CHAPTER FOUR

New Insight into Cancer Aneuploidy in Zebrafish GuangJun Zhang1, *, Jer-Yen Yang2 and Zhibin Cui1 1

Department of Comparative Pathobiology, Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN, USA Department of Basic Medical Sciences, Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN, USA *Corresponding author: E-mail: [email protected]

2

Contents 1. Introduction 2. The Cause of Aneuploidy 3. Biological Effects of Aneuploidy 3.1 Gene Expression and Dosage Compensation 3.2 Impacts on Organism Fitness 3.3 Cellular Impacts on Noncancerous Cells 3.4 Aneuploidy in Cancer 4. Zebrafish as a Cancer Model for Human Cancers 4.1 Polyploid Zebrafish 4.2 Zebrafish Aneuploid Mutants 4.3 Aneuploid Nature of Zebrafish Cancers 5. Cancer Driver Genes on Aneuploid Chromosomes 5.1 Finding Cancer Driver Genes by Cross-Species Comparisons 5.2 Functional Validations of Cancer Driver Genes 6. Future Directions Acknowledgments References

150 151 152 152 153 154 154 155 156 157 158 159 159 162 162 164 164

Abstract Aneuploidy is one of the most common genetic alterations in cancer cell genomes. It greatly contributes to the heterogeneity of cancer cell genomes, and its roles in tumorigenesis are attracting more and more attentions. Zebrafish is emerging as a new genetic model for many human diseases including cancer. The zebrafish cancer model has shown an equivalent degree of aneuploidy as found in corresponding human cancers, thus it provides a great tool for us to study cancer aneuploidy and, in general, cancer biology. Here, we discuss some new advances of aneuploidy and the potential usages of this cancer model system. International Review of Cell and Molecular Biology, Volume 314 ISSN 1937-6448 http://dx.doi.org/10.1016/bs.ircmb.2014.09.001

© 2015 Elsevier Inc. All rights reserved.

149

j

150

GuangJun Zhang et al.

1. INTRODUCTION For most organisms, their genomes generally are maintained as euploidy (e.g., haploidy and diploidy). When the chromosome number alters from euploidy, we refer to this situation as aneuploidy. Thus, the definition of aneuploidy is quite broad, as it implicates endless combinations of gains and losses of one or more chromosomes. Aneuploidy is regarded as one of the most common causes of miscarriages in the human population, due to the dosage changes of many genes that are involved in embryonic development (Hassold and Hunt, 2001; Nagaoka et al., 2012). However, a few human aneuploidies can survive to the adulthood. Down syndrome is one typical example of a human aneuploidy syndrome, which results from trisomy of chromosome 21. Polyploidy refers to the situation when there are more than two whole sets of chromosomes in cells. In nature, certain species exist as polyploidy. For example, some of bony fish and amphibians with increased ecological tolerance have been reported as tetraploid (Mable et al., 2011), supporting the hypothesis that “ploidy” might increase survival fitness in certain environments (Comai, 2005; Otto, 2007). Even though polyploidy is not thought to commonly occur in mammals, some exceptions have recently been discovered. One such example is normal liver cell, which can be either tetraploid or octoploid in aged mammals (Duncan, 2013; Lee et al., 2009). Certain percentages of neurons in the human central nervous system are also aneuploid, which might contribute the complex neural activities (Rehen et al., 2001). Though aneuploidies may not be commonly found in normal human cells, they are one of the most common genetic alterations in human cancers (Mitelman et al., 2014). Despite the high prevalence of aneuploidy in human cancer cells, it continues to be debated whether aneuploidy is the cause or consequence of the cancer genome instability. Recently, a consistent view has emerged that aneuploidies are playing important roles during tumorigenesis (Gordon et al., 2012; Holland and Cleveland, 2012; Roschke and Rozenblum, 2013; Siegel and Amon, 2012). Since aneuploidy usually has complex karyotypes in human solid tumors and displays a milder phenotype when compared to the diploid counterpart, people have started to suspect that aneuploidy might be the product of genomic instability. However, with the advance of highthroughput genome scanning technologies, such as comparative genomic hybridization (CGH) and parallel massive sequencing, it is clearer than ever that the overall karyotype patterns of most cancer cells are not random, suggesting

New Insight into Cancer Aneuploidy in Zebrafish

151

the existence of selections on chromosomes or chromosome fragments (Beroukhim et al., 2010; Davoli et al., 2013). In this chapter, we will briefly introduce the cause of aneuploidy and its impacts on cellular fitness and gene expression. Then, we will focus on why zebrafish is a good model for studying human cancer aneuploidy. Finally, we will discuss the advantages of this vertebrate model and how we can use zebrafish cancer models to identify cancer driver genes on large-sized aneuploid chromosomes.

2. THE CAUSE OF ANEUPLOIDY The research on aneuploidy has a long history, which can be traced back to the beginning of the last century. Theodor Boveri performed extensive experiments with sea urchin fertilizations and found that double-fertilized eggs were able to generate aneuploid cells, leading to severe developmental defects and causing lethality in the majority of embryos (Boveri, 2008). The first theoretical origin of cancer was thus proposed by Boveri and Davis Housman who found extensive aneuploid cells in many types human tumors about a century ago (Bignold et al., 2006; Satzinger, 2008). Most multicellular organisms develop from fertilized gametes, an ontogeny process that requires millions of cell divisions. On the adult tissue level, certain cells (e.g., adult stem cells) also divide constantly to maintain tissue homeostasis. Thus, the missegregation of chromosomes is unavoidable. Somatic aneuploid cells usually are generated by mitotic error through unbalanced chromosome separation. There are multiple routes that can lead to aneuploid cells. More specific examples include aberrant kinetochore attachment by microtubules of spindles (merotelic attachment, monotelic attachment, syntenic attachment, etc.), spindle assembly checkpoint defects, chromosome cohesion defects, and centrosome mis-amplifications. For details, please refer to previous reviews (Cimini, 2008; Foley and Kapoor, 2013; Kops et al., 2005; Losada, 2014). More ways of generating aneuploid are still being discovered. Recently, it was discovered that endocytosis could also lead to the formation of aneuploid cells (Overholtzer et al., 2007). Interestingly, this is similar to an experimental approach, cell fusion, which was used to study cell biology decades ago (Sidebottom and Deak, 1976). Individuals in which all cells exhibit same aneuploidy usually develop from aneuploid germ cells. During the formation of the gametes, aneuploid gametes could be created through inappropriate chromosome segregations. Chromosome nondisjunction, i.e., failure of separation of chromosome pairs or sister chromatids during cell division, is generally correlated with

152

GuangJun Zhang et al.

increased maternal age (Nagaoka et al., 2012). Human trisomies may result from errors in both meiosis I and meiosis II, although meiosis I errors are more common. In one such example, trisomy 21 (Down syndrome) and trisomy 18 (Edward syndrome) predominately arise during meiosis I and meiosis II, respectively (Hassold et al., 2007). As seen in somatic cells, spindle assembly checkpoint defects can also lead to aneuploid germ cells (Jones and Lane, 2013; Lara-Gonzalez et al., 2012).

