EXPOsOMICs: Meet-in-the-middle and network perturbation

Abstract

Systems biology has been driven by technology (the development of omics) and by statistical modelling and bioinformatics. We aim to bring biological thinking back. We suggest that three traditions of thought need to be considered: (a) causality in epidemiology, for example the "sufficient-component-cause framework", and causality in other sciences, for example the Salmon and Dowe approach; (b) new acquisitions about disease pathogenesis, for example the "branched evolution model" in cancer, and the role of biomarkers in this process; (c) the burgeoning of omic research, with a large number of "signals" that need to be interpreted. To address the new challenges of epidemiology, the concept of the "exposome" has been proposed. We show examples from recent projects in the field, namely, new omic approaches applied to epidemiological studies; and in particular, the identification of hallmarks of cancer as intermediate steps between exposure to carcinogens and the cancer phenotype, according to the "meet-in-the-middle" concept. We use examples derived from the study of mutational spectra in tumours and benzo(a) pyrene and bisphenol A as model carcinogens. We suggest conceptualising the detection and tracing of signals in terms of information transmission.