E-Poster Presentation 33rd Lorne Cancer Conference 2021

Modelling chemotherapy-induced apoptosis to improve response in high-risk neuroblastoma (#122)

Jeremy Han 1 , Monica Phimmachanh 1 , Sharissa Latham 1 , Alvin Kamili 2 , Jamie Fletcher 2 , David Croucher 1
  1. Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
  2. Children's Cancer Institute Australia, Lowy Cancer Research Centre, UNSW, Sydney, Kensington, NSW, Australia

High-risk neuroblastoma is an aggressive and invasive paediatric malignancy, with few actionable somatic mutations. As such, intense multi-agent chemotherapy remains the standard-of-care. Unfortunately, only half these children are cured and survivors are at increased risk of serious complications such as deafness, infertility and secondary cancers. There is therefore an urgent need for predictive markers of therapeutic response, to guide rationalized treatment of high-risk neuroblastoma patients.

Failure to effectively activate apoptosis, or the ability to evade apoptosis, has been established as a key mechanism of chemoresistance in neuroblastoma. Despite this, there is little understanding of the apoptotic mechanism-of-action of current standard-of-care drugs, let alone their combined mechanism of action or any potential for synergistic/antagonistic interactions. Therefore, the aim of this project is to apply a network-wide, systems level approach to defining the apoptotic mechanisms activated by each of the main standard-of-care neuroblastoma drugs in order to identify rationalized patient-specific, synergistic drug combinations, that will be validated in vitro and in PDX models.

To this end, a high-content, functional genomics screen was conducted with an esiRNA library of 200 apoptotic genes and seven treatment conditions; including current standard-of-care neuroblastoma drugs doxorubicin, irinotecan, topotecan and vincristine, and prospective neuroblastoma drugs, alisertib and romidepsin. Multi-dimensional analysis of this dataset has elegantly demonstrated that synergy between any two chemotherapy drugs is proportional to the magnitude of divergence in apoptotic pathway utilization. Therefore, the application of this systems biology approach to rationalized mechanism-based drug selection will address fundamental questions about the network level functioning of apoptotic signalling pathways, and also inform the development of a precision medicine approach that will aim to improve outcomes for high-risk neuroblastoma patients.