Quantum Interactomics and Cancer Molecular Mechanisms

Baianu, Dr. I.C. (1987) Quantum Interactomics and Cancer Molecular Mechanisms. [Departmental Technical Report] (In Press)

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Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quantum states emerging from complex quantum dynamics of interacting networks of biomolecules, such as proteins and nucleic acids that are now collectively defined as quantum interactomics. On the other hand, the time dependent evolution over several generations of cancer cells --that are generally known to undergo frequent and extensive genetic mutations and, indeed, suffer genomic transformations at the chromosome level (such as extensive chromosomal aberrations found in many colon cancers)-- cannot be correctly represented in the ‘standard’ terms of quantum automaton modules, as the normal somatic cells can. This significant difference at the cancer cell genomic level is therefore reflected in major changes in cancer cell interactomics often from one cancer cell ‘cycle’ to the next, and thus it requires substantial changes in the modeling strategies, mathematical tools and experimental designs aimed at understanding cancer mechanisms. Novel solutions to this important problem in carcinogenesis are proposed and experimental validation procedures are suggested. From a medical research and clinical standpoint, this approach has important consequences for addressing and preventing the development of cancer resistance to medical therapy in ongoing clinical trials involving stage III cancer patients, as well as improving the designs of future clinical trials for cancer treatments. *Communicated to: The Institute of Genomic Biology (currently under construction at UIUC, at 905 S. Goodwin Avenue, Urbana,IL.61801,USA). KEYWORDS: Cancer cell interactomics; Somatic cell genomics and Proteomics; current limitations of modular models of carcinogenesis; Complex quantum dynamics; Quantum Automata models and Quantum Interactomics; quantum-weave dynamic patterns underlying human consciousness; specific molecular processes underlying extensive memory, learning, anticipation mechanisms and human consciousness; emergence of human consciousness during the early brain development in children; Cancer cell ‘cycling’; interacting networks of proteins and nucleic acids; genetic mutations and chromosomal aberrations in cancers, such as colon cancer; development of cancer resistance to therapy; ongoing clinical trials involving stage III cancer patients’ possible improvements of the designs for future clinical trials and cancer treatments.

Item Type:Departmental Technical Report
Additional Information:Complex Systems Biology, Łukasiewicz-Topos and Higher-Dimensional Algebraic Models of Cell Interactomics; cell interactomics, dynamics of coupled genetic-proteomic networks and signaling pathways, development, regeneration, and control mechanisms of cell dynamic programming in cells, neoplastic transformations and oncogenesis; complex system modeling and biomolecular network representations in categories of Łukasiewicz Logic Algebras and Łukasiewicz-Topos Relational and Molecular Biology, Cell Genomics and Proteomics, and Cancer Cell Interactomics are represented in Supercategories defined currently as n-categories (or higher dimensional algebra), Axiomatic definitions of Categories and Supercategories of Relational, Complex Biological Systems, Dynamic Computations with Algebraic Varieties, Cell Transformations to Malignant Cancer. Early, Reliable and Sensitive Detection of Cancers by Ultra-sensitive, in vivo, Non-Invasive detection methods.
Keywords:Quantum Computation,Quantum Automata, Carcinogenesis; Malignant Tumors; Cancer Cell Interactomics; dynamics of genetic-proteomic networks and signalling pathways, development, regeneration, the control mechanisms of cell dynamic programming in cells; Neoplastic Transformations and Oncogenesis; Categories and Functors; Homology Theory applications to Qualitative Dynamics; Quantum Genetics; Relational Oscillations; Organismic Supercategories; Qualitative Dynamics of Systems in Organismic Supercategories; Algebraic Geometry in Biology, Cell Division Control and Dynamic Programnming;Cancer Cell Cycling; Categorical Dynamic Systems; Observables Generating Diagram, Relational Biology;Single Molecule Dynamics; Quantum, Electron Tunneling mechanisms in Enzyme Catalized reactions; Cell Transformations to Malignant Cancer;Telomerase and Reverse Transcriptase roles; c-Myc , TP53 and Ras tumor suppressor genes; p27 and p21 inhibition and uncontrolled cell cycling leading to neoplastic transformation/ malignant cell re-differentiation; rational, individualized therapy of cancers; rational clinical trials; molecular medicine, high-throughput genomics and proteomics technologies, tumor cell lines separation and complete genomic analysis; cancer cell biomarker pattern identification; Early, Reliable and Sensitive Detection of Cancers by Ultra-sensitive, in vivo, Non-Invasive Detection methods.
Subjects:Computer Science > Dynamical Systems
Computer Science > Complexity Theory
Computer Science > Artificial Intelligence
Biology > Theoretical Biology
ID Code:3810
Deposited By: Baianu, Professor I. C.
Deposited On:07 Sep 2004
Last Modified:11 Mar 2011 08:55

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