3. BIOLOGICAL EFFECTS OF ANEUPLOIDY 3.1 Gene Expression and Dosage Compensation Aneuploid chromosomes usually affect hundreds to thousands of genes, depending on the sizes of the chromosomes. Although it was found that there is a general trend that gene expression is correlated with its copy numbers, many variables have been reported and several different models have been proposed. Briefly, a gene’s expression can either be stable, upregulated (slightly or severely), or downregulated when its DNA copy number increases. Detailed discussions for each of these can be found in other reviews (Birchler et al., 2001; Tang and Amon, 2013). When genes are upregulated or downregulated, one might suspect to have altered gene copy numbers; however, how an individual gene could have stable expression with altered gene copy numbers was not that obvious. The concept of gene dosage compensation, which helped to provide answers to how cells could have gene copy number alterations (CNAs) but stable gene expression, was first introduced for sex chromosomes (Payer and Lee, 2008; Straub and Becker, 2007). The existence of autosome dosage compensation has been debated due to equivocal data from different model organisms, different technologies, and different methods of normalizations and comparisons. Very recently, it was proposed that gene dosage compensation might be taking place at the protein level, rather than the gene expression level, based on data from brewer’s yeast (Torres et al., 2007). This also led to a new concept of “proteotoxic stress,” which might be a targetable feature for cancer treatment if this concept proved to be true. However, protein expression also has been reported to roughly correlate with chromosome numbers in yeast (Pavelka et al., 2010b). Another recent study on human trisomic and tetrosomic cell lines revealed a complex but reasonable scenario: in general, transcription and translation reflect the changes of chromosome copy numbers, but the abundance of some proteins (e.g., protein complexes and protein kinases) is similar to diploid status (Stingele et al., 2012). This phenomenon

New Insight into Cancer Aneuploidy in Zebrafish

153

might be due to the protein stoichiometry through protein folding and proteolysis (Oromendia and Amon, 2014). Furthermore, the gene expression of aneuploidy also varies in different species. For example, in chromosome 5 trisomic Arabidopsis, only 3% of genes showed the effect of dosage compensation (Huettel et al., 2008), whereas 60% of genes showed dosage compensation in segmental trisomic maize on the gene expression level (Makarevitch et al., 2008). In Drosophila melanogaster segmental aneuploid S2 cells, dosage compensation was found in both X chromosomes and autosomes (Zhang et al., 2010b). In allotriploid Iberian cyprinid fish, Squalius alburnoides, the dosage compensation was found in the gene transcription level through random allelic silencing (Pala et al., 2008). As all the reported systems used different models, different aneuploidy, different detection and analysis methods, it is difficult to make direct comparisons. The gene expression impact of aneuploid is not only limited to the involved chromosomes, but also includes other genes on unaffected chromosomes through unbalanced gene regulatory effects (Huettel et al., 2008; Zhang et al., 2013c). Global gene expression alterations have complex effects on the organism and cell fitness. For example, in human trisomy 21, gene expression was found to be affected in not only chromosome 21, but also in all other chromosomes in twin fetal fibroblast transcriptomes. More interestingly, genes were dysregulated in a domain fashion and were therefore named gene expression dysregulation domains. Additionally, this domain-regulated fashion is also syntenicly conserved in mouse model of Down syndrome (Letourneau et al., 2014).

3.2 Impacts on Organism Fitness As reported so far, aneuploidy is usually detrimental and causes affected organisms to be less fit compared to diploid ones, but aneuploidy is also found in nature as a genetic variation (Chen et al., 2012; Siegel and Amon, 2012; Torres et al., 2008). For example, about 8% of the Saccharomyces cerevisiae lab strains from the genome-wide ORF knockout library are aneuploid, and aneuploid yeasts also exist in natural environments (Hughes et al., 2000). Other species such as Candida albicans, Lishmanis sp., and Arabidopsis were also found to be aneuploid in nature as well. Thus, it was proposed that certain aneuploidies might be able to outperform their diploid counterparts in extreme environments (Chen et al., 2012). In normal tissues of mammals, aneuploid cells are also frequently found. For example, 60% of hepatocytes in mice and 30–90% in humans could be aneuploid in normal physiological conditions (Duncan, 2013). Human and mouse brains are another examples,

154

GuangJun Zhang et al.

containing about 30–35% aneuploid neuroblasts (Rehen et al., 2001), and it was recently confirmed as widespread large DNA copy number variations in human neurons using single-cell sequencing technology (McConnell et al., 2013). These physiological aneuploid cells are thought to be the consequences of aging and/or adaptation to special cell functional requirements, e.g., neuron circuit formation, etc. (Bushman and Chun, 2013; Duncan, 2013; Faggioli et al., 2011).

3.3 Cellular Impacts on Noncancerous Cells On the cellular level, generally two categories of aneuploid effects were reported. The first category is chromosome-specific effects. It is reasonable that cell phenotypes are altered by the specific genes on the altered chromosomes. Second, some “common” phenomena, which are shared by many kinds of aneuploidy, were reported recently in yeast and mouse aneuploid cells (Torres et al., 2007; Williams et al., 2008). For example, in disomic yeast strains, aneuploid cells show a decrease in cell growth rate, an increase in glucose uptake, and are more sensitive to protein synthesis and folding interruptions (Torres et al., 2007). In trisomic human cells, increased autophagy was also reported (Stingele et al., 2012). Although it has been claimed, whether aneuploidy always increases genomic instability is not yet clear (Sheltzer et al., 2011). These “common” features of aneuploidy need further validations as there have been limited studies in only a few of aneuploid forms.

3.4 Aneuploidy in Cancer Aneuploid cells are typically found to be less fit (slow growth, etc.) when compared to their diploid counterpart in evaluation on cellular and organismal levels. However, this condition is very common in cancer cell genomes. As cancer cells are usually intuitively thought to be more proliferative and aggressive, this phenomenon has been termed as “aneuploid paradox” (Sheltzer and Amon, 2011). Like the word “mutation,” aneuploidy refers to endless chromosomal numerical alterations. In most of the aneuploidy experiments so far, simple aneuploidies (like trisomy or tetrasomy) are dominantly used due to the ease of chromosomal manipulations. Contrastingly, the aneuploidy in human and other vertebrate solid tumors is usually very complex, usually involving multiple chromosomes. Even though all of them are called aneuploidy, they are not directly comparable. In addition, there is milieu of nucleotide sequence mutations in cancer genomes, which makes the direct comparisons of experimental and tumor aneuploidies invalid. Since aneuploidy is also considered as a genetic variant,

New Insight into Cancer Aneuploidy in Zebrafish

155

another explanation of the “aneuploid paradox” is through selection or adaptation (Chen et al., 2012; Pavelka et al., 2010a; Sheltzer and Amon, 2011). The massive formation of aneuploidies in cancer is the result of certain selections, thus they could aggressively grow in given environments (Merlo et al., 2006; Nowell, 1976), while the individual aneuploidies created in most experiments might be minor representatives of massive cancer aneuploidies. Furthermore, aneuploidy leads to the unbalanced genomes found in tumor cells; this might further induce a “rebalance” process through the introduction of more chromosomal instabilities, leading to psuedotriploidy, which is often found in many advanced cancers. Thus, aneuploidy is a dynamic process in cancer that is not only a process of losing chromosomal balance (Holland and Cleveland, 2012), but also a process of rebalancing through further chromosome gains and losses, which might be intrinsically related to chromosomal instability. In tumors, due to chromosome instability, millions of aneuploid forms are created during the somatic evolution process. The unfit cells die, but certain aneuploid cells might survive better than diploid cells and other aneuploid forms; they eventually break the bottlenecks of their microenvironment restrictions and contribute to the bulk part of tumors. As shown in yeast, certain aneuploid yeasts survive better in extreme environments (Pavelka et al., 2010b). Some gained chromosomes (e.g., human 8q) may carry oncogenes (e.g., MYC), and lost chromosomes (e.g., 17p) may carry tumor suppressor genes (e.g., TP53). The combination of unbalanced chromosomes could be critical for tumorigenesis. Of course, many genes on the altered chromosomes do not contribute to cancer formation, but are hijacked as bystanding passenger genes. Furthermore, gene point mutations also accumulate during the tumorigenic process, and it is reasonable to speculate that they might directly interact with the big mutation, aneuploidy. Indeed, a deubiquitinating enzyme, ubp6, was identified to be able to improve the fitness of certain aneuploid yeast strains (Torres et al., 2010). Interestingly, in another yeast cancer model, mcm4chaos3/chaos3 yeast showed improved growth and aneuploidy simultaneously, although improved growth was due to gene sequence mutations instead of aneuploidy (Li et al., 2009).

