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10.1016/j.celrep.2024.114559
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Article
A simple and scalable zebrafish model of Sonic hedgehog medulloblastoma
Casey Mattie J. 1
Chan Priya P. 23
Li Qing 4
Zu Ju-Fen 156
Jette Cicely A. 1
Kohler Missia 7
Myers Benjamin R. 156
Stewart Rodney A. 18*
1 Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
2 Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT 84108, USA
3 Primary Children’s Hospital, Salt Lake City, UT 84113, USA
4 High-Throughput Genomics and Cancer Bioinformatics Shared Resource, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA
5 Department of Biochemistry, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
6 Department of Bioengineering, University of Utah, Salt Lake City, UT 84112, USA
7 Department of Anatomic Pathology, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
8 Lead contact
AUTHOR CONTRIBUTIONS

This study was conceived and designed by M.J.C. and R.A.S. M.J.C., P.P.C., and J.-F.Z. performed the experiments. M.J.C., Q.L., J.-F.Z., M.K., and R.A.S. analyzed the data. The manuscript was prepared by M.J.C., C.A.J., B.R.M., and R.A.S. with input from all authors.

* Correspondence: rodney.stewart@utah.edu
11 9 2024
27 8 2024
29 7 2024
16 9 2024
43 8 114559114559
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
SUMMARY

Medulloblastoma (MB) is the most common malignant brain tumor in children and is stratified into three major subgroups. The Sonic hedgehog (SHH) subgroup represents ~30% of all MB cases and has significant survival disparity depending upon TP53 status. Here, we describe a zebrafish model of SHH MB using CRISPR to create mutant ptch1, the primary genetic driver of human SHH MB. In these animals, tumors rapidly arise in the cerebellum and resemble human SHH MB by histology and comparative onco-genomics. Similar to human patients, MB tumors with loss of both ptch1 and tp53 have aggressive tumor histology and significantly worse survival outcomes. The simplicity and scalability of the ptch1-crispant MB model makes it highly amenable to CRISPR-based genome-editing screens to identify genes required for SHH MB tumor formation in vivo, and here we identify the gene encoding Grk3 kinase as one such target.

Graphical Abstract

In brief

Sonic hedgehog medulloblastoma (SHH MB) is a malignant pediatric brain tumor with concomitant mutations in ptch1 and tp53 signifying poor survival. Here, Casey et al. present a zebrafish model of ptch1; tp53-deficient SHH MB and identify Grk2/3 kinases as therapeutic targets for the treatment of SHH MB.
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pmcINTRODUCTION

Medulloblastoma (MB) is the most common malignant brain tumor to arise in children. It is frequently diagnosed between 1 and 9 years of age but can occur in adolescents and adults.1 MB arises in the cerebellum and often presents with symptoms of ataxia, compromised motor skills, and vision problems.2 Depending on the presence of specific driver mutations and/or gene signatures within tumor cells at diagnosis, MB is currently classified into three main types: Wingless (WNT), Sonic hedgehog (SHH), and non-WNT/non-SHH (formerly known as group 3 and group 4). The latter two subgroups have poor overall survival (42%–88%) compared to the WNT subgroup (97%–100%).3

The most common genetic alteration in SHH MB is loss/mutation of PTCH1, which is found in ~42% of cases.4 SHH MB and WNT MB tumors often exhibit TP53 mutations at diagnosis,5,6 and MB patients often relapse following the acquisition of mutations in TP53 and amplification of MYC/MYCN from standard radiation and chemotherapy regimens.7 SHH MB patients, in particular, show a dramatic decrease in overall survival in response to TP53 mutation (76%–86% survival for TP53 wild type; 32%–50% survival for TP53 mutant),3,5 thus prompting the World Health Organization to assign a more aggressive treatment regimen for these patients.6,8

SHH MB has been well characterized at the genomic level, with clear drivers of tumorigenesis arising from mutations that activate the SHH signaling pathway. During normal embryonic development, the canonical SHH pathway is activated when the ligand SHH binds to the transmembrane receptor Patched 1 (PTCH1). PTCH1 is a negative regulator of the G-protein-coupled receptor Smoothened (SMO). Thus, SHH indirectly activates SMO by inactivating PTCH1. Active SMO directly binds to and inhibits the catalytic subunit of protein kinase A (PKA), which normally inhibits SHH-pathway signaling by phosphorylating and inactivating GLI transcription factors.9–13 In the absence of SMO activity, suppressor of fused (SUFU) binds to GLI transcription factors and prevents their activation. There are three GLI proteins: GLI1, a transcriptional activator that is produced upon activation of the SHH pathway by GLI2 and GLI3, both of which act as either transcriptional repressors or activators depending on pathway activation.14 In the absence of SHH signaling, proteasomal degradation of GLI2 and GLI3 causes repression of SHH target genes. However, when SHH activates SMO, GLI2/3 are converted from repressor to activator forms, enabling them to transactivate SHH-pathway target genes that regulate CNS polarity and neural patterning.15 In MB, inactivating mutations in PTCH1 or SUFU or activating mutations in SMO or GLI2 promote constitutive activation of the SHH pathway, leading to hyperplasia and tumorigenesis.16,17

Frontline treatment for children with MB includes tumor resection, radiation, and cytotoxic chemotherapy, which leads to devastating consequences for a developing brain.18,19 For SHH MB, pharmacological inhibition of the SHH pathway, through targeting either SMO or downstream GLI transcription factors, has been challenging due to the development of drug resistance.20,21 Drug resistance typically occurs through acquisition of secondary mutations, in either SMO or downstream effectors, that reactivate the SHH pathway, or an oncogenic program switch to alternate signaling pathways such as PI3K (phosphatidylinositol 3-kinase).22–26 Moreover, many potential alternative therapies have limited efficacy due to their inability to cross the blood-brain barrier.27 Current therapies therefore remain ineffective at improving long-term outcomes for patients, and the majority of TP53-mutant SHH MB patients eventually succumb to their disease.

Numerous SHH MB mouse models have been developed to better understand the etiology of SHH MB, to evaluate the response from targeted therapies, and to identify additional signaling pathways for therapeutic exploitation,28 yet current treatment regimens remain suboptimal. Efforts to improve treatment strategies and patient outcomes may require large-scale identification of new therapeutic targets and the analysis of combination therapies using a scalable animal model system such as the zebrafish.

Here, we establish a zebrafish model of SHH-pathway-driven MB. Transient CRISPR-Cas9-mediated gene knockout of the ptch1 gene in zebrafish leads to the rapid development of tumors that resemble SHH MB at the cellular and genomic levels. Similar to humans, combining tp53 mutation with ptch1 loss generates more aggressive tumors and reduced overall survival compared to ptch1 loss alone. To test the potential for using multiplexed CRISPR29 in this model to identify new therapeutic targets for SHH MB, we injected zebrafish embryos with a combination of ptch1 and grk3 guide RNAs (gRNAs). Grk3 is the zebrafish homolog of mammalian GRK2, a downstream positive effector of the SHH pathway that has been previously reported to promote MB growth.30,31 Indeed, loss of grk3 significantly improved the survival of ptch1-crispant animals, indicating that GRK2/3 represents a promising new therapeutic target for SHH MB. To test this notion, we used mammalian SHH MB cell models to show that pharmacological inhibition of GRK2/3 significantly inhibited pathway activity and cell viability. Our data provide a platform for combining high scalability and low cost using in vivo zebrafish MB models with primary mammalian MB-cell-based models for the rapid identification of new therapeutic targets and combination treatments for the most aggressive MB subgroups.

