Supplementary Table 3 from Insertional Mutagenesis in Mice Deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 Reveals Cancer Gene Interactions and Correlations with Tumor Phenotypes

Supplementary Figure Legends 1-3 from Insertional Mutagenesis in Mice Deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 Reveals Cancer Gene Interactions and Correlations with Tumor Phenotypes

Supplementary Tables 1-5 from Novel Candidate Cancer Genes Identified by a Large-Scale Cross-Species Comparative Oncogenomics Approach

Supplementary Figure Legends 1-3 from Insertional Mutagenesis in Mice Deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 Reveals Cancer Gene Interactions and Correlations with Tumor Phenotypes

Retroviral insertional mutagenesis is a powerful tool for identifying putative cancer genes in mice. To uncover the regulatory mechanisms by which common insertion loci affect downstream processes, we supplemented genotyping data with genome-wide mRNA expression profiling data for 97 tumors induced by retroviral insertional mutagenesis. We developed locus expression signature analysis, an algorithm to construct and interpret the differential gene expression signature associated with each common insertion locus. Comparing locus expression signatures to promoter affinity profiles allowed us to build a detailed map of transcription factors whose protein-level regulatory activity is modulated by a particular locus. We also predicted a large set of drugs that might mitigate the effect of the insertion on tumorigenesis. Taken together, our results demonstrate the potential of a locus-specific signature approach for identifying mammalian regulatory mechanisms in a cancer context.

Cancer develops through a multistep process in which normal cells progress to malignant tumors via the evolution of their genomes as a result of the acquisition of mutations in cancer driver genes. The number, identity and mode of action of cancer driver genes, and how they contribute to tumor evolution is largely unknown. This study deployed the Mouse Mammary Tumor Virus (MMTV) as an insertional mutagen to find both the driver genes and the networks in which they function. Using deep insertion site sequencing we identified around 31000 retroviral integration sites in 604 MMTV-induced mammary tumors from mice with mammary gland-specific deletion of Trp53, Pten heterozygous knockout mice, or wildtype strains. We identified 18 known common integration sites (CISs) and 12 previously unknown CISs marking new candidate cancer genes. Members of the Wnt, Fgf, Fgfr, Rspo and Pdgfr gene families were commonly mutated in a mutually exclusive fashion. The sequence data we generated yielded also information on the clonality of insertions in individual tumors, allowing us to develop a data-driven model of MMTV-induced tumor development. Insertional mutations near Wnt and Fgf genes mark the earliest “initiating” events in MMTV induced tumorigenesis, whereas Fgfr genes are targeted later during tumor progression. Our data shows that insertional mutagenesis can be used to discover the mutational networks, the timing of mutations, and the genes that initiate and drive tumor evolution.

We propose mutational genomics as an approach for identifying putative cancer pathways. This approach relies on expression profiling tumors that are induced by retroviral insertional mutagenesis. Akin to genetical genomics, this provides the opportunity to search for associations between tumor-initiating events (the viral insertion sites) and the consequent transcription changes, thus revealing putative regulatory interactions. An important advantage is that in mutational genomics the selective pressure exerted by the tumor growth is exploited to yield a relatively small number of loci that are likely to be causal for tumor formation. This is unlike genetical genomics which relies on the natural occurring genetic variation between samples to reveal the effects of a locus on gene expression. We performed mutational genomics using a set of 97 lymphoma from mice presenting with splenomegaly. This identified several known as well as novel interactions, including many known targets of Notch1 and Gfi1. In addition to direct one-to-one associations, many multilocus networks of association were found. This is indicative of the fact that a cell has many parallel possibilities in which it can reach a state of uncontrolled proliferation. One of the identified networks suggests that Zmiz1 functions upstream of Notch1. Taken together, our results illustrate the potential of mutational genomics as a powerful approach to dissect the regulatory pathways of cancer.

