSCCs from our mouse model, we were able to identify frequently mutated genes likely important for this disease. Our analysis also defined cooperation between sets of genes not previously appreciated in cuSCC. Our mouse model and ensuing data provide a framework for understanding the genetics of cuSCC and for defining the molecular changes that may lead to the future therapies for patients.

Understanding How Genetic Mutations Collaborate with Genomic Instability in Cancer

Chromosomal instability is the process of mis-segregation for ongoing chromosomes, which leads to cells with an abnormal number of chromosomes, also known as an aneuploid state. Induced aneuploidy is detrimental during development and in primary cells but aneuploidy is also a hallmark of cancer cells. It is therefore believed that premalignant cells need to overcome aneuploidy-imposed stresses to become tumorigenic. Over the past decade, some aneuploidy-tolerating pathways have been identified through small-scale screens, which suggest that aneuploidy tolerance pathways can potentially be therapeutically exploited. However, to better understand the processes that lead to aneuploidy tolerance in cancer cells, large-scale and unbiased genetic screens are needed, both in euploid and aneuploid cancer models. In this review, we describe some of the currently known aneuploidy-tolerating hits, how large-scale genome-wide screens can broaden our knowledge on aneuploidy specific cancer driver genes, and how we can exploit the outcomes of these screens to improve future cancer therapy.

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.

A Genetic Screen to Identify Gain- and Loss-of-Function Modifications that Enhance T-cell Infiltration into Tumors

T-cell-mediated cancer immunotherapies, including anti-PD-1 and T cells expressing chimeric antigen receptors (CAR-T cells), are becoming standard treatments for many cancer types. CAR-T therapy, in particular, has been successful in treating circulating, but not solid, tumors. One challenge limiting immunotherapy success is that tumors lacking T-cell infiltration do not respond to treatment. Therefore, one potential strategy to overcome resistance is to enhance the ability of T cells to traffic into tumors. Here, we describe an unbiased in vivo genetic screen approach utilizing the Sleeping Beauty mutagenesis system to identify candidate genes in T cells that might be modified to drive intratumoral T-cell accumulation. This screen identified over 400 candidate genes in three tumor models. These results indicated substantial variation in gene candidate selection, depending on the tumor model and whether or not mice were treated with anti-PD-1, yet some candidate genes were identified in all tumor models and with anti-PD-1 therapy. Inhibition of the most frequently mutated gene, Aak1, affected chemokine receptor expression and enhanced T-cell trafficking in vitro and in vivo Screen candidates should be further validated as therapeutic targets, with particular relevance to enhancing infiltration of adoptively transferred T cells into solid tumors.

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.

Ex Vivo Transposon-Mediated Genetic Screens for Cancer Gene Discovery

Transposon mutagenesis has emerged as a powerful methodology for functionally annotating cancer genomes. Although in vivo transposon-mediated forward genetic screens have proven to be valuable for cancer gene identification, they are also time consuming and resource intensive. To facilitate the rapid and cost-effective identification of genes that regulate tumor-promoting pathways, we developed a complementary ex vivo transposon mutagenesis approach wherein human or mouse cells growing in culture are mutagenized and screened for the acquisition of specific phenotypes in vitro or in vivo, such as growth factor independence or tumor-forming ability. This approach allows discovery of both gain- and loss-of-function mutations in the same screen. Transposon insertions sites are recovered by high-throughput sequencing. We recently applied this system to comprehensively identify and validate genes that promote growth factor independence and transformation of murine Ba/F3 cells. Here we describe a method for performing ex vivo Sleeping Beauty-mediated mutagenesis screens in these cells, which may be adapted for the acquisition of many different phenotypes in distinct cell types.

Sleeping Beauty Mouse Models of Cancer: Microenvironmental Influences on Cancer Genetics

The Sleeping Beauty (SB) transposon insertional mutagenesis system offers a streamlined approach to identify genetic drivers of cancer. With a relatively random insertion profile, SB is uniquely positioned for conducting unbiased forward genetic screens. Indeed, SB mouse models of cancer have revealed insights into the genetics of tumorigenesis. In this review, we highlight experiments that have exploited the SB system to interrogate the genetics of cancer in distinct biological contexts. We also propose experimental designs that could further our understanding of the relationship between tumor microenvironment and tumor progression.

