Shizhen Zhu

Phosphatase-dependent and -independent functions of Shp2 in neural crest cells underlie LEOPARD syndrome pathogenesis.

The tyrosine phosphatase SHP2 (PTPN11) regulates cellular proliferation, survival, migration, and differentiation during development. Germline mutations in PTPN11 cause Noonan and LEOPARD syndromes, which have overlapping clinical features. Paradoxically, Noonan syndrome mutations increase SHP2 phosphatase activity, while LEOPARD syndrome mutants are catalytically impaired, raising the possibility that SHP2 has phosphatase-independent roles. By comparing shp2-deficient zebrafish embryos with those injected with mRNA encoding LEOPARD syndrome point mutations, we identify a phosphatase- and Erk-dependent role for Shp2 in neural crest specification and migration. We also identify an unexpected phosphatase- and Erk-independent function, mediated through its SH2 domains, which is evolutionarily conserved and prevents p53-mediated apoptosis in the brain and neural crest. Our results indicate that previously enigmatic aspects of LEOPARD syndrome pathogenesis can be explained by the combined effects of loss of Shp2 catalytic function and retention of an SH2 domain-mediated role that is essential for neural crest cell survival.

Pten mediates Myc oncogene dependence in a conditional zebrafish model of T cell acute lymphoblastic leukemia.

Loss-of-function mutations in pten genes, or expression of a constitutively active version of Akt2, render T-ALL cell survival and disease progression independent of Myc.

Oligodendrocyte progenitor cell numbers and migration are regulated by the zebrafish orthologs of the NF1 tumor suppressor gene

Neurofibromatosis type 1 is the most commonly inherited human cancer predisposition syndrome. Neurofibromin (NF1) gene mutations lead to increased risk of neurofibromas, schwannomas, low grade, pilocytic optic pathway gliomas, as well as malignant peripheral nerve sheath tumors and glioblastomas. Despite the evidence for NF1 tumor suppressor function in glial cell tumors, the mechanisms underlying transformation remain poorly understood. In this report, we used morpholinos to knockdown the two nf1 orthologs in zebrafish and show that oligodendrocyte progenitor cell (OPC) numbers are increased in the developing spinal cord, whereas neurons are unaffected. The increased OPC numbers in nf1 morphants resulted from increased proliferation, as detected by increased BrdU labeling, whereas TUNEL staining for apoptotic cells was unaffected. This phenotype could be rescued by the forced expression of the GTPase-activating protein (GAP)-related domain of human NF1. In addition, the in vivo analysis of OPC migration following nf1 loss using time-lapse microscopy demonstrated that olig2-EGFP(+) OPCs exhibit enhanced cell migration within the developing spinal cord. OPCs pause intermittently as they migrate, and in nf1 knockdown animals, they covered greater distances due to a decrease in average pause duration, rather than an increase in velocity while in motion. Interestingly, nf1 knockdown also leads to an increase in ERK signaling, principally in the neurons of the spinal cord. Together, these results show that negative regulation of the Ras pathway through the GAP activity of NF1 limits OPC proliferation and motility during development, providing insight into the oncogenic mechanisms through which NF1 loss contributes to human glial tumors.

Synergy between loss of NF1 and overexpression of MYCN in neuroblastoma is mediated by the GAP-related domain

Earlier reports showed that hyperplasia of sympathoadrenal cell precursors during embryogenesis in Nf1-deficient mice is independent of Nf1’s role in down-modulating RAS-MAPK signaling. We demonstrate in zebrafish that nf1 loss leads to aberrant activation of RAS signaling in MYCN-induced neuroblastomas that arise in these precursors, and that the GTPase-activating protein (GAP)-related domain (GRD) is sufficient to suppress the acceleration of neuroblastoma in nf1-deficient fish, but not the hypertrophy of sympathoadrenal cells in nf1 mutant embryos. Thus, even though neuroblastoma is a classical “developmental tumor”, NF1 relies on a very different mechanism to suppress malignant transformation than it does to modulate normal neural crest cell growth. We also show marked synergy in tumor cell killing between MEK inhibitors (trametinib) and retinoids (isotretinoin) in primary nf1a-/- zebrafish neuroblastomas. Thus, our model system has considerable translational potential for investigating new strategies to improve the treatment of very high-risk neuroblastomas with aberrant RAS-MAPK activation. DOI: http://dx.doi.org/10.7554/eLife.14713.001

MYC Drives a Subset of High-Risk Pediatric Neuroblastomas and Is Activated through Mechanisms Including Enhancer Hijacking and Focal Enhancer Amplification