Retroviral and transposon-based insertional mutagenesis (IM) screens are widely used for cancer gene discovery in mice. Exploiting the full potential of IM screens requires methods for high-throughput sequencing and mapping of transposon and retroviral insertion sites. Current protocols are based on ligation-mediated PCR amplification of junction fragments from restriction endonuclease-digested genomic DNA, resulting in amplification biases due to uneven genomic distribution of restriction enzyme recognition sites. Consequently, sequence coverage cannot be used to assess the clonality of individual insertions. We have developed a novel method, called shear-splink, for the semiquantitative high-throughput analysis of insertional mutations. Shear-splink employs random fragmentation of genomic DNA, which reduces unwanted amplification biases. Additionally, shear-splink enables us to assess clonality of individual insertions by determining the number of unique ligation points (LPs) between the adapter and genomic DNA. This parameter serves as a semiquantitative measure of the relative clonality of individual insertions within heterogeneous tumors. Mixing experiments with clonal cell lines derived from mouse mammary tumor virus (MMTV)-induced tumors showed that shear-splink enables the semiquantitative assessment of the clonality of MMTV insertions. Further, shear-splink analysis of 16 MMTV-and 127 Sleeping Beauty (SB)-induced tumors showed enrichment for cancer-relevant insertions by exclusion of irrelevant background insertions marked by single LPs, thereby facilitating the discovery of candidate cancer genes. To fully exploit the use of the shear-splink method, we set up the Insertional Mutagenesis Database (iMDB), offering a publicly available web-based application to analyze both retroviral-and transposon-based insertional mutagenesis data.

Insertional mutagenesis (IM) screens in genetically engineered mouse models of cancer are a powerful tool to identify genes or regions in the genome contributing to tumorigenesis. Current methods to identify the integration sites are not quantitative and do not give information about the clonality of a given insertion in a tumor. Consequently, the results of IM screens are hard to interpret since the obtained data are incomplete and highly biased due to technical variation. We have developed and optimized a next-generation sequencing-based method for ultra high-throughput analysis of insertional mutations in a less biased and quantitative manner. Integration sites of retroviral or transposon based insertional mutagens are amplified using Splinkerette-mediated PCR and subsequent 454 sequencing. In contrast to current protocols, based on restriction enzyme (RE) fragmentation, we randomly shear gDNA, which allows a random ligation of the Splinkerette. This enables us to generate randomly sized amplicons per integration, which reduces amplification- and sequencing bias compared to amplicons with a fixed length per integration using RE based methods. Since Splinkerette ligation can occur at every base pair, we can determine the amount of cells containing the given insertion by counting unique ligation points, each representing a unique chromosome, and thereby a cell, in the tumor. This latter feature, addressing clonality of an insertional mutagen, will allow the identification of both clonal and sub-clonal mutations in genetically heterogeneous tumors. More importantly, we are now able to study co-occurring mutations, e.g. underlying synthetic lethality, which cannot be performed reliably using the current method. The insertional mutagenesis data obtained with the improved method will represent the biological situation of a given integration within a tumor, thereby facilitating subsequent validation experiments. Additionally, data obtained from our retroviral- and transposon-based screens in various mouse models of cancer will serve as a catalogue of cancer-relevant mutations that can be used for cross-species comparative analysis of the large numbers of mutations found in human breast cancer. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2208.

Abstract The cyclin dependent kinase (CDK) inhibitors p15, p16, p21, and p27 are frequently deleted, silenced, or downregulated in many malignancies. Inactivation of CDK inhibitors predisposes mice to tumor development, showing that these genes function as tumor suppressors. Here, we describe high-throughput murine leukemia virus insertional mutagenesis screens in mice that are deficient for one or two CDK inhibitors. We retrieved 9,117 retroviral insertions from 476 lymphomas to define hundreds of loci that are mutated more frequently than expected by chance. Many of these loci are skewed toward a specific genetic context of predisposing germline and somatic mutations. We also found associations between these loci with gender, age of tumor onset, and lymphocyte lineage (B or T cell). Comparison of retroviral insertion sites with single nucleotide polymorphisms associated with chronic lymphocytic leukemia revealed a significant overlap between the datasets. Together, our findings highlight the importance of genetic context within large-scale mutation detection studies, and they show a novel use for insertional mutagenesis data in prioritizing disease-associated genes that emerge from genome-wide association studies. Cancer Res; 70(2); 520–31

Our lab has a long-standing interest in epigenetic gene regulation dictated by chromatin modifications. We study the mechanism of transcriptional repression by Polycomb- group (Pc-G) protein complexes, and the effects of deregulation of Pc-G genes on development, Cell cycle control, cancer formation and stem cell maintenance. In addition, we are performing large-scale genetic screens in primary cells and in cancer-predisposed mice to identify cancer-relevant networks of oncogenes and tumor-suppressor genes. Model organisms comprise Mouse and Drosophila. Functional characterization of Pc-G protein complexes Repressive Pc-G proteins and counteracting Trithorax-group (Trx-G) of nucleosome remodeling factors are involved in maintenance of proper gene expression patterns during development at the level of chromatin structure. Pc-G protein complexes control large sets of genes including Hox gene clusters and the INK4a/ARF tumor suppressor locus. At least two biochemical distinct evolutionary highly conserved Pc-G protein complexes can be distinguished. The first (PRC2) contains EzH1/EzH2 (SET domain proteins acting as Histone H3 methylases), Su(z)12, Eed and histone deacetylases. The second large complex (PRC1) encompasses Bmi1/Mel18, M33/MPc2, Mph1/Mph2 and Ring1b/ Ring1a together with other more loosely associated proteins is required throughout development. To study Pc-G, function we focus on representative members of PRC1 and PRC2 in gain- and loss-of-function studies in mice and Drosophila. In genetic and biochemical experiments we identified the Bmi1/Ring1b heterodimer as an E3 ubiquitin ligase for monoubiquitination of histone H2A (collaboration with

Abstract Comparative genomic hybridization (CGH) can reveal important disease genes but the large regions identified could sometimes contain hundreds of genes. Here we combine high-resolution CGH analysis of 598 human cancer cell lines with insertion sites isolated from 1,005 mouse tumors induced with the murine leukemia virus (MuLV). This cross-species oncogenomic analysis revealed candidate tumor suppressor genes and oncogenes mutated in both human and mouse tumors, making them strong candidates for novel cancer genes. A significant number of these genes contained binding sites for the stem cell transcription factors Oct4 and Nanog. Notably, mice carrying tumors with insertions in or near stem cell module genes, which are thought to participate in cell self-renewal, died significantly faster than mice without these insertions. A comparison of the profile we identified to that induced with the Sleeping Beauty (SB) transposon system revealed significant differences in the profile of recurrently mutated genes. Collectively, this work provides a rich catalogue of new candidate cancer genes for functional analysis. Cancer Res; 70(3); 883–95

Insertional mutagens such as viruses and transposons are a useful tool for performing forward genetic screens in mice to discover cancer genes. These screens are most effective when performed using hundreds of mice; however, until recently, the cost-effective isolation and sequencing of insertion sites has been a major limitation to performing screens on this scale. Here we present a method for the high-throughput isolation of insertion sites using a highly efficient splinkerette-PCR method coupled with capillary or 454 sequencing. This protocol includes a description of the procedure for DNA isolation, DNA digestion, linker or splinkerette ligation, primary and secondary PCR amplification, and sequencing. This method, which takes about 1 week to perform, has allowed us to isolate hundreds of thousands of insertion sites from mouse tumors and, unlike other methods, has been specifically optimized for the murine leukemia virus (MuLV), and can easily be performed in a 96-well plate format for the efficient multiplex isolation of insertion sites.

Nature Reviews Cancer 9, 389–399 (2009) On page 398 of this article, the highlighted description for reference 12 should instead be attributed to reference 11: An elegant study in which a hypomorphic Blm allele is used to induce LOH of retrovirally inactivated tumour suppressor genes. On page 399, the highlighted description for reference 54 should instead be attributed to reference 56: These authors demonstrate that insertional mutagenesis can be used to screen for genes that confer resistance to therapeutic agents in vivo.

p53 and p19ARF are tumor suppressors frequently mutated in human tumors. In a high-throughput screen in mice for mutations collaborating with either p53 or p19ARF deficiency, we identified 10,806 retroviral insertion sites, implicating over 300 loci in tumorigenesis. This dataset reveals 20 genes that are specifically mutated in either p19ARF-deficient, p53-deficient or wild-type mice (including Flt3, mmu-mir-106a-363, Smg6, and Ccnd3), as well as networks of significant collaborative and mutually exclusive interactions between cancer genes. Furthermore, we found candidate tumor suppressor genes, as well as distinct clusters of insertions within genes like Flt3 and Notch1 that induce mutants with different spectra of genetic interactions. Cross species comparative analysis with aCGH data of human cancer cell lines revealed known and candidate oncogenes (Mmp13, Slamf6, and Rreb1) and tumor suppressors (Wwox and Arfrp2). This dataset should prove to be a rich resource for the study of genetic interactions that underlie tumorigenesis.