4. ZEBRAFISH AS A CANCER MODEL FOR HUMAN CANCERS As aneuploid is generally detrimental to organisms and too many types of aneuploidy exist, it is not easy to create aneuploid models in higher

156

GuangJun Zhang et al.

vertebrates to study their biology. So far, yeast serves as a dominant model, as spontaneous aneuploid yeast exits naturally. In the last few years, certain mouse trisomy models were made to meet this demand (Williams et al., 2008). Additionally, animal models of spindle checkpoint genes have also been extensively investigated (Holland and Cleveland, 2012; Lara-Gonzalez et al., 2012; Musacchio and Salmon, 2007; Nezi and Musacchio, 2009). Other models such as Arabidopsis and maize are used for plant aneuploidy investigations. As a rapidly growing vertebrate model system, zebrafish have many advantages over the more traditional models, such as tractable genetics, early transparent embryos, large number of offspring, and conservation of vertebrate tissue organs that could be compared directly to humans (Mione and Trede, 2010; White et al., 2013). This system is also finding its way into cancer and aneuploidy biology research (Zhang et al., 2010a, 2013a).

4.1 Polyploid Zebrafish Although it is relatively rare in vertebrates, polyploid animals exist in nature. For example, certain tree frog and fish species were reported to be polyploid naturally (Mable et al., 2011). One critical experiment to establish zebrafish as a model organism took advantage of the ease with which one can manipulate the zebrafish genome to become tetraploid (Streisinger et al., 1981). Tetraploid zebrafish are not able to survive to adulthood (Zhang, unpublished data), but both tetraploid and triploid zebrafish can easily be generated through transient early-stage high-pressure or heat-shock treatment (Marian, 1997; Mizgireuv et al., 2004). Thus, this could provide us a great model to investigate the biology of polyploidy and understanding its roles in cancer development. In fact, one chemical carcinogenesis study has been carried out on the triploid zebrafish, and it has been found that certain types of hepatocarcinoma could occur earlier in triploid fish than in diploid fish, and vice versa in other types of cancer (Mizgireuv et al., 2004). Due to the nature of chemical carcinogenesis, it is hard to conclude in this situation, as there are many uncertain issues with the carcinogen treatment, including chemical penetration and metabolism in the fish body. In the future, it would be very interesting to test the effects of ploidy increases on tumorigenesis using either current existing transgenic oncogene zebrafish models (myc, BRAF, etc.) or loss-of-function zebrafish models of mutant tumor suppressors (nf1, nf2, pten, etc.). In this way, we might have a unique chance to dissect the relationships between the ploidy alterations and tumor driver genes (oncogenes and tumor suppressor genes). Recently, we made tp53 null triploid zebrafish (tp53/), and found that the malignant peripheral

New Insight into Cancer Aneuploidy in Zebrafish

157

Figure 1 Similar aneuploid cancer genome from different starting ploidy. Tumor aneuploidies from diploid and triploid zebrafish with tp53 mutant (M214K) are similar by DNA copy number analysis using Illumina sequencing technology. The alternative green and black dots indicate zebrafish genes on different chromosomes. The y-axis shows the DNA copy number gains (2–0) and losses (02).

nerve sheath tumors from both diploid and triploid fish showed similar overall copy number alterations, suggesting that there is a strong selection on the aneuploid chromosomes in cancer genomes (Figure 1) (Zhang et al., 2013a).

4.2 Zebrafish Aneuploid Mutants In zebrafish, a few mutants have been reported to produce aneuploid embryos. For example, a majority of the offspring of mlh1 homozygous mutants are aneuploid with different combinations of chromosomes due to the defects of germ cells (Feitsma et al., 2007). Similarly, one quarter of mps1 mutant offspring were found to be aneuploid, as the mps1 is an important gene for controlling mitotic spindle checkpoint (Poss et al., 2004). The embryos of such mutants could be valuable to study the basic biology of aneuploidy. For example, what is the relationship between gene expression and chromosome numbers; are there gene dosage compensations; does the

158

GuangJun Zhang et al.

Figure 2 Polyploid and aneuploid zebrafish. (a) Triploid and tetraploid zebrafish can be made by heat shock at right time windows. (b) Diagram of making aneuploid zebrafish embryos by crossing of diploid and triploid zebrafish. (c) Three days postfertilization aneuploid embryos.

reported proteomic stress found in humans exist in zebrafish as well. Since the embryos might still carry the mutant-causing genes, we need to distinguish the effects of the genes from the aneuploidies. In this sense, the offspring of diploid and triploid zebrafish might better fit this unique need. Although triploid fish cannot reproduce, we have found that they are not completely sterile. They can still generate aneuploid gametes and thus aneuploid embryos without creating mutant genes (Figure 2, Zhang, unpublished data). In addition, the gametogenesis of triploid zebrafish is also interesting for understanding the cause of human aneuploid syndromes, such as Down syndrome, etc.

4.3 Aneuploid Nature of Zebrafish Cancers Aneuploidy is the one of the most common distinguishing features of human and other vertebrate cancers. Since we use animal models to study human cancers, the animal models should at least mimic the particular features of human tumors. In the past, we have proved that zebrafish malignant peripheral nerve sheath tumors (MPNSTs) from either tp53 homozygous mutants or ribosomal

New Insight into Cancer Aneuploidy in Zebrafish

159

Figure 3 Aneuploidy diversity in the same tumors. (a–d) Four chromosomal spreads by Giemsa staining in the same tumor, which was induced with rpsL36aþ/. Each cell has different chromosome numbers, which are indicated by n.

protein heterozygous mutants are highly aneuploid (Zhang et al., 2010a). Overall, cancer cells tend to be pseudotriploid, but this varies from cancer to cancer on an individual level (Figure 3). Cancers bearing an aneuploid nature, similar to that found in humans, include not only MPSNTs, but also zebrafish melanoma induced by BRAF V600E and T cell acute lymphoid leukemia induced by Myc (Zhang, unpublished data). Thus, zebrafish cancer models are complementary to laboratory genetically modified mouse cancer models that generally show less aneuploid when compared to human and zebrafish, with some exceptions (Maser et al., 2007).

5. CANCER DRIVER GENES ON ANEUPLOID CHROMOSOMES 5.1 Finding Cancer Driver Genes by Cross-Species Comparisons From recent cytogenetic and genomic research it is known that cancer cells generally have a nonrandom distribution of the chromosome gains and losses (Beroukhim et al., 2010; Davoli et al., 2013; Mitelman et al., 2014), although there is variability between cells within a single tumor (Vogelstein et al., 2013; Zhang et al., 2010a). These chromosomal imbalances are often

160

GuangJun Zhang et al.

