Year: 2017
Type: article
Abstract: One of the most remarkable expansions in complexity of life on Earth was the transition from single cell to multicellular organisms.This transition lead to cellular specialization and cooperation among cell types, including the ability to reproduce the entire organism from highly specialized single cells.Cancer is the failure of the normal cooperation among cellular components of an organ or a tissue system, and the invasion and colonization by new aberrant cells of other systems and organs.Although the specifics of each cancer vary between tissue and cell types, and often from patient to patient, these general characteristics capture the common features among all cancers at the systems level.Despite the focus on genetic mutations and epigenetic changes as drivers of cancer in the era of molecular biology, cancer has traditionally been viewed in a more organismal fashion: as the transition from homeostasis to dysregulated behavior of a tissue that is associated with, and promoted by, altered stromal signaling, inflammatory events, failure of the immune system, miscommunications between cells and aging of tissue architecture.Often one driving factor triggers the others leading to a cascade of events that give rise to an irreversible process.This integrated failure of the system makes cancer one of the most complex yet most common diseases known to humankind.In the face of this complexity and the robustness of cancer, we require quantitative and predictive models that promote an integrated understanding of all systems involved and their interactions at many different scales from the molecular to the organismal.We believe that such understanding can be achieved only by converging all science and engineering fields on the cancer problem.Physicists, mathematicians, and engineers often look for commonalities and foundational principles among seemingly divergent natural phenomena and work to extract basic principles that are common among a class of systems.Biologists, in contrast, often focus on the detailed, distinctive behavior of a specific biological system.This dichotomy of approach has persisted and been perpetuated despite modern biology's increasing embrace of computational analysis and quantitative models which requires the need for developing a system to handle the flood of data, for quantitating the distinctive behaviors and evaluating their statistical significance.The quantitative sciences offer a powerful set of tools in the quest for common fundamental principles and connections among seemingly disparate biological phenomena.The synthesis of these two approaches will be essential for solving the cancer problem.The new Springer Nature journal Cancer Convergence is an open access platform for quantitative research on tissue homeostasis and how cancer is a departure from it, with the aim of helping to accelerate the development of new experimental and theoretical approaches understanding cancer and opening new therapeutic avenues.In striving to Cancer Convergence
Source: Cancer Convergence
Language: English
Subfield: Modeling and Simulation
Field: Mathematics
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,340
OpenAlex ID: W2766938516