Mouse models in the era of large human tumour sequencing studies

Cancer is a complex disease in which cells progressively accumulate mutations disrupting their cellular processes. A fraction of these mutations drive tumourigenesis by affecting oncogenes or tumour suppressor genes, but many mutations are passengers with no clear contribution to tumour development. The advancement of DNA and RNA sequencing technologies has enabled in-depth analysis of thousands of human tumours from various tissues to perform systematic characterization of their (epi)genomes and transcriptomes in order to identify (epi)genetic changes associated with cancer. Combined with considerable progress in algorithmic development, this expansion in scale has resulted in the identification of many cancer-associated mutations, genes and pathways that are considered to be potential drivers of tumour development. However, it remains challenging to systematically identify drivers affected by complex genomic rearrangements and drivers residing in non-coding regions of the genome or in complex amplicons or deletions of copy-number driven tumours. Furthermore, functional characterization is challenging in the human context due to the lack of genetically tractable experimental model systems in which the effects of mutations can be studied in the context of their tumour microenvironment. In this respect, mouse models of human cancer provide unique opportunities for pinpointing novel driver genes and their detailed characterization. In this review, we provide an overview of approaches for complementing human studies with data from mouse models. We also discuss state-of-the-art technological developments for cancer gene discovery and validation in mice.

Advances in functional genetic screening with transposons and CRISPR/Cas9 to illuminate cancer biology

Large-scale genome sequencing studies have identified a wealth of mutations in human tumors and have dramatically advanced the field of cancer genetics. However, the functional consequences of an altered gene in tumor progression cannot always be inferred from mutation status alone. This underscores the critical need for complementary methods to assign functional significance to mutated genes in cancer. Transposons are mobile genetic elements that serve as powerful tools for insertional mutagenesis. Over the last decade, investigators have employed mouse models with ondemand transposon-mediated mutagenesis to perform unbiased genetic screens to identify clinically relevant genes that participate in the pathogenesis of human cancer. Two distinct DNA transposon mutagenesis systems, Sleeping Beauty (SB) and PiggyBac (PB), have been applied extensively in vivo and more recently, in ex vivo settings. These studies have informed our understanding of the genes and pathways that drive cancer initiation, progression, and metastasis. This review highlights the latest progress on cancer gene identification for specific cancer subtypes, as well as new technological advances and incorporation of the CRISPR/Cas9 toolbox into transposon-mediated functional genetic studies.

p120-Catenin is an obligate haploinsufficient tumor suppressor in intestinal neoplasia

p120-Catenin (p120) functions as a tumor suppressor in intestinal cancer, but the mechanism is unclear. Here, using conditional p120 knockout in Apc-sensitized mouse models of intestinal cancer, we have identified p120 as an "obligatory" haploinsufficient tumor suppressor. Whereas monoallelic loss of p120 was associated with a significant increase in tumor multiplicity, loss of both alleles was never observed in tumors from these mice. Moreover, forced ablation of the second allele did not further enhance tumorigenesis, but instead induced synthetic lethality in combination with Apc loss of heterozygosity. In tumor-derived organoid cultures, elimination of both p120 alleles resulted in caspase-3-dependent apoptosis that was blocked by inhibition of Rho kinase (ROCK). With ROCK inhibition, however, p120-ablated organoids exhibited a branching phenotype and a substantial increase in cell proliferation. Access to data from Sleeping Beauty mutagenesis screens afforded an opportunity to directly assess the tumorigenic impact of p120 haploinsufficiency relative to other candidate drivers. Remarkably, p120 ranked third among the 919 drivers identified. Cofactors α-catenin and epithelial cadherin (E-cadherin) were also among the highest scoring candidates, indicating a mechanism at the level of the intact complex that may play an important role at very early stages of of intestinal tumorigenesis while simultaneously restricting outright loss via synthetic lethality.

