Including Rationalizations of Tumor-Associated Normative Notions in Pathophysiologic Considerations: Communication-Theoretical Implications

Currently, the individual experimental setting irrevocably attributes distinct communicative expressions to tumor systems objects, irrespectively of the situative evolutionary context. This reductionist view legitimizes the application of any of the large number of classic targeted therapies available, irrespectively of how tumor-immanent normative notions are physically rationalized. In our perception, normative notions, which are ubiquitous and not circumventable, include all observation levels, either the clinical or the experimental setting, i.e., ‘high and low-grade’ lymphoma, ‘dysplasia’, and the ‘hallmarks’ of cancer, etc. Evolution-adjusted tumor pathophysiology categorizes normative notions of tumors in a pragmatic and discursive manner; this way, aspects derived from basic and clinical science to comparatively uncover systems biological processes are equally acknowledged. From the formal-pragmatic communication theory we may delineate that normative structures, action norms, and decision maxims are concretely rationalized and that the (therapeutic) implementation of non-normative boundary conditions leads to remodeling and redirecting tumor-associated rationalization processes and their corresponding normative notions. Thus, the communicative expression of communication lines and communicative presuppositions facilitating distinct identities of systems objects are digitalized within the range of situative evolutionary constrains—a fact that does not exclude analogously or stochastically working subsystems. At that stage, genomic patterns become reconstructable on the basis of scientifically verifiable rationalization processes. Differential origins of rationalization processes, for instance, sequential long-term vs. short-term (‘de novo’) genetic aberrations, could impact systems robustness and intrinsic resistance. Rationalization processes are important therapeutic targets, particularly in metastatic tumor diseases, for overcoming the obstacle of ‘bottom-up’ strategies with genetically based tumor heterogeneity.