RESULTS

Transient ptch1-crispant zebrafish develop brain tumors

To determine whether ptch1 loss promotes tumorigenesis in zebrafish, we knocked out ptch1 using CRISPR-Cas9-mediated gene editing. The zebrafish Ptch1 protein shows 73% identity with human PTCH1 and is composed of a sterol-sensing domain in its transmembrane region as well as two extracellular domains required for ligand recognition (Figure 1A).32 We therefore designed gRNAs to target the first extracellular domain and the C-terminal domain of the ptch1 gene (gRNAs #1 and #2, respectively; see Figure 1A). We injected one or both ptch1 gRNAs into one-cell-stage wild-type AB embryos, confirmed the ptch1 gene was disrupted via CRISPR sequencing (Figures 1B and 1C), and subsequently monitored them for tumor formation. Brain protrusions were evident by 3–4 weeks post fertilization (wpf) in fish with ptch1 single- and double-injected gRNAs (called ptch1 crispants), with ~76% of injected animals exhibiting obvious tumors and circular swimming behaviors by 150 days (Figures 1D and 1E). H&E staining of the brain protrusions revealed cells with high nuclear-to-cytoplasmic ratios as well as scant to near-absent cytoplasm and hyperchromatic nuclei suggestive of an embryonal neoplasm (or round-blue-cell tumor, Figure 1E). Smaller pupil sizes were also observed in at least one eye in 25 of 38 tumor-bearing, 5- to 8-week-old, ptch1-crispant animals (Figure 1F), consistent with previous reports showing ptch1 is required for optic vesicle development.33,34 Survival was significantly decreased in double ptch1-crispant animals compared to single ptch1 crispants (Figure 1G). These data show that ptch1 is a conserved tumor-suppressor gene during zebrafish brain-tumor formation.

tp53 loss promotes aggressiveness in transient ptch1-crispant brain tumors in zebrafish

In murine models with either germline Ptch1 mutation or somatic Ptch1 disruption, Tp53 loss accelerates tumor incidence and onset.35,36 To determine whether Tp53 functions as a tumor suppressor in the zebrafish ptch1 crispants, we injected one or both ptch1 gRNAs into one-cell-stage embryos derived from a cross between heterozygous tp53-mutant adults (tp53M214K/+)37 and subsequently monitored them for tumor formation and survival. We found that loss of tp53 significantly decreased the survival of single and double ptch1-gRNA-injected animals (Figures 2A and 2B), mimicking the decreased survival outcomes in human SHH MB patients with concurrent TP53 mutations3,5 and mammalian model systems.35,36 Tumor penetrance in the ptch1-crispant; tp53 model depended on the number of gRNAs used (single or double) as well as the gRNA dosage (12.5–25 μM) but was ~92% when the gRNAs were used at the maximum dose. The mutant-tp53-mediated decrease in survival also correlated with an aggressive histopathology, as the tumors contained larger neoplastic cells with increased nuclear molding (Figures 2C and S1A; Table S1).

Adult germline ptch1 mutants develop brain tumors

To independently verify that loss of ptch1 causes brain tumors in zebrafish, we next tested whether germline loss of ptch1 also gives rise to brain tumors. Due to the short lifespan and compromised health of the transient ptch1-crispant adult animals (Figure 1), it was not possible to establish a stable line using our ptch1-crispant methodology. We therefore obtained and analyzed a previously established ptch1tj222 line that has a premature stop codon at position 590 (Figures 1A and 3) and has primarily been studied during embryonic development.38,39 As expected from previous reports, most of the ptch1tj222 homozygotes died at early developmental stages; however, we identified four homozygous mutant escapers out of 147 adults (~37 homozygotes would be expected with normal Mendelian ratios) from an incross between ptch1tj222 heterozygotes. All four homozygous mutants developed brain tumors that resemble ptch1-crispant tumors at the morphological level, and the ability to form tumors was independent of tp53 status (Figure 3A). Analysis of the germline ptch1-null allele supports the conclusion that loss of ptch1 drives the development of brain tumors in zebrafish.

ptch1-crispant tumors genetically resemble human SHH MB

To determine the degree to which the zebrafish ptch1-crispant brain tumors resemble human embryonal tumors, we performed comparative oncogenomics using RNA sequencing on dissected control zebrafish brain tissue (tp53M214K; Casper) and ptch1; tp53M214K-mutant tumors (gRNA #1) (Figure 4A and Table S2). Genes that were differentially expressed between the two groups were analyzed by gene set enrichment analysis (GSEA), which identified a small number of enriched pathways, the most significant of which included genes either expressed in pediatric cancer or regulated by the SHH pathway (Figure 4B). We compared the transcriptional signatures of zebrafish ptch1; tp53M214K-mutant tumors to published human MB signatures that previously defined the four major MB subgroups using principal-component analysis (PCA) (GEO: GSE85217).3 We found that the zebrafish ptch1; tp53M214K-mutant brain tumors tightly cluster with human SHH MB signatures but not other MB-subtype signatures (Figure 4C). These data show that ptch1-crispant zebrafish tumors closely resemble SHH MB at the genomic level.

ptch1-mutant tumors exhibit mixed-lineage stem-cell and neuronal markers

To validate the genetic and genomic analysis of the ptch1-deficient brain tumors and further characterize their histological features, we performed immunohistochemistry (IHC) and RNAscope analysis on ptch1-mutant tumor sections. We performed IHC on zebrafish ptch1-deficient brain tumors as well as control brains for the neural stem-cell marker Sox2, which is specifically expressed in SHH MB,41–43 and found that the ptch1-mutant tumors are positive for Sox2 nuclear staining in a subset of tumor cells compared to control cerebellum (Figures 5A and S1B). However, areas of ptch1-deficient tumors were also Sox2 negative. Since previous studies showed that SOX2-positive human SHH MBs exhibit a heterogeneous population of stem cells and differentiated neurons,42 we next assessed the extent to which the ptch1-deficient brain tumors display neuronal differentiation using the pan-neuronal marker HuC/D. Indeed, we found positive nuclear staining for HuC/D in ptch1-mutant tumor cells (Figures 5A and S1B) that were adjacent to those expressing Sox2. For comparison, we also performed IHC analysis on zebrafish CNS NB-FOXR2 tumors, as these tumors have similar small-round-blue-cell morphologies but are derived from oligodendrocyte precursor cells (OPCs) with activated mitogen-activated protein kinase (MAPK) signaling.44 We found that the CNS NB-FOXR2 tumor cells were Sox2 positive in most tumor cells but were HuC/D negative, which is consistent with an OPC origin (Figure 5A). The IHC data therefore suggest that ptch1-deficient tumors are a mixed-lineage (stem-/differentiated-cell) tumor type, as previously described for SOX2-positive human SHH MB.42

The transcriptomic analysis of ptch1-crispant tumors (Figure 4) was performed on grossly dissected brain-tumor samples, which may include surrounding normal tissue. Therefore, to confirm the genomic data and provide higher-resolution spatial information on transcriptomic gene expression patterns, we performed RNAscope to visualize RNA specific to individual tumor cells in situ.45 We focused on genes that were highly upregulated in human medulloblastoma (sox11a),46 in SHH-pathway activation (gli1),14 and expressed during anterior cerebellar and midbrain morphogenesis (otx2b and atoh1b),47–49 the location where most of the ptch1-mutant tumors arise (Figures 5B and 5C). Comparable to our RNA-sequencing analysis, we observed elevated sox11a, gli1, atoh1b, and otx2 levels in our ptch1-crispant tumors compared to both control brain and CNS NB-FOXR2 tumors. Thus, the genetic, genomic, and histological analyses collectively demonstrate that loss of ptch1 in zebrafish induces SHH MB.

