title: Human tissue in systems medicine.
abstract: Histopathology, the examination of an architecturally artefactual, two-dimensional and static image remains a potent tool allowing diagnosis and empirical expectation of prognosis. Considerable optimism exists that the advent of molecular genetic testing and other biomarker strategies will improve or even replace this ancient technology. A number of biomarkers already add considerable value for prediction of whether a treatment will work. In this short review we argue that a systems medicine approach to pathology will not seek to replace traditional pathology, but rather augment it. Systems approaches need to incorporate quantitative morphological, protein, mRNA and DNA data. A significant challenge for clinical implementation of systems pathology is how to optimize information available from tissue, which is frequently sub-optimal in quality and amount, and yet generate useful predictive models that work. The transition of histopathology to systems pathophysiology and the use of multiscale data sets usher in a new era in diagnosis, prognosis and prediction based on the analysis of human tissue.
authors.affiliation: Digital Pathology Unit, Laboratory Medicine, Royal Infirmary of Edinburgh, UK.
authors.forename: Peter D
authors.initials: PD
authors.lastname: Caie
authors.forename: Klaas
authors.initials: K
authors.lastname: Schuur
authors.forename: Anca
authors.initials: A
authors.lastname: Oniscu
authors.forename: Peter
authors.initials: P
authors.lastname: Mullen
authors.forename: Paul A
authors.initials: PA
authors.lastname: Reynolds
authors.forename: David J
authors.initials: DJ
authors.lastname: Harrison
mesh_terms: D014408:Biomarkers, Tumor / Q000378:metabolism*; D006801:Humans; D025202:Molecular Diagnostic Techniques; D058990:Molecular Targeted Therapy; D009369:Neoplasms / Q000378:metabolism / Q000473:pathology* / Q000628:therapy*; D057285:Precision Medicine; D011379:Prognosis; D049490:Systems Biology
chemical_list: D014408:Biomarkers, Tumor
keywords: histopathology; human disease; predictive models; systems biology; systems medicine