Systems and Network-Based Approaches for Personalized Medicine

Abstract

Most biological outcomes in a cell arise from a complex interplay between different cellular entities such as proteins, DNA, RNA and metabolites. Therefore, a key challenge for biology in the twenty-first century is to understand the structure and dynamics of the complex web of interactions in a cell that contribute to its proper functioning. Recent years have seen a surge in the amount of "omics" data and an integration of several disciplines which has influenced all areas of life sciences, from molecular biology to medicine. With the emergence of a number of sophisticated tools and technologies as a result of genomics revolution, we are now in a position to view the molecular aspects of diseases at a systems level by incorporating various cellular entities into a network framework. Such systems/network-based approaches are not only enabling us to develop models of disease and wellness in a population but also contributing to our efforts to reverse engineer the molecular networks corresponding to disease states by perturbing using drug cocktails. These multi-scale personalized medicine approaches are likely to significantly re-shape the health care industry in the coming decades and decrease the division that we currently see between medicine and other biotechnology disciplines.Keywords: Systems biology; Network pharmacology; Drug discovery; Personal genomics; Patient profiling; Health care EditorialReductionism, which has been the paradigm in biological research for more than a century, has provided us with a wealth of knowledge about the individual cellular components, their functions and mechanisms. Despite its huge success in the last century, post-genomic biology has increasingly made it clear that discrete biological function can only rarely be attributed to an individual molecule. Instead, most biological outcomes in a cell arise from a complex interplay between different cellular entities such as proteins, DNA, RNA and metabolites. Therefore, a key challenge for biology in the twenty-first century is to understand the structure and dynamics of the complex web of interactions in a cell that contribute to its proper functioning. Although, we cannot answer this question in full in the very near future, the analyses, concepts and frameworks that have resulted in the recent years have provided the scientific community with tools to interpret and better understanding the logic behind the several layers of complex web of interactions happening in the cell.In the last few years there has been a rapid development in various high-throughput technologies which has led to the accumulation of a large amount of data from different areas of molecular and cellular biology. These developments together with increasing interest in the community for gaining a systems-wide understanding of the cellular machinery have provided us unprecedented insights into the structure, organization and dynamics of various major cellular processes such as transcription, translation, degradation, replication, metabolism etc. Likewis...

Understanding cancer complexome using networks, spectral graph theory and multilayer framework

“…Importantly, these common proteins also exhibit functional importance for occurrence of cancer revealed through pathway ontology and miRNA analysis. The framework paves a new way to the promising and nascent concept of single drug therapy 39 for multiple diseases as well as personalized medicine 40 in a time efficient and cost effective manner.…”

Dynamical systems approaches to personalized medicine

“…Even so, differential parameter profiles for health and disease may include values of zero for some rates or other features, which may be due to a gene mutation leading to loss of function, and because these parameters represent particular system structures, the corresponding processes operating in healthy individuals may cease to exist in disease. Because uncounted shifts away from a healthy parameter profile are possible, individuals might migrate from health toward any number of personal disease states, as it is indeed observed [14,16]. Some of these disease states may have the same phenotype but respond differently to treatment.…”

“…This repertoire of differences is further augmented by variations in lifestyle, diet, and environmental exposures, which all affect well-being and can lead to persistent epigenetic differences [15•]. Given this complexity, it seems that the only truly valid control for distinguishing health and disease is an individual's own healthy baseline [16].…”