involved in many chromosomes. In the past, cancer cell chromosomes were investigated through cytogenetic approaches, such as chromosome spread, chromosome banding, spectral karyotyping, and chromosome painting based on multicolor fluorescence in situ hybridizations (Schrock et al., 1996; Speicher et al., 1996). Recently, high-throughput genome scanning technologies like CGH and massively parallel sequencing have dramatically improved our ability to probe such chromosome alterations in cancer cells (Chiang et al., 2009; Pinkel et al., 1998). In particular, parallel sequencing is able to get single-nucleotide resolution and has been applied on single cells (Navin et al., 2011; Xu et al., 2012). This approach could potentially reveal unprecedented details of chromosomal alterations in cancer cell genomes. Understanding whole chromosome alterations, or aneuploidy, in cancer still remains a great challenge, even with powerful parallel sequencing tools. There are many genes on such large chromosomal regions, ranging from hundreds to thousands of genes on a single chromosomal arm. Though it is possible, but still is not easy to distinguish which genes on the aneuploid chromosomes are functioning as cancer drivers even with genome-wide loss-of-function screening technologies such as shRNA and CRISPR libraries (Shalem et al., 2014; Wang et al., 2014). Recently, comparative oncogenomics has emerged as a solution for this recalcitrant problem of aneuploidy (Maser et al., 2007; Zhang et al., 2010a, 2013a). Since functions of genes in vertebrates are usually conserved, it is very reasonable the cancer driver genes will be selected in multiple species for the same types of tumors. Since the syntenic relationships between the species are different due to the reshuffling of the genes’ positions along chromosomes, the more closely related two species are, the more likely it will be that they share similar genes linked along their chromosomes. To this end, relatively distant species are more effective for finding cancer driver genes along the aneuploid chromosomes. For example, in our recent studies with human–zebrafish comparative oncogenomics, we found that the evolutionarily conserved driver candidate gene pool could be reduced to one-fourth overall, and this number can be much higher for some chromosomes such as 17q (w85%) (Zhang et al., 2013a). Interestingly, by this relatively distant cross-spices comparison, we identified only three focal CNAs shared between humans and zebrafish. Differential distribution of chromosomal fragile sites in both species might explain this phenomenon. Based on the content of these shared focal CNAs, it is very likely they are conserved chromosomal fragile sites. Comparative oncogenomics not only provide us information about the cancer driver genes, but also other information about cancer genome

New Insight into Cancer Aneuploidy in Zebrafish

161

evolution. One such example, oncogene addition, refers to cancer cells that are reliant on the high activity of certain oncogenes. Once these oncogenes’ activities are inhibited, cancer cells are not able to survive, leading this conception to become one of the main principles of modern targeted cancer therapy (Luo et al., 2009). The best example is the effectiveness of Imatinib on the chronic myeloid leukemia by inhibiting the constitutively active chimera BCR-ABL protein, which is created by Philadelphia chromosome translocations (Druker et al., 2006). One extension of oncogene addiction is the inclusion of genes that are not oncogenes, but are still needed for tumorigenesis (Tischler et al., 2008). For example, it was recently discovered that GATA2 is required for RAS oncogene-driven nonsmall cell lung cancer (Kumar et al., 2012). Such required oncogenes or nononcogenes could reside on the highly amplified chromosomal regions in different vertebrate species due to their evolutionarily conserved functions. Thus, the shared highly amplified genes on the gained chromosomes could potentially contain the addicted genes. Because tumor suppressor genes generally show loss-of-function mutations, conceptually it is hard to make them useful for cancer therapies. While, synthetic lethality makes it possible to target tumor suppressors. Synthetic lethality describes the co-occurrence of two simultaneous genetic events, resulting in organismal or cellular death. This phenomenon was first discovered a century ago in D. melanogaster, and was later extended to other organisms and cancer (Dobzhansky, 1946; Hartman et al., 2001; Nijman, 2011). The most notable example of this idea is the application of PAPR inhibitors on BRCA1- and/or BRCA2-deficient tumor cells which leads to cell death and thus makes the tumor suppressors druggable (Kaelin, 2005; Lord and Ashworth, 2013). Although RNAi library screening is the routine way for identifying synthetic lethality relationships of tumor suppressor genes, unbalanced cancer karyotypes may also shed some light on this, as the co-loss of chromosomes will never be detected due to the cell lethality caused by such combinations. Moreover, zebrafish are finding their way in the synthetic lethal screening (Hajeri and Amatruda, 2012). Since zebrafish only have BRAC2 ortholog, but no BRAC1 ortholog (Rodriguez-Mari et al., 2011), it would be interesting to learn the synthetic lethal interactions in fish if the human or mouse BRAC1 orthologous gene can be put into the zebrafish genome through transgenesis. With the comparative oncogenomic approach, we might also be able to identify the cooperation between/among certain genes that are important for tumorigenesis. It has been noted that there could be multiple genes on

162

GuangJun Zhang et al.

the same aneuploid chromosomes (Kendall et al., 2007; Xue et al., 2012). The additive effect and synergistic effect thus are expected whenever there is cooperation among the multiple driver genes (Pavelka et al., 2010a; Xue et al., 2012). From the view of gene regulatory networks, the gains and losses of chromosomes in cancer cell genomes might provide the malignant cells more diverse regulations that could be adapted to local microenvironments (Heng et al., 2010, 2011). It might also be possible to combine the cancer cell DNA copy number analysis and gene functional investigations to reveal unique “reorganized” signaling pathways or regulatory relationships between cancer driver genes on the aneuploid chromosomes.

5.2 Functional Validations of Cancer Driver Genes Zebrafish are not only a good system to identify cancer driver genes on large aneuploid chromosomes through comparative oncogenomics, but also a great system to validate the identified driver genes (Liu and Leach, 2011; White et al., 2013). Due to the ease and effectiveness of germ line transgenesis, this approach has been successfully used to generate zebrafish cancer models (Langenau et al., 2005; Mudbhary et al., 2014; Patton et al., 2005). Another high-throughput approach is mosaic transgenesis, which could be very useful for large-scale cancer driver candidate gene validations. As a great example, human candidate genes on recurrent human chromosome 1q21 (chr1: 147.2–149.2 mbs) were cloned into a Tol2 transposonbased vector miniCoopR, then delivered into zebrafish genes in order to evaluate their tumorigenic roles in Tg(mitfa:BRAF(V600E));tp53/ zebrafish (Ceol et al., 2011). Forward genetic mutagenesis technology using N-ethyl-N-nitrosourea (ENU), transposon (e.g., Tol2), and retroviral insertional mutagenesis have made many mutants that have been used for evaluating cancer genes’ functions, as seen with ribosomal protein genes, tp53, bmyb, nf1, and pten (Amsterdam et al., 2004; Berghmans et al., 2005; Faucherre et al., 2008; Lai et al., 2009; Shepard et al., 2005; Shin et al., 2012). With the nearing saturation of zebrafish genome-wide mutagenesis with ENU and retroviral insertional mutagenesis, mutants of every zebrafish gene will soon be available for cancer biology analysis.

6. FUTURE DIRECTIONS Like nucleic acid sequence mutations, aneuploidy is composed of endless combinations of gained and/or lost chromosomes in a given species. Moreover, genes on each chromosome vary dramatically; it is almost

New Insight into Cancer Aneuploidy in Zebrafish

163

impossible to directly compare between currently available results of aneuploidy research. It is obvious that each aneuploidy has specific phenotypes (e.g., Down syndrome vs Turner’s syndrome), but whether there is a uniform cellular response to all kinds of aneuploidy will need more data on more aneuploid forms and more species before we are able to make a clear conclusion. With the zebrafish model and its advantages, the directions below might be worth pursuing for the cancer aneuploidy research advancement: 1. Cellular originality of aneuploidy and polyploidy With the transparent early zebrafish embryos, mitotic cells or organelles (centrosomes, spindle) could be labeled in a similar way as the Fucci zebrafish (Sugiyama et al., 2009). Thus, by combining with forward genetic screening, we might be able to identify new genes that are involved in the spindle checkpoint, cytokinesis, and other molecular mechanisms that are required for the maintenance of euploid status in zebrafish. 2. Cancer aneuploidy lineage tracking in zebrafish Recently, Brainbow labeling was developed in zebrafish (Pan et al., 2013). With some modification, this could be used to track individual chromosomes in the future. We then might have a tool to track aneuploidy lineage in live fish embryos and fish tumors. 3. Identification of evolutionarily conserved cancer driver genes on aneuploid chromosomes Recently, we have shown that potential cancer driver gene pools can be dramatically reduced by zebrafish–human comparative oncogenomics in MPNSTs. This cross-species comparison approach should not be limited to this type of tumor. Other solid tumors with obvious aneuploid chromosome abnormalities could also be assessed in this way. Moreover, other types of genetic alteration such as point mutations and chromosomal translocations can also be compared in a similar way to identify cancer driver genes, combining functional tests as demonstrated by the mouse lung cancer model (McFadden et al., 2014). Furthermore, the cross-species analysis can be extended to other vertebrate organisms in a phylogenetic background (Zhang et al., 2013b). 4. Rapid cancer driver functional validations in zebrafish Except for the mosaic transgenic approach in zebrafish, newly developed technologies such as TALEN (transcription activator-like effector nucleases) and CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats–CRISPR-associated 9) facilitate rapid functional studies in zebrafish (Auer and Del Bene, 2014). Beside targeted gene modifications, these