Zebrafish SHH medulloblastomas display transcriptional signatures of neuronal progenitors

To begin to identify potential cellular origins for the ptch1-crispant brain tumors, we compared genes differentially expressed in the ptch1-crispant brain tumors to those of the previously published CNS NB-FOXR2 pediatric brain-tumor model.44 The CNS NB-FOXR2 brain-tumor model originates from the expression of either wild-type or oncogenic NRAS in OPCs. As expected, the CNS NB-FOXR2 brain tumors revealed significant upregulation of OPC markers sox10 and erbb3 (Figure S2A, GEO: GSE80768).44 In contrast, ptch1-crispant brain tumors were positively enriched for ciliogenesis and neuronal (specifically glutamatergic) markers and lacked expression of oligodendrocyte markers (Figure S2B and Table S3). PCA also verified that ptch1-crispant tumors cluster independently from the CNS NB-FOXR2 zebrafish tumor model as well as normal brain (Figure S2C). These data indicate that the ptch1-crispant brain tumors have characteristics of neural progenitor/stem cells and likely arise from a different cell of origin than CNS NB-FOXR2 tumors. These data also suggest that ptch1-crispant brain tumors originate in a neural stem-cell compartment in the cerebellum, similar to human SHH MB.50

Zebrafish ptch1-crispant tumors arise in the anterior cerebellum and midbrain region

A morphological feature of the ptch1-crispant tumors is a “bump” on the head, usually located just anterior to the cerebellum (Figure 1). Histologically, we also observed aggressive infiltration of ptch1-crispant tumor cells coming from the anterior cerebellar region toward the third ventricular space at the mid-hindbrain boundary (MHB) region (Figure 1). In addition, the structure of the corpus cerebelli and lobus caudalis cerebelli (located in the posterior region of the hindbrain, Figure 1D) appeared relatively normal in the majority of ptch1-crispant animals (see Figures 1E and 2C). As these tumors are quite aggressive by 5–7 wpf, we also performed histology on ptch1-crispant animals at 2, 3, and 4 wpf before any obvious phenotypes were present to attempt to visualize the location of tumor onset. Strikingly, ptch1-crispants with no apparent brain protrusion or behavioral phenotypes still had tumor-cell infiltration in multiple areas throughout the brain at 2 wpf, thus hindering an accurate assessment of tumor onset via histology alone (Figure S3A). Based on prior anatomical observations, we hypothesized that the ptch1-crispant tumors arise in the valvula cerebelli, a unique anterior extension/lobe of the teleost cerebellum adjacent to the midbrain, or the MHB subventricular region, or both. To test this, we analyzed candidate regions of the zebrafish cerebellum that are responsive to hedgehog signaling and, therefore, might contain the cell of origin for the ptch1-crispant brain tumors, by using available transgenic lines with green-fluorescent SHH-producing cells (Tg(shh:H2A-GFP)) and red-fluorescent SHH-responsive cells (Tg(8xGli:mCH)).51,52 We generated double-transgenic lines to visualize these two cell types within the zebrafish MHB and cerebellum (Figures S4A and S4B). Interestingly, we found that SHH-producing and -responding cells were tightly juxtaposed at the MHB anterior cerebellar region (Figures S4A and S4B). Considering that cerebellar granule neural progenitor (GNP) cells are the cell of origin in human SHH MB and that GNP cells arise from the valvula cerebelli in zebrafish, we reasoned that the valvula cerebelli is at least one origin for the ptch1-crispant tumors. To evaluate this model, we compiled a list of genes that are known to be expressed in the zebrafish MHB region (Table S4) and analyzed whether they are enriched in ptch1-crispant brains compared to control brains. Indeed, this analysis revealed positive enrichment for anterior cerebellar/MHB-expressing genes within the ptch1-crispant brains (Figures S5A and S5B), suggesting that the brain tumors we observe in ptch1-crispant zebrafish likely originate in the region of the anterior cerebellum/MHB, which includes the valvula cerebelli (see discussion).

SHH MB tumorigenesis requires Grk3

With the ultimate goal of using the ptch1 crispants for target discovery in high-throughput screens, we investigated whether CRISPR-based genome editing could be a useful tool to rapidly identify important mediators of SHH MB in fish.29 We prioritized the analysis of GRK2, a G-protein-coupled-receptor kinase that promotes activation of the SHH signaling pathway through phosphorylation of SMO.11,13,53 GRK2 has been shown to stimulate the growth and proliferation of MB cell lines30,31 but has not been tested in vivo for its importance in SHH-pathway-induced tumorigenesis. To knock out the zebrafish GRK2 homolog, called grk3, we designed gRNAs to target the catalytic and RGS-homology (RH) domains of grk3 and confirmed gRNA-mediated grk3 mutations in F0-injected embryos by high-resolution melting analysis (Figure 6A). We next injected zebrafish one-cell-stage embryos with the ptch1 gRNA either alone or in combination with grk3 gRNAs and subsequently monitored their survival (Figure 6B). We found that loss of grk3, via two independent grk3 gRNAs, significantly improved the lifespan of ptch1-crispant animals compared to animals injected with ptch1 plus negative control gRNAs (Figure 6B). We also tested various smo gRNAs as positive controls; however, loss of smo in ptch1 crispants induced early developmental defects, thus preventing the development and analysis of tumors in these animals. By comparison, the grk3 gRNAs likely allowed the development of tumors because grk3 mRNA/protein is maternally supplied.54 These findings highlight the potential of a transient, multiplexed-CRISPR-based approach to generate large numbers of ptch1-crispant, brain-tumor-bearing animals for drug discovery.

To determine whether the in vivo findings were conserved in mammalian SHH MB, we used the recently developed murine Ptch1-deficient MB cell line SMB21 that strictly requires continuous SHH-pathway activation to proliferate in culture.26,55 We treated SMB21 cells with two SMO inhibitors called vismodegib and SANT-1, as well as two GRK2/3 inhibitors called Cmpd101 and 14AS.56,57 We found that all four inhibitors strongly block SHH-pathway activity in Ptch1-deficient murine SMB21 cells as monitored by qPCR of Gli1, a universal transcriptional readout of SHH-pathway activity (Figure 6C). Importantly, we also found that the two GRK2/3 inhibitors (Cmpd101 and 14AS) significantly inhibited SMB21 cell viability to the same extent as SMO inhibitors (Figure 6C). These data show that GRK2/3 has a conserved role in promoting tumor-cell viability during Ptch1-deficient SHH MB tumorigenesis, and these proteins represent a promising target for the treatment of SHH MB.

DISCUSSION

Preclinical models of SHH-driven MB are an important tool for identifying and testing new strategies to eliminate high-risk tumors. Several robust mouse models of SHH-driven MB, including the high-risk TP53 subgroup, have been used to enhance our understanding of the genetic and epigenetic drivers underlying tumor formation as well as for preclinical testing of SHH-pathway inhibitors, such as vismodegib and sonidegib (reviewed by Roussel and Stripay28). While murine models will continue to be valuable for identifying and testing rationally designed treatments, they are not ideal for high-throughput screening approaches, such as genetic and drug screens, due to their small litter sizes and high costs associated with scaling up. Unbiased screening approaches in animals are needed to complement mechanism-based approaches to identify both tumor- and host-dependent vulnerabilities that overcome the shortcomings of the current generation of SHH-pathway inhibitors, such as rapid drug resistance and developmental toxicities. As a first step to addressing this problem, we have established a simple and scalable CRISPR-Cas9-based method to generate ptch1-deficient zebrafish models of SHH-driven MB that recapitulate the histology and genomic signatures of human SHH MB. Based on our experience, we recommend using the single ptch1 gRNA #1 to generate zebrafish MB if improved survival and larger tumors are needed, whereas the rapid onset associated with using both ptch1 gRNAs would be more amenable for analysis of tumor initiation and cell-of-origin or lineage studies.

Previous studies of ptch1 in zebrafish focused on its requirement during organogenesis of the eye, ear, and fin.38,58–60 In addition, ptch1 loss was shown to modify the malignancy of notch1-driven T cell acute lymphoblastic leukemia in zebrafish tumor models.61 Here, we demonstrate that germline or somatic loss of ptch1 alone is sufficient to drive formation of embryonal brain tumors in zebrafish that resemble SHH MB at both histological and genomic levels, thus demonstrating that ptch1 is a highly conserved tumor suppressor in brain-tumor etiology. In addition, we show that the combined loss of ptch1 and tp53 significantly enhances tumor malignancy and decreases survival, consistent with observations in murine MB models and SHH MB patients.5,6,35 These data also suggest that zebrafish may succumb to other SHH-driven tumors, such as rhabdomyosarcoma and basal cell carcinoma,62 which we were unable to analyze in this study due to the severity and early lethality of the brain tumors. However, these tumors could be tested in future experiments using conditionally targeted ptch1 alleles.