The amplified MYCN gene serves as an oncogenic driver in approximately 20% of high-risk pediatric neuroblastomas. Here, we show that the family member MYC is a potent transforming gene in a separate subset of high-risk neuroblastoma cases (∼10%), based on (i) its upregulation by focal enhancer amplification or genomic rearrangements leading to enhancer hijacking, and (ii) its ability to transform neuroblastoma precursor cells in a transgenic animal model. The aberrant regulatory elements associated with oncogenic MYC activation include focally amplified distal enhancers and translocation of highly active enhancers from other genes to within topologically associating domains containing the MYC gene locus. The clinical outcome for patients with high levels of MYC expression is virtually identical to that of patients with amplification of the MYCN gene, a known high-risk feature of this disease. Together, these findings establish MYC as a bona fide oncogene in a clinically significant group of high-risk childhood neuroblastomas.Significance: Amplification of the MYCN oncogene is a recognized hallmark of high-risk pediatric neuroblastoma. Here, we demonstrate that MYC is also activated as a potent oncogene in a distinct subset of neuroblastoma cases through either focal amplification of distal enhancers or enhancer hijacking mediated by chromosomal translocation. Cancer Discov; 8(3); 320-35. ©2017 AACR.This article is highlighted in the In This Issue feature, p. 253.

Neuroblastoma, a Paradigm for Big Data Science in Pediatric Oncology.

Pediatric cancers rarely exhibit recurrent mutational events when compared to most adult cancers. This poses a challenge in understanding how cancers initiate, progress, and metastasize in early childhood. Also, due to limited detected driver mutations, it is difficult to benchmark key genes for drug development. In this review, we use neuroblastoma, a pediatric solid tumor of neural crest origin, as a paradigm for exploring “big data” applications in pediatric oncology. Computational strategies derived from big data science–network- and machine learning-based modeling and drug repositioning—hold the promise of shedding new light on the molecular mechanisms driving neuroblastoma pathogenesis and identifying potential therapeutics to combat this devastating disease. These strategies integrate robust data input, from genomic and transcriptomic studies, clinical data, and in vivo and in vitro experimental models specific to neuroblastoma and other types of cancers that closely mimic its biological characteristics. We discuss contexts in which “big data” and computational approaches, especially network-based modeling, may advance neuroblastoma research, describe currently available data and resources, and propose future models of strategic data collection and analyses for neuroblastoma and other related diseases.

Neuroblastoma and Its Zebrafish Model

Neuroblastoma, an important developmental tumor arising in the peripheral sympathetic nervous system (PSNS), accounts for approximately 10 % of all cancer-related deaths in children. Recent genomic analyses have identified a spectrum of genetic alterations in this tumor. Amplification of the MYCN oncogene is found in 20 % of cases and is often accompanied by mutational activation of the ALK (anaplastic lymphoma kinase) gene, suggesting their cooperation in tumor initiation and spread. Understanding how complex genetic changes function together in oncogenesis has been a continuing and daunting task in cancer research. This challenge was addressed in neuroblastoma by generating a transgenic zebrafish model that overexpresses human MYCN and activated ALK in the PSNS, leading to tumors that closely resemble human neuroblastoma and new opportunities to probe the mechanisms that underlie the pathogenesis of this tumor. For example, coexpression of activated ALK with MYCN in this model triples the penetrance of neuroblastoma and markedly accelerates tumor onset, demonstrating the interaction of these modified genes in tumor development. Further, MYCN overexpression induces adrenal sympathetic neuroblast hyperplasia, blocks chromaffin cell differentiation, and ultimately triggers a developmentally-timed apoptotic response in the hyperplastic sympathoadrenal cells. In the context of MYCN overexpression, activated ALK provides prosurvival signals that block this apoptotic response, allowing continued expansion and oncogenic transformation of hyperplastic neuroblasts, thus promoting progression to neuroblastoma. This application of the zebrafish model illustrates its value in rational assessment of the multigenic changes that define neuroblastoma pathogenesis and points the way to future studies to identify novel targets for therapeutic intervention.

The pre-rRNA processing factor DEF is rate limiting for the pathogenesis of MYCN-driven neuroblastoma

The nucleolar factor, digestive organ expansion factor (DEF), has a key role in ribosome biogenesis, functioning in pre-ribosomal RNA (pre-rRNA) processing as a component of the small ribosomal subunit (SSU) processome. Here we show that the peripheral sympathetic nervous system (PSNS) is very underdeveloped in def-deficient zebrafish, and that def haploinsufficiency significantly decreases disease penetrance and tumor growth rate in a MYCN-driven transgenic zebrafish model of neuroblastoma that arises in the PSNS. Consistent with these findings, DEF is highly expressed in human neuroblastoma, and its depletion in human neuroblastoma cell lines induces apoptosis. Interestingly, overexpression of MYCN in zebrafish and in human neuroblastoma cells results in the appearance of intermediate pre-rRNAs species that reflect the processing of pre-rRNAs through Pathway 2, a pathway that processes pre-rRNAs in a different temporal order than the more often used Pathway 1. Our results indicate that DEF and possibly other components of the SSU processome provide a novel site of vulnerability in neuroblastoma cells that could be exploited for targeted therapy.

