Systems Biology And The Challenge Of Deciphering The Metabolic Mechanisms Underlying Cancer

Since the discovery of the Warburg effect in the 1920s cancer has been tightly associated with the genetic and metabolic state of the cell. One of the hallmarks of cancer is the alteration of the cellular metabolism in order to promote proliferation and undermine cellular defense mechanisms such as apoptosis or detection by the immune system. However, the strategies by which this is achieved in different cancers and sometimes even in different patients of the same cancer is very heterogeneous, which hinders the design of general treatment options. Recently, there has been an ongoing effort to study this phenomenon on a genomic scale in order to understand the causality underlying the disease. Hence, current “omics” technologies have contributed to identify and monitor different biological pieces at different biological levels, such as genes, proteins or metabolites. These technological capacities have provided us with vast amounts of clinical data where a single patient may often give rise to various tissue samples, each of them being characterized in detail by genomescale data on the sequence, expression, proteome and metabolome level. Data with such detail poses the imminent problem of extracting meaningful interpretations and translating them into specific treatment options. To this purpose, Systems Biology provides a set of promising computational tools in order to decipher the mechanisms driving a healthy cell’s metabolism into a cancerous one. However, this enterprise requires bridging the gap between large data resources, mathematical analysis and modeling specifically designed to work with the available data. This is by no means trivial and requires high levels of communication and adaptation between the experimental and theoretical side of research.

Since the discovery of the Warburg effect in the 1920s cancer has been tightly associated with the genetic and metabolic state of the cell. One of the hallmarks of cancer is the alteration of the cellular metabolism in order to promote proliferation and undermine cellular defense mechanisms such as apoptosis or detection by the immune system. However, the strategies by which this is achieved in different cancers and sometimes even in different patients of the same cancer is very heterogeneous, which hinders the design of general treatment options.Recently, there has been an ongoing effort to study this phenomenon on a genomic scale in order to understand the causality underlying the disease. Hence, current "omics" technologies have contributed to identify and monitor different biological pieces at different biological levels, such as genes, proteins or metabolites. These technological capacities have provided us with vast amounts of clinical data where a single patient may often give rise to various tissue samples, each of them being characterized in detail by genomescale data on the sequence, expression, proteome and metabolome level. Data with such detail poses the imminent problem of extracting meaningful interpretations and translating them into specific treatment options. To this purpose, Systems Biology provides a set of promising computational tools in order to decipher the mechanisms driving a healthy cell's metabolism into a cancerous one. However, this enterprise requires bridging the gap between large data resources, mathematical analysis and modeling specifically designed to work with the available data. This is by no means trivial and requires high levels of communication and adaptation between the experimental and theoretical side of research.

Systems Biology represents a new paradigm aiming at a whole-organism-level understanding of biological phenomena, emphasizing interconnections and functional interrelationships rather than component parts. The study of network properties, and how they control and regulate behavior from the cellular to organism level, constitutes a main focus of Systems Biology. This book addresses from a novel perspective a major unsolved biological problem: understanding how a cell works and what goes wrong in pathology. The task undertaken by the authors is in equal parts conceptual and methodological, integrative and analytical, experimental and theoretical, qualitative and quantitative, didactic and comprehensive. Essentially, they unravel the spatio-temporal unfolding of interacting mass-energy and information networks at the cellular and organ levels, as well as its modulation through activation or repression by signaling networks to produce a certain phenotype or (patho)physiological response. Starting with the historical roots, in thirteen chapters this work explores the Systems Biology of signaling networks, cellular structures and fluxes, organ and microorganism functions. In doing so, it establishes the basis of a 21st century approach to biological complexity.

An overview of the current systems biology-based knowledge and the experimental approaches for deciphering the biological basis of cancer.

Systems Biology brings the potential to discover fundamental principles of Life that cannot be discovered by considering individual molecules. This chapter discusses a number of early, more recent, and upcoming discoveries of such network principles. These range from the balancing of fluxes through metabolic networks, the potential of those networks for truly individualized medicine, the time dependent control of fluxes and concentrations in metabolism and signal transduction, the ways in which organisms appear to regulate metabolic processes vis-à-vis limitations therein, tradeoffs in robustness and fragility, and a relation between robustness and time dependences in the cell cycle. The robustness considerations will lead to the issue whether and how evolution has been able to put in place design principles of control engineering such as infinite robustness and perfect adaptation in the hierarchical biochemical networks of cell biology.

This volume presents an overview of recent developments in systems biology and their applications in cancer-related research. The ongoing advances in our understanding of genomics and proteomics, coupled with the development of new and more robust tools, have led to an emphasis on analyzing biological systems at multiple levels. Thus, there is a need to integrate different types of data into a comprehensive "systems" view. Written by active researchers in the emerging areas, this book gives senior undergraduate students, graduate students and new researchers an idea of where the frontiers of systems biology are and an opportunity to learn high-throughput techniques in use. One of the particular emphases of the book is to elucidate the molecular mechanisms in cancer. The discovery of biomarkers and anti-cancer drugs using systems biology approach is also extensively discussed.

This second edition volume expands on the previous edition with discussions of the latest advancements and methods used by scientists to study systems biology. The chapters in this book are organized into four parts. Part One looks at models in systems biology and parameters identification such as short peptide analysis, metastasis models, and metabolomics. Part Two covers computational methods in the study of organisms, and cancer non-linear dynamics. Part Three discusses critical transition states across Waddington’s like landscapes such as understanding cell differentiation through single-cell approaches and modeling mammary organogenesis from biological first principles. Part Four talks about specific fields of investigation including inborn errors of metabolism, system biology approach in epithelial-mesenchymal transition, and an approach to understanding how COVID-19 spreads in the population. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and comprehensive, Systems Biology, Second Edition is a valuable tool for any researcher looking to learn more about this important and developing field.