GNPs are an established cell of origin for SHH-driven MB in mammals.63–65 During cerebellar development, mammalian GNPs arise from the rhombic lip and migrate tangentially to cover the surface of the dorsal cerebellum and form the external granule layer (EGL).66,67 The secretion of SHH from underlying Purkinje cells induces proliferation of the EGL that occurs from embryogenesis until puberty, which is required to produce enough GNPs to sustain the growth of the cerebellum during development and attain its final size for the rest of adult life. Sustained SHH signaling in GNPs (for example, through PTCH1 loss) maintains a proliferative state in the EGL and prevents differentiation, thereby promoting MB formation in infants and adolescents. In contrast, zebrafish lack the transient EGL proliferation zone during embryogenesis, and Shh-pathway components (e.g., shh, gli1/2/3, ptch1) are absent from the dorsal cerebellum.68–70 Thus, we believe the formation of MB in zebrafish arises from Sox2-positive neural stem/progenitor cells that generate GNPs at different times/locations in the cerebellum that are distinct from mammals. Nevertheless, because these zebrafish brain tumors involve the same molecular (SHH-pathway activation) and cellular (EGL/GNP proliferation) mechanisms as their mammalian counterparts, we expect them to be broadly useful for the study of MB.

We hypothesize that zebrafish SHH-driven MB arises in the valvula cerebelli, a unique anterior lobe of the teleost cerebellum that is an extension of the corpus cerebelli located underneath the optic tectum adjacent to the midbrain ventricle cavity.63–65 The valvula cerebelli maintains the same layered structure as the corpus cerebelli (molecular, Purkinje, and granule neuron layers) and produces atoh1a-positive GNPs that migrate into the granule neuron layer throughout the life of the fish.71–75 Indeed, a unique feature of the zebrafish cerebellum is its ability to regenerate and grow throughout adulthood due to the presence of cerebellar stem-cell niches that continually generate GNPs, so a transient period of EGL proliferation is not necessary during embryogenesis.71–75 In addition, the anterior-ventral location of the valvula cerebelli places it in proximity to Shh-producing cells in the ventral neural tube,63–65 and we show that zebrafish express both Shh-producing and Shh-responsive cells at the border of the cerebellum and MHB. The location of the zebrafish MB tumors by gross morphology and histology shows a preponderance of tumors arising at the midbrain boundary region and expanding via the mesencephalic cavity to dorsal regions. Finally, our genomic and histological analysis shows transcriptional signatures consistent with SHH-induced GNP proliferation as well as cerebellar and MHB cell types. Thus, we propose that the continuous supply of GNPs in the valvula cerebelli may be an origin of MB tumor formation in zebrafish, which could be tested in the future using conditional systems to inactivate ptch1 in different cerebellar compartments and label different cell lineages to determine the precise cell of origin.

In this study, we have outlined methods to establish SHH MB tumors in zebrafish, which develop obvious masses within 3–4 weeks and can be scaled to hundreds of animals each day by a single user. For rapid identification of genes required for tumor formation and survival, we utilized a dual CRISPR-based approach to genetically modify potential therapeutic targets. These experiments support the idea that multiple gRNAs can be injected into embryos with the ptch1 gRNAs to perform an unbiased screen for genes that impact tumor growth while at the same time assessing embryonic and developmental toxicities that currently hamper the use of single-agent SHH inhibitors. Here, we applied this approach to study the role of GRK2 (zebrafish Grk3) in MB tumorigenesis, which we recently demonstrated plays a role in SHH signaling by phosphorylating SMO to promote PKA recruitment and inactivation, leading to GLI activation (Figure 6D).11–13 Loss of grk3 in zebrafish causes stereotypical shh-deficient developmental phenotypes, such as cyclopia.54 However, the potential role of grk3/GRK2 during SHH MB tumorigenesis in vivo is not known. Here, we show that CRISPR-mediated inactivation of grk3 significantly improves the survival of ptch1 crispants, demonstrating that Grk3 represents a key mediator of oncogenic SHH signaling in vivo as well as a potential therapeutic target.30 Finally, we provide a roadmap for translating the zebrafish MB findings to mammalian MB systems using the mouse SMB21 MB cell model. This complementary approach identified GRK2/3 small-molecule inhibitors as a potential new therapy for SHH MB. These inhibitors include Cmpd101, 14AS, and paroxetine (a US Food and Drug Administration-approved selective serotonin reuptake inhibitor) that are currently used in cardiovascular disease models and should be evaluated in future murine and human patient-derived xenograft models of SHH-driven MB.57,76–78

Limitations of the study

The optical transparency of the zebrafish system is a valuable feature for imaging studies in cancer initiation, cancer progression, and drug response.79 A current limitation of the ptch1-crispant MB model is the lack of a bright fluorescent reporter expressed in the tumor, which complicates drug-screening efforts in vivo using methods we previously described.80 Despite evaluating reporters expressed in different cerebellar cell types (driven by atoh1c, ptf1a, dbx1a, and ngn1 promoters), we were unable to identify one that gave rise to bright and/or consistent fluorescence, thus preventing the discrimination of fluorescent tumor cells from surrounding normal cerebellar/midbrain cell types. Ideally, targeting ptch1 (or other tumor suppressors) in zebrafish using CRISPR-Cas9-based methods would be coupled with integration of a fluorescent reporter for cell-autonomous labeling. Fortunately, new techniques in zebrafish, such as GeneWeld,81 will allow such experiments to be performed in the future, which will enable a more accurate determination of the cell of origin. In addition, our findings support the generation of zebrafish transgenic approaches in which constitutively activated SMO alleles can be expressed in the cerebellum with fluorescent tags. To this end, the Zebrafish Brain Browser82,83 is an invaluable online tool to identify established transgenic lines in specific cerebellar cell types. Such fluorescently labeled zebrafish tumor models will greatly facilitate the repertoire of transplantation-based techniques that will be ideal for rapid in vivo drug screening and examination of tumor-host and tumor-microenvironment interactions.

STAR★METHODS

Detailed methods are provided in the online version of this paper and include the following:

RESOURCE AVAILABILITY

Lead contact

Further information and requests for resources and reagents should be directed to Rodney Stewart (rodney.stewart@utah.edu).

Materials availability

This study did not generate new unique reagents.

Data and code availability

Raw RNA sequencing data is publicly available and has been deposited at GEO under the acquisition number GSE242897. Analyzed RNA sequencing data is available via Table S2.

This paper does not report any original code.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

EXPERIMENTAL MODEL AND SUBJECT DETAILS

Ethics statement

All experiments using zebrafish conformed to the regulatory standards and guidelines of the University of Utah Institutional Animal Care and Use Committee.

Zebrafish husbandry

Zebrafish were bred and maintained as described.96 Lines utilized throughout the study included Tg(8xGli:mCH),52 Tg(shh:H2A-GFP),51 tp53M214K,37 and Tg(actb2:loxP-GFP-loxP-TagRFP).84 The ptch1tj222 line was obtained from the International Zebrafish Resource Center (htttp://www.zebrafish.org/home/guide.php) and has been previously described.38 All experiments were performed before animals reached sexual maturity or were too small to determine sex. The age/developmental stage of animals is noted in the figure or legend when applicable.

Cell culture conditions

Murine SMB21 cells were cultured in DMEM/F-12 with HEPES (Thermofisher 11330-057) and supplemented with B27 (Gibco 17504044) and Pen/Strep. Cells were grown on low attachment plates (Fisher Scientific 07-200-601 and 10-320-171) as neurospheres at 37°C with 5% CO2. Cells were confirmed to have constitutive SMO activation by comparing proliferation rates between cells treated with vehicle or SMO inhibitor as previously published.55

METHOD DETAILS

Genomic DNA extraction and genotyping

Genomic DNA was extracted from adult zebrafish by fin clipping. Fins were lysed in alkaline lysis solution (25 mM NaOH, 0.2 mM EDTA) at 95°C for 2 h and neutralized with 40 mM Tris pH 5.0. Genotyping was performed using high resolution melting analysis (HRMA) as previously described.97–100 Each well of a 96-well plate (BioRad HSP9665) contained 20 μL of mineral oil, 2 μL of LightScanner master mix (BioFire Defense HRLS-ASY-0003), 0.5 μM of each primer, and 1 μL of genomic DNA. The plate was sealed with an optically transparent cover and centrifuged at 1800 rcf for 2 min. grk3 (gRNA #1, gRNA #2, and gRNA #3), ptch1 (gRNA #1), and ptch1tj222 were cycled with the following conditions: denaturation at 96°C for 5 min; 55 cycles of 30 s at 96°C, 30 s at 68°C, 30 s at 72°C, ending with 3 min at 95°C and cooled to 4°C. ptch1 (gRNA #2) was cycled with: denaturation at 94°C for 3 min; 50 cycles of 30 s at 94°C, 20 s at 70°C, ending with 30 s at 94°C, 30 s at 25°C and cooled to 4°C. HRMA was used to amplify a 103-bp and 96-bp product for ptch1 (gRNA #1) and ptch1 (gRNA #2), respectively. Similarly, HRMA was used to amplify a 71-bp product for ptchtj222, a 109-bp product for grk3 (gRNA #1), a 123-bp product for grk3 (gRNA #2), and a 105-bp product for grk3 (gRNA #3). HRMA results were analyzed with the LightScanner Call-IT Software (Idaho Technology Inc.) and validated by standard polymerase chain reaction (PCR) of genomic DNA and Sanger sequencing. Primers are listed in Table S5.

