Literature DB >> 11395397

A quantitative model for the dynamics of serum prostate-specific antigen as a marker for cancerous growth: an explanation for a medical anomaly.

K R Swanson1, L D True, D W Lin, K R Buhler, R Vessella, J D Murray.   

Abstract

Prostate-specific antigen (PSA) is an enzyme produced by both normal and cancerous prostate epithelial cells. Although PSA is the most widely used serum marker to detect and follow patients with prostatic adenocarcinoma, there are certain anomalies in the values of serum levels of PSA that are not understood. We developed a mathematical model for the dynamics of serum levels of PSA as a function of the tumor volume. Our model results show good agreement with experimental observations and provide an explanation for the existence of significant prostatic tumor mass despite a low-serum PSA. This result can be very useful in enhancing the use of serum PSA levels as a marker for cancer growth.

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Year:  2001        PMID: 11395397      PMCID: PMC2216460          DOI: 10.1016/S0002-9440(10)64691-3

Source DB:  PubMed          Journal:  Am J Pathol        ISSN: 0002-9440            Impact factor:   4.307


  12 in total

1.  Prostate-specific antigen: advances and challenges.

Authors:  D W Chan; L J Sokoll
Journal:  Clin Chem       Date:  1999-06       Impact factor: 8.327

2.  The significance of DNA-ploidy and S-phase fraction in node-positive (stage D1) prostate cancer treated with androgen ablation.

Authors:  A Pollack; P Troncoso; G K Zagars; A C von Eschenbach; A C Mak; C S Wu; N H Terry
Journal:  Prostate       Date:  1997-04-01       Impact factor: 4.104

3.  Combination of prostate-specific antigen, clinical stage, and Gleason score to predict pathological stage of localized prostate cancer. A multi-institutional update.

Authors:  A W Partin; M W Kattan; E N Subong; P C Walsh; K J Wojno; J E Oesterling; P T Scardino; J D Pearson
Journal:  JAMA       Date:  1997-05-14       Impact factor: 56.272

Review 4.  Prostate specific antigen: a critical assessment of the most useful tumor marker for adenocarcinoma of the prostate.

Authors:  J E Oesterling
Journal:  J Urol       Date:  1991-05       Impact factor: 7.450

5.  Transition zone prostate specific antigen density: lack of use in prediction of prostatic carcinoma.

Authors:  D W Lin; M H Gold; S Ransom; W J Ellis; M K Brawer
Journal:  J Urol       Date:  1998-07       Impact factor: 7.450

6.  The volume of prostate cancer in the biopsy specimen cannot reliably predict the quantity of cancer in the radical prostatectomy specimen on an individual basis.

Authors:  M R Cupp; D G Bostwick; R P Myers; J E Oesterling
Journal:  J Urol       Date:  1995-05       Impact factor: 7.450

7.  Implication of cell kinetic changes during the progression of human prostatic cancer.

Authors:  R R Berges; J Vukanovic; J I Epstein; M CarMichel; L Cisek; D E Johnson; R W Veltri; P C Walsh; J T Isaacs
Journal:  Clin Cancer Res       Date:  1995-05       Impact factor: 12.531

8.  Prostate-specific antigen variability in men without prostate cancer: effect of sampling interval on prostate-specific antigen velocity.

Authors:  H B Carter; J D Pearson; Z Waclawiw; E J Metter; D W Chan; H A Guess; P C Walsh
Journal:  Urology       Date:  1995-04       Impact factor: 2.649

9.  Prediction of prostate cancer volume using prostate-specific antigen levels, transrectal ultrasound, and systematic sextant biopsies.

Authors:  M K Terris; D J Haney; I M Johnstone; J E McNeal; T A Stamey
Journal:  Urology       Date:  1995-01       Impact factor: 2.649

10.  Rate of change in serum prostate specific antigen levels as a method for prostate cancer detection.

Authors:  D S Smith; W J Catalona
Journal:  J Urol       Date:  1994-10       Impact factor: 7.450

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  9 in total

1.  Vignettes from the field of mathematical biology: the application of mathematics to biology and medicine.

Authors:  J D Murray
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2.  A stochastic model for PSA levels: behavior of solutions and population statistics.

Authors:  Pavel Belík; P W A Dayananda; John T Kemper; Mikhail M Shvartsman
Journal:  J Math Biol       Date:  2006-07-11       Impact factor: 2.259

3.  Mechanistic modelling of prostate-specific antigen dynamics shows potential for personalized prediction of radiation therapy outcome.

Authors:  Guillermo Lorenzo; Víctor M Pérez-García; Alfonso Mariño; Luis A Pérez-Romasanta; Alessandro Reali; Hector Gomez
Journal:  J R Soc Interface       Date:  2019-08-14       Impact factor: 4.118

4.  Tissue-scale, personalized modeling and simulation of prostate cancer growth.

Authors:  Guillermo Lorenzo; Michael A Scott; Kevin Tew; Thomas J R Hughes; Yongjie Jessica Zhang; Lei Liu; Guillermo Vilanova; Hector Gomez
Journal:  Proc Natl Acad Sci U S A       Date:  2016-11-16       Impact factor: 11.205

5.  Stochastic model for tumor control probability: effects of cell cycle and (a)symmetric proliferation.

Authors:  Andrew Dhawan; Kamran Kaveh; Mohammad Kohandel; Sivabal Sivaloganathan
Journal:  Theor Biol Med Model       Date:  2014-11-22       Impact factor: 2.432

6.  Modeling therapeutic response to radioiodine in metastatic thyroid cancer: a proof-of-concept study for individualized medicine.

Authors:  Dominique Barbolosi; Ilyssa Summer; Christophe Meille; Raphaël Serre; Antony Kelly; Slimane Zerdoud; Claire Bournaud; Claire Schvartz; Michel Toubeau; Marie-Elisabeth Toubert; Isabelle Keller; David Taïeb
Journal:  Oncotarget       Date:  2017-06-13

Review 7.  Assessment of miR-98-5p, miR-152-3p, miR-326 and miR-4289 Expression as Biomarker for Prostate Cancer Diagnosis.

Authors:  Leire Moya; Jonelle Meijer; Sarah Schubert; Farhana Matin; Jyotsna Batra
Journal:  Int J Mol Sci       Date:  2019-03-06       Impact factor: 5.923

8.  An Analytical Study of Prostate-Specific Antigen Dynamics.

Authors:  Ernesto P Esteban; Giovanni Deliz; Jaileen Rivera-Rodriguez; Stephanie M Laureano
Journal:  Comput Math Methods Med       Date:  2016-11-13       Impact factor: 2.238

9.  Mathematical Prostate Cancer Evolution: Effect of Immunotherapy Based on Controlled Vaccination Strategy.

Authors:  Dorota Ba Dziul; Paweł Jakubczyk; Levan Chotorlishvili; Zaza Toklikishvilie; Julian Traciak; Joanna Jakubowicz-Gil; Sylwia Chmiel-Szajner
Journal:  Comput Math Methods Med       Date:  2020-01-13       Impact factor: 2.238

  9 in total

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