Cogprints

Complex Systems Analysis of Arrested Neural Cell Differentiation during Development and Analogous Cell Cycling Models in Carcinogenesis

Baianu, Professor I.C. and Prisecaru, M.S. V (2004) Complex Systems Analysis of Arrested Neural Cell Differentiation during Development and Analogous Cell Cycling Models in Carcinogenesis. [Preprint]

Full text available as:

[img]
Preview
 PDF
164Kb

Abstract

A new approach to the modular, complex systems analysis of nonlinear dynamics of arrested neural cell Differentiation--induced cell proliferation during organismic development and the analogous cell cycling network transformations involved in carcinogenesis is proposed. Neural tissue arrested differentiation that induces cell proliferation during perturbed development and Carcinogenesis are complex processes that involve dynamically inter-connected biomolecules in the intercellular, membrane, cytosolic, nuclear and nucleolar compartments. Such 'dynamically inter-connected' biomolecules form numerous inter-related pathways referred to as 'molecular networks'. One such family of signaling pathways contains the cell cyclins. Cyclins are proteins that link several critical pro-apoptotic and other cell cycling/division components, including the tumor suppressor gene TP53 and its product, the Thomsen-Friedenreich antigen (T antigen), Rb, mdm2, c-Myc, p21, p27, Bax, Bad and Bcl-2, which play major roles in various neoplastic transformations of many tissues. The novel theoretical analysis presented here is based on recently published studies of arrested cell differentiation that normally leads to neural system formation during early developmental stages; the perturbed development may involve cyclin signaling and cell cycling responsible for rapidly induced cell proliferation without differentiation into neural cells in such experimental studies; special emphasis in this modular model is placed upon the roles of cyclins D1 and E, and does suggest novel clinical trials as well as rational therapies of cancer through re-establishment of cell cycling inhibition in metastatic cancer cells. Cyclins are proteins that are often over-expressed in cancerous cells (Dobashi et al., 2004). They may also be over-expressed in cells whose differentiation is arrested during the early stages of organismic development, leading to increased cell proliferation instead of differentiation into specialized tissues such as those forming the neural system. Cyclin-dependent kinases (CDK), their respective cyclins, and inhibitors of CDKs (CKIs) were identified as instrumental components of the cell cycle-regulating machinery. In mammalian cells the complexes of cyclins D1, D2, D3, A and E with CDKs are considered motors that drive cells to enter and pass through the “S” phase. Cell cycle regulation is a critical mechanism governing cell division and proliferation, and it is finely regulated by the interaction of cyclins with CDKs and CKIs, among other molecules (Morgan et al., 1995). A categorical and Topos framework for Łukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional genomes and cell interactomes is also proposed. Łukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of varying 'next-state' functions is extended in a Łukasiewicz-Topos with an n-valued Łukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis. Important aspects of Cell Cycling, the Control of Cell Division,and the Neoplastic Transformation in Carcinogenesis are being considered and subjected to algebraic-logico- relational, and computer-aided investigations. The essential roles of various levels of c-Myc, p27 quasi-complete inhibition/blocking, TP53 and/or p53 inactivation, as well as the perpetual hTERT activation of Telomerase biosynthesis are pointed out as key conditions for Malignant Cell transformations and partial re-differentiation leading to various types of cancer such as lung, breast,skin, prostate and colon. Rational Clinical trials, Individualized Medicine and the potential for optimized Radio-, Chemo-, Gene-, and Immuno- therapies of Cancers are suggested on the basis of integrated complex systems biology modeling of oncogenesis, coupled with extensive genomic/proteomic and interactomic High-throughput/high-sensitivity measurements of identified, sorted cell lines that are being isolated from malignant tumors of patients undergoing clinical trials with adjuvant signaling drug therapies. The implications of the cyclin model for abnormal neural development during early development are being considered in this model that may lead to explanations of subsequent cognitive changes associated with abnormal neural cell differentiation in environmentally-affected embryos. This new model may also be relevant to detecting the onset of senescing neuron transformations in Alzheimer's and related diseases of the human brain in ageing populations at risk.

