Characterisation of appendiceal tumours: a step towards rational therapeutics

Abstract

The optimal approach for the combination and sequencing of systemic chemotherapy, cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) is not known. The first aim is to evaluate the role of perioperative chemotherapy and establish predictors of clinical outcomes in patients with ATPD who undergo CRS with or without HIPEC. The biological understanding of appendiceal tumours lags behind that of other tumours. Exploring the tumour microenvironment (TME) provides greater understanding of both tumour-host interplay and tumour specific characteristics. Single cell transcriptomic analysis has the power to accurately characterise all cells in the TME and to better understand their individual roles in the malignant process. Spatial transcriptomic profiling can provide insights into the influence of the architecture of the microenvironment, particularly relevant for the mucinous disease that is characteristic of ATPD. The second aim is to perform a comprehensive biological analysis of ATPD to better understand the biology of the disease. Robust preclinical models that recapitulate the TME are essential for understanding patient-specific tumour biology and ex vivo testing of therapies. Patient-derived explants (PDEs) are a novel method to characterise the TME. PDEs maintain native tissue architecture, microenvironment and tumour heterogeneity and can be used to inform biomarker discovery. The third aim is to establish a PDE model of ATPD. This study will address the urgent need to define relevant clinical predictors of outcome and the role of perioperative systemic chemotherapy in ATPD. Comprehensive biological profiling of the TME may identify active therapeutic agents and lay the foundation for rationally designed clinical studies. This study will provide a step towards optimising treatment options, identifying prognostic and predictive biomarkers, and ultimately selecting patients for a rational therapeutic approach to improve clinical outcomes.