Significance of murine retroviral mutagenesis for identification of disease genes in human acute myeloid leukemia

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.

Comprehensive investigation of parameter choice in viral integration site analysis and its effects on the gene annotations produced

Introducing therapeutic genes into hematopoietic stem cells using retroviral vector-mediated gene transfer is an effective treatment for monogenic diseases. The risks of therapeutic gene integration include aberrant expression of a neighboring gene, resulting in oncogenesis at low frequencies (10(-7)-10(-6)/transduced cell). Mechanisms governing insertional mutagenesis are the subject of intensive ongoing studies that produce large amounts of sequencing data representing genomic regions flanking viral integration sites (IS). Validating and analyzing these data require automated bioinformatics applications. The exact methods used vary between applications, based on the requirements and preferences of the designer. The parameters used to analyze sequence data are capable of shaping the resulting integration site annotations, but a comprehensive examination of these effects is lacking. Here we present a web-based tool for integration site analysis, called Methods for Analyzing ViRal Integration Collections (MAVRIC), and use its highly customizable interface to look at how IS annotations can vary based on the analysis parameters. We used the integration data of the previously published adenosine deaminase severe combined immunodeficiency (ADA-SCID) gene therapy trials for evaluation of MAVRIC. The output illustrates how MAVRIC allows for direct multiparameter comparison of integration patterns. Careful analysis of the SCID data and reanalyses using different parameters for trimming, alignment, and repeat masking revealed the degree of variation that can be expected to arise due to changes in these parameters. We observed mainly small differences in annotation, with the largest effects caused by masking repeat sequences and by changing the size of the window around the IS.

In ovo eye electroporation

Electroporation has been used successfully to introduce macromolecules such as DNA into the chick embryo for at least 15 years. Purified plasmid DNA is microinjected into embryo and then a series of low voltage electrical pulses are applied to the embryo which allows naked DNA to enter cells. Following entrance into the cytoplasm, the DNA is transported to the nucleus where it is transiently expressed. This powerful technique is useful for studies involving overexpression, misexpression, and knockdown of genes of interest at a variety of developmental timepoints.

Computational identification of insertional mutagenesis targets for cancer gene discovery

Insertional mutagenesis is a potent forward genetic screening technique used to identify candidate cancer genes in mouse model systems. An important, yet unresolved issue in the analysis of these screens, is the identification of the genes affected by the insertions. To address this, we developed Kernel Convolved Rule Based Mapping (KC-RBM). KC-RBM exploits distance, orientation and insertion density across tumors to automatically map integration sites to target genes. We perform the first genome-wide evaluation of the association of insertion occurrences with aberrant gene expression of the predicted targets in both retroviral and transposon data sets. We demonstrate the efficiency of KC-RBM by showing its superior performance over existing approaches in recovering true positives from a list of independently, manually curated cancer genes. The results of this work will significantly enhance the accuracy and speed of cancer gene discovery in forward genetic screens. KC-RBM is available as R-package.

High levels of the adhesion molecule CD44 on leukemic cells generate acute myeloid leukemia relapse after withdrawal of the initial transforming event

Multiple genetic hits are detected in patients with acute myeloid leukemia (AML). To investigate this further, we developed a tetracycline-inducible mouse model of AML, in which the initial transforming event, overexpression of HOXA10, can be eliminated. Continuous overexpression of HOXA10 is required to generate AML in primary recipient mice, but is not essential for maintenance of the leukemia. Transplantation of AML to secondary recipients showed that in established leukemias, ∼80% of the leukemia-initiating cells (LICs) in bone marrow stopped proliferating upon withdrawal of HOXA10 overexpression. However, the population of LICs in primary recipients is heterogeneous, as ∼20% of the LICs induce leukemia in secondary recipients despite elimination of HOXA10-induced overexpression. Intrinsic genetic activation of several proto-oncogenes was observed in leukemic cells resistant to inactivation of the initial transformation event. Interestingly, high levels of the adhesion molecule CD44 on leukemic cells are essential to generate leukemia after removal of the primary event. This suggests that extrinsic niche-dependent factors are also involved in the host-dependent outgrowth of leukemias after withdrawal of HOXA10 overexpression event that initiates the leukemia.

