Systems pathology—taking molecular pathology into a new dimension

Abstract

The wealth of morphological, histological, and molecular data from human cancers available to pathologists means that pathology is poised to become a truly quantitative systems science. By measuring morphological parameters such as tumor stage and grade, and by measuring molecular biomarkers such as hormone receptor status, pathologists have sometimes accurately predicted what will happen to a patient's tumor. While 'omic' technologies have seemingly improved prognostication and prediction, some molecular 'signatures' are not useful in clinical practice because of the failure to independently validate these approaches. Many associations between gene 'signatures' and clinical response are correlative rather than mechanistic, and such associations are poor predictors of how cellular biochemical networks will behave in perturbed, diseased cells. Using systems biology, the dynamics of reactions in cells and the behavior between cells can be integrated into models of cancer. The challenge is how to integrate multiple data from the clinic into tractable models using mathematical models and systems biology, and how to make the resultant model sufficiently robust to be of practical use. We discuss the difficulties in using mathematics to model cancer, and review some approaches that may be used to allow systems biology to be successfully applied in the clinic.

Trastuzumab and Pertuzumab Produce Changes in Morphology and Estrogen Receptor Signaling in Ovarian Cancer Xenografts Revealing New Treatment Strategies

“…In this case, clear cell areas seem to be more sensitive to the effects of trastuzumab, whereas residual disease seems to be sensitized to the effects of endocrine therapy through upregulation of ERa. Consideration of both spatial and temporal heterogeneity is a challenge in the clinical setting, as diagnostic biopsies are frequently small and may not be representative of the tumor as a whole and multiple biopsies during the course of treatment may carry unacceptable clinical risk or be impossible; nevertheless, multiple tissue samples are often taken in cancer therapy in the neoadjuvant (i.e., systemic treatment before surgery) setting or in "window-of-opportunity" studies in clinical trials (44). Our data suggest that molecular analysis of tumor samples after therapy may be more informative for driving future treatment decisions than tests carried out on treatment-naive biopsies alone, as the cancer changes in response to therapy.…”

Systems biology and the integration of mechanistic explanation and mathematical explanation

“…Studies on (changes in) gene regulatory networks are germane to evolutionary biology (Davidson, 2006;Davidson & Erwin, 2006;Linksvayer et al, 2012;O'Malley & Soyer, 2012). Of course, research on the workings of biological systems also has medical applications in view, most notably in the context of cancer biology (Faratian et al, 2009;Kitano, 2004b;Patel & Nagl, 2010;Wang, 2010), and such broader technological applications as synthetic biology (Fu & Panke, 2009).…”

Combining micro-bottom-up and macro-top-down modelling responses to nutrient cycles in complex agricultural systems

“…A universally applied ''best'' practice will not fit a unique system (Kurtz and Snowden 2003). Studies in network topography and in drug pathways that influence the cell cycle provide useful examples for understanding the nature of complex systems (Clyde et al 2006;Faratian et al 2009;Liu et al 2011). …”