Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma

Cancer fighting treatments are expanding, and a promising type, targeted molecular therapies have a new approach. The aim of these therapies is not to eliminate the whole tumor, but to control the tumor into a given state and keep it there. Explicit knowledge of tumor growth dynamics and the effects of targeted molecular therapies is crucial in tumor treatment development. We show the results of mouse experiments where tumor growth was investigated in case of C38 colon adenocarcinoma and B16 melanoma. Several curves were fitted and tumor growth dynamics was examined. Three attributes of tumor were measured: tumor volume, tumor mass and vascularization; and tumor growth dynamics was examined. Tumor volume was measured with digital caliper, vascularization was investigated with CD31 antibody immunohistochemistry staining on frozen sections. The relationship between these tumor attributes were examined with linear regression analysis. The dynamics of tumor growth was identified as a second order linear system.

[1]  Ervin Lumnitzer,et al.  Modeling and the Use of Simulation Methods for the Design of Lighting Systems , 2011 .

[2]  J. Horton Medical Oncology: Basic Principles and Clinical Management of Cancer, , 1986 .

[3]  Farhad Toorani,et al.  Gray-Box Modeling of a Pneumatic Servo-Valve , 2010 .

[4]  Gyula Mester,et al.  The Modeling and Simulation of an Autonomous Quad-Rotor Microcopter in a Virtual Outdoor Scenario , 2011 .

[5]  H. Kreipe,et al.  Beyond typing and grading: target analysis in individualized therapy as a new challenge for tumour pathology. , 2007, Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer.

[6]  A. Fischer,et al.  Hematoxylin and eosin staining of tissue and cell sections. , 2008, CSH protocols.

[7]  E. Berg,et al.  World Health Organization Classification of Tumours , 2002 .

[8]  E. Somers International Agency for Research on Cancer. , 1985, CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne.

[9]  A. Khuri Introduction to Linear Regression Analysis, Fifth Edition by Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining , 2013 .

[10]  J. Bussink,et al.  Hypoxic cell turnover in different solid tumor lines. , 2005, International journal of radiation oncology, biology, physics.

[11]  Levente Kovács,et al.  Flat control of tumor growth with angiogenic inhibition , 2012, 2012 7th IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI).

[12]  J. Verweij,et al.  Combination therapy of ACNU and ifosfamide in tumor bearing mice with M2661 breast cancer, B16 malignant melanoma or C38 colon cancer. , 1990, European journal of cancer.

[13]  L. Kovacs,et al.  Linear state-feedback control synthesis of tumor growth control in antiangiogenic therapy , 2012, 2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI).

[14]  B. Benyo,et al.  Model-based control algorithms for optimal therapy of high-impact public health diseases , 2012, 2012 IEEE 16th International Conference on Intelligent Engineering Systems (INES).

[15]  A. Heerschap,et al.  Carbogen breathing differentially enhances blood plasma volume and 5-fluorouracil uptake in two murine colon tumor models with a distinct vascular structure. , 2006, Neoplasia.

[16]  Levente Kovács,et al.  Model-based analysis and synthesis of tumor growth under angiogenic inhibition: A case study , 2011 .

[17]  Harold Chestnut The International Federation of Automatic Control , 1960 .

[18]  Bart Landuyt,et al.  Vascular Endothelial Growth Factor and Angiogenesis , 2004, Pharmacological Reviews.

[19]  W. S. Rasband,et al.  ImageJ: Image processing and analysis in Java , 2012 .

[20]  A. Heerschap,et al.  5‐fluorouracil metabolite patterns in viable and necrotic tumor areas of murine colon carcinoma determined by 19F NMR spectroscopy , 1996, Magnetic resonance in medicine.

[21]  L. Kovács,et al.  Modeling and optimal control strategies of diseases with high public health impact , 2011, 2011 15th IEEE International Conference on Intelligent Engineering Systems.

[22]  N. Restifo,et al.  B16 as a Mouse Model for Human Melanoma , 2000, Current protocols in immunology.

[23]  D. Gerber,et al.  Targeted therapies: a new generation of cancer treatments. , 2008, American family physician.

[24]  D. Ma,et al.  Cancer recurrence after surgery: Direct and indirect effects of anesthetic agents * , 2012, International journal of cancer.

[25]  C. Ling,et al.  Modeling the development of metastases from primary and locally recurrent tumors: comparison with a clinical data base for prostatic cancer. , 1993, Cancer research.

[26]  M. Larson Analysis of Variance , 2008, Circulation.

[27]  Levente Kovács,et al.  Model-based angiogenic inhibition of tumor growth using modern robust control method , 2014, Comput. Methods Programs Biomed..