RNA sequencing

RNA was isolated from three tumor-bearing ptch1 crispant brains and three normal zebrafish brains using the QIAGEN miRNeasy micro kit (217084). RNA quality was assessed using the Agilent RNA ScreenTape Assay (Agilent 5067–5579 and 5067–5580). The Illumina TruSeq Stranded Total RNA kit with Ribo-Zero Gold (Illumina 20020598) was used for library preparation. Sequencing libraries were chemically denatured and applied to Illumina NovaSeq flow cells using the NovaSeq XP chemistry workflow (Illumina 20021665). The flow cell was transferred to an Illumina NovaSeq instrument and a 2 × 150 cycle paired end sequence run with 100 M reads was performed using a NovaSeq S2 reagent kit (Illumina 20012860). The hciR package was used for all RNA sequencing data analysis (https://github.com/HuntsmanCancerInstitute/hciR). STAR was used to align samples to the zebrafish genome (GRCz11 v104).88 Count matrices were generated using featureCounts86 and DESeq2 was used to perform differential gene expression analysis on ptch1 tumor-bearing zebrafish compared to controls or NB-FOXR2 CNS-PNET tumors using a 5% false discovery rate.44,87 A heatmap of the top 40 differentially regulated genes was generated in RStudio. Tumors were not able to be distinguished from normal brain tissue therefore, animals were deemed to be tumor-bearing due to a protrusion of the brain and abnormal swimming behavior.

GSEA

The homologene and biomaRt packages were run to convert zebrafish gene names to human gene names.90,89 Zebrafish gene names without a human homolog were not included in the final rank list. Duplicate genes with the highest log2FC value were retained. Rank lists were generated using ptch1 tumor versus normal brain or ptch1 tumor versus the zebrafish NB-FOXR2 CNS-PNET model.44 Analysis was performed using GSEA (v4.2.2).

Lists of zebrafish midbrain-hindbrain boundary (MHB) genes and hindbrain glutamatergic neuron markers were curated from the available literature (Tables S3 and S4). Zebrafish gene names were converted to human gene names and GSEA was run with the rank lists described above.

PCA

To determine which human medulloblastoma subtype is modeled by the zebrafish ptch1 tumors, PCA of human medulloblastoma and zebrafish ptch1 crispant samples was performed based on the genes differentially expressed between ptch1 tumors and our previously published zebrafish NRAS tumors.44 Human homologs for zebrafish genes were downloaded from biomaRt,90 and only homologs with percent identity greater than 30% were kept and joined to zebrafish RNA-seq log2 normalized counts using ensembl id, sorted by rowmean, and filtered to remove any duplicated genes. Human microarray expression (GEO: GSE85217)3 and zebrafish RNA-seq log2 normalized counts were joined together, and only genes that exist in both human microarray and zebrafish RNA-seq data were kept. Similarly, PCA was performed comparing normal brain, zebrafish ptch1 crispant samples and zebrafish NB-FOXR2 CNS-PNET (GEO: GSE80768).44 PCA data was generated using an in-house R package plot_pca (https://github.com/HuntsmanCancerInstitute/hciR).

Immunohistochemistry

Paraffin-embedded zebrafish sections were generated and hematoxylin-and-eosin staining was performed by the Histology Core at the Huntsman Cancer Institute. Immunohistochemistry for Sox2 (1:200, EMD Millipore ab5603) and HuC/D (1:1000, Invitrogen A-21271) were performed by the Research Immunohistochemistry Core at Huntsman Cancer Institute. Staining was completed on the Leica BOND RX automated research stainer using the BOND Polymer Refine Detection kit (Leica DS9800). Slides were dewaxed using BOND Dewax Solution (Leica AR9222) and antigen retrieval was performed for 30 min with either BOND Epitope Retrieval Solution 1 (citrate based with pH 6) (Leica AR9961) for HuC/D or BOND Epitope Retrieval Solution 2 (EDTA based with pH 6) (Leica AR9640) for Sox2. Primary antibody was incubated for 15 min. Slides were imaged on a Zeiss Axio Scan.Z1 microscope at a magnification of 10X and 20X.

RNAScope

RNAScope was performed on paraffin-embedded zebrafish sections by the Research Immunohistochemistry Core at Huntsman Cancer Institute. The slides were run in the Leica BOND RX automated research stainer with the BOND Research Detection System 2 tray (Leica DS9777). RNAscope was performed using the RNAscope LS Multiplex Fluorescent Reagent kit (ACD Bio 322800) with the RNAscope LS 4-Plex Ancillary kit (ACD Bio 322830). Retrieval conditions were optimized with the BOND Epitope Retrieval Solution 2 (Leica AR9640) (EDTA with pH 9) at 88°C using a set of control probes: myod1 in opal 480 (ACD Bio 481231), actb2 in opal 520 (ACD Bio 486831-C2), vasa in opal 690 (ACD Bio 407271-C3) and gad1b in opal 620 (ACD Bio 455921). Under these conditions, the reaction was again carried out with probes against sox11a in opal 480 (ACD Bio 590461), gli1 in opal 520 (ACD Bio 542721-C2), atoh1b in opal 620 (ACD Bio 1300401-C4), and otx2 in opal 690 (ACD Bio 507371-C3) according to the manufacturer’s instructions with the following modifications. The C2, C3 and C4 probes were diluted at a 1:50 ratio into the C1 probe (myod1 or sox11a). All opals were diluted to 1:100. Slides were mounted using ProLong Diamond Antifade Mountant (Invitrogen P36961). Slides were imaged by the University of Utah Cell Imaging Core on a Zeiss Axio Scan.Z7 microscope at a magnification of 20X.

Multiplexed immunofluorescent images were analyzed by the University of Utah Cell Imaging Core using QuPath (version 0.5.1).91 The brain was selected as the region of interest (ROI) and the STARDIST nucleus segmentation algorithm was applied (https://github.com/qupath/qupath-extension-stardist).92 To obtain cell borders, the nuclear outlines were expanded by 5 pixels. Any RNA objects with an intensity above a certain threshold (sox11a, 5000; gli1, 600; atoh1b, 500; otx2, 1200) and size ranging from 0.1 to 4 μm2 were detected by the subcellular spot detection in QuPath. Cells were classified as negative, 1+ subcellular object, 4+ subcellular objects, and 10+ subcellular objects and the overall percent positive and H score were calculated.

Tumor survival and penetrance

To generate survival curves, fish were visually monitored in tanks weekly. Animals were sacrificed when the tumor impaired the animals ability to swim or behave normally. Statistical significance was calculated using the Mantel-Cox test with GraphPad Prism 9.

Tumor penetrance was calculated by determining the total number of animals with confirmed gRNA-mediated ptch1 editing at 2 weeks via tail fin genotyping (denominator) and then measuring the number of those animals that developed tumors (numerator), and multiplying by 100.

gRNA target site design and preparation

gRNA target sites were designed using CHOPCHOP (http://chopchop.cbu.uib.no) or the IDT custom gRNA design tool as previously described.101,85 Briefly, target sites were selected that had low self-complementarity, a GC content between 45 and 75%, no off-targets, a predicted efficiency of 45% or greater, and contained a GGG or AGG PAM sequence. Alt-R crRNA and Alt-R tracrRNA were synthesized by IDT.

