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Evolution Theory: Its Practical Relevance for Understanding Tumor Development and Specifying Tumor Therapy

  • A. Reichle
  • G. C. Hildebrandt
Chapter

Abstract

At that time the introduction of a cancer evolution concept, has failed to revolutionize cancer research. Models of rational reconstruction within an evolution historical frame can be suggested, if an innovative achievement may be denoted for a complex ‘learning process’. Because such models admit a clear normative reference and action-theoretical interpretation; they may be used for narrative presentations. Three main factors emerged as starting point for evolution theoretical considerations, an unmet medical need (systemically pretreated patients with metastatic tumors), a hypothesis-driven vision (the formal pragmatic communication theory) and technological advances to pursue that vision (biomodulatory therapy approaches, clinical proteomics, epigenetics and molecular imaging techniques). An evolution theory allows for virtualizing the engagement to get experiences and decisions (pragmatic virtualization of communication acts) via implementation of non-normative boundary conditions (for example, biomodulatory therapies). The feasibility to virtualize the engagement to get situate experiences about tumor systems and decisions to tailor biomodulatory therapies (communication-derived tumor pathophysiology), the availability of an evolutionarily adapted modeling of cancer (cellular therapy in situ by adaptive therapies) will continue to increase our understanding of tumor pathophysiology and may contribute to an evolution-oriented design of systems biological strategies to diagnose and clinically manage tumor diseases on a novel personalized level. Basic science is getting directly involved in the reconstructive process, even though an approach has been established directed from bedside to bench aimed at implementing clinical practical care (adaptive trial designs) as scientific object in patient care.

Keywords

Evolution Theory Tumor System Communicative Expression System Object Communication Line 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Hematology and OncologyUniversity Hospital RegensburgRegensburgGermany
  2. 2.Division of Hematology and Hematologic Malignancies, Huntsman Cancer InstituteUniversity of Utah School of MedicineSalt Lake CityUSA

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