Functional precision medicine programs including ZERO (Australia), INFORM (international), and iTHER (Netherlands) combine tumour molecular profiling with ex vivo drug sensitivity profiling (DSP) to guide personalised therapy recommendations for children with cancer. However, the clinical impact of integrating ex vivo tumour DSP in childhood cancer precision medicine programs is unknown, and clinical responses to personalised therapies remain difficult to predict. Therefore, this study aims to compare the pharmacogenomic landscapes of childhood cancer cohorts and correlate these findings with matching in vivo and clinical response data across the three programs.
Ex vivo DSP was completed for 387 patient-derived tumour samples from 367 patients (ZERO=154/151; INFORM=154/137; iTHER=79/79) using paediatric specific drug libraries. A novel automated data analysis pipeline was established to generate drug efficacy parameters including area under the dose-response curve (AUC) values, half-maximal inhibitory concentrations (IC50), and half-maximal lethal concentrations (LC50). Next, tumour-specific drug and co-occurring drug vulnerabilities were studied. Lastly, integrative data analysis was performed to investigate biomarker-drug associations and correlations between ex vivo and in vivo or clinical responses.
Known pharmacologic vulnerabilities were confirmed including sensitivity of NTRK fusion-positive samples to NTRK inhibition. Additionally, unexpected MEK inhibitor efficacies were observed in Wilms tumours and high-grade gliomas without driver alterations in the MAPK pathway across programs. Co-occurring sensitivities were observed, such as between HDAC inhibitor vorinostat and specific chemotherapeutic drugs. Implementation of LC50 values distinguished between cytostatic and cytotoxic drug effects. For specific drugs such as the PARP inhibitor talazoparib, LC50 values correlated better with in vivo and clinical responses compared to the traditional AUC or IC50 values.
This collaborative initiative underscores the critical role of ex vivo DSP in strengthening molecular profiling results, identifying novel treatments, and identifying novel predictive biomarkers of response. Global collaboration and data sharing are key in tackling rare diseases like childhood cancer.