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BioMed Research InternationalVolume 2014 2014, Article ID 934038, 9 pages

Review Article

Department of Experimental Medicine, “Sapienza” University of Rome, Systems Biology Group, Viale Regina Elena 324, Via A. Scarpa 14, 00161 Rome, Italy

Department of Surgery “Pietro Valdoni”, “Sapienza” University of Rome, Via A. Scarpa 14, 00161 Rome, Italy

Received 7 May 2014; Accepted 27 May 2014; Published 12 June 2014

Academic Editor: Zhen Chen

Copyright © 2014 Mariano Bizzarri and Alessandra Cucina. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The somatic mutation theory of carcinogenesis has eventually accumulated an impressive body of shortfalls and paradoxes, as admittedly claimed by its own supporters given that the cell-based approach can hardly explain the emergence of tissue-based processes, like cancer. However, experimental data and alternatives theories developed during the last decades may actually provide a new framework on which cancer research should be reframed. Such issue may be fulfilled embracing new theoretical perspectives, taking the cells-microenvironment interplay as the privileged level of observation and assuming radically different premises as well as new methodological frameworks. Within that perspective, the tumor microenvironment cannot be merely considered akin to new “factor” to be added to an already long list of “signaling factors”; microenvironment represents the physical-biochemical support of the morphogenetic field which drives epithelial cells towards differentiation and phenotype transformation, according to rules understandable only by means of a systems biology approach. That endeavour entails three fundamental aspects: general biological premises, the level of observation i.e., the systems to which we are looking for, and the principles of biological organization that would help in integrating and understanding experimental data.





Autor: Mariano Bizzarri and Alessandra Cucina

Fuente: https://www.hindawi.com/



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