Microinjections

25μM gRNA:Cas9 RNP complexes were prepared as previously described101 and injected into the single cell at a dosage of 50–65 ng. Briefly, crRNA was annealed to tracrRNA by heating equal volumes at 95°C for 5 min, cooling at 0.1 °C/s to 25°C, incubating for 5 min at 25°C, and cooling to 4°C. Double gRNA injections utilized a total of 25μM–50μM gRNA (12.5μM–25μM gRNA each). Triple gRNA injections utilized a total of 37.5μM–75μM gRNA (12.5μM–25μM gRNA each). Prior to injection, gRNA and Cas9 were incubated at 37°C for 5 min for form the RNP complex.

CRISPR/Cas9

crRNA was designed against exon 6 and exon 23 of ptch1 (GRCz10 transcript 201) (GAGCTGATAATGGGCAGTCGGGG and TCTCGTCAAAGGGCACGTGAGGG, respectively). crRNA was designed against exon 3, exon 12 and exon 18 of grk3 (GRCz11 transcript 202) (CTGCATGAACGAGATCGACGAGG, ACACGTCCGCATCTCTGACCTGG, and ATAAAAACGAGGCTCGCAAGAGG, respectively). crRNA was designed against exon 3 of inka1b (GRCz11 transcript 201) (GGAGAATCACGCTGAACGTTTGG) (negative control). crRNA was synthesized by IDT and annealed to tracrRNA (IDT) as described above.

CRISPR sequencing

Genomic DNA was isolated from ptch1 crispant brains using the QIAGEN DNeasy Blood and Tissue kit (69504) without the addition of RNase A. For crispant embryos (24 hpf), genomic DNA was pooled after verification of CRISPR cutting via HRMA. Crispant genomic DNA had been previously isolated with alkaline lysis solution (25 mM NaOH, 0.2 mM EDTA) and neutralized with 40 mM Tris pH 5.0. The genomic region of the ptch1 gRNA #1 target was amplified using Phusion Hot Start II high-fidelity PCR master mix (Thermo Scientific F565). PCR was performed under the following conditions: denaturation at 98°C for 30 s; 35 cycles of 10 s at 98°C, 30 s at 63°C, 30 s at 72°C, ending with 10 min at 72°C and cooled to 4°C. Amplification was confirmed by gel electrophoresis and the remaining PCR products were purified using QIAGEN PCR Purification kit (28104). The quality of the purified PCR product was assessed using the Qubit dsDNA HS Assay (Thermo Scientific Q32851). The ChIP-Seq with NEBNext Ultra II DNA Library Prep kit (New England Biolabs E7634L) was used for library preparation. PCR-amplified libraries were qualified on an Agilent Technologies 4150 TapeStation using a D1000 ScreenTape assay (5067–5582 and 5067–5583) and the molarity of the adapter-modified molecules was defined by quantitative PCR using the Kapa Biosystems Kapa Library Quant kit (KK4824). Sequencing libraries were normalized, pooled then chemically denatured. Denatured samples were transferred to an Illumina NovaSeq × instrument and a 150 × 150 cycle paired end sequence run was performed using a NovaSeq × Series 10B reagent kit (Illumina 20085594).

UMI Fastq files were merged with the paired-end Fastq files using in house UMIscripts (https://github.com/HuntsmanCancerInstitute/UMIScripts). Samples were aligned to the reference target region (GRCz10 transcript 201) (AAAGCAGATGTGGGTCAAGGTTACATGAACCGGCCCTGCCTGAATCCTGCAGACCCCGACTGCCCATTATCAGCTCCCAACAAGAACACCACAGGGGTGAGCTTAGTCAACAAATCACATGCGATCATGTGTTTATCTGTGTCAAATGTCTGTTCTCATTTTGCCTAGTCATTAGCAAACAGCTAAAGATTTGGCAATTAAAGTGATGTTGTTTTGCATCTCAAGCGTGTCTCTAATTTATGATCTGTCTCCTTCTTAAGCCTTTTGACGTGGCTCCTGT) using Bowtie2.93 Samtools was used to append the mate score and then sort by chromosome and increasing coordinate.94 Duplicates were discarded based on the UMI sequence using in house UMIscripts. Final de-duplicated BAM files were exported as new Fastq files using Samtools and the CRISPResso2 package was used to quantitatively assess the outcome of genome-editing.94,95

qRT-PCR and cell viability

SMB21 cells (initially derived from Ptch1+/−; p53−/− mice) were cultured as previously described.26,55 Cells were treated with SMO inverse agnoists vismodegib (Vismo, 10 μM) or SANT-1 (250 nM), the GRK2/3 inhibitors Compound 101 (Cmpd101, 30 μM) or 14AS (30 μM) or vehicle control (DMSO). Cells were treated overnight for qRT-PCR, or 7 days to assess cell viability. For qRT-PCR measurements, total RNA was isolated from vehicle- or drug-treated SMB21 cells using an RNeasy Mini kit (QIAGEN, 74104), and first-strand cDNA was prepared using SuperScript III reverse transcriptase (Thermo Fisher, 18080093) with an oligodT primer according to the manufacturer’s instructions. Gli1 qRT-PCR measurements were performed using a 2X SYBR Green Supermix (BioRad, 1725272). Primer sequences for Gli1 are ccaagccaactttatgtcaggg and agcccgcttctttgttaatttga, and for Gapdh (housekeeping gene) are tgttcctacccccaatgtgt and ggtcctcagtgtagcccaag. Relative transcript abundance was calculated using ΔΔCT measurements. Viability assays were performed using a CellTiterGlo kit (Promega, G7570). Mean ± the standard deviation from three technical replicates are reported, and each experiment was repeated twice with similar results.

Image acquisition and processing

Brightfield images were taken using an Olympus SZX16 microscope with an aperture of 0.3 and configured with an Olympus DP74-CU camera. Fluorescent images were taken using an Olympus Fluoview FV1200 confocal microscope with a UPlanSApo 10X/0.40 or UPlanSApo 60X/1.20W objective. H&E and RNAscope images were taken using a Zeiss Axio Scan.Z1 slide scanner at a magnification of 10X and 20X. For visualization purposes, RNAscope images were adjusted in QuPath (version 0.5.1)91 with each channel minimum set to the peak pixel intensity. Channel maximums were left at auto adjusted levels. Figures were generated using Adobe Illustrator (2022) and Adobe Photoshop (2022).

QUANTIFICATION AND STATISTICAL ANALYSIS

Statistical analysis

The Mantel-Cox test was used to determine the statistical significance of survival data. An unpaired two-tailed t test with Welch’s correction was used to calculate the significance of animals with pupil size differences, the significance of RNAscope H-score differences between tp53-mut; Casper and tp53-mut; ptch1 gRNA #1 animals, and the significance of cell viability and Gli1 mRNA measurements. Additional statistical details can be found in the figures and legends where applicable. All statistical analysis was calculated using Prism 9.

Supplementary Material

1

2

ACKNOWLEDGMENTS

We thank the Bruce Appel, Richard Dorsky, and Kristen Kwan labs for reagents and Kazuyuki Hoshijima, David Grunwald, Timothy Parnell, Brian Dalley, Erika Egal, Jeffrey Stanley, Xiang Wang, Wei Zhang, Annika Thorpe, and Mya Scheib for technical support. We thank Christian Davidson for initial pathology consultation. SMB21 cells were generously provided by Rosalind Segal and Xuesong Zhao. Research reported in this publication utilized the high-throughput genomics, bioinformatic analysis, and biorepository and molecular pathology shared resources (including the Research Histology and Research Immunohistochemistry cores) at the University of Utah Huntsman Cancer Institute, which is supported by the National Cancer Institute (P30CA042014). The computational resources used were partially funded by the NIH Shared Instrumentation grant 1S10OD021644-01A1. We acknowledge the Cell Imaging Core at the University of Utah for use of the Zeiss Axio Scan.Z1 slide scanner and image analysis. We thank current and former members of the R.A.S. laboratory for thoughtful discussions and the zebrafish core at the University of Utah for providing animal husbandry. This work was supported by funding from the NIH National Institute for Neurological Disorders and Stroke (R01NS106527) (R.A.S.) as well as the Cell Response and Regulation Program at the Huntsman Cancer Institute (#230202) (R.A.S. and B.R.M.), the Huntsman Cancer Foundation (R.A.S and B.R.M.), the NIH National Cancer Institute (P30CA042014) (R.A.S. and B.R.M.), and the American Cancer Society (RSG-22-077-01-CCB) (B.R.M.). The funders had no role in the design, data analysis, manuscript preparation or decision to publish, and the content is solely the responsibility of the authors.

