There have been significant successes in the treatment of childhood cancer, with the overall survival rate reaching nearly 80%. However, certain leukaemias and solid tumours, as well as metastatic and relapsed cancers, remain resistant to current therapeutic approaches. These patients endure aggressive therapies and severe treatment-related toxicities, often with little chance of a cure. Therefore, novel, less toxic therapeutics with increased efficacies are greatly needed. Immunotherapies have emerged as potential solutions to these challenges. However, not all patients respond to these treatments, and reliable biomarkers that could guide the accurate use of therapy are lacking. In particular, we lack a complete understanding of interactions between the patient’s immune system and tumour. We hypothesised that biological properties of tumours that do not respond to immunotherapy can be detected prior to treatment and serve as biomarkers for patient selection. Furthermore, we hypothesise that tumour cell phenotype, including the diagnosis and genomic background, and prior exposure to therapy can shape the tumour immune microenvironment (TME) and that deep profiling of the patient TME could unmask clinically relevant biomarkers of response and inform future trials. This thesis aimed to both understand non-response to immunotherapies and to deeply profile the TME using established and novel multi-omic analysis platforms on patient samples.

To test these hypotheses, we employed three cancer models from paediatric patients. To identify tumour-intrinsic mechanisms of resistance to cellular immunotherapy, we studied B-cell acute lymphoblastic leukaemia treated with CD19 CAR T-cells. To investigate the TME we utilised bulk RNA-seq from patient medulloblastomas and performed highly multiplexed immune focused imaging of paediatric neuroblastoma.

We discovered a distinctive methylation pattern and associated stem-cell epigenome as a novel candidate pre-treatment biomarker of non-response to CD19 CAR T-cell therapy in paediatric acute lymphoblastic leukaemia. We next utilised well established deconvolution methods to investigate the TME in medulloblastoma and discovered five transcriptionally distinct clusters, including one that was composed of WNT, SHH, Group 3, and Group 4 tumours, which were associated with differential TME landscapes. We next developed novel immune focused imaging panels to investigate the spatial TME in neuroblastoma. We found that the frequency and spatial distribution of immune cells is influenced both by tumour genotype and exposure to chemotherapy. Finally, we found that high pre-treatment expression of PTEN, TIM-3, CD127, and markers of NK-cells and M1 macrophages and low expression of VISTA and CD40L were associated with improved overall survival.

Collectively, this work provides novel insights into tumour-immune interactions across paediatric malignancies. Furthermore, we identify promising biomarkers to be further validated for risk stratification, for predicting response to immunotherapy, and to be utilised as novel therapeutic targets in the TME, which could improve outcomes for children with cancer.