A functional genomics approach to identify pathways of drug resistance in medulloblastoma
KeywordsCancer Brain tumor Medulloblastoma Drug resistance Functional genomics Transposon mutagenesis Sleeping beauty
Medulloblastoma (MB) is the most common malignant pediatric brain tumor . Although continued advances have been made in our understanding of medulloblastoma, questions remain about its etiology and treatment [3, 4, 7, 9, 13, 14, 15, 17, 18]. Medulloblastoma is classified into four demographically, clinically, and molecularly distinct subgroups called WNT, SHH, Group 3 and Group 4 (As reviewed in ), and further divided into additional distinct molecular subtypes [3, 14]. While patients with (WNT) pathway driven medulloblastoma have favorable outcomes, recurrence rates are higher in other subtypes such as SHH, which tend to recur locally, and Group 3 and 4, which are associated with distal metastases . The biology of metastatic medulloblastoma is distinct from primary medulloblastoma; representing potentially a different therapeutic disease [6, 8, 13]. Approaches are needed to identify pathways of therapy resistance in both primary and metastatic compartments of medulloblastoma to guide selection of targeted therapies. As an example, the MET proto-oncogene is upregulated in SHH and Group 3 medulloblastoma, and can be targeted by treatment of cells and mouse models with the small molecule inhibitor, Foretinib . We utilized a spontaneous metastatic mouse model of medulloblastoma driven by the Sleeping Beauty mutagenesis transposon system  to pinpoint functional drivers and pathways of resistance to Foretinib  in both primary and metastatic medulloblastoma. This serves as a novel approach to dissecting patterns of therapy resistance at multiple tumor sites simultaneously which can be readily applied to other cancer systems.
Results and discussion
Our study has identified potential pathways that medulloblastoma cells may co-opt to overcome Foretinib inhibition, and provides a strategy for which drug resistance pathways to other medulloblastoma targeted therapies may be identified. Prospective identification of these pathways could be used to determine combinatory treatments that may be effective for resistant primary and metastatic tumor clones. We further demonstrate in our model that primary and metastatic medulloblastoma are genetically distinct, and in response to Foretinib-therapy, exhibit divergent mechanisms of resistance. A limitation of our method is that while driver pathways may be identified, they may not represent the exact genes targeted in resistant human primary tumors. Therefore, integrative functional mouse modeling using this Sleeping Beauty Approach paired with genomic characterization of resistant primary tumors, may prioritize pathways and specific targets that mediate cancer therapy resistance. Finally, our data lends support that treatments armed against genetic targets in the primary site may be ineffective for metastatic lesions, and that potentially distinct genetic evolution occurs between primary and metastatic medulloblastoma under therapy.
Materials and methods
All mouse studies were approved and performed in accordance to the policies and regulations of the Institutional Animal Care and Use Committee of the University of Toronto and the Hospital for Sick Children. A medulloblastoma Sleeping Beauty transposon mutagenesis murine model (Ptch+/−/SB11/T2Onc) was used, which frequently and spontaneously develops primary and metastatic MB. Ptch+/−/SB11/T2Onc mice were generously provided by Dr. Michael D. Taylor, Hospital for Sick Children, Toronto, Canada. Mice at post-natal day 30–35 were treated with vehicle or Foretinib (6 mg/kg), via Alzet osmotic pump (Model 2004) slow-infusion into the cerebrospinal fluid of the right lateral ventricle, for 28 days at a rate of 0.25ul/hour. Nucleic acid extractions were carried out as previously described. Statistical differences in survival curves of mice was assessed using a Kaplan-Meier estimate and log-rank test.
Splinkerette PCR and common genomic insertion site analysis
Transposon common insertion sites were identified by SPLINK PCR of tumour DNA, followed by 100 bp paired-end Illumina next-generation sequencing (HiSeq 2500). Genomic DNA was digested and ligated with linker +/− primers, amplified through PCR, then further amplified with barcoded primers through a second PCR. DNA was then purified and prepared for sequencing; protocol as previously described . Gene pathways were identified by querying gene lists with GeneMania , and significance measured using a hypergeometric distribution test. Data availability: The datasets supporting the conclusions of this article are included within this article. Raw data will be made openly available through the GEO repository.
We would like to thank Rob Denroche for assistance in DNA sequence analysis. This study was supported by the Canadian Cancer Society Research Institute (grant #2011-70051), the Pediatric Brain Tumor Formation of the United States, the Brain Tumour Foundation of Canada, b.r.a.i.n.child, Meagan’s Walk, and the Wiley Fund at The Hospital for Sick Children. SCM is supported by an Alex’s Lemonade Stand Young Investigator Award, The CIHR Banting Fellowship, The Cancer Prevention Research Institute of Texas (SCM-RR170023), Rally research grant, BEAR Necessities Pediatric Cancer Foundation Grant, Children’s Cancer Research Fund award, and Baylor College of Medicine Junior Faculty Award, Children’s Brain Tumor Foundation Grant, and an Alex’s Lemonade Stand Foundation Young Investigator and A award. MDT is supported by The Garron Family Chair in Childhood Cancer Research, and grants from the Pediatric Brain Tumour Foundation, Grand Challenge Award from CureSearch for Children’s Cancer, the National Institutes of Health (R01CA148699 R01CA159859), The Terry Fox Research Institute, and Brainchild. MDT is also supported by a Stand Up To Cancer St. Baldrick’s Pediatric Dream Team Translational Research Grant (SU2C-AACR-DT1113). Stand Up To Cancer is a program of the Entertainment Industry Foundation administered by the American Association for Cancer Research.
KCB led the study, interpreted the genomic analysis, and wrote the manuscript. CCF performed the animal experiments and collected tissue for the study. PS and LG performed the Sleeping Beauty Insertion analysis. AL assisted with pump implantation, and tissue collection and organization. XW provided the transgenic mice. SA, JNR, CAS, SCM, MDT provided analytical advice, data interpretation, and assisted with manuscript preparation. JTR funded and directed the entire research effort, from data interpretation, analysis, to manuscript preparation. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
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- 5.Fontebasso AM et al (2014) Recurrent somatic mutations in ACVR1 in pediatric midline high-grade astrocytoma. 46:462–466. https://doi.org/10.1038/ng.2950
- 8.Jenkins NC et al (2014) Genetic drivers of metastatic dissemination in sonic hedgehog medulloblastoma. Acta Neuropathologica Commun 2:85. https://doi.org/10.1186/preaccept-1860372034135162 CrossRefGoogle Scholar
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