Pathway analysis in microarray data: a comparison of two different pathway analysis devices in the same data set

Oligonucleotide microarray technology has been developed to a very powerful and favorable biotechnique. However, it is an explicit challenge to judge the potential biological meaning of such extensive amounts of data. There are various-commercially available or free-software applications for pathway analyses on microarray data on the market. The aim of the present study was to test whether pathway analyses on the same data set using different commercially available devices lead to roughly comparable or massively diverging results and, if so, to give potential explanations. Two different commercially available pathway analysis programs (GeneGo and Pathway Studio 6) have been elected. The programs have been compared concerning their different analyses tools, underlying databases, database constructions, and network-building algorithms. The same data set has been uploaded into two different programs. Pathway analysis was performed according to the following three criteria: the five top networks, the five top diseases, and the five top canonical networks that are associated with the uploaded gene list. The different programs differ in extracting their information from the literature, in database construction, and network-building algorithms. The "top networks," as suggested by the programs as to be "most important," substantially differ from each other and share only one same gene. Concerning the most represented diseases in the data set, there are certain overlaps but no uniform results in the different applications. Pathway analyses of microarray data using preformed software devices offer valuable options for investigating on the biological relevance and function of a focus gene set. However, there is no standard in constructing such programs. This leads to substantial differences when investigating on the same data set using different devices. The intention of this work is to sensitize for the potentialities and also pitfalls doing pathway analysis using automated software tools.

Functional characterization of high levels of meningioma 1 as collaborating oncogene in acute leukemia

Retroviral expression of leukemogenic oncogenes in the murine hematopoietic system is essential but not sufficient to induce acute leukemia. Proviral integration-mediated elevated expression of the meningioma 1 (MN1) oncogene suggested MN1 acting as cooperating event in mixed-lineage leukemia 1 (MLL) and eleven nineteen leukemia (ENL)-induced murine leukemia. Indeed, co-expression of MN1 with MLL-ENL enhanced transformation in vivo, and resulted in a significantly reduced latency for induction of an aggressive acute leukemia when compared with MN1 or MLL-ENL alone. In addition, co-expression of MN1 increased the granulocyte macrophage progenitor cell population with leukemia-initiating properties as shown in secondary transplantation experiments. Gene expression profiling experiments identified putative downstream MN1 targets, of which FMS-like tyrosine kinase 3 (FLT3) and CD34 were upregulated in both MN1-overexpressing murine leukemias and in pediatric acute leukemias with high MN1 levels. Interestingly, small interfering RNA (siRNA)-mediated MN1 knockdown resulted in cell cycle arrest and impaired clonogenic growth of human leukemia cell lines with high MN1 levels. Our work shows for the first time that high MN1 levels are important for the growth of leukemic cells, and that increased MN1 expression can synergize with MLL-ENL and probably other transforming fusion genes in leukemia induction through a distinct gene expression program that is able to expand the leukemia-initiating cell population.

High-throughput insertional mutagenesis screens in mice to identify oncogenic networks

Retroviral insertional mutagenesis screens have been used for many years as a tool for cancer gene discovery. In recent years, completion of the mouse genome sequence as well as improved technologies for cloning and sequencing of retroviral insertions have greatly facilitated the retrieval of more complete data sets from these screens. The concomitant increase of the size of the screens allows researchers to address new questions about the genes and signalling networks involved in tumour development. In addition, the development of new insertional mutagenesis tools such as DNA transposons enables screens for cancer genes in tissues that previously could not be analysed by retroviral insertional mutagenesis.

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 decade of genome-wide gene expression profiling in acute myeloid leukemia: flashback and prospects

The past decade has shown a marked increase in the use of high-throughput assays in clinical research into human cancer, including acute myeloid leukemia (AML). In particular, genome-wide gene expression profiling (GEP) using DNA microarrays has been extensively used for improved understanding of the diagnosis, prognosis, and pathobiology of this heterogeneous disease. This review discusses the progress that has been made, places the technologic limitations in perspective, and highlights promising future avenues.

Retroviral insertion mutagenesis in mice as a comparative oncogenomics tool to identify disease genes in human leukemia

Retroviral insertion mutagenesis has recently received much attention because of its adverse effects in the application of retroviral vector-based gene therapy, resulting in leukemia in certain patients. At the same time, retroviral mutagenesis in mice is being considered a powerful forward genetic strategy to identify disease genes involved in cancer. The publication of the mouse genome sequence and the development of high-throughput genomic approaches have given a further boost to this rapidly evolving field. The increasing numbers of new potential oncogenes identified in retroviral screens have given a valuable basis for a better understanding of cancer related pathways in mice. Important challenges that now lie ahead of us are (i) to determine the relevance and causal relationship of these genes with various types of human cancer (ii) to develop strategies to identify tumor suppressor genes on a large scale, (iii) to place the disease genes into regulatory networks to better understand their role in the complex pathogenesis of cancer, and (iv) to determine their value for diagnosis refinement and therapeutic target intervention in human disease. In this review, we will give a brief update of the current state-of-the-art and thoughts concerning these issues. We will specifically focus on the value of employing retroviral insertion mutagenesis in mice and gene expression profiling in man in the context of acute myeloid leukemia.

