Co-occurrence analysis of insertional mutagenesis data reveals cooperating oncogenes

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.

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.

Transposon Mutagenesis Screen Identifies Potential Lung Cancer Drivers and CUL3 as a Tumor Suppressor

Non-small cell lung cancers (NSCLC) harbor thousands of passenger events that hide genetic drivers. Even highly recurrent events in NSCLC, such as mutations in PTEN, EGFR, KRAS, and ALK, are detected, at most, in only 30% of patients. Thus, many unidentified low-penetrant events are causing a significant portion of lung cancers. To detect low-penetrance drivers of NSCLC, a forward genetic screen was performed in mice using the Sleeping Beauty (SB) DNA transposon as a random mutagen to generate lung tumors in a Pten-deficient background. SB mutations coupled with Pten deficiency were sufficient to produce lung tumors in 29% of mice. Pten deficiency alone, without SB mutations, resulted in lung tumors in 11% of mice, whereas the rate in control mice was approximately 3%. In addition, thyroid cancer and other carcinomas, as well as the presence of bronchiolar and alveolar epithelialization, in mice deficient for Pten were also identified. Analysis of common transposon insertion sites identified 76 candidate cancer driver genes. These genes are frequently dysregulated in human lung cancers and implicate several signaling pathways. Cullin3 (Cul3), a member of a ubiquitin ligase complex that plays a role in the oxidative stress response pathway, was identified in the screen and evidence demonstrates that Cul3 functions as a tumor suppressor.

IMPLICATIONS

This study identifies many novel candidate genetic drivers of lung cancer and demonstrates that CUL3 acts as a tumor suppressor by regulating oxidative stress.

Detecting recurrent gene mutation in interaction network context using multi-scale graph diffusion

Background

Delineating the molecular drivers of cancer, i.e. determining cancer genes and the pathways which they deregulate, is an important challenge in cancer research. In this study, we aim to identify pathways of frequently mutated genes by exploiting their network neighborhood encoded in the protein-protein interaction network. To this end, we introduce a multi-scale diffusion kernel and apply it to a large collection of murine retroviral insertional mutagenesis data. The diffusion strength plays the role of scale parameter, determining the size of the network neighborhood that is taken into account. As a result, in addition to detecting genes with frequent mutations in their genomic vicinity, we find genes that harbor frequent mutations in their interaction network context.

Results

We identify densely connected components of known and putatively novel cancer genes and demonstrate that they are strongly enriched for cancer related pathways across the diffusion scales. Moreover, the mutations in the clusters exhibit a significant pattern of mutual exclusion, supporting the conjecture that such genes are functionally linked. Using multi-scale diffusion kernel, various infrequently mutated genes are found to harbor significant numbers of mutations in their interaction network neighborhood. Many of them are well-known cancer genes.

Conclusions

The results demonstrate the importance of defining recurrent mutations while taking into account the interaction network context. Importantly, the putative cancer genes and networks detected in this study are found to be significant at different diffusion scales, confirming the necessity of a multi-scale analysis.

TAPDANCE: an automated tool to identify and annotate transposon insertion CISs and associations between CISs from next generation sequence data

Background

Next generation sequencing approaches applied to the analyses of transposon insertion junction fragments generated in high throughput forward genetic screens has created the need for clear informatics and statistical approaches to deal with the massive amount of data currently being generated. Previous approaches utilized to 1) map junction fragments within the genome and 2) identify Common Insertion Sites (CISs) within the genome are not practical due to the volume of data generated by current sequencing technologies. Previous approaches applied to this problem also required significant manual annotation.