Figure 1. Transient ptch1 crispants develop brain tumors

(A) Schematic of the zebrafish Ptch1 protein domains and corresponding exons. gRNA target sites and the germline premature stop mutation (tj222, relevant to Figure 3) are indicated. The chromosomal location is noted above the first and last exon, and the number of amino acids from N terminus to C terminus is indicated. N, N-terminal domain; TM, transmembrane domain; ECD1 and ECD2, extracellular domains 1 and 2; C, C-terminal domain.

(B) Allele frequency of the mutations caused by the ptch1 gRNA #1 identified in a pooled batch of primary injected (crispant) 24-hpf genomic DNA. Embryos were pooled after verification of CRISPR cutting via high-resolution melting analysis. Mutations with the same deletion size (“Delta #”) but different genomic locations are denoted by “Delta#.1” or “Delta#.2” (e.g., “Δ48.1” and “Δ48.2” are both a deletion of 48 bp but in different genomic locations).

(C) Allele frequency of the mutations caused by the ptch1 gRNA #1 identified from three individual ptch1-crispant whole brains as determined by CRISPR sequencing, with duplicates removed based upon unique molecular identifier (UMI) sequence information. Mutations with the same deletion size but different genomic location are denoted as in (B).

(D) Schematic of the major regions of the zebrafish brain (top), with distinct subcompartments of the cerebellum highlighted (bottom).

(E) (Left) Bright-field images of 5–6 wpf wild-type AB animals that were injected at the one-cell stage with the indicated ptch1 gRNAs. Uninjected wild-type fish served as a negative control for this experiment. (Middle and right) Sagittal sections of either control brain or ptch1-crispant brain tumors stained with H&E. White arrowheads indicate the location of the tumor in the left. White boxes in the middle are shown at higher magnification in the right. Black dashed lines indicate the cerebellum.

(F) Animals from the experiment described in (E) were analyzed for the presence of smaller pupils. The percentage of animals from each experimental group with normal pupil size was quantified. Data are plotted as a violin plot, with the upper portion indicating the number of normal animals and the lower portion the number of animals with smaller pupils. The total number of animals per group is indicated in the lower right corner. Statistical significance was calculated using an unpaired two-tailed t test. ***p = 0.0003, ****p < 0.0001.

(G) Wild-type zebrafish were either left uninjected or were injected at the one-cell stage with either ptch1 gRNAs #1 and #2 or ptch1 gRNA #1 alone, and analyzed for survival following injection. The arrowhead on the x axis indicates the beginning of survival analysis. The total number of animals per group is indicated on the right. Data are plotted from a single experiment, and experiments were repeated twice. Statistical significance was calculated using the Mantel-Cox test. ****p < 0.0001.

See also Figure S1 and Table S1.

Figure 2. Mutation in tp53 promotes aggressiveness in ptch1-crispant brain tumors

(A and B) Zebrafish from the indicated genetic backgrounds were injected at the one-cell stage with either ptch1 gRNAs #1 and #2 (A) or ptch1 gRNA #1 alone

(B) and analyzed for survival following injection. The arrowhead on the x axis indicates the beginning of survival analysis. The total number of animals per group is indicated on the right. Data are plotted from a single experiment except for tp53-mut conditions, where data had to be pooled from multiple experiments to generate enough animals. Experiments were repeated at least twice. Statistical significance was calculated using the Mantel-Cox test. ****p < 0.0001.

(C) (Left) Bright-field images of 6–12 wpf animals with the indicated genetic backgrounds that were injected at the one-cell stage with either ptch1 gRNA #1 alone or ptch1 gRNAs #1 and #2. (Middle and right) Sagittal sections of control brain or ptch1-crispant brain tumors stained with H&E. White arrowheads indicate location of the tumor in the left. Black arrowheads in the lower right indicate larger neoplastic cells with more nuclear molding. White boxes in the middle are shown at higher magnification in the right. Black dashed lines in the middle indicate the cerebellum.

See also Figure S1 and Table S1.

Figure 3. Zebrafish germline ptch1-mutant adults develop brain tumors

(Left) Bright-field images of the germline ptch1tj222 homozygous mutant animals that survived to juvenile/adult stages. (Middle and right) Sagittal sections of ptch1tj222 brain tumors stained with H&E. White arrowheads indicate location of the tumor in the left. White boxes in the middle are shown at higher magnification in the right. Black dashed lines indicate the cerebellum in the middle. See also Figure S1.

Figure 4. Zebrafish ptch1-crispant brain tumors resemble human SHH medulloblastoma

(A) Heatmap of the top 40 differentially regulated genes in tp53M214K control brain tissue (Control) and tp53M214K; ptch1 gRNA #1 brain-tumor tissue (Tumor). Three biological replicates were analyzed per group. Control animals were 52 wpf, and tumor animals were 4–7 wpf. Genes were filtered for those that had clear human homologs. SHH-pathway response genes are boxed.40

(B) GSEA was performed to identify expression pathways enriched in tp53M214K; ptch1-crispant brain-tumor tissue compared to tp53M214K control brain. NES, normalized enrichment score; FDR, false discovery rate.

(C) Principal-component analysis (PCA) comparing zebrafish tp53M214K; ptch1-crispant brain tumors with human MB samples that previously defined four major MB subgroups: SHH, WNT, group 3, and group 4. The zebrafish tumors (pink boxes) cluster with the human SHH subgroup, as indicated.

See also Figures S2–S5 and Table S2.

Figure 5. Zebrafish ptch1-crispant brain tumors are heterogeneous for neural stem cells and differentiated neurons with elevated SHH-pathway genes

(A) Immunohistochemistry of Sox2 (left) and HuC/D (right) in the indicated genetic backgrounds. A higher magnification of the black-boxed area is shown in the adjacent panels to the right. Black dashed lines indicate the cerebellum.

(B) Immunofluorescent RNAscope in the indicated genetic backgrounds with probes against sox11a, gli1, atoh1b, and otx2. Individual probes are shown in grayscale. White boxes in the upper left are shown at higher magnification below. DAPI was used as a nuclear marker.

(C) The H score was independently calculated for each RNAscope probe and is plotted with the standard deviation. Each dot represents an individual section. Statistical significance was calculated using an unpaired two-tailed t test. **p < 0.006, ***p = 0.0004, ****p < 0.0001.

See also Figures S1 and S2.

Figure 6. Loss of grk3 improves overall survival of ptch1 animals and decreases viability of SHH MB cells

(A) (Top) Schematic of the zebrafish Grk3 protein domains and corresponding exons. gRNA target sites are indicated. The chromosomal location is noted above the first and last exon, and the number of amino acids from N terminus to C terminus is indicated. RH, RGS-homology domain; Catalytic, catalytic domain; PH, pleckstrin-homology domain. (Bottom) Schematic of injection strategy and predicted zebrafish Grk3 mutant protein.

(B) Zebrafish from the indicated genetic backgrounds were injected at the one-cell stage with (1) ptch1 gRNA #1 alone, (2) ptch1 gRNA #1 + negative control gRNA, (3) ptch1 gRNA #1 + grk3 gRNA #1 and #3, or (4) ptch1 gRNA #1 + grk3 gRNA #2 and #3 and analyzed for survival following injection. The arrowhead on the x axis indicates the beginning of survival analysis. The total number of animals per group is indicated on the right. Data are plotted from a single experiment, and experiments were repeated twice. Statistical significance was calculated using the Mantel-Cox test. ****p < 0.0001.