Acute Myeloid Leukemia: The Challenge of Capturing Disease Variety

The difference between success and failure of treatment of acute myeloid leukemia (AML) is largely determined by genotypic leukemia-specific differences among patients. The diversity of AML genotypes result from somatic genetic alterations settling down in succession in an individual’s leukemia clone during the development of the disease. Gene mutations, gene expression abnormalities and other molecular alterations (e.g., microRNA variations) affect critical functions in AML cells, and may exert profound effects on the therapeutic response and outcome of the disease. Prototypes of common clinically significant gene aberrations involve transcription factors, signaling molecules and growth factor receptors. The expanding knowledge in this area allowing for risk stratified therapy decisions and the development of targeted drug therapy, is becoming an increasingly important part of the modern individualized clinical management of AML. This chapter highlights recent insights into the diagnostic, prognostic and therapeutic impact of chromosomal (e.g., the so-called monosomal karyotype) as well as particular genomic abnormalities, and presents examples of decision algorithms for individualized therapy.

Retroviral insertions in the VISION database identify molecular pathways in mouse lymphoid leukemia and lymphoma

AKXD recombinant inbred (RI) strains develop a variety of leukemias and lymphomas due to somatically acquired insertions of retroviral DNA into the genome of hematopoetic cells that can mutate cellular proto-oncogenes and tumor suppressor genes. We generated a new set of tumors from nine AKXD RI strains selected for their propensity to develop B-cell tumors, the most common type of human hematopoietic cancers. We employed a PCR technique called viral insertion site amplification (VISA) to rapidly isolate genomic sequence at the site of provirus insertion. Here we describe 550 VISA sequence tags (VSTs) that identify 74 common insertion sites (CISs), of which 21 have not been identified previously. Several suspected proto-oncogenes and tumor suppressor genes lie near CISs, providing supportive evidence for their roles in cancer. Furthermore, numerous previously uncharacterized genes lie near CISs, providing a pool of candidate disease genes for future research. Pathway analysis of candidate genes identified several signaling pathways as common and powerful routes to blood cancer, including Notch, E-protein, NFκB, and Ras signaling. Misregulation of several Notch signaling genes was confirmed by quantitative RT-PCR. Our data suggest that analyses of insertional mutagenesis on a single genetic background are biased toward the identification of cooperating mutations. This tumor collection represents the most comprehensive study of the genetics of B-cell leukemia and lymphoma development in mice. We have deposited the VST sequences, CISs in a genome viewer, histopathology, and molecular tumor typing data in a public web database called VISION (Viral Insertion Sites Identifying Oncogenes), which is located at http://www.mouse-genome.bcm.tmc.edu/vision.

Viral insertion in Evi12 causes expression of aberrant Grp94 mRNAs containing the viral gag myristylation motif

Ecotropic Virus Integration site 12 (Evi12) is a common virus insertion site (cVIS) in retrovirally induced murine models of leukemia and lymphoma, suggesting an important role for this locus in these hematopoietic disorders. Evi12 is located near the promoter of the ER chaperone protein and Hsp90 family member Grp94. Here we show that viral insertion in Evi12 results in the expression of aberrant Grp94 transcripts in Cas-Br-MuLV as well as in AKXD induced hematopoietic tumors, demonstrating that Grp94 is a common viral target gene. While most transcripts encode for truncated forms of Grp94, transcripts containing viral gag sequences were detected in the leukemia cell line NFS107. Interestingly, these fusion transcripts encode for myristylated viral-Grp94 fusion proteins that localize to the plasma membrane. Combined with recent evidence that myristylated forms of Hsp90 transform cells, our data suggest that myristylation of target genes may be an important mechanism in retrovirally mediated oncogenesis. Since retroviral insertion in Evi12 also affects the expression of a recently identified novel gene Grp94 neighboring nucleotidase (Gnn), located at the other side of Evi12, it appears that proviral insertion can lead to deregulation of two genes present in the same locus.