Results

We describe Transposon Annotation Poisson Distribution Association Network Connectivity Environment (TAPDANCE) software, which automates the identification of CISs within transposon junction fragment insertion data. Starting with barcoded sequence data, the software identifies and trims sequences and maps putative genomic sequence to a reference genome using the bowtie short read mapper. Poisson distribution statistics are then applied to assess and rank genomic regions showing significant enrichment for transposon insertion. Novel methods of counting insertions are used to ensure that the results presented have the expected characteristics of informative CISs. A persistent mySQL database is generated and utilized to keep track of sequences, mappings and common insertion sites. Additionally, associations between phenotypes and CISs are also identified using Fisher’s exact test with multiple testing correction. In a case study using previously published data we show that the TAPDANCE software identifies CISs as previously described, prioritizes them based on p-value, allows holistic visualization of the data within genome browser software and identifies relationships present in the structure of the data.

Conclusions

The TAPDANCE process is fully automated, performs similarly to previous labor intensive approaches, provides consistent results at a wide range of sequence sampling depth, has the capability of handling extremely large datasets, enables meaningful comparison across datasets and enables large scale meta-analyses of junction fragment data. The TAPDANCE software will greatly enhance our ability to analyze these datasets in order to increase our understanding of the genetic basis of cancers.

New methods for finding common insertion sites and co-occurring common insertion sites in transposon- and virus-based genetic screens

Insertional mutagenesis screens in mice are used to identify individual genes that drive tumor formation. In these screens, candidate cancer genes are identified if their genomic location is proximal to a common insertion site (CIS) defined by high rates of transposon or retroviral insertions in a given genomic window. In this article, we describe a new method for defining CISs based on a Poisson distribution, the Poisson Regression Insertion Model, and show that this new method is an improvement over previously described methods. We also describe a modification of the method that can identify pairs and higher orders of co-occurring common insertion sites. We apply these methods to two data sets, one generated in a transposon-based screen for gastrointestinal tract cancer genes and another based on the set of retroviral insertions in the Retroviral Tagged Cancer Gene Database. We show that the new methods identify more relevant candidate genes and candidate gene pairs than found using previous methods. Identification of the biologically relevant set of mutations that occur in a single cell and cause tumor progression will aid in the rational design of single and combinatorial therapies in the upcoming age of personalized cancer therapy.

Insertional mutagenesis in mice deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 reveals cancer gene interactions and correlations with tumor phenotypes

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.

Identification of networks of co-occurring, tumor-related DNA copy number changes using a genome-wide scoring approach

Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs) are one of the ways in which cancer genes are deregulated in tumor cells. We hypothesized that synergistic interactions between cancer genes might be identified by looking for regions of co-occurring gain and/or loss. To this end we developed a scoring framework to separate truly co-occurring aberrations from passenger mutations and dominant single signals present in the data. The resulting regions of high co-occurrence can be investigated for between-region functional interactions. Analysis of high-resolution DNA copy number data from a panel of 95 hematological tumor cell lines correctly identified co-occurring recombinations at the T-cell receptor and immunoglobulin loci in T- and B-cell malignancies, respectively, showing that we can recover truly co-occurring genomic alterations. In addition, our analysis revealed networks of co-occurring genomic losses and gains that are enriched for cancer genes. These networks are also highly enriched for functional relationships between genes. We further examine sub-networks of these networks, core networks, which contain many known cancer genes. The core network for co-occurring DNA losses we find seems to be independent of the canonical cancer genes within the network. Our findings suggest that large-scale, low-intensity copy number alterations may be an important feature of cancer development or maintenance by affecting gene dosage of a large interconnected network of functionally related genes.

It is generally accepted that a normal cell has to acquire multiple mutations in order to become a malignant tumor cell. Considerable effort has been invested in finding single genes involved in tumor initiation and progression, but relatively little is known about the constellations of cancer genes that effectively collaborate in oncogenesis. In this study we focus on the identification of co-occurring DNA copy number alterations (i.e., gains and losses of pieces of DNA) in a series of tumor samples. We describe an analysis method to identify DNA copy number mutations that specifically occur together by examining every possible pair of positions on the genome. We analyze a dataset of hematopoietic tumor cell lines, in which we define a network of specific DNA copy number mutations. The regions in this network contain several well-studied cancer related genes. Upon further investigation we find that the regions of DNA copy number alteration also contain large networks of functionally related genes that have not previously been linked to cancer formation. This might illuminate a novel role for these recurrent DNA copy number mutations in hematopoietic malignancies.

