In the Systems and Precision Cancer Medicine team at The Institute of Cancer Research, the ICR, the research focuses on translational cancer research and patient benefit and leverages national and international clinical trials and tissue resources. Their interdisciplinary work effectively integrates experimental, computational and clinical biology.
Cancers are highly heterogeneous at molecular and phenotypic levels, so it is essential to stratify cancer patients to deliver more personalised cancer diagnosis and therapy. To this end, the Systems and Precision Cancer Medicine team’s efforts build on their pioneering molecular stratification in different cancers, including colorectal and pancreatic cancers, among others.
Our partners at The ICR systematically study tumour and immune/stromal heterogeneity by developing innovative artificial intelligence and machine-learning models to concurrently integrate multi-omics with phenome data. Multi-omics data include, but are not limited to, image, transcriptome, genome and methylome. Phenome data include clinical outcomes and in vitro/in vivo data such as proliferation and migration, for example. This careful, systematic approach to data integration generates biomarkers and highly probable hypotheses for personalised cancer therapies.
Once identified, biomarkers can be translated into potential molecular assays and tested in the clinic or in trial/study samples. Hypotheses about suitable treatments can also be validated using mechanism-based pre-clinical models and experiments.
This approach streamlines solutions to evolving areas in the field of multidisciplinary science including inter/intra-tumoral heterogeneity, companion diagnostic assay development, deconvolution statistical approaches, cell-of-origin/phenotypes-based evolution of tumour, and pre-clinical trials for modelling precision cancer therapy.