(C) Cell viability and Gli1 mRNA levels in murine SMB21 cells treated with the indicated SMO inhibitors (vismodegib [Vismo] or SANT-1), GRK2/3 inhibitors (compound 101 [Cmpd101] or 14AS), or DMSO control (vehicle). The viability and RT-qPCR measurements were normalized against vehicle control to 100% (left y axis) or 1 (right y axis), respectively, and plotted with the standard deviation. Experiments were repeated twice with three technical replicates. Statistical signficance was calculated using an unpaired two-tailed t test. AU, arbitrary units. *p = 0.02, ***p = 0.0003.

(D) Model describing how loss of GRK2 disrupts SHH-induced tumorigenesis. (Left) In PTCH1-deficient MB tumors, SMO cannot be inhibited by mutant PTCH1 (step 1). Consequently, SMO is in an active, sterol-bound confirmation, leading to GRK2 phosphorylation (step 2), which enables SMO to bind and inhibit PKA (step 3). Since GLI transcription factors are no longer phosphorylated by PKA, they constitutively transactivate SHH target genes (step 4). (Right) In PTCH1-deficient MB tumors, SMO cannot be inhibited by mutant PTCH1 (step 1). Loss/inhibition of GRK2 prevents the phosphorylation of SMO (step 2), and as a result SMO is unable to bind and inhibit PKA (step 3). Free PKA phosphorylates GLI transcription factors and prevents their activation (step 4), and SHH target genes fail to be transactivated. Thus, inhibition of GRK2 represents a potentially useful treatment strategy for PTCH1-mutant MB tumors.

KEY RESOURCES TABLE REAGENTor RESOURCE	SOURCE	IDENTIFIER	
	
Antibodies	
	
HuC/D	Invitrogen A-21271	RRID: AB_221448	
Sox2	Millipore ab5603	RRID: AB_2286686	
	
Chemicals, peptides, and recombinant proteins	
	
DMSO	Fisher Scientific #BP231-100	N/A	
14AS (GRK2-IN-1)	MedChem Express #HY-109562A	N/A	
Compound 101	Hello Bio #HB2840	N/A	
Vismodegib	LC Laboratories #V-4050	N/A	
Cas9	IDT #1081058	N/A	
tracrRNA	IDT #1072534	N/A	
ptch1 sgRNA #1	IDT Dr.Cas9.PTCH1.1.AC	See Table S5	
ptch1 sgRNA #2	IDT CD.Cas9.RCVZ4617.AA	See Table S5	
grk3 sgRNA #1	IDT Dr.Cas9.ADRBK2.1.AA	See Table S5	
grk3 sgRNA #2	IDT CD.Cas9.WKXJ2467.AA	See Table S5	
grk3 sgRNA #3	IDT CD.Cas9.XPPT1510.AA	See Table S5	
inka1b sgRNA (negative control)	IDT Dr.Cas9.FAM212AB.1.AC	See Table S5	
RNAscope Probe- Dr-gli1-C2	ACD Bio #542721-C2	N/A	
RNAscope Probe- Dr-sox11a	ACD Bio #590461	N/A	
RNAscope Probe- Dr-atoh1b-C4	ACD Bio #1300401-C4	N/A	
RNAscope Probe- Dr-otx2-C3	ACD Bio #507371-C3	N/A	
RNAscope Probe- Dr-myod1	ACD Bio #481231	N/A	
RNAscope Probe- Dr-actb2-C2	ACD Bio #486831-C2	N/A	
RNAscope Probe- Dr-vasa-C3	ACD Bio #407271-C3	N/A	
RNAscope Probe- Dr-gad1 b-C4	ACD Bio #455921	N/A	
	
Critical commercial assays	
	
LightScanner Master Mix	BioFire Defense #HRLS-ASY-0003	N/A	
miRNeasy micro kit	QIAGEN #217084	N/A	
PCR Purification kit	QIAGEN #28104	N/A	
RNAscope LS Multiplex Fluorescent Reagent Kit	ACD Bio #322800	N/A	
RNAscope LS 4-plex Ancillary Kit	ACD Bio #322830	N/A	
Opal 520	Akoya Biosciences #FP1487001KT	N/A	
Opal 570	Akoya Biosciences #FP1488001KT	N/A	
Opal 620	Akoya Biosciences #FP1495001KT	N/A	
Opal 690	Akoya Biosciences #FP1497001KT	N/A	
RNeasy mini kit	QIAGEN #74104	N/A	
Superscript III Reverse Transcriptase	Thermo Fisher #18080093	N/A	
SSoAdvanced Universal SYBR Green Supermix	BioRad #1725272	N/A	
CellTiterGlo Luminescent Cell Viability Assay	Promega #G7570	N/A	
BOND Polymer Refine Detection kit	Leica #DS9800	N/A	
BOND Dewax Solution	Leica #AR9222	N/A	
BOND Epitope Retrieval Solution 1	Leica #AR9961	N/A	
BOND Epitope Retrieval Solution 2	Leica #AR9640	N/A	
NovaSeq XP Chemistry Workflow	Illumina #20021665	N/A	
NovaSeq S2 Reagent Kit	Illumina #20012860	N/A	
DNeasy Blood and Tissue Kit	QIAGEN #69504	N/A	
NEBNext Ultra II DNA Library Prep Kit	NEB #E7634L	N/A	
NovaSeq X Series 10B Reagent Kit	Illumina #20085594	N/A	
IlluminaTruSeq Stranded Total RNAkit with Ribo-Zero Gold	Illumina #20020598	N/A	
	
Deposited data	
	
Zebrafish SHH MB	This paper	GEO: GSE242897; Table S1	
Human microarray expression	Cavalli et al.3	GEO:	
Zebrafish NB-FOXR2 CNS-PNET	Modzelewska et al.44	GEO: GSE80768	
	
Experimental models: Cell lines	
	
SMB21	Zhao et al.26	N/A	
	
Experimental models: Organisms/strains	
	
Zebrafish: Tg(8XGli:mCH)	Mich et al.52	ZDB-FISH-150901 -29969	
Zebrafish: Tg(shhH2A-GFP)	Gordon et al.51	ZDB-ALT-190322-11	
Zebrafish: tp53 M214K	Berghmans et al.37	ZDB-FISH-150901 -6661	
Zebrafish: ptchl tj222	Heisenberg et al.38	ZDB-FISH-150901 -7644	
Zebrafish: Tg(actb2:loxP-GFP-loxP-TagRFP)	Horstick et al.84	ZDB-ALT-150721-8	
	
Oligonucleotides	
	
Primers for genotyping	This paper	See Table S5	
Primers for CRISPR sequencing	This paper	See Table S5	
Primers for qRT-PCR	This paper	See Table S5	
	
Software and algorithms	
	
LightScanner Call-IT	Idaho Technology Inc.	N/A	
Adobe Illustrator	Adobe	N/A	
Adobe Photoshop	Adobe	N/A	
Rstudio	Rstudio	N/A	
GraphPad Prism	Dotmatics	N/A	
GSEA	Broad Institute	N/A	
CHOPCHOP	(Labun et al.)85	N/A	
IDT custom gRNA design tool	IDT	N/A	
featureCounts	(Liao et al.)86	N/A	
DESeq2	(Love et al.)87	N/A	
STAR	(Dobin et al.)88	N/A	
Homologene	(Sayers et al.)89	N/A	
biomaRt	(Durinck et al.)90	N/A	
QuPath	(Bankhead et al.)91	N/A	
STARDIST	(Schmidt et al.)92	N/A	
Bowtie2	(Langmead et al.)93	N/A	
Samtools	(Danecek et al.)94	N/A	
CRISPResso2	(Clement et al.)95	N/A	

Highlights

Zebrafish patched 1 (ptch1) is a conserved tumor-suppressor gene

Somatic and germline mutations in zebrafish ptch1 cause embryonal brain tumors

ptch1-deficient brain tumors model the human SHH medulloblastoma (MB) subgroup

CRISPR screens using zebrafish identify Grk2/3 as a therapeutic target in SHH MB

DECLARATION OF INTERESTS

The authors declare no competing interests.

SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.celrep.2024.114559.
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