Single-cell analyses to reveal hematopoietic stem cell fate decisions

Hematopoietic stem cells (HSCs) are the best studied adult stem cells with enormous clinical value. Most of our knowledge about their biology relies on assays at the single HSC level. However, only the recent advances in developing new single cell technologies allowed the elucidation of the complex regulation of HSC fate decision control. This Review will focus on current attempts to investigate individual HSCs at molecular and functional levels. The advantages of these technologies leading to groundbreaking insights into hematopoiesis will be highlighted, and the challenges facing these technologies will be discussed. The importance of combining molecular and functional assays to enlighten regulatory networks of HSC fate decision control, ideally at high temporal resolution, becomes apparent for future studies.

DNA Transposition at Work

DNA transposons are defined segments of DNA that are able to move from one genomic location to another. Movement is facilitated by one or more proteins, called the transposase, typically encoded by the mobile element itself. Here, we first provide an overview of the classification of such mobile elements in a variety of organisms. From a mechanistic perspective, we have focused on one particular group of DNA transposons that encode a transposase with a DD(E/D) catalytic domain that is topologically similar to RNase H. For these, a number of three-dimensional structures of transpososomes (transposase-nucleic acid complexes) are available, and we use these to describe the basics of their mechanisms. The DD(E/D) group, in addition to being the largest and most common among all DNA transposases, is the one whose members have been used for a wide variety of genomic applications. Therefore, a second focus of the article is to provide a nonexhaustive overview of transposon applications. Although several non-transposon-based approaches to site-directed genome modifications have emerged in the past decade, transposon-based applications are highly relevant when integration specificity is not sought. In fact, for many applications, the almost-perfect randomness and high frequency of integration make transposon-based approaches indispensable.

Sleeping Beauty transposition: from biology to applications

Sleeping Beauty (SB) is the first synthetic DNA transposon that was shown to be active in a wide variety of species. Here, we review studies from the last two decades addressing both basic biology and applications of this transposon. We discuss how host-transposon interaction modulates transposition at different steps of the transposition reaction. We also discuss how the transposon was translated for gene delivery and gene discovery purposes. We critically review the system in clinical, pre-clinical and non-clinical settings as a non-viral gene delivery tool in comparison with viral technologies. We also discuss emerging SB-based hybrid vectors aimed at combining the attractive safety features of the transposon with effective viral delivery. The success of the SB-based technology can be fundamentally attributed to being able to insert fairly randomly into genomic regions that allow stable long-term expression of the delivered transgene cassette. SB has emerged as an efficient and economical toolkit for safe and efficient gene delivery for medical applications.

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.

Structural Determinants of Sleeping Beauty Transposase Activity

Transposases are important tools in genome engineering, and there is considerable interest in engineering more efficient ones. Here, we seek to understand the factors determining their activity using the Sleeping Beauty transposase. Recent work suggests that protein coevolutionary information can be used to classify groups of physically connected, coevolving residues into elements called "sectors", which have proven useful for understanding the folding, allosteric interactions, and enzymatic activity of proteins. Using extensive mutagenesis data, protein modeling and analysis of folding energies, we show that (i) The Sleeping Beauty transposase contains two sectors, which span across conserved domains, and are enriched in DNA-binding residues, indicating that the DNA binding and endonuclease functions of the transposase coevolve; (ii) Sector residues are highly sensitive to mutations, and most mutations of these residues strongly reduce transposition rate; (iii) Mutations with a strong effect on free energy of folding in the DDE domain of the transposase significantly reduce transposition rate. (iv) Mutations that influence DNA and protein-protein interactions generally reduce transposition rate, although most hyperactive mutants are also located on the protein surface, including residues with protein-protein interactions. This suggests that hyperactivity results from the modification of protein interactions, rather than the stabilization of protein fold.

