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

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Evolution-adjusted Tumor Pathophysiology:

Abstract

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.

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References

  1. Reichle A, Hildebrandt GC (2010) The comparative uncovering of tumor systems biology by modularly targeting tumor-associated inflammation. In: From molecular to modular tumor therapy: the tumor microenvironment, vol 3, part 4. Springer, pp 287–303. doi:10.1007/978-90-481-9531-2_13

    Google Scholar 

  2. Reichle A, Hildebrandt GC (2009) Principles of modular tumor therapy. Cancer Microenviron 2(Suppl 1):227–237

    Article  PubMed  Google Scholar 

  3. Hanahan D, Weinberg RA (2011) Hallmarks of cancer: the next generation. Cell 144(5):646–74 (Review)

    Article  PubMed  CAS  Google Scholar 

  4. Marcucci G, Haferlach T, Döhner H (2011) Molecular genetics of adult acute myeloid leukemia: prognostic and therapeutic implications. J Clin Oncol 29(5):475–486 (Review). Erratum in: J Clin Oncol 29(13):1798

    CAS  Google Scholar 

  5. Kvinlaug BT, Chan WI, Bullinger L, Ramaswami M, Sears C, Foster D, Lazic SE, Okabe R, Benner A, Lee BH, De Silva I, Valk PJ, Delwel R, Armstrong SA, Döhner H, Gilliland DG, Huntly BJ (2011) Common and overlapping oncogenic pathways contribute to the evolution of acute myeloid leukemias. Cancer Res 71(12):4117–4129

    Article  PubMed  CAS  Google Scholar 

  6. Wassmann B, Pfeifer H, Goekbuget N, Beelen DW, Beck J, Stelljes M, Bornhäuser M, Reichle A, Perz J, Haas R, Ganser A, Schmid M, Kanz L, Lenz G, Kaufmann M, Binckebanck A, Brück P, Reutzel R, Gschaidmeier H, Schwartz S, Hoelzer D, Ottmann OG (2006) Alternating versus concurrent schedules of imatinib and chemotherapy as front-line therapy for Philadelphia positive acute lymphoblastic leukemia (Ph+ALL). Blood 108(5):1469–1477

    Article  PubMed  CAS  Google Scholar 

  7. Ernst T, Hochhaus A (2012) Chronic myeloid leukemia: clinical impact of BCR-ABL1 mutations and other lesions associated with disease progression. Semin Oncol 39(1):58–66 (Review)

    Article  PubMed  CAS  Google Scholar 

  8. Collins SR, Miller KM, Maas NL, Roguev A, Fillingham J, Chu CS, Schuldiner M, Gebbia M, Recht J, Shales M, Ding H, Xu H, Han J, Ingvarsdottir K, Cheng B, Andrews B, Boone C, Berger SL, Hieter P, Zhang Z, Brown GW, Ingles CJ, Emili A, Allis CD, Toczyski DP, Weissman JS, Greenblatt JF, Krogan NJ (2007) Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map. Nature 446(7137):806–10

    Article  PubMed  CAS  Google Scholar 

  9. Reichle A (2010) Bridging theory and therapeutic practice: from generalized disease models to particular patients. In: From molecular to modular tumor therapy the tumor microenvironment, vol 3, part 1. Springer, pp 3–7. doi: 10.1007/978-90-481-9531-2_23

    Google Scholar 

  10. Alexander S, Friedl P (2012) Cancer invasion and resistance: interconnected processes of disease progression and therapy failure. Trends Mol Med 18(1):13–26

    Article  PubMed  Google Scholar 

  11. Dean M et al (2005) Tumour stem cells and drug resistance. Nat Rev Cancer 5(2005):275–284

    Article  PubMed  CAS  Google Scholar 

  12. Lee AJ, Swanton C (2012) Tumour heterogeneity and drug resistance: personalizing cancer medicine through functional genomics. Biochem Pharmacol 83(8):1013–20

    Article  PubMed  CAS  Google Scholar 

  13. Noble D (2010) Biophysics and systems biology. Philos Transact A Math Phys Eng Sci 368(1914):1125–1139

    Article  CAS  Google Scholar 

  14. Lin C, Yang L, Tanasa B et al (2009) Nuclear receptor-induced chromosomal proximity and DNA breaks underlie specific translocations in cancer. Cell 11(139):1069–1083

    Article  Google Scholar 

  15. Goyette MC, Cho K, Fasching CL, Levy DB, Kinzler KW, Paraskeva C, Vogelstein B, Stanbridge EJ (1992) Progression of colorectal cancer is associated with multiple tumor suppressor gene defects but inhibition of tumorigenicity is accomplished by correction of any single defect via chromosome transfer. Mol Cell Biol 12(3):1387–95

    PubMed  CAS  Google Scholar 

  16. Raaijmakers MH, Mukherjee S, Guo S et al (2010) Bone progenitor dysfunction induces myelo-dysplasia and secondary leukaemia. Nature 21 [Epub ahead of print]