MOTIVATION Cancers are caused by an accumulation of multiple independent mutations that collectively deregulate cellular pathways, e.g. such as those regulating cell division and cell-death. The publicly available Retroviral Tagged Cancer Gene Database (RTCGD) contains the data of many insertional mutagenesis screens, in which the virally induced mutations result in tumor formation in mice. The insertion loci therefore indicate the location of putative cancer genes. Additionally, the presence of multiple independent insertions within one tumor hints towards a cooperation between the insertionally mutated genes. In this study we focus on the detection of statistically significant co-mutations. RESULTS We propose a two-dimensional Gaussian Kernel Convolution method (2DGKC), a computational technique that identifies the cooperating mutations in insertional mutagenesis data. We define the Common Co-occurrence of Insertions (CCI), signifying the co-mutations that are statistically significant across all different screens in the RTCGD. Significance estimates are made on multiple scales, and the results visualized in a scale space, thereby providing valuable extra information on the putative cooperation. The multidimensional analysis of the insertion data results in the discovery of 86 statistically significant co-mutations, indicating the presence of cooperating oncogenes that play a role in tumor development. Since oncogenes may cooperate with several members of a parallel pathway, we combined the co-occurrence data with gene family information to find significant cooperations between oncogenes and families of genes. We show, for instance, the interchangeable cooperation of Myc insertions with insertions in the Pim family. AVAILABILITY A list of the resulting CCIs is available at: http://ict.ewi.tudelft.nl/~jeroen/CCI/CCI_list.txt.

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.

Retroviral insertion mutagenesis screens in mice are powerful tools for efficient identification of oncogenic mutations in an in vivo setting. Many oncogenes identified in these screens have also been shown to play a causal role in the development of human cancers. Sequencing and annotation of the mouse genome, along with recent improvements in insertion site cloning has greatly facilitated identification of oncogenic events in retrovirus-induced tumours. In this review, we discuss the features of retroviral insertion mutagenesis screens, covering the mechanisms by which retroviral insertions mutate cellular genes, the practical aspects of insertion site cloning, the identification and analysis of common insertion sites, and finally we address the potential for use of somatic insertional mutagens in the study of nonhaematopoietic and nonmammary tumour types.

The nucleotide excision repair (NER) system consists of two sub-pathways, global genome repair (GGR) and transcription-coupled repair (TCR), which exhibit distinct functions in the cellular response to genotoxic stress. Defects in TCR result in prolonged UV light-induced stalling of RNA polymerase II and hypersensitivity to apoptosis induced by UV and certain chemotherapeutic drugs. Here, we show that low doses of UV trigger delayed activation of the stress-induced MAPkinase JNK and its proapoptotic targets c-Jun and ATF-3 in TCR-deficient primary human fibroblasts from Xeroderma Pigmentosum (XP) and Cockayne syndrome (CS) patients. This delayed activation of the JNK pathway is not observed in GGR-deficient TCR-proficient XP cells, is independent of functional p53, and is established through repression of the JNK-phosphatase MKP-1 rather than by activation of the JNK kinases MKK4 and 7. Enzymatic reversal of UV-induced cyclobutane pyrimidine dimers (CPDs) by CPD photolyase abrogated JNK activation, MKP-1 repression, and apoptosis in TCR-deficient XPA cells. Ectopic expression of MKP-1 inhibited DNA-damage-induced JNK activity and apoptosis. These results identify both MKP-1 and JNK as sensors and downstream effectors of persistent DNA damage in transcribed genes and suggest a link between the JNK pathway and UV-induced stalling of RNApol II.