Item Type:Preprint
Additional Information:Rational Clinical trials, Individualized Medicine and the potential for optimized Radio-, Chemo-, Gene-, and Immuno- therapies of Cancers are suggested on the basis of integrated complex systems biology modeling of oncogenesis, coupled with extensive genomic/proteomic and interactomic High-throughput/high-sensitivity measurements of identified, sorted cell lines that are being isolated from malignant tumors of patients undergoing clinical trials with adjuvant signaling drug therapies.
Keywords:Cell cycling, control of cell division and the neoplastic transformation in carcinogenesis; essential roles of high c-Myc, p27 Inhibition, p53 inactivation and hTERT activation of Telomerase biosynthesis in Malignant Cell Transformation; Rational Clinical trials, Individualized Medicine and potential for optimized Radio-Chemo-, Gene-, and Immuno- therapies of Cancers; Łukasiewicz models of Genetic Networks; Genome and cell interactomics models in terms of categories of Łukasiewicz logic Algebras and Lukasiewicz Topos;Łukasiewicz Topos with an n-valued Łukasiewicz Algebraic Logic subobject classifier; genetic network transformations in Carcinogenesis, developmental processes and Evolution/ Evolutionary Biology; Relational Biology of Archea, yeast and higher eukaryotic organisms; nonlinear dynamics in non-random, hierarchic genetic networks; proteomics coupled genomes via signaling pathways;mechanisms of neoplastic transformations of cells and topological grupoid models of genetic networks in cancer cells; natural transformations of organismic structures in Molecular Biology.
Subjects:Computer Science > Dynamical Systems
Computer Science > Complexity Theory
JOURNALS > Medical Education Online > MEO PrePrint
Biology > Theoretical Biology
ID Code:3703
Deposited By: Baianu, Professor I. C.
Deposited On:06 Jul 2004
Last Modified:11 Mar 2011 08:55

References in Article

Select the SEEK icon to attempt to find the referenced article. If it does not appear to be in cogprints you will be forwarded to the paracite service. Poorly formated references will probably not work.

Alle KM, Henshall SM, Field AS, and Sutherland RL. 1998. Cyclin D1 protein is overexpressed in hyperplasia and intraductal carcinoma of the breast. Clin. Cancer Res., 4:847–854.

Andersen G, Busso D, Poterszman A, Hwang JR, Wurtz J, Ripp R, Thierry J, Egly J and Moras D.1997. The structure of cyclin H: common mode of kinase activation and specific features. EMBO J,

16(5):958–967.

Bagui TK, Jackson RJ, Agrawal D,and Pledger WJ. 2000. Analysis of cyclin D3-cdk4 complexes in fibroblasts expressing and lacking p27kip1 and p21cip1. Mol. Cell. Biol., 20:8748– 8757.

Baianu,I.C. 1969. Chs. 3 to 5 in: “ Theoretical and Experimental Models of Carcinogenesis. M.S.

Thesis, Physics and Medical Biophysics Depts.”, BU.

Baianu,I.C. 1987. Computer Models and Automata Theory in Biology and Medicine. In:

“Mathematical Modelling in Medicine”, M.Witten, Ed., New York: Pergamon Press, vol.7, pp.1513-1577.

Bryja V, Pachernik J, Faldikova L, Krejci P, Pogue R, Nevriva I I, Dvorak P, Hampl A. 2004 May.

The role of p27(Kip1) in maintaining the levels of D-type cyclins in vivo. Biochim Biophys Acta,

3;1691(2-3):105-116.

Cheng M, Olivier P, Diehl JA, Fero M, Roussel MF, Roberts JM, and Sherr CJ. 1999. The

p21Cip1 and p27kip1 ‘inhibitors’ are essential activators of cyclin D-dependent kinases in murine

fibroblasts. EMBO J, 18:1571– 1583.

