A partial differential equation model of metastasized prostatic cancer

  • Received: 01 October 2012 Accepted: 29 June 2018 Published: 01 April 2013
  • MSC : Primary: 92C40, 92C50; Secondary: 37N25.

  • Biochemically failing metastatic prostate cancer is typically treated with androgen ablation. However, due to the emergence of castration-resistant cells that can survive in low androgen concentrations, such therapy eventually fails. Here, we develop a partial differential equation model of the growth and response to treatment of prostate cancer that has metastasized to the bone. Existence and uniqueness results are derived for the resulting free boundary problem. In particular, existence and uniqueness of solutions for all time are proven for the radially symmetric case. Finally, numerical simulations of a tumor growing in 2-dimensions with radial symmetry are carried in order to evaluate the therapeutic potential of different treatment strategies. These simulations are able to reproduce a variety of clinically observed responses to treatment, and suggest treatment strategies that may result in tumor remission, underscoring our model's potential to make a significant contribution in the field of prostate cancer therapeutics.

    Citation: Avner Friedman, Harsh Vardhan Jain. A partial differential equation model of metastasized prostatic cancer[J]. Mathematical Biosciences and Engineering, 2013, 10(3): 591-608. doi: 10.3934/mbe.2013.10.591

    Related Papers:

    [1] Tin Phan, Changhan He, Alejandro Martinez, Yang Kuang . Dynamics and implications of models for intermittent androgen suppression therapy. Mathematical Biosciences and Engineering, 2019, 16(1): 187-204. doi: 10.3934/mbe.2019010
    [2] Alacia M. Voth, John G. Alford, Edward W. Swim . Mathematical modeling of continuous and intermittent androgen suppression for the treatment of advanced prostate cancer. Mathematical Biosciences and Engineering, 2017, 14(3): 777-804. doi: 10.3934/mbe.2017043
    [3] Zhimin Wu, Tin Phan, Javier Baez, Yang Kuang, Eric J. Kostelich . Predictability and identifiability assessment of models for prostate cancer under androgen suppression therapy. Mathematical Biosciences and Engineering, 2019, 16(5): 3512-3536. doi: 10.3934/mbe.2019176
    [4] Leonardo Schultz, Antonio Gondim, Shigui Ruan . Gompertz models with periodical treatment and applications to prostate cancer. Mathematical Biosciences and Engineering, 2024, 21(3): 4104-4116. doi: 10.3934/mbe.2024181
    [5] Leo Turner, Andrew Burbanks, Marianna Cerasuolo . PCa dynamics with neuroendocrine differentiation and distributed delay. Mathematical Biosciences and Engineering, 2021, 18(6): 8577-8602. doi: 10.3934/mbe.2021425
    [6] Hao Shen, Xiao-Dong Weng, Du Yang, Lei Wang, Xiu-Heng Liu . Long noncoding RNA MIR22HG is down-regulated in prostate cancer. Mathematical Biosciences and Engineering, 2020, 17(2): 1776-1786. doi: 10.3934/mbe.2020093
    [7] Salman Lari, Hossein Rajabzadeh, Mohammad Kohandel, Hyock Ju Kwon . A holistic physics-informed neural network solution for precise destruction of breast tumors using focused ultrasound on a realistic breast model. Mathematical Biosciences and Engineering, 2024, 21(10): 7337-7372. doi: 10.3934/mbe.2024323
    [8] Peng Gu, Dongrong Yang, Jin Zhu, Minhao Zhang, Xiaoliang He . Bioinformatics analysis identified hub genes in prostate cancer tumorigenesis and metastasis. Mathematical Biosciences and Engineering, 2021, 18(4): 3180-3196. doi: 10.3934/mbe.2021158
    [9] J. Ignacio Tello . On a mathematical model of tumor growth based on cancer stem cells. Mathematical Biosciences and Engineering, 2013, 10(1): 263-278. doi: 10.3934/mbe.2013.10.263
    [10] Heyrim Cho, Allison L. Lewis, Kathleen M. Storey, Anna C. Zittle . An adaptive information-theoretic experimental design procedure for high-to-low fidelity calibration of prostate cancer models. Mathematical Biosciences and Engineering, 2023, 20(10): 17986-18017. doi: 10.3934/mbe.2023799
  • Biochemically failing metastatic prostate cancer is typically treated with androgen ablation. However, due to the emergence of castration-resistant cells that can survive in low androgen concentrations, such therapy eventually fails. Here, we develop a partial differential equation model of the growth and response to treatment of prostate cancer that has metastasized to the bone. Existence and uniqueness results are derived for the resulting free boundary problem. In particular, existence and uniqueness of solutions for all time are proven for the radially symmetric case. Finally, numerical simulations of a tumor growing in 2-dimensions with radial symmetry are carried in order to evaluate the therapeutic potential of different treatment strategies. These simulations are able to reproduce a variety of clinically observed responses to treatment, and suggest treatment strategies that may result in tumor remission, underscoring our model's potential to make a significant contribution in the field of prostate cancer therapeutics.