164

GuangJun Zhang et al.

new technologies could also modify chromosomes (e.g., translocations and inversions) (Xiao et al., 2013). Thus, they are rapidly finding their way into zebrafish scientific communities. 5. Drug-screening platform for aneuploidy biology Last but not least, the zebrafish embryo is also becoming an in vivo chemical screening platform (Barros et al., 2008; Tat et al., 2013; Zon and Peterson, 2005). With zebrafish embryos, it might be possible to screen out chemicals that can induce or inhibit aneuploidy formations. Such chemicals could be useful for future scientific research, miscarriage prevention, and cancer therapies.

ACKNOWLEDGMENTS I would like to thank John T. and Winifred M. Hayward Foundation for financial support. I would also like to thank my lab members, Monica R. Hensley and Anna E. Smith for their comments and suggestions on the manuscript.

REFERENCES Amsterdam, A., Sadler, K.C., Lai, K., Farrington, S., Bronson, R.T., Lees, J.A., Hopkins, N., 2004. Many ribosomal protein genes are cancer genes in zebrafish. PLoS Biol. 2, E139. Auer, T.O., Del Bene, F., 2014. CRISPR/Cas9 and TALEN-mediated knock-in approaches in zebrafish. Methods 69 (2), 142–150. Barros, T.P., Alderton, W.K., Reynolds, H.M., Roach, A.G., Berghmans, S., 2008. Zebrafish: an emerging technology for in vivo pharmacological assessment to identify potential safety liabilities in early drug discovery. Br. J. Pharmacol. 154, 1400–1413. Berghmans, S., Murphey, R.D., Wienholds, E., Neuberg, D., Kutok, J.L., Fletcher, C.D., Morris, J.P., Liu, T.X., Schulte-Merker, S., Kanki, J.P., Plasterk, R., Zon, L.I., Look, A.T., 2005. tp53 mutant zebrafish develop malignant peripheral nerve sheath tumors. Proc. Natl. Acad. Sci. U.S.A. 102, 407–412. Beroukhim, R., Mermel, C.H., Porter, D., Wei, G., Raychaudhuri, S., Donovan, J., Barretina, J., Boehm, J.S., Dobson, J., Urashima, M., Mc Henry, K.T., Pinchback, R.M., Ligon, A.H., Cho, Y.J., Haery, L., Greulich, H., Reich, M., Winckler, W., Lawrence, M.S., Weir, B.A., Tanaka, K.E., Chiang, D.Y., Bass, A.J., Loo, A., Hoffman, C., Prensner, J., Liefeld, T., Gao, Q., Yecies, D., Signoretti, S., Maher, E., Kaye, F.J., Sasaki, H., Tepper, J.E., Fletcher, J.A., Tabernero, J., Baselga, J., Tsao, M.S., Demichelis, F., Rubin, M.A., Janne, P.A., Daly, M.J., Nucera, C., Levine, R.L., Ebert, B.L., Gabriel, S., Rustgi, A.K., Antonescu, C.R., Ladanyi, M., Letai, A., Garraway, L.A., Loda, M., Beer, D.G., True, L.D., Okamoto, A., Pomeroy, S.L., Singer, S., Golub, T.R., Lander, E.S., Getz, G., Sellers, W.R., Meyerson, M., 2010. The landscape of somatic copy-number alteration across human cancers. Nature 463, 899–905. Bignold, L.P., Coghlan, B.L., Jersmann, H.P., 2006. Hansemann, Boveri, chromosomes and the gametogenesis-related theories of tumours. Cell Biol. Int. 30, 640–644. Birchler, J.A., Bhadra, U., Bhadra, M.P., Auger, D.L., 2001. Dosage-dependent gene regulation in multicellular eukaryotes: implications for dosage compensation, aneuploid syndromes, and quantitative traits. Dev. Biol. 234, 275–288. Boveri, T., 2008. Concerning the origin of malignant tumours by Theodor Boveri. Translated and annotated by Henry Harris. J. Cell Sci. 121, 1–84.

New Insight into Cancer Aneuploidy in Zebrafish

165

Bushman, D.M., Chun, J., 2013. The genomically mosaic brain: aneuploidy and more in neural diversity and disease. Semin. Cell Dev. Biol. 24, 357–369. Ceol, C.J., Houvras, Y., Jane-Valbuena, J., Bilodeau, S., Orlando, D.A., Battisti, V., Fritsch, L., Lin, W.M., Hollmann, T.J., Ferre, F., Bourque, C., Burke, C.J., Turner, L., Uong, A., Johnson, L.A., Beroukhim, R., Mermel, C.H., Loda, M., Ait-Si-Ali, S., Garraway, L.A., Young, R.A., Zon, L.I., 2011. The histone methyltransferase SETDB1 is recurrently amplified in melanoma and accelerates its onset. Nature 471, 513–517. Chen, G., Rubinstein, B., Li, R., 2012. Whole chromosome aneuploidy: big mutations drive adaptation by phenotypic leap. Bioessays 34, 893–900. Chiang, D.Y., Getz, G., Jaffe, D.B., O’Kelly, M.J., Zhao, X., Carter, S.L., Russ, C., Nusbaum, C., Meyerson, M., Lander, E.S., 2009. High-resolution mapping of copy-number alterations with massively parallel sequencing. Nat. Methods 6, 99–103. Cimini, D., 2008. Merotelic kinetochore orientation, aneuploidy, and cancer. Biochim. Biophys. Acta 1786, 32–40. Comai, L., 2005. The advantages and disadvantages of being polyploid. Nature reviews. Genetics 6, 836–846. Davoli, T., Xu, A.W., Mengwasser, K.E., Sack, L.M., Yoon, J.C., Park, P.J., Elledge, S.J., 2013. Cumulative haploinsufficiency and triplosensitivity drive aneuploidy patterns and shape the cancer genome. Cell 155, 948–962. Dobzhansky, T., 1946. Genetics of natural populations. Xiii. Recombination and variability in populations of Drosophila Pseudoobscura. Genetics 31, 269–290. Druker, B.J., Guilhot, F., O’Brien, S.G., Gathmann, I., Kantarjian, H., Gattermann, N., Deininger, M.W., Silver, R.T., Goldman, J.M., Stone, R.M., Cervantes, F., Hochhaus, A., Powell, B.L., Gabrilove, J.L., Rousselot, P., Reiffers, J., Cornelissen, J.J., Hughes, T., Agis, H., Fischer, T., Verhoef, G., Shepherd, J., Saglio, G., Gratwohl, A., Nielsen, J.L., Radich, J.P., Simonsson, B., Taylor, K., Baccarani, M., So, C., Letvak, L., Larson, R.A., Investigators, I., 2006. Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia. N. Engl. J. Med. 355, 2408–2417. Duncan, A.W., 2013. Aneuploidy, polyploidy and ploidy reversal in the liver. Semin. Cell Dev. Biol. 24, 347–356. Faggioli, F., Vijg, J., Montagna, C., 2011. Chromosomal aneuploidy in the aging brain. Mech. Ageing Dev. 132, 429–436. Faucherre, A., Taylor, G.S., Overvoorde, J., Dixon, J.E., Hertog, J., 2008. Zebrafish pten genes have overlapping and non-redundant functions in tumorigenesis and embryonic development. Oncogene 27, 1079–1086. Feitsma, H., Leal, M.C., Moens, P.B., Cuppen, E., Schulz, R.W., 2007. Mlh1 deficiency in zebrafish results in male sterility and aneuploid as well as triploid progeny in females. Genetics 175, 1561–1569. Foley, E.A., Kapoor, T.M., 2013. Microtubule attachment and spindle assembly checkpoint signalling at the kinetochore. Nat. Rev. Mol. Cell Biol. 14, 25–37. Gordon, D.J., Resio, B., Pellman, D., 2012. Causes and consequences of aneuploidy in cancer. Nat. Rev. Genet. 13, 189–203. Hajeri, V.A., Amatruda, J.F., 2012. Studying synthetic lethal interactions in the zebrafish system: insight into disease genes and mechanisms. Dis. Model Mech. 5, 33–37. Hartman, J.L.t., Garvik, B., Hartwell, L., 2001. Principles for the buffering of genetic variation. Science 291, 1001–1004. Hassold, T., Hall, H., Hunt, P., 2007. The origin of human aneuploidy: where we have been, where we are going. Hum. Mol. Genet. 16. Spec No. 2, R203–R208. Hassold, T., Hunt, P., 2001. To err (meiotically) is human: the genesis of human aneuploidy. Nat. Rev. Genet. 2, 280–291.

