Identification Of Myc-Dependent Therapeutic Vulnerabilities For Targeting Group 3 Medulloblastoma

Abstract Group 3 medulloblastoma (MBGroup3) is a highly aggressive tumour characterised by MYC amplification and elevated expression (17% of MBGroup3). MYC amplification in MBGroup3 confers a dismal prognosis using standard therapies, and there is an urgent unmet need for novel therapeutic approaches. The identification and targeting of MYC’s biological dependencies thus represents a promising strategy to treat MYC-MBGroup3 tumours. Three independent isogenic MYC-regulable MBGroup3 human cell-based models, in which elevated MYC expression can be directly down-regulated by doxycycline-inducible shRNAs, were developed and used initially to establish MYC-dependent growth of each model. Our novel models were then used to investigate MYC-dependent drug sensitivity, by characterising responses to a panel of candidate cancer therapeutics and small molecule inhibitors, including a high-throughput compound screen of >500 established/clinically-relevant small molecule inhibitors. This approach identified several specific, consistently observed, druggable MYC-dependencies (e.g. cell cycle regulators, DNA-damage response controllers, mitotic control machinery) with potential for the development of treatments against MYC-MBGroup3 tumours. PLK1, CHK1 and AURK were identified as prime candidate targets with consistent MYC-dependent response profiles. Subsequent validation of each candidate, by genetic and pharmacological target inhibition, confirmed their MYC-dependent effects, associated with downregulation of MYC and established target-dependent pharmacodynamic biomarkers/pathways. Results were consistent across all of our MBGroup3 models. In summary, our novel models reveal druggable MYC-associated dependencies as a feature of MBGroup3. Our findings support the development of PLK1, CHK1 and AURK inhibition as therapeutic approaches against MYC-dependent MBGroup3. Future work is now essential to validate our findings in vivo, to support the design of future clinical trials.