    [1] J. Natl. Cancer. Inst., 91 (1999), 1869-1876.
    [2] N. Engl. J. Med., 360 (2009), 1310-1319.
    [3] Clin. Cancer Res., 1 (1995), 473-480.
    [4] J. Urol., 162 (1999), 897-901.
    [5] SIAM J. Math. Anal., 35 (2003), 974-986.
    [6] Cancer Res., 56 (1996), 3091-3102.
    [7] Semin. Oncol. Nurs., 27 (2011), 241-250.
    [8] Biol. Direct, 5 (2010), 24-52.
    [9] Nat. Rev. Cancer, 1 (2001), 34-45.
    [10] Interface. Free Bound., 10 (2008), 245-262.
    [11] J. Cancer Res. Clin. Oncol., 132 (2006), S17-S26.
    [12] N. Engl. J. Med., 324 (1991), 236-245.
    [13] Prostate Cancer Prostatic Dis., 1 (1998), 289-296.
    [14] Urology, 45 (1995), 839-844.
    [15] AJR Am. J. Roentgenol., 189 (2007), 323-328.
    [16] Endocr. Rev., 25 (2004), 276-308.
    [17] J. Theor. Biol., 264 (2010), 517-527.
    [18] J. Nonlinear Sci., 18 (2008), 593-614.
    [19] Discrete Cont. Dyn.-B, 4 (2004), 187-201.
    [20] Neoplasia, 6 (2004), 697-704.
    [21] Proc. Natl. Acad. Sci. USA, 108 (2011), 19701-19706.
    [22] Discrete Cont. Dyn.-B, in press.
    [23] Mol. Endocrinol., 4 (1990), 1105-1116.
    [24] J. Theor. Biol., 257 (2009), 292-302.
    [25] Endocrinology, 141 (2000), 953-958.
    [26] AIP Advances, 2 (2012), 011002.
    [27] Am. J. Physiol. Endocrinol. Metab., 291 (2006), E952-E964.
    [28] J. Clin. Invest., 98 (1996), 255-263.
    [29] Cancer Res., 59 (1999), 781-786.
    [30] Cancer Res., 51 (1991), 3748-3752.
    [31] Urology, 52 (1998), 44-47.
    [32] Proc. Natl. Acad. Sci. USA, 93 (1996), 15152-15157.
  • This article has been cited by:

    1. Tin Phan, Sharon M. Crook, Alan H. Bryce, Carlo C. Maley, Eric J. Kostelich, Yang Kuang, Review: Mathematical Modeling of Prostate Cancer and Clinical Application, 2020, 10, 2076-3417, 2721, 10.3390/app10082721
    2. Javier Baez, Yang Kuang, Mathematical Models of Androgen Resistance in Prostate Cancer Patients under Intermittent Androgen Suppression Therapy, 2016, 6, 2076-3417, 352, 10.3390/app6110352
    3. Navid Mohammad Mirzaei, Zuzana Tatarova, Wenrui Hao, Navid Changizi, Alireza Asadpoure, Ioannis K. Zervantonakis, Yu Hu, Young Hwan Chang, Leili Shahriyari, A PDE Model of Breast Tumor Progression in MMTV-PyMT Mice, 2022, 12, 2075-4426, 807, 10.3390/jpm12050807
    4. Nourridine Siewe, Avner Friedman, Afsheen Raza, Combination therapy for mCRPC with immune checkpoint inhibitors, ADT and vaccine: A mathematical model, 2022, 17, 1932-6203, e0262453, 10.1371/journal.pone.0262453
    5. Ellina Grigorieva, Evgenii Khailov, Bilinear controlled model in adaptive cancer therapy, 2025, 0, 1531-3492, 0, 10.3934/dcdsb.2025015
  • Reader Comments
  • © 2013 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(3718) PDF downloads(1108) Cited by(5)

Article outline

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog