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  • [1]H. Kitano: Systems biology: a brief overview. Science, 295(5560), 1662-4 (2002)

  • [2]H. Kitano: Computational systems biology. Nature, 420(6912), 206-10 (2002)

  • [3]E. Wang. A roadmap of cancer systems biology. In: Cancer systems biology. Ed: E. Wang, CRC Press (2010)

  • [4]N. H. Ha and K. W. Hunter: Using a systems biology approach to understand and study the mechanisms of metastasis. Wires Syst Biol Med, 6(1), 107-114 (2014)

  • [5]Gaziel-Sovran, A., I. Osman and E. Hernando: In vivo Modeling and Molecular Characterization: A Path Toward Targeted Therapy of Melanoma Brain Metastasis. Front Oncol, 3, 127 (2013)

  • [6]T. G. Whitsett, L. J. Inge, H. D. Dhruv, P. Y. Cheung, G. J. Weiss, R. M. Bremner, J. A. Winkles and N. L. Tran: Molecular determinants of lung cancer metastasis to the central nervous system. Transl Lung Cancer Res, 2(4), 273-83 (2013)

  • [7]M. Hanibuchi, S. J. Kim, I. J. Fidler and Y. Nishioka: The molecular biology of lung cancer brain metastasis: an overview of current comprehensions and future perspectives. J Med Invest, 61(3-4), 241-53 (2014)

  • [8]C. L. Chaffer and R. A. Weinberg: A perspective on cancer cell metastasis. Science, 331(6024), 1559-64 (2011)

  • [9]A. A. Powell, A. H. Talasaz, H. Zhang, M. A. Coram, A. Reddy, G. Deng, M. L. Telli, R. H. Advani, R. W. Carlson, J. A. Mollick, S. Sheth, A. W. Kurian, J. M. Ford, F. E. Stockdale, S. R. Quake, R. F. Pease, M. N. Mindrinos, G. Bhanot, S. H. Dairkee, R. W. Davis and S. S. Jeffrey: Single cell profiling of circulating tumor cells: transcriptional heterogeneity and diversity from breast cancer cell lines. PLoS One, 7(5), e33788 (2012)

  • [10]K. Wu, K. Fukuda, F. Xing, Y. Zhang, S. Sharma, Y. Liu, M. D. Chan, X. Zhou, S. A. Qasem, R. Pochampally, Y. Y. Mo and K. Watabe: Roles of the cyclooxygenase 2 matrix metalloproteinase 1 pathway in brain metastasis of breast cancer. J Biol Chem, 290(15), 9842-54 (2015)

  • [11]E. Sahai: Illuminating the metastatic process. Nat Rev Cancer, 7(10), 737-49 (2007)

  • [12]S. Paget: The distribution of secondary growths in cancer of the breast. Cancer Metastasis Rev, 8(2), 98-101 (1989)

  • [13]L. Bubendorf, A. Schopfer, U. Wagner, G. Sauter, H. Moch, N. Willi, T. C. Gasser and M. J. Mihatsch: Metastatic patterns of prostate cancer: an autopsy study of 1,589 patients. Hum Pathol, 31(5), 578-83 (2000)

  • [14]B. Weigelt, J. L. Peterse and L. J. van ‘t Veer: Breast cancer metastasis: markers and models. Nat Rev Cancer, 5(8), 591-602 (2005)

  • [15]F. Lerebours, G. Cizeron-Clairac, A. Susini, S. Vacher, E. Mouret-Fourme, C. Belichard, E. Brain, J. L. Alberini, F. Spyratos, R. Lidereau and I. Bieche: miRNA expression profiling of inflammatory breast cancer identifies a 5-miRNA signature predictive of breast tumor aggressiveness. Int J Cancer, 133(7), 1614-23 (2013)

  • [16]R. Baffa, M. Fassan, S. Volinia, B. O’Hara, C. G. Liu, J. P. Palazzo, M. Gardiman, M. Rugge, L. G. Gomella, C. M. Croce and A. Rosenberg: MicroRNA expression profiling of human metastatic cancers identifies cancer gene targets. J Pathol, 219(2), 214-21 (2009)

  • [17]D. Hanniford, J. Zhong, L. Koetz, A. Gaziel-Sovran, D. J. Lackaye, S. Shang, A. Pavlick, R. L. Shapiro, R. S. Berman, F. Darvishian, Y. Shao, I. Osman and E. Hernando: A miRNA-based signature detected in primary melanoma tissue predicts development of brain metastasis. Clin Cancer Res (2015)

  • [18]V. A. Gennarino, M. Sardiello, R. Avellino, N. Meola, V. Maselli, S. Anand, L. Cutillo, A. Ballabio and S. Banfi: MicroRNA target prediction by expression analysis of host genes. Genome Res, 19(3), 481-90 (2009)

  • [19]S. Nasser, A. R. Ranade, S. Sridhar, L. Haney, R. L. Korn, M. B. Gotway, G. J. Weiss and S. Kim: Biomarkers associated with metastasis of lung cancer to brain predict patient survival. Int J Data Min Bioinform, 5(3), 287-307 (2011)

  • [20]M. D. Bashyam: Understanding cancer metastasis: an urgent need for using differential gene expression analysis. Cancer, 94(6), 1821-9 (2002)

  • [21]P. D. Bos, X. H. F. Zhang, C. Nadal, W. P. Shu, R. R. Gomis, D. X. Nguyen, A. J. Minn, M. J. van de Vijver, W. L. Gerald, J. A. Foekens and J. Massague: Genes that mediate breast cancer metastasis to the brain. Nature, 459(7249), 1005-U137 (2009)

  • [22]G. Hu, Y. Kang and X. F. Wang: From breast to the brain: unraveling the puzzle of metastasis organotropism. J Mol Cell Biol, 1(1), 3-5 (2009)

  • [23]A. Klein, C. Olendrowitz, R. Schmutzler, J. Hampl, P. M. Schlag, N. Maass, N. Arnold, R. Wessel, J. Ramser, A. Meindl, S. Scherneck and S. Seitz: Identification of brain-and bone-specific breast cancer metastasis genes. Cancer Lett, 276(2), 212-20 (2009)

  • [24]L. Sevenich, R. L. Bowman, S. D. Mason, D. F. Quail, F. Rapaport, B. T. Elie, E. Brogi, P. K. Brastianos, W. C. Hahn, L. J. Holsinger, J. Massague, C. S. Leslie and J. A. Joyce: Analysis of tumour-and stroma-supplied proteolytic networks reveals a brain-metastasis-promoting role for cathepsin S. Nat Cell Biol, 16(9), 876-88 (2014)

  • [25]A. Sadanandam, M. L. Varney, L. Kinarsky, H. Ali, R. L. Mosley and R. K. Singh: Identification of functional cell adhesion molecules with a potential role in metastasis by a combination of in vivo phage display and in silico analysis. OMICS, 11(1), 41-57 (2007)

  • [26]G. Gundem, P. Van Loo, B. Kremeyer, L. B. Alexandrov, J. M. Tubio, E. Papaemmanuil, D. S. Brewer, H. M. Kallio, G. Hognas, M. Annala, K. Kivinummi, V. Goody, C. Latimer, S. O’Meara, K. J. Dawson, W. Isaacs, M. R. Emmert-Buck, M. Nykter, C. Foster, Z. Kote-Jarai, D. Easton, H. C. Whitaker, I. P. U. Group, D. E. Neal, C. S. Cooper, R. A. Eeles, T. Visakorpi, P. J. Campbell, U. McDermott, D. C. Wedge and G. S. Bova: The evolutionary history of lethal metastatic prostate cancer. Nature, 520(7547), 353-7 (2015)

  • [27]Y. Hu, G. Wu, M. Rusch, L. Lukes, K. H. Buetow, J. Zhang and K. W. Hunter: Integrated cross-species transcriptional network analysis of metastatic susceptibility. Proc Natl Acad Sci U S A, 109(8), 3184-9 (2012)

  • [28]H. Zhao, G. Jin, K. Cui, D. Ren, T. Liu, P. Chen, S. Wong, F. Li, Y. Fan, A. Rodriguez, J. Chang and S. T. Wong: Novel modeling of cancer cell signaling pathways enables systematic drug repositioning for distinct breast cancer metastases. Cancer Res, 73(20), 6149-63 (2013)

  • [29]V. Nygaard, L. Prasmickaite, K. Vasiliauskaite, T. Clancy and E. Hovig: Melanoma brain colonization involves the emergence of a brain-adaptive phenotype. Oncoscience, 1(1), 82-94 (2014)

  • [30]R. M. Burnett, K. E. Craven, P. Krishnamurthy, C. P. Goswami, S. Badve, P. Crooks, W. P. Mathews, P. Bhat-Nakshatri and H. Nakshatri: Organ-specific adaptive signaling pathway activation in metastatic breast cancer cells. Oncotarget, 6(14), 12682-96 (2015)

  • [31]J. Dutkowski and T. Ideker: Protein Networks as Logic Functions in Development and Cancer. Plos Comput Biol, 7(9), e1002180 (2011)