Comprehensive Ex Vivo Transposon Mutagenesis Identifies Genes That Promote Growth Factor Independence and Leukemogenesis

Aberrant signaling through cytokine receptors and their downstream signaling pathways is a major oncogenic mechanism underlying hematopoietic malignancies. To better understand how these pathways become pathologically activated and to potentially identify new drivers of hematopoietic cancers, we developed a high-throughput functional screening approach using ex vivo mutagenesis with the Sleeping Beauty transposon. We analyzed over 1,100 transposon-mutagenized pools of Ba/F3 cells, an IL3-dependent pro-B-cell line, which acquired cytokine independence and tumor-forming ability. Recurrent transposon insertions could be mapped to genes in the JAK/STAT and MAPK pathways, confirming the ability of this strategy to identify known oncogenic components of cytokine signaling pathways. In addition, recurrent insertions were identified in a large set of genes that have been found to be mutated in leukemia or associated with survival, but were not previously linked to the JAK/STAT or MAPK pathways nor shown to functionally contribute to leukemogenesis. Forced expression of these novel genes resulted in IL3-independent growth in vitro and tumorigenesis in vivo, validating this mutagenesis-based approach for identifying new genes that promote cytokine signaling and leukemogenesis. Therefore, our findings provide a broadly applicable approach for classifying functionally relevant genes in diverse malignancies and offer new insights into the impact of cytokine signaling on leukemia development.

Screening for tumor suppressors: Loss of ephrin receptor A2 cooperates with oncogenic KRas in promoting lung adenocarcinoma

Lung adenocarcinoma, a major form of non-small cell lung cancer, is the leading cause of cancer deaths. The Cancer Genome Atlas analysis of lung adenocarcinoma has identified a large number of previously unknown copy number alterations and mutations, requiring experimental validation before use in therapeutics. Here, we describe an shRNA-mediated high-throughput approach to test a set of genes for their ability to function as tumor suppressors in the background of mutant KRas and WT Tp53. We identified several candidate genes from tumors originated from lentiviral delivery of shRNAs along with Cre recombinase into lungs of Loxp-stop-Loxp-KRas mice. Ephrin receptorA2 (EphA2) is among the top candidate genes and was reconfirmed by two distinct shRNAs. By generating knockdown, inducible knockdown and knockout cell lines for loss of EphA2, we showed that negating its expression activates a transcriptional program for cell proliferation. Loss of EPHA2 releases feedback inhibition of KRAS, resulting in activation of ERK1/2 MAP kinase signaling, leading to enhanced cell proliferation. Intriguingly, loss of EPHA2 induces activation of GLI1 transcription factor and hedgehog signaling that further contributes to cell proliferation. Small molecules targeting MEK1/2 and Smoothened hamper proliferation in EphA2-deficient cells. Additionally, in EphA2 WT cells, activation of EPHA2 by its ligand, EFNA1, affects KRAS-RAF interaction, leading to inhibition of the RAS-RAF-MEK-ERK pathway and cell proliferation. Together, our studies have identified that (i) EphA2 acts as a KRas cooperative tumor suppressor by in vivo screen and (ii) reactivation of the EphA2 signal may serve as a potential therapeutic for KRas-induced human lung cancers.

The utility of transposon mutagenesis for cancer studies in the era of genome editing

The use of transposons as insertional mutagens to identify cancer genes in mice has generated a wealth of information over the past decade. Here, we discuss recent major advances in transposon-mediated insertional mutagenesis screens and compare this technology with other screening strategies.

Use of DNA transposons for functional genetic screens in mouse models of cancer

Cancer is a very heterogeneous disease with complex genetic interactions. In recent years, the systematic sequencing of cancer genomes has provided information to design personalized therapeutic interventions. However, the complexity of cancer genomes commonly makes it difficult to identify specific genes involved in tumour development or therapeutic responsiveness. The generation of mouse models of cancer using transposon-mediated approaches has provided a powerful tool to unveil the role of key genes during cancer development. Here we will discuss how the use of forward and reverse genetic approaches mediated by DNA transposons can support the investigation of cancer pathogenesis, including the identification of cancer promoting mechanisms and potential therapeutic targets.

Library Construction for High-Throughput Mobile Element Identification and Genotyping

Mobile genetic elements are discrete DNA elements that can move around and copy themselves in a genome. As a ubiquitous component of the genome, mobile elements contribute to both genetic and epigenetic variation. Therefore, it is important to determine the genome-wide distribution of mobile elements. Here we present a targeted high-throughput sequencing protocol called Mobile Element Scanning (ME-Scan) for genome-wide mobile element detection. We will describe oligonucleotides design, sequencing library construction, and computational analysis for the ME-Scan protocol.