Unraveling Neuroblastoma Pathogenesis with the Zebrafish

Ten years of genome-wide association studies (GWAS) by many investigators have produced a series of remarkable discoveries based on large numbers of patients with diverse diseases, leading to optimism that insights gained through GWAS will increasingly be translated into new diagnostics and therapeutics [1]. The future of GWAS appears especially bright given the recent widespread application of whole genome sequencing and CRISPR-Cas9 genome editing technology, which promise to more precisely elucidate molecular pathogenesis and provide genomic strategies for therapeutic intervention. Neuroblastoma GWAS studies led by J. Maris have been among the most successful in human cancer, leading to the identification of multiple inherited associations involving specific genomic regions that significantly impact the risk of a child developing either low risk or high risk disease [2]. Among the GWAS hits reported by the Maris group, single nucleotide polymorphisms (SNPs) associated with the LIM-domain-only1 gene (LMO1) are perhaps the most predictive and are associated with increased expression of LMO1 in neuroblastoma patients with high-risk features: metastatic disease, advanced age, and an unfavorable pathologic tumor grade [3]. One of these SNPs resides in a noncoding region and is necessary for the formation of a large super-enhancer that drives the high levels of LMO1 expression required for neuroblastoma development [4]. This property illustrates the general finding that disease-associated SNPs are often located within super-enhancers that control cell state by regulating the expression of key lineage-associated developmental regulatory genes [4]. To substantiate the significance of LMO1 in neuroblastoma pathogenesis in vivo, S. Zhu and A.T. Look, in collaboration with J. Maris, generated stable transgenic zebrafish lines that overexpress the wild-type LMO1 gene in the peripheral sympathetic nervous system (PSNS) under control of the dopamineb-hydroxylase (dbh) promoter. We found that transgenic fish overexpressing LMO1 alone do not develop neuroblastoma over 6 months of monitoring, consistent with the hypothesis that LMO1 cooperates with other genetic abnormalities to promote neuroblastomagenesis [5]. Indeed, in this study, overexpressed LMO1 synergized with high levels of MYCN expression to accelerate neuroblastoma onset and increase disease penetrance [5] (Figure 1), providing the first direct in vivo support for the GWAS prediction that LMO1 overexpression might promote the initiation of neuroblastoma. As reported by Wang et al., SNPs that correlate with high levels of LMO1 expression are specifically enriched in high-risk neuroblastoma patients with widespread metastasis [3]. Strikingly, we detected distant metastasis of neuroblastoma in transgenic fish overexpressing both MYCN and LMO1 at 6 months of age, which was not observed in fish of the same age that overexpressed MYCN alone [5]. Thus, because of the dire prognosis carried by wildly disseminated neuroblastoma, we sought to better understand the mechanisms underlying the propensity of this tumor for metastatic spread. The zebrafish model system provides clear advantages for elucidating the basis of neuroblastoma metastasis. It faithfully recapitulates all stages of tumor metastasis in vivo, and its relative transparency permits real-time imaging of tumor initiation, progression and dissemination over time. Using this model and neuroblastoma cell lines both overexpressing LMO1, we demonstrated enhanced expression of a panel of genes affecting the tumor cell-extracellular matrix interactions, including loxl3, itga2b, itga3, and itga5, and correlation of their upregulation with neuroblastoma cell invasion and migration [5] (Figure 1). A very recent study using an avian model of metastatic neuroblastoma [6] supports these findings, contributing to a rational for wider use of the zebrafish model to unravel critical cell-cell and cell-microenvironment interactions that drive neuroblastoma metastasis. We also suggest that the zebrafish would provide a valuable resource for evaluating new small-molecule inhibitors or combination therapeutics against metastatic tumor cells. We have shown that suppression of LOX (lysyl oxidase) enzymatic activity with aminopropionitrile (BAPN), a small-molecule inhibitor of the LOX family, can successfully abolish the enhanced invasive and migratory properties induced by LMO1 overexpression in the BE2C neuroblastoma cell line [5]. In addition, cilengitide,

Machine Learning-Assisted Network Inference Approach to Identify a New Class of Genes that Coordinate the Functionality of Cancer Networks

Emerging evidence indicates the existence of a new class of cancer genes that act as “signal linkers” coordinating oncogenic signals between mutated and differentially expressed genes. While frequently mutated oncogenes and differentially expressed genes, which we term Class I cancer genes, are readily detected by most analytical tools, the new class of cancer-related genes, i.e., Class II, escape detection because they are neither mutated nor differentially expressed. Given this hypothesis, we developed a Machine Learning-Assisted Network Inference (MALANI) algorithm, which assesses all genes regardless of expression or mutational status in the context of cancer etiology. We used 8807 expression arrays, corresponding to 9 cancer types, to build more than 2 × 108 Support Vector Machine (SVM) models for reconstructing a cancer network. We found that ~3% of ~19,000 not differentially expressed genes are Class II cancer gene candidates. Some Class II genes that we found, such as SLC19A1 and ATAD3B, have been recently reported to associate with cancer outcomes. To our knowledge, this is the first study that utilizes both machine learning and network biology approaches to uncover Class II cancer genes in coordinating functionality in cancer networks and will illuminate our understanding of how genes are modulated in a tissue-specific network contribute to tumorigenesis and therapy development.