  • [32]H. B. Engin, E. Guney, O. Keskin, B. Oliva and A. Gursoy: Integrating Structure to Protein-Protein Interaction Networks That Drive Metastasis to Brain and Lung in Breast Cancer. Plos One, 8(11), e81035 (2013)

  • [33]G. Improta, A. Zupa, H. Fillmore, J. Deng, M. Aieta, P. Musto, L. A. Liotta, W. Broaddus, E. F. Petricoin, 3rd and J. D. Wulfkuhle: Protein pathway activation mapping of brain metastasis from lung and breast cancers reveals organ type specific drug target activation. J Proteome Res, 10(7), 3089-97 (2011)

  • [34]L. Ding, M. J. Ellis, S. Li, D. E. Larson, K. Chen, J. W. Wallis, C. C. Harris, M. D. McLellan, R. S. Fulton, L. L. Fulton, R. M. Abbott, J. Hoog, D. J. Dooling, D. C. Koboldt, H. Schmidt, J. Kalicki, Q. Zhang, L. Chen, L. Lin, M. C. Wendl, J. F. McMichael, V. J. Magrini, L. Cook, S. D. McGrath, T. L. Vickery, E. Appelbaum, K. Deschryver, S. Davies, T. Guintoli, L. Lin, R. Crowder, Y. Tao, J. E. Snider, S. M. Smith, A. F. Dukes, G. E. Sanderson, C. S. Pohl, K. D. Delehaunty, C. C. Fronick, K. A. Pape, J. S. Reed, J. S. Robinson, J. S. Hodges, W. Schierding, N. D. Dees, D. Shen, D. P. Locke, M. E. Wiechert, J. M. Eldred, J. B. Peck, B. J. Oberkfell, J. T. Lolofie, F. Du, A. E. Hawkins, M. D. O’Laughlin, K. E. Bernard, M. Cunningham, G. Elliott, M. D. Mason, D. M. Thompson, Jr., J. L. Ivanovich, P. J. Goodfellow, C. M. Perou, G. M. Weinstock, R. Aft, M. Watson, T. J. Ley, R. K. Wilson and E. R. Mardis: Genome remodelling in a basal-like breast cancer metastasis and xenograft. Nature, 464(7291), 999-1005 (2010)

  • [35]F. Michor, T. P. Hughes, Y. Iwasa, S. Branford, N. P. Shah, C. L. Sawyers and M. A. Nowak: Dynamics of chronic myeloid leukaemia. Nature, 435(7046), 1267-70 (2005)

  • [36]F. Michor, M. A. Nowak and Y. Iwasa: Stochastic dynamics of metastasis formation. J Theor Biol, 240(4), 521-30 (2006)

  • [37]F. Michor and Y. Iwasa: Dynamics of metastasis suppressor gene inactivation. J Theor Biol, 241(3), 676-89 (2006)

  • [38]D. Dingli, F. Michor, T. Antal and J. M. Pacheco: The emergence of tumor metastases. Cancer Biol Ther, 6(3), 383-90 (2007)

  • [39]H. Haeno and F. Michor: The evolution of tumor metastases during clonal expansion. J Theor Biol, 263(1), 30-44 (2010)

  • [40]H. Haeno, M. Gonen, M. B. Davis, J. M. Herman, C. A. Iacobuzio-Donahue and F. Michor: Computational modeling of pancreatic cancer reveals kinetics of metastasis suggesting optimum treatment strategies. Cell, 148(1-2), 362-75 (2012)

  • [41]P. Moran: Random processes in genetics. Mathematical Proceedings of the Cambridge Philosophical Society, 54(1), 60-71 (1958)

  • [42]K. R. Hess, G. R. Varadhachary, S. H. Taylor, W. Wei, M. N. Raber, R. Lenzi and J. L. Abbruzzese: Metastatic patterns in adenocarcinoma. Cancer, 106(7), 1624-33 (2006)

  • [43]S. Y. Wang, X. Ye, W. Ou, Y. B. Lin, B. B. Zhang and H. Yang: Risk of cerebral metastases for postoperative locally advanced non-small-cell lung cancer. Lung Cancer, 64(2), 238-43 (2009)

  • [44]K. J. Wang, B. Makond and K. M. Wang: Modeling and predicting the occurrence of brain metastasis from lung cancer by Bayesian network: a case study of Taiwan. Comput Biol Med, 47, 147-60 (2014)

  • [45]P. K. Newton, J. Mason, K. Bethel, L. A. Bazhenova, J. Nieva and P. Kuhn: A stochastic Markov chain model to describe lung cancer growth and metastasis. PLoS One, 7(4), e34637 (2012)