Dobashi, Y., Goto, A., Fukayama, M., Abe, A., and Ooi, A. 2004. Overexpression of Cdk4/Cyclin

D1, a possible mediator of apoptosis and an indicator of prognosis in human primary lung

carcinoma. Int.J.Cancer:110,532 41.

Dobashi Y, Jiang SX, Shoji M, et al., 2003. Diversity in expression and prognostic significance of

G1/S cyclins in human primary lung carcinomas. J Pathol, 199:208-20.

Fukuse T, Hirata T, Naiki H, Hitomi S, and Wada H. 2000. Prognostic significance of cyclin E

overexpression in resected non-small cell lung cancer. Cancer Res., 60:242-4.

Gillett C, Fantl V, Smith R, Fisher C, et al. (1994). Amplification and overexpression of cyclin D1

in breast cancer detected by immunohistochemical staining. Cancer Res., 54:1812–1817.

Handa K, Yamakawa M, Takeda H, Kimura S, and Takahashi T. 1999. Expression of cell cycle

markers in colorectal carcinoma:superiority of cyclin A as an indicator of poor prognosis. Int J

Cancer, 84:225-33.

Hershko A and Ciechanover A. 1998. The ubiquitin system. Annu. Rev. Biochem, 67:425–479.

Klint P, and Claesson-Welsh L. 1999. Signal transduction by fibroblast

growth factor receptors. Front. Biosci., 4,D165–D177.

Koziczak M, Holbro T., and Hynes NE. 2004. Blocking of FGFR signaling inhibits breast cancer

cell proliferation through downregulation of D-type cyclins. Oncogene, 23:3501–3508.

Loden M, Sighall M, Nielsen NH, Roos G, Emdin SO, et al. 2002. The cyclin D1 high and cyclin

E high subgroups of breast cancer: Separate pathways in tumorigenesis based on pattern of genetic

aberrations and inactivation of the pRb node. Oncogene, 21:4680–4690.

Malumbres M, and Barbacid M. 2001. To cycle or not to cycle: A critical decision in cancer. Nat.

Rev. Cancer, 1:222–231.

Morgan, DO. 1995. Principles of CDK regulation. Nature, 374:131-4.

Muraoka RS, Lenferink AEG, Simpson J, Brantley DM, Roebuck LR, Yakes FM, and Arteaga CL.

2001. Cyclin-dependent kinase inhibitor p27kip1 is required for mouse mammary gland

morphogenesis and function, J. Cell Biol, 153:917–931.

Noguchi T, Dobashi Y, Minehara H, Itoman M, and Kameya T. 2000. Involvement of cyclins in

cell proliferation and their clinical implications in soft tissue smooth muscle tumors. Am J Pathol,

156:2135–47.

Ohta T, and Fukuda M. 2004. Ubiquitin and breast cancer. Oncogene, 23(11):2079-88.

Ormandy CJ, Musgrove EA, Hui R, Daly RJ, and Sutherland RL. 2003. Cyclin D1, EMS1 and

11q13 amplification in human breast cancers. Breast Cancer Res. Treat., 78:323–335.

Sutherland RL, Musgrove EA. 2004 Jan. Cyclins and breast cancer. J Mammary Gland Biol

Neoplasia., 9(1):95-104.

van Diest PJ, Michalides RJ, Jannink L,van der Valk P, Peterse HL, de Jong JS, Meijer CJ, and

Baak JP. 1995. Cyclin D1 expression in invasive breast cancer: Correlation and prognostic value.

Am J Pathol 1995; 150:705-11. </html>

Baianu, I. and Marinescu, M. 1968. Organismic Supercategories: I. Proposals for a General Unitary Theory of Systems. Bull. Math. Biophys., 30: 625-635.

