Literature DB >> 1650408

A mathematical computer stimulation model for the development of colonic polyps and colon cancer.

L E Mehl1.   

Abstract

Currently known information about the development and progression of colon polyps and cancer is summarized and organized into a mathematical computer simulation model that successfully predicts the natural history of colon polyp and cancer development for an average patient with (1) familial polyposis coli (2) genetic susceptibility as measured by a positive family history, and (3) negative family history with a high fat diet. The mathematical model uses four distinct types of cells (normal, transformed, polypoid, and cancerous) and two kinetic processes (mutation and promotion). Arachidonic acid metabolites play a role in the model in the promotion of cancer from polyps, and account for that promotion through: (1) their effect on encouraging more polypoid cells in mitosis to move toward cancer; and (2) their immunosuppressive effect over time. The model also shows that one defect in allowing more cells to mutate to the transformed state is sufficient to account for the chain of events leading to the clinical sequelae of familial polyposis coli. A second genetic effect at another point in the process is unnecessary. The mechanism of action of Sulindac on colon polyps is explained by the model through inhibition of production of arachidonic acid metabolites, most notably prostaglandin E.

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Year:  1991        PMID: 1650408     DOI: 10.1002/jso.2930470409

Source DB:  PubMed          Journal:  J Surg Oncol        ISSN: 0022-4790            Impact factor:   3.454


  5 in total

1.  The distribution of cellular turnover in the human body.

Authors:  Ron Sender; Ron Milo
Journal:  Nat Med       Date:  2021-01-11       Impact factor: 53.440

2.  Immunoglobulin Receptors Expression in Indian Colon Cancer Patients and Healthy Subjects Using a Noninvasive Approach and Flowcytometry.

Authors:  Rama Chaudhry; Vishwa Deepak Bamola; Projoyita Samanta; Divya Dubey; Tej Bahadur; Monica Chandan; Shyam Tiwary; Abhipray Gahlowt; Neha Nair; Harneet Kaur; Chena Passi; Atul Sharma; Dinesh S Chandel; Pinaki Panigrahi
Journal:  Int J Appl Basic Med Res       Date:  2020-07-11

3.  Data Driven Mathematical Model of Colon Cancer Progression.

Authors:  Arkadz Kirshtein; Shaya Akbarinejad; Wenrui Hao; Trang Le; Sumeyye Su; Rachel A Aronow; Leili Shahriyari
Journal:  J Clin Med       Date:  2020-12-05       Impact factor: 4.241

Review 4.  Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics.

Authors:  Mahnoor Naseer Gondal; Safee Ullah Chaudhary
Journal:  Front Oncol       Date:  2021-11-24       Impact factor: 6.244

5.  Predicting the progress of colon cancer by DNA methylation markers of the p16 gene in feces - Evidence from an animal model.

Authors:  Wen-Chih Wu; Chih-Hsiung Hsu; Jen-Chun Kuan; Jih-Fu Hsieh; Chien-An Sun; Tsan Yang; Chang-Chieh Wu; Yu-Ching Chou
Journal:  Genet Mol Biol       Date:  2013-08-30       Impact factor: 1.771

  5 in total

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