Personalised Immunotherapy Platform

The Personalised Immunotherapy Program (PIP) is a multicenter biomarker discovery and validation program of multi-omic biomarker based predictive models which aim to identify patients with immunotherapy resistant disease. PIP developed predictive models in retrospective setting, with validation within a prospective clinical observational study. Immune checkpoint inhibitors targeting the cytotoxic T-cell lymphocyte antigen 4 (CTLA-4) and programmed cell death 1 (PD-1) receptors have revolutionised the treatment of advanced melanoma, resulting in long-term durable responses and a 5-year overall survival of 52% with combination immunotherapy. However, clinical benefit is not universal, and half of these patients do not respond. Therefore, there is an urgent need for clinically validated biomarkers which can identify patients who are at high risk of not responding to standard-of-care immunotherapies and determine which emerging clinical trial agent is most appropriate for a particular patient's disease. Researchers performed mutation, gene expression and tumour immune profiling on tumour biopsies from melanoma patients treated with anti-PD-1 monotherapy or combined anti-PD-1 and anti-CTLA-4 therapy. From this dataset PIP has developed predictive models to identify patients with immunotherapy resistant disease. The subsequent PIP-PREDICT is a prospective clinical study that enrols advanced cancer patients who are eligible to receive approved immunotherapies. PIP testing and biomarker reporting is used to screen potential patients. Each patient enrolled in the study receives an individual PIP Biomarker Report, which is presented as part of the established Biomarker Multidisciplinary Team (MDT) meeting of clinical oncologists, pathologists, molecular biologists, trials nursing, PIP, and biospecimen staff on a fortnightly basis. PIP-PREDICT has a primary goal of determining the accuracy of biomarker predictions from PIP prospectively within oncology clinics. Secondary goals include assessing the feasibility of biomarker assay workflows within diagnostic providers, conducting a cost-benefit ratio analysis, evaluating the effect of biomarker reports on treatment selection within multidisciplinary teams (MDTs), and performing a post-implementation analysis of personalised immunotherapy biomarker reports in treatment decision making.