Baianu, I. 1970. "Organismic Supercategories: II On Multistable Systems."Bull. Math.Biophysics., 32: 539-561.

Baianu, I.1971a. "Organismic Supercategories and Qualitative Dynamics of Systems." Ibid., 33, 339-353.

Baianu, I. 1971. Categories, Functors and Automata Theory. The 4th Intl. Congress LMPS, August-Sept. 1971b.

Baianu, I. and Scripcariu, D. 1973. On Adjoint Dynamical Systems. Bull. Math. Biology., 35: 475-486.

Baianu, I. 1973. Some Algebraic Properties of (M,R)-Systems in Categories. Bull. Math. Biophys, 35: 213-218.

Baianu, I. and Marinescu, M. 1974. A Functorial Construction of (M,R)-Systems. Rev. Roum. Math. Pures et Appl., 19: 389-392.

Baianu, I.C. 1977. A Logical Model of Genetic Activities in Lukasiewicz Algebras: The Non-Linear Theory., Bull. Math. Biol.,39:249-258.Baianu, I.C. 1977.

Baianu, I.C. 1980. Natural Transformations of Organismic Structures. Bull.Math. Biology, 42:431-446.

Baianu, I.C.1983. Natural Transformations Models in Molecular Biology. SIAM Natl. Meeting, Denver, CO, USA.

Baianu, I.C. 1984. A Molecular-Set-Variable Model of Structural and Regulatory Activities in Metabolic and Genetic Systems., Fed. Proc. Amer. Soc. Experim. Biol. 43:917.

Baianu, I.C. 1987. “Computer Models and Automata Theory in Biology and Medicine” (A Review). In: "Mathematical models in Medicine.",vol.7., M. Witten, Ed., Pergamon Press: New York, pp.1513-1577.

Baianu, I.C. 2004. “Cell Genome and Interactome Nonlinear Dynamic Models in Łukasiewicz Logic Algebras. Neoplastic Transformation Models in a Łukasiewicz Topos.” Submitted archive preprint, June 25th 2004. # GN 0406050.

Baianu, I.C., J. Glazebrook, G. Georgescu and R.Brown, 2004. “A Novel Approach to Complex Systems Biology and Observation Strategies based on Categories, Higher Dimensional Algebra and Łukasiewicz Topos. “ Manuscript in preparation, 16 pp.

Carnap. R. 1938. "'The Logical Syntax of Language" New York: Harcourt, Brace and Co.

Georgescu, G. and C. Vraciu 1970. "On the Characterization of Lukasiewicz Algebras." J Algebra, 16 4, 486-495.

Hilbert, D. and W. Ackerman. 1927. Grunduge.der Theoretischen Logik, Berlin: Springer.

McCulloch, W and W. Pitts. 1943. “A logical Calculus of Ideas Immanent in Nervous Activity” Ibid., 5, 115-133.

Pitts, W. 1943. “The Linear Theory of Neuron Networks” Bull. Math. Biophys., 5, 23-31.

Rosen, R.1958.a.”A Relational Theory of Biological Systems” Bull. Math. Biophys., 20, 245-260.

Rosen, R. 1958b. “The Representation of Biological Systems from the Standpoint of the Theory of Categories” Bull. Math. Biophys., 20, 317-341.

Rosen, Robert. 1973. On the Dynamical realization of (M,R)-Systems. Bull. Math. Biology., 35:1-10.

Rosen, Robert. 2001. “Essays on Life Itself “. New York: Columbia University Press, 221 pp.

Russel, Bertrand and A.N. Whitehead, 1925. Principia Mathematica, Cambridge: Cambridge Univ. Press.

Warner, M. 1982. Representations of (M,R)-Systems by Categories of Automata., Bull. Math. Biol., 44:661-668.

Metadata

Repository Staff Only: item control page

Cogprints is powered by EPrints 3 which is developed by the School of Electronics and Computer Science at the University of Southampton. More information and software credits.