166

GuangJun Zhang et al.

Heng, H.H., Stevens, J.B., Bremer, S.W., Liu, G., Abdallah, B.Y., Ye, C.J., 2011. Evolutionary mechanisms and diversity in cancer. Adv. Cancer Res. 112, 217–253. Heng, H.H., Stevens, J.B., Bremer, S.W., Ye, K.J., Liu, G., Ye, C.J., 2010. The evolutionary mechanism of cancer. J. Cell Biochem. 109, 1072–1084. Holland, A.J., Cleveland, D.W., 2012. Losing balance: the origin and impact of aneuploidy in cancer. EMBO Rep. 13, 501–514. Huettel, B., Kreil, D.P., Matzke, M., Matzke, A.J., 2008. Effects of aneuploidy on genome structure, expression, and interphase organization in Arabidopsis thaliana. PLoS Genet. 4, e1000226. Hughes, T.R., Roberts, C.J., Dai, H., Jones, A.R., Meyer, M.R., Slade, D., Burchard, J., Dow, S., Ward, T.R., Kidd, M.J., Friend, S.H., Marton, M.J., 2000. Widespread aneuploidy revealed by DNA microarray expression profiling. Nat. Genet. 25, 333–337. Jones, K.T., Lane, S.I., 2013. Molecular causes of aneuploidy in mammalian eggs. Development 140, 3719–3730. Kaelin Jr., W.G., Jr., 2005. The concept of synthetic lethality in the context of anticancer therapy. Nat. Rev. Cancer 5, 689–698. Kendall, J., Liu, Q., Bakleh, A., Krasnitz, A., Nguyen, K.C., Lakshmi, B., Gerald, W.L., Powers, S., Mu, D., 2007. Oncogenic cooperation and coamplification of developmental transcription factor genes in lung cancer. Proc. Natl. Acad. Sci. U.S.A. 104, 16663–16668. Kops, G.J., Weaver, B.A., Cleveland, D.W., 2005. On the road to cancer: aneuploidy and the mitotic checkpoint. Nat. Rev. Cancer 5, 773–785. Kumar, M.S., Hancock, D.C., Molina-Arcas, M., Steckel, M., East, P., Diefenbacher, M., Armenteros-Monterroso, E., Lassailly, F., Matthews, N., Nye, E., Stamp, G., Behrens, A., Downward, J., 2012. The GATA2 transcriptional network is requisite for RAS oncogene-driven non-small cell lung cancer. Cell 149, 642–655. Lai, K., Amsterdam, A., Farrington, S., Bronson, R.T., Hopkins, N., Lees, J.A., 2009. Many ribosomal protein mutations are associated with growth impairment and tumor predisposition in zebrafish. Dev. Dyn. 238, 76–85. Langenau, D.M., Feng, H., Berghmans, S., Kanki, J.P., Kutok, J.L., Look, A.T., 2005. Cre/ lox-regulated transgenic zebrafish model with conditional myc-induced T cell acute lymphoblastic leukemia. Proc. Natl. Acad. Sci. U.S.A. 102, 6068–6073. Lara-Gonzalez, P., Westhorpe, F.G., Taylor, S.S., 2012. The spindle assembly checkpoint. Curr. Biol. 22, R966–R980. Lee, H.O., Davidson, J.M., Duronio, R.J., 2009. Endoreplication: polyploidy with purpose. Genes Dev. 23, 2461–2477. Letourneau, A., Santoni, F.A., Bonilla, X., Sailani, M.R., Gonzalez, D., Kind, J., Chevalier, C., Thurman, R., Sandstrom, R.S., Hibaoui, Y., Garieri, M., Popadin, K., Falconnet, E., Gagnebin, M., Gehrig, C., Vannier, A., Guipponi, M., Farinelli, L., Robyr, D., Migliavacca, E., Borel, C., Deutsch, S., Feki, A., Stamatoyannopoulos, J.A., Herault, Y., van Steensel, B., Guigo, R., Antonarakis, S.E., 2014. Domains of genome-wide gene expression dysregulation in Down’s syndrome. Nature 508, 345–350. Li, X.C., Schimenti, J.C., Tye, B.K., 2009. Aneuploidy and improved growth are coincident but not causal in a yeast cancer model. PLoS Biol 7, e1000161. Liu, S., Leach, S.D., 2011. Zebrafish models for cancer. Annu. Rev. Pathol. 6, 71–93. Lord, C.J., Ashworth, A., 2013. Mechanisms of resistance to therapies targeting BRCA-mutant cancers. Nat. Med. 19, 1381–1388. Losada, A., 2014. Cohesin in cancer: chromosome segregation and beyond. Nat. Rev. Cancer 14, 389–393. Luo, J., Solimini, N.L., Elledge, S.J., 2009. Principles of cancer therapy: oncogene and nononcogene addiction. Cell 136, 823–837.

