Cancer is associated with widespread systemic perturbations that may be captured in molecular profiles such as the proteomes, transcriptomes and methylomes of peripheral and target tissues. Inflammation, for example, is prominent in cancer, contributing to microenvironments that foster tumorigenesis and metastasis. Consequently, understanding cancer risk, progression and survival requires a deep understanding of these systemic perturbations beyond the contributions of individual genes.

Toward this goal, we systematically characterise systemic perturbations linked to cancer using multi-omic profiles at the level of molecular pathways and high-level processes, distinguishing between mere associations and causal relationships using recently-developed hypothesis-free causal inference methods.

This theme is co-chaired by Matt Suderman and Paul Yousefi.