  • [46]P. K. Newton, J. Mason, K. Bethel, L. Bazhenova, J. Nieva, L. Norton and P. Kuhn: Spreaders and sponges define metastasis in lung cancer: a Markov chain Monte Carlo mathematical model. Cancer Res, 73(9), 2760-9 (2013)

  • [47]L. L. Chen, N. Blumm, N. A. Christakis, A. L. Barabasi and T. S. Deisboeck: Cancer metastasis networks and the prediction of progression patterns. Br J Cancer, 101(5), 749-58 (2009)

  • [48]J. G. Scott, D. Basanta, A. R. Anderson and P. Gerlee: A mathematical model of tumour self-seeding reveals secondary metastatic deposits as drivers of primary tumour growth. J R Soc Interface, 10(82), 20130011 (2013)

  • [49]S. J. Kim, J. S. Kim, E. S. Park, J. S. Lee, Q. Lin, R. R. Langley, M. Maya, J. He, S. W. Kim, Z. Weihua, K. Balasubramanian, D. Fan, G. B. Mills, M. C. Hung and I. J. Fidler: Astrocytes upregulate survival genes in tumor cells and induce protection from chemotherapy. Neoplasia, 13(3), 286-98 (2011)

  • [50]E. S. Park, S. J. Kim, S. W. Kim, S. L. Yoon, S. H. Leem, S. B. Kim, S. M. Kim, Y. Y. Park, J. H. Cheong, H. G. Woo, G. B. Mills, I. J. Fidler and J. S. Lee: Cross-species hybridization of microarrays for studying tumor transcriptome of brain metastasis. Proc Natl Acad Sci U S A, 108(42), 17456-61 (2011)

  • [51]F. Xing, A. Kobayashi, H. Okuda, M. Watabe, S. K. Pai, P. R. Pandey, S. Hirota, A. Wilber, Y. Y. Mo, B. E. Moore, W. Liu, K. Fukuda, M. Iiizumi, S. Sharma, Y. Liu, K. Wu, E. Peralta and K. Watabe: Reactive astrocytes promote the metastatic growth of breast cancer stem-like cells by activating Notch signalling in brain. EMBO Mol Med, 5(3), 384-96 (2013)

  • [52]A. H. Wu, J. C. Drees, H. Wang, S. R. VandenBerg, A. Lal, W. D. Henner and R. Pillai: Gene expression profiles help identify the tissue of origin for metastatic brain cancers. Diagn Pathol, 5, 26 (2010)

  • [53]B. Salhia, J. Kiefer, J. T. Ross, R. Metapally, R. A. Martinez, K. N. Johnson, D. M. DiPerna, K. M. Paquette, S. Jung, S. Nasser, G. Wallstrom, W. Tembe, A. Baker, J. Carpten, J. Resau, T. Ryken, Z. Sibenaller, E. F. Petricoin, L. A. Liotta, R. K. Ramanathan, M. E. Berens and N. L. Tran: Integrated genomic and epigenomic analysis of breast cancer brain metastasis. PLoS One, 9(1), e85448 (2014)

  • [54]A. Bleckmann, L. Siam, F. Klemm, E. Rietkotter, C. Wegner, F. Kramer, T. Beissbarth, C. Binder, C. Stadelmann and T. Pukrop: Nuclear LEF1/TCF4 correlate with poor prognosis but not with nuclear beta-catenin in cerebral metastasis of lung adenocarcinomas. Clin Exp Metastasis, 30(4), 471-82 (2013)

  • [55]A. M. Broadbent, G. Hruby, M. M. Tin, M. Jackson and I. Firth: Survival following whole brain radiation treatment for cerebral metastases: an audit of 474 patients. Radiother Oncol, 71(3), 259-65 (2004)

  • [56]M. Staudt, K. Lasithiotakis, U. Leiter, F. Meier, T. Eigentler, M. Bamberg, M. Tatagiba, P. Brossart and C. Garbe: Determinants of survival in patients with brain metastases from cutaneous melanoma. Br J Cancer, 102(8), 1213-8 (2010)

  • [57]N. F. Marko, Z. Xu, T. Gao, M. W. Kattan and R. J. Weil: Predicting survival in women with breast cancer and brain metastasis: a nomogram outperforms current survival prediction models. Cancer, 118(15), 3749-57 (2012)

  • [58]T. Z. Vern-Gross, J. A. Lawrence, L. D. Case, K. P. McMullen, J. D. Bourland, L. J. Metheny-Barlow, T. L. Ellis, S. B. Tatter, E. G. Shaw, J. J. Urbanic and M. D. Chan: Breast cancer subtype affects patterns of failure of brain metastases after treatment with