    Google Scholar 

  17. Mueller MM, Fusenig NE (2006) Friends or foes—bipolar effects of the tumour stroma in cancer. Nat Rev Cancer 4:839–849

    Article  Google Scholar 

  18. Kalluri R, Zeisberg M (2006) Fibroblasts in cancer. Nat Rev Cancer 6:392–401

    Article  PubMed  CAS  Google Scholar 

  19. Hida K, Klagsbrun M (2005) A new perspective on tumor endothelial cells: unexpected chromosome and centrosome abnormalities. Cancer Res 65:2507–2510

    Article  PubMed  CAS  Google Scholar 

  20. Tlsty TD, Coussens LM (2006) Tumor stroma and regulation of cancer development. Annu Rev Pathol 1:119–150

    Article  PubMed  CAS  Google Scholar 

  21. Yuan H, Wang Z, Li L, Zhang H, Modi H, Horne D, Bhatia R, Chen W (2012) Activation of stress response gene SIRT1 by BCR-ABL promotes leukemogenesis. Blood 119(8):1904–1914

    Article  PubMed  CAS  Google Scholar 

  22. Furlan A, Stagni V, Hussain A, Richelme S, Conti F, Prodosmo A, Destro A, Roncalli M, Barilà D, Maina F (2011) Abl interconnects oncogenic met and p53 core pathways in cancer cells. Cell Death Differ 18(10):1608–1616. doi: 10.1038/cdd.2011.23

    Article  PubMed  CAS  Google Scholar 

  23. Reuter JA, Ortiz-Urda S, Kretz M et al (2009) Modeling inducible human tissue neoplasia identifies an extracellular matrix interaction network involved in cancer progression. Cancer Cell 15(6):477–488

    Article  PubMed  CAS  Google Scholar 

  24. Chao MP, Majeti R, Weissman IL (2011) Programmed cell removal: a new obstacle in the road to developing cancer. Nat Rev Cancer 12(1):58–67

    PubMed  Google Scholar 

  25. Reichle A, Hildebrandt Gerhard C (2008) Systems biology: a therapeutic target for tumor therapy. Cancer Microenviron 1(1):159–170

    Article  PubMed  Google Scholar 

  26. Ben-Neriah Y, Karin M (2011) Inflammation meets cancer, with NF-κB as the matchmaker. Nat Immunol 12(8):715–23. (Review)

    Article  PubMed  CAS  Google Scholar 

  27. Pitteri SJ, Kelly-Spratt KS, Gurley KE, Kennedy J, Buson TB, Chin A, Wang H, Zhang Q, Wong CH, Chodosh LA, Nelson PS, Hanash SM, Kemp CJ (2011) Tumor microenvironment-derived proteins dominate the plasma proteome response during breast cancer induction and progression. Cancer Res 71(15):5090–5100

    Article  PubMed  CAS  Google Scholar 

  28. Paulitschke V et al (2010) Secretome proteomics, a novel tool for Biomarkers discovery and for guiding biomodulatory therapy approaches. In: From molecular to modular tumor therapy: the tumor microenvironment, vol 3, part 6. Springer, pp 405–431. doi: 10.1007/978-90-481-9531-2_21

    Google Scholar 

  29. Kiessling F, Lederle W (2010) Early detection of systems response: molecular and functional imaging of angiogenesis. In: Reichle A (ed) From molecular to modular tumor therapy: the tumor microenvironment, vol 3, part 6. Springer, pp 385–403. doi:10.1007/978-90-481-9531-2_20

    Google Scholar 

  30. Heinz S, Glass CK (2011) Roles of lineage-determining transcription factors in establishing open chromatin: lessons from high-throughput studies. Curr Top Microbiol Immunol [Epub ahead of print]

    Google Scholar 

  31. Lian JB, Stein GS, Javed A, van Wijnen AJ, Stein JL, Montecino M, Hassan MQ, Gaur T, Lengner CJ, Young DW (2006) Networks and hubs for the transcriptional control of osteoblastogenesis. Rev Endocr Metab Disord 7(1–2):1–16

    PubMed  CAS  Google Scholar 

  32. Jeong H, Mason SP, Barabási AL, Oltvai ZN (2001) Lethality and centrality in protein networks. Nature 411(6833):41–2

    Article  PubMed  CAS  Google Scholar 

  33. Remark R, Alifano M, Cremer I, Sautès-Fridman C, Fridman WH, Damotte D (2012) Composition, organization and clinical impact of the adaptive and innate immune microenvironments in lung metastases from colorectal and renal cell carcinoma. CSH Asia/ICMS Joint Conference on Tumor Microenvironment Cancer. Microenviron:S4–6

    Google Scholar 

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Correspondence to Albrecht Reichle .

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Reichle, A. (2013). Including Rationalizations of Tumor-Associated Normative Notions in Pathophysiologic Considerations: Communication-Theoretical Implications. In: Reichle, A. (eds) Evolution-adjusted Tumor Pathophysiology:. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6866-6_16

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