New Insight into Cancer Aneuploidy in Zebrafish

167

Mable, B.K., Alexandrou, M.A., Taylor, M.I., 2011. Genome duplication in amphibians and fish: an extended synthesis. J. Zoology 284, 151–182. Makarevitch, I., Phillips, R.L., Springer, N.M., 2008. Profiling expression changes caused by a segmental aneuploid in maize. BMC Genomics 9, 7. Marian, L.A., 1997. Production of triploid transgenic zebrafish, Brachydanio rerio (Hamilton). Indian J. Exp. Biol. 35, 1237–1242. Maser, R.S., Choudhury, B., Campbell, P.J., Feng, B., Wong, K.K., Protopopov, A., O’Neil, J., Gutierrez, A., Ivanova, E., Perna, I., Lin, E., Mani, V., Jiang, S., McNamara, K., Zaghlul, S., Edkins, S., Stevens, C., Brennan, C., Martin, E.S., Wiedemeyer, R., Kabbarah, O., Nogueira, C., Histen, G., Aster, J., Mansour, M., Duke, V., Foroni, L., Fielding, A.K., Goldstone, A.H., Rowe, J.M., Wang, Y.A., Look, A.T., Stratton, M.R., Chin, L., Futreal, P.A., DePinho, R.A., 2007. Chromosomally unstable mouse tumours have genomic alterations similar to diverse human cancers. Nature 447, 966–971. McConnell, M.J., Lindberg, M.R., Brennand, K.J., Piper, J.C., Voet, T., CowingZitron, C., Shumilina, S., Lasken, R.S., Vermeesch, J.R., Hall, I.M., Gage, F.H., 2013. Mosaic copy number variation in human neurons. Science 342, 632–637. McFadden, D.G., Papagiannakopoulos, T., Taylor-Weiner, A., Stewart, C., Carter, S.L., Cibulskis, K., Bhutkar, A., McKenna, A., Dooley, A., Vernon, A., Sougnez, C., Malstrom, S., Heimann, M., Park, J., Chen, F., Farago, A.F., Dayton, T., Shefler, E., Gabriel, S., Getz, G., Jacks, T., 2014. Genetic and clonal dissection of murine small cell lung carcinoma progression by genome sequencing. Cell 156, 1298–1311. Merlo, L.M.F., Pepper, J.W., Reid, B.J., Maley, C.C., 2006. Cancer as an evolutionary and ecological process. Nat. Rev. Cancer 6, 924–935. Mione, M.C., Trede, N.S., 2010. The zebrafish as a model for cancer. Dis. Model Mech. 3, 517–523. Mitelman, F., Johansson, B., Mertens, F.E., 2014. In: Mitelman, F., Johansson, B., Mertens, F. (Eds.), Mitelman Database of Chromosome Aberrations in Cancer (2013). http://cgap.nci.nih.gov/Chromosomes/Mitelman. Mizgireuv, I.V., Majorova, I.G., Gorodinskaya, V.M., Khudoley, V.V., Revskoy, S.Y., 2004. Carcinogenic effect of N-nitrosodimethylamine on diploid and triploid zebrafish (Danio rerio). Toxicol. Pathol. 32, 514–518. Mudbhary, R., Hoshida, Y., Chernyavskaya, Y., Jacob, V., Villanueva, A., Fiel, M.I., Chen, X., Kojima, K., Thung, S., Bronson, R.T., Lachenmayer, A., Revill, K., Alsinet, C., Sachidanandam, R., Desai, A., SenBanerjee, S., Ukomadu, C., Llovet, J.M., Sadler, K.C., 2014. UHRF1 overexpression drives DNA hypomethylation and hepatocellular carcinoma. Cancer Cell. 25, 196–209. Musacchio, A., Salmon, E.D., 2007. The spindle-assembly checkpoint in space and time. Nat. Rev. Mol. Cell Biol. 8, 379–393. Nagaoka, S.I., Hassold, T.J., Hunt, P.A., 2012. Human aneuploidy: mechanisms and new insights into an age-old problem. Nat. Rev. Genet. 13, 493–504. Navin, N., Kendall, J., Troge, J., Andrews, P., Rodgers, L., McIndoo, J., Cook, K., Stepansky, A., Levy, D., Esposito, D., Muthuswamy, L., Krasnitz, A., McCombie, W.R., Hicks, J., Wigler, M., 2011. Tumour evolution inferred by singlecell sequencing. Nature 472, 90–94. Nezi, L., Musacchio, A., 2009. Sister chromatid tension and the spindle assembly checkpoint. Curr. Opin. Cell Biol. 21, 785–795. Nijman, S.M., 2011. Synthetic lethality: general principles, utility and detection using genetic screens in human cells. FEBS Lett. 585, 1–6. Nowell, P.C., 1976. The clonal evolution of tumor cell populations. Science 194, 23–28. Oromendia, A.B., Amon, A., 2014. Aneuploidy: implications for protein homeostasis and disease. Dis. Model Mech. 7, 15–20.

168

GuangJun Zhang et al.

Otto, S.P., 2007. The evolutionary consequences of polyploidy. Cell 131, 452–462. Overholtzer, M., Mailleux, A.A., Mouneimne, G., Normand, G., Schnitt, S.J., King, R.W., Cibas, E.S., Brugge, J.S., 2007. A nonapoptotic cell death process, entosis, that occurs by cell-in-cell invasion. Cell 131, 966–979. Pala, I., Coelho, M.M., Schartl, M., 2008. Dosage compensation by gene-copy silencing in a triploid hybrid fish. Curr. Biol. 18, 1344–1348. Pan, Y.A., Freundlich, T., Weissman, T.A., Schoppik, D., Wang, X.C., Zimmerman, S., Ciruna, B., Sanes, J.R., Lichtman, J.W., Schier, A.F., 2013. Zebrabow: multispectral cell labeling for cell tracing and lineage analysis in zebrafish. Development 140, 2835– 2846. Patton, E.E., Widlund, H.R., Kutok, J.L., Kopani, K.R., Amatruda, J.F., Murphey, R.D., Berghmans, S., Mayhall, E.A., Traver, D., Fletcher, C.D., Aster, J.C., Granter, S.R., Look, A.T., Lee, C., Fisher, D.E., Zon, L.I., 2005. BRAF mutations are sufficient to promote nevi formation and cooperate with p53 in the genesis of melanoma. Curr. Biol. 15, 249–254. Pavelka, N., Rancati, G., Li, R., 2010a. Dr Jekyll and Mr Hyde: role of aneuploidy in cellular adaptation and cancer. Curr. Opin. cell Biol. 22, 809–815. Pavelka, N., Rancati, G., Zhu, J., Bradford, W.D., Saraf, A., Florens, L., Sanderson, B.W., Hattem, G.L., Li, R., 2010b. Aneuploidy confers quantitative proteome changes and phenotypic variation in budding yeast. Nature 468, 321–325. Payer, B., Lee, J.T., 2008. X chromosome dosage compensation: how mammals Keep the balance. Annu. Rev. Genet. 42, 733–772. Pinkel, D., Segraves, R., Sudar, D., Clark, S., Poole, I., Kowbel, D., Collins, C., Kuo, W.L., Chen, C., Zhai, Y., Dairkee, S.H., Ljung, B.M., Gray, J.W., Albertson, D.G., 1998. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat. Genet. 20, 207–211. Poss, K.D., Nechiporuk, A., Stringer, K.F., Lee, C., Keating, M.T., 2004. Germ cell aneuploidy in zebrafish with mutations in the mitotic checkpoint gene mps1. Genes. Dev. 18, 1527–1532. Rehen, S.K., McConnell, M.J., Kaushal, D., Kingsbury, M.A., Yang, A.H., Chun, J., 2001. Chromosomal variation in neurons of the developing and adult mammalian nervous system. Proc. Natl. Acad. Sci. U.S.A. 98, 13361–13366. Rodriguez-Mari, A., Wilson, C., Titus, T.A., Canestro, C., BreMiller, R.A., Yan, Y.L., Nanda, I., Johnston, A., Kanki, J.P., Gray, E.M., He, X., Spitsbergen, J., Schindler, D., Postlethwait, J.H., 2011. Roles of brca2 (fancd1) in oocyte nuclear architecture, gametogenesis, gonad tumors, and genome stability in zebrafish. PLoS Genet. 7, e1001357. Roschke, A.V., Rozenblum, E., 2013. Multi-layered cancer chromosomal instability phenotype. Front. Oncol. 3, 302. Satzinger, H., 2008. Theodor and Marcella Boveri: chromosomes and cytoplasm in heredity and development. Nat. Rev. Genet. 9, 231–238. Schrock, E., du Manoir, S., Veldman, T., Schoell, B., Wienberg, J., Ferguson-Smith, M.A., Ning, Y., Ledbetter, D.H., Bar-Am, I., Soenksen, D., Garini, Y., Ried, T., 1996. Multicolor spectral karyotyping of human chromosomes. Science 273, 494–497. Shalem, O., Sanjana, N.E., Hartenian, E., Shi, X., Scott, D.A., Mikkelsen, T.S., Heckl, D., Ebert, B.L., Root, D.E., Doench, J.G., Zhang, F., 2014. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science 343, 84–87. Sheltzer, J.M., Amon, A., 2011. The aneuploidy paradox: costs and benefits of an incorrect karyotype. Trends Genet. 27, 446–453. Sheltzer, J.M., Blank, H.M., Pfau, S.J., Tange, Y., George, B.M., Humpton, T.J., Brito, I.L., Hiraoka, Y., Niwa, O., Amon, A., 2011. Aneuploidy drives genomic instability in yeast. Science 333, 1026–1030.