A modified sleeping beauty transposon system that can be used to model a wide variety of human cancers in mice

Recent advances in cancer therapeutics stress the need for a better understanding of the molecular mechanisms driving tumor formation. This can be accomplished by obtaining a more complete description of the genes that contribute to cancer. We previously described an approach using the Sleeping Beauty (SB) transposon system to model hematopoietic malignancies in mice. Here, we describe modifications of the SB system that provide additional flexibility in generating mouse models of cancer. First, we describe a Cre-inducible SBase allele, RosaSBase(LsL), that allows the restriction of transposon mutagenesis to a specific tissue of interest. This allele was used to generate a model of germinal center B-cell lymphoma by activating SBase expression with an Aid-Cre allele. In a second approach, a novel transposon was generated, T2/Onc3, in which the CMV enhancer/chicken beta-actin promoter drives oncogene expression. When combined with ubiquitous SBase expression, the T2/Onc3 transposon produced nearly 200 independent tumors of more than 20 different types in a cohort of 62 mice. Analysis of transposon insertion sites identified novel candidate genes, including Zmiz1 and Rian, involved in squamous cell carcinoma and hepatocellular carcinoma, respectively. These novel alleles provide additional tools for the SB system and provide some insight into how this mutagenesis system can be manipulated to model cancer in mice.

The genotoxic potential of retroviral vectors is strongly modulated by vector design and integration site selection in a mouse model of HSC gene therapy

gamma-Retroviral vectors (gammaRVs), which are commonly used in gene therapy, can trigger oncogenesis by insertional mutagenesis. Here, we have dissected the contribution of vector design and viral integration site selection (ISS) to oncogenesis using an in vivo genotoxicity assay based on transplantation of vector-transduced tumor-prone mouse hematopoietic stem/progenitor cells. By swapping genetic elements between gammaRV and lentiviral vectors (LVs), we have demonstrated that transcriptionally active long terminal repeats (LTRs) are major determinants of genotoxicity even when reconstituted in LVs and that self-inactivating (SIN) LTRs enhance the safety of gammaRVs. By comparing the genotoxicity of vectors with matched active LTRs, we were able to determine that substantially greater LV integration loads are required to approach the same oncogenic risk as gammaRVs. This difference in facilitating oncogenesis is likely to be explained by the observed preferential targeting of cancer genes by gammaRVs. This integration-site bias was intrinsic to gammaRVs, as it was also observed for SIN gammaRVs that lacked genotoxicity in our model. Our findings strongly support the use of SIN viral vector platforms and show that ISS can substantially modulate genotoxicity.

Cancer gene discovery in mouse and man

The elucidation of the human and mouse genome sequence and developments in high-throughput genome analysis, and in computational tools, have made it possible to profile entire cancer genomes. In parallel with these advances mouse models of cancer have evolved into a powerful tool for cancer gene discovery. Here we discuss the approaches that may be used for cancer gene identification in both human and mouse and discuss how a cross-species 'oncogenomics' approach to cancer gene discovery represents a powerful strategy for finding genes that drive tumourigenesis.

A retroviral mutagenesis screen reveals strong cooperation between Bcl11a overexpression and loss of the Nf1 tumor suppressor gene

NF1 inactivation occurs in specific human cancers, including juvenile myelomonocytic leukemia, an aggressive myeloproliferative disorder of childhood. However, evidence suggests that Nf1 loss alone does not cause leukemia. We therefore hypothesized that inactivation of the Nf1 tumor suppressor gene requires cooperating mutations to cause acute leukemia. To search for candidate genes that cooperate with Nf1 deficiency in leukemogenesis, we performed a forward genetic screen using retroviral insertion mutagenesis in Nf1 mutant mice. We identified 43 common proviral insertion sites that contain candidate genes involved in leukemogenesis. One of these genes, Bcl11a, confers a growth advantage in cultured Nf1 mutant hematopoietic cells and causes early onset of leukemia of either myeloid or lymphoid lineage in mice when expressed in Nf1-deficient bone marrow. Bcl11a-expressing cells display compromised p21(Cip1) induction, suggesting that Bcl11a's oncogenic effects are mediated, in part, through suppression of p21(Cip1). Importantly, Bcl11a is expressed in human chronic myelomonocytic leukemia and juvenile myelomonocytic leukemia samples. A subset of AML patients, who had poor outcomes, of 16 clusters, displayed high levels of BCL11A in leukemic cells. These findings suggest that deregulated Bcl11a cooperates with Nf1 in leukemogenesis, and a therapeutic strategy targeting the BCL11A pathway may prove beneficial in the treatment of leukemia.

Resistance of mature T cells to oncogene transformation

Leukemia caused by retroviral insertional mutagenesis after stem cell gene transfer has been reported in several experimental animals and in patients treated for X-linked severe combined immunodeficiency. Here, we analyzed whether gene transfer into mature T cells bears the same genotoxic risk. To address this issue in an experimental "worst case scenario," we transduced mature T cells and hematopoietic progenitor cells from C57BL/6 (Ly5.1) donor mice with high copy numbers of gamma retroviral vectors encoding the potent T-cell oncogenes LMO2, TCL1, or DeltaTrkA, a constitutively active mutant of TrkA. After transplantation into RAG-1-deficient recipients (Ly5.2), animals that received stem cell transplants developed T-cell lymphoma/leukemia for all investigated oncogenes with a characteristic phenotype and after characteristic latency periods. Ligation-mediated polymerase chain reaction analysis revealed monoclonality or oligoclonality of the malignancies. In striking contrast, none of the mice that received T-cell transplants transduced with the same vectors developed leukemia/lymphoma despite persistence of gene-modified cells. Thus, our data provide direct evidence that mature T cells are less prone to transformation than hematopoietic progenitor cells.

Large-scale mutagenesis in p19(ARF)- and p53-deficient mice identifies cancer genes and their collaborative networks

p53 and p19(ARF) are tumor suppressors frequently mutated in human tumors. In a high-throughput screen in mice for mutations collaborating with either p53 or p19(ARF) 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 p19(ARF)-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.

Identifying candidate genes involved in brain tumor formation

Malignant primary brain tumors, gliomas, often overexpress both platelet-derived growth factor (PDGF) ligands and receptors providing an autocrine and/or paracrine boost to tumor growth. Glioblastoma multiforme (GBM) is the most frequent glioma. Its aggressive and infiltrative growth renders it extremely difficult to treat. Median survival after diagnosis is currently only 12-14 months. The present review describes the use of retroviral tagging to identify candidate cancer-causing genes that cooperate with PDGF in brain tumor formation. Newborn mice injected intracerebrally with a Moloney murine leukemia retrovirus carrying the sis/PDGF-B oncogene and a replication competent helper virus developed brain tumors with many characteristics of human gliomas. Analysis of proviral integrations in the brain tumors identified almost 70 common insertion sites (CISs). These CISs were named brain tumor loci and harbored known but also putative novel cancer-causing genes. Microarray analysis identified differentially expressed genes in the mouse brain tumors compared to normal brain. Known tumor genes and markers of immature cells were upregulated in the tumors. Tumors developed 13-42 weeks after injection and short latency tumors were further distinguished as fast growing and GBM-like. Long latency tumors resembled slow-growing oligodendrogliomas and contained significantly less integrations as compared to short latency tumors. Several candidate genes tagged in this retroviral screen have known functions in neoplastic transformation and oncogenesis. Some candidates with a previously unknown function in tumorigenesis were found and their putative role in brain tumor formation will be discussed in this review. The results show that proviral tagging may be a useful tool in the search for candidate glioma genes.