Quantitative expression profiling guided by common retroviral insertion sites reveals novel and cell type specific cancer genes in leukemia

Proviral insertional mutagenesis is a powerful tool for the discovery of cancer-associated genes. The ability of integrated proviruses to affect gene expression over long distances combined with the lack of methods to determine the expression levels of large numbers of genes in a systematic and truly quantitative manner have limited the identification of cancer genes by proviral insertional mutagenesis. Here, we have characterized a new model of proviral insertional mutagenesis-induced lymphoid tumors derived from Eed Polycomb group gene mutant mice and quantitatively determined the expression levels of all genes within 100 kb of 20 different retroviral common insertion sites (CISs) identified in these tumors. Using high-throughput quantitative reverse transcription-polymerase chain reaction (Q-RT-PCR), we document an average of 13 CIS-associated genes deregulated per tumor, half of which are leukemia subtype-specific, while the others are coordinately deregulated in the majority of tumors analyzed. Interestingly, we find that genes located distantly from common proviral integration sites are as frequently deregulated as proximal genes, with multiple genes affected per integration. Our studies reveal an unsuspected conservation in the group of genes deregulated among phenotypically similar subtypes of lymphoid leukemias, and suggest that identification of common molecular determinants of this disease is within reach.

Co-occurrence analysis of insertional mutagenesis data reveals cooperating oncogenes

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.

Insertional mutagenesis in gene therapy and stem cell biology

PURPOSE OF REVIEW

Recent preclinical and clinical studies revealed that the semirandom insertion of transgenes into chromosomal DNA of hematopoietic cells may induce clonal competition, which potentially may even trigger leukemia or sarcoma. Insertional mutagenesis caused by gene vectors has thus led to major uncertainty among those developing advanced hematopoietic cell therapies. This review summarizes novel studies of underlying mechanisms; these studies have demonstrated the possibility of improved gene vector biosafety and generated new insights into stem cell biology.

RECENT FINDINGS

The characteristic insertion pattern of various retroviral gene vector systems may be explained by properties of the viral integrase and associated cellular cofactors. Cell culture assays and animal models, including disease-specific and cancer-prone mouse models, are emerging that reveal the contributions of vector features and systemic factors to induction of clonal imbalance. Databases summarizing vector insertion sites in dominant hematopoietic clones are evolving as new tools to identify genes that regulate clonal homeostasis.

SUMMARY

Mechanistic studies of insertional mutagenesis by random gene vector insertion will lead to improved tools for advanced hematopoietic cell therapy. Simultaneously, fascinating insights into gene networks that regulate cell fitness will be generated, with important consequences for the fields of hematology, oncology and regenerative medicine.

Retroviral vector insertion sites associated with dominant hematopoietic clones mark "stemness" pathways

Evidence from model organisms and clinical trials reveals that the random insertion of retrovirus-based vectors in the genome of long-term repopulating hematopoietic cells may increase self-renewal or initiate malignant transformation. Clonal dominance of nonmalignant cells is a particularly interesting phenotype as it may be caused by the dysregulation of genes that affect self-renewal and competitive fitness. We have accumulated 280 retrovirus vector insertion sites (RVISs) from murine long-term studies resulting in benign or malignant clonal dominance. RVISs (22.5%) are located in or near (up to 100 kb [kilobase]) to known proto-oncogenes, 49.6% in signaling genes, and 27.9% in other or unknown genes. The resulting insertional dominance database (IDDb) shows substantial overlaps with the transcriptome of hematopoietic stem/progenitor cells and the retrovirus-tagged cancer gene database (RTCGD). RVISs preferentially marked genes with high expression in hematopoietic stem/progenitor cells, and Gene Ontology revealed an overrepresentation of genes associated with cell-cycle control, apoptosis signaling, and transcriptional regulation, including major "stemness" pathways. The IDDb forms a powerful resource for the identification of genes that stimulate or transform hematopoietic stem/progenitor cells and is an important reference for vector biosafety studies in human gene therapy.

Commonly dysregulated genes in murine APL cells

To identify genes that are commonly dysregulated in a murine model of acute promyelocytic leukemia (APL), we first defined gene expression patterns during normal murine myeloid development; serial gene expression profiling studies were performed with primary murine hematopoietic progenitors that were induced to undergo myeloid maturation in vitro with G-CSF. Many genes were reproducibly expressed in restricted developmental "windows," suggesting a structured hierarchy of expression that is relevant for the induction of developmental fates and/or differentiated cell functions. We compared the normal myeloid developmental transcriptome with that of APL cells derived from mice expressing PML-RARalpha under control of the murine cathepsin G locus. While many promyelocyte-specific genes were highly expressed in all APL samples, 116 genes were reproducibly dysregulated in many independent APL samples, including Fos, Jun, Egr1, Tnf, and Vcam1. However, this set of commonly dysregulated genes was expressed normally in preleukemic, early myeloid cells from the same mouse model, suggesting that dysregulation occurs as a "downstream" event during disease progression. These studies suggest that the genetic events that lead to APL progression may converge on common pathways that are important for leukemia pathogenesis.