New Insight into Cancer Aneuploidy in Zebrafish

169

Shepard, J.L., Amatruda, J.F., Stern, H.M., Subramanian, A., Finkelstein, D., Ziai, J., Finley, K.R., Pfaff, K.L., Hersey, C., Zhou, Y., Barut, B., Freedman, M., Lee, C., Spitsbergen, J., Neuberg, D., Weber, G., Golub, T.R., Glickman, J.N., Kutok, J.L., Aster, J.C., Zon, L.I., 2005. A zebrafish bmyb mutation causes genome instability and increased cancer susceptibility. Proc. Natl. Acad. Sci. U.S.A. 102, 13194–13199. Shin, J., Padmanabhan, A., de Groh, E.D., Lee, J.S., Haidar, S., Dahlberg, S., Guo, F., He, S., Wolman, M.A., Granato, M., Lawson, N.D., Wolfe, S.A., Kim, S.H., SolnicaKrezel, L., Kanki, J.P., Ligon, K.L., Epstein, J.A., Look, A.T., 2012. Zebrafish neurofibromatosis type 1 genes have redundant functions in tumorigenesis and embryonic development. Dis. Model Mech. 5, 881–894. Sidebottom, E., Deak II, , II, 1976. The function of the nucleolus in the expression of genetic information: studies with hybrid animal cells. Int. Rev. Cytol. 44, 29–53. Siegel, J.J., Amon, A., 2012. New insights into the troubles of aneuploidy. Annu. Rev. Cell Dev. Biol. 28, 189–214. Speicher, M.R., Gwyn Ballard, S., Ward, D.C., 1996. Karyotyping human chromosomes by combinatorial multi-fluor FISH. Nat. Genet. 12, 368–375. Stingele, S., Stoehr, G., Peplowska, K., Cox, J., Mann, M., Storchova, Z., 2012. Global analysis of genome, transcriptome and proteome reveals the response to aneuploidy in human cells. Mol. Syst. Biol. 8, 608. Straub, T., Becker, P.B., 2007. Dosage compensation: the beginning and end of generalization. Nat. Rev. Genet. 8, 47–57. Streisinger, G., Walker, C., Dower, N., Knauber, D., Singer, F., 1981. Production of clones of homozygous diploid zebra fish (Brachydanio rerio). Nature 291, 293–296. Sugiyama, M., Sakaue-Sawano, A., Iimura, T., Fukami, K., Kitaguchi, T., Kawakami, K., Okamoto, H., Higashijima, S., Miyawaki, A., 2009. Illuminating cell-cycle progression in the developing zebrafish embryo. Proc. Natl. Acad. Sci. U.S.A. 106, 20812–20817. Tang, Y.C., Amon, A., 2013. Gene copy-number alterations: a cost-benefit analysis. Cell 152, 394–405. Tat, J., Liu, M., Wen, X.Y., 2013. Zebrafish cancer and metastasis models for in vivo drug discovery. Drug discovery today. Technologies 10, e83–89. Tischler, J., Lehner, B., Fraser, A.G., 2008. Evolutionary plasticity of genetic interaction networks. Nat Genet 40, 390–391. Torres, E.M., Dephoure, N., Panneerselvam, A., Tucker, C.M., Whittaker, C.A., Gygi, S.P., Dunham, M.J., Amon, A., 2010. Identification of aneuploidy-tolerating mutations. Cell 143, 71–83. Torres, E.M., Sokolsky, T., Tucker, C.M., Chan, L.Y., Boselli, M., Dunham, M.J., Amon, A., 2007. Effects of aneuploidy on cellular physiology and cell division in haploid yeast. Science 317, 916–924. Torres, E.M., Williams, B.R., Amon, A., 2008. Aneuploidy: cells losing their balance. Genetics 179, 737–746. Vogelstein, B., Papadopoulos, N., Velculescu, V.E., Zhou, S., Diaz Jr., L.A., Jr., Kinzler, K.W., 2013. Cancer genome landscapes. Science 339, 1546–1558. Wang, T., Wei, J.J., Sabatini, D.M., Lander, E.S., 2014. Genetic screens in human cells using the CRISPR-Cas9 system. Science 343, 80–84. White, R., Rose, K., Zon, L., 2013. Zebrafish cancer: the state of the art and the path forward. Nat. Rev. Cancer 13, 624–636. Williams, B.R., Prabhu, V.R., Hunter, K.E., Glazier, C.M., Whittaker, C.A., Housman, D.E., Amon, A., 2008. Aneuploidy affects proliferation and spontaneous immortalization in mammalian cells. Science 322, 703–709. Xiao, A., Wang, Z., Hu, Y., Wu, Y., Luo, Z., Yang, Z., Zu, Y., Li, W., Huang, P., Tong, X., Zhu, Z., Lin, S., Zhang, B., 2013. Chromosomal deletions and inversions mediated by TALENs and CRISPR/Cas in zebrafish. Nucleic Acids Res. 41, e141.

170

GuangJun Zhang et al.

Xu, X., Hou, Y., Yin, X., Bao, L., Tang, A., Song, L., Li, F., Tsang, S., Wu, K., Wu, H., He, W., Zeng, L., Xing, M., Wu, R., Jiang, H., Liu, X., Cao, D., Guo, G., Hu, X., Gui, Y., Li, Z., Xie, W., Sun, X., Shi, M., Cai, Z., Wang, B., Zhong, M., Li, J., Lu, Z., Gu, N., Zhang, X., Goodman, L., Bolund, L., Wang, J., Yang, H., Kristiansen, K., Dean, M., Li, Y., Wang, J., 2012. Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor. Cell 148, 886–895. Xue, W., Kitzing, T., Roessler, S., Zuber, J., Krasnitz, A., Schultz, N., Revill, K., Weissmueller, S., Rappaport, A.R., Simon, J., Zhang, J., Luo, W., Hicks, J., Zender, L., Wang, X.W., Powers, S., Wigler, M., Lowe, S.W., 2012. A cluster of cooperating tumor-suppressor gene candidates in chromosomal deletions. Proc. Natl. Acad. Sci. U.S.A. 109, 8212–8217. Zhang, G., Hoersch, S., Amsterdam, A., Whittaker, C.A., Beert, E., Catchen, J.M., Farrington, S., Postlethwait, J.H., Legius, E., Hopkins, N., Lees, J.A., 2013a. Comparative oncogenomic analysis of copy number alterations in human and zebrafish tumors enables cancer driver discovery. PLoS Genet. 9, e1003734. Zhang, G., Hoersch, S., Amsterdam, A., Whittaker, C.A., Lees, J.A., Hopkins, N., 2010a. Highly aneuploid zebrafish malignant peripheral nerve sheath tumors have genetic alterations similar to human cancers. Proc. Natl. Acad. Sci. U.S.A. 107, 16940–16945. Zhang, G., Vemulapalli, T.H., Yang, J.-Y., 2013b. Phylooncogenomics: examining the cancer genome in the context of vertebrate evolution. Appl. Transl. Genomics 2, 48–54. Zhang, R., Hao, L., Wang, L., Chen, M., Li, W., Li, R., Yu, J., Xiao, J., Wu, J., 2013c. Gene expression analysis of induced pluripotent stem cells from aneuploid chromosomal syndromes. BMC Genomics 14 (Suppl. 5), S8. Zhang, Y., Malone, J.H., Powell, S.K., Periwal, V., Spana, E., Macalpine, D.M., Oliver, B., 2010b. Expression in aneuploid Drosophila S2 cells. PLoS Biol. 8, e1000320. Zon, L.I., Peterson, R.T., 2005. In vivo drug discovery in the zebrafish. Nat. Rev. Drug Discov. 4, 35–44.