Patient-derived tumour models as predictor of treatment response in cancer patients: How precise is precision medicine?

Abstract

Standard cut, poison and burn approaches to cancer treatment fail to save around 10 million patients every year across the globe. Precision medicine cancer treatment attempts to improve treatment by molecularly profiling a patient through (epi)genomics and transcriptomics to identify biomarkers in the patient's tumour. Personalized treatment is hence targeted towards these biomarkers for optimal patient care. While targeted treatment is more effective than non-targeted treatment, due to interand intratumour heterogeneity and clonal dynamics in a tumour, biomarker-targeted treatment often cannot treat a tumour completely. Combining drug candidates with patient-derived tumour models allow for sensitivity screening to assess drug efficacy before deciding on a treatment plan for an individual patient. In this literature review, five patient-derived tumour models applicable to precision medicine are discussed and compared. These include cell culture, tumour explants, mice or zebrafish xenograft transplantation and tumour organoids. The models are scored on several features regarding patient tumour representation, practicality of the model and drug screen effectiveness. Within these criteria, patient-derived organoids make a good case for suitability in a precision medicine context. Future improvements in co-culturing protocols and drug screen automation will further strengthen its position. Additionally, important considerations for drug screen study design, such as clear design and reporting guidelines and protocol standardization, will further improve the precision medicine approach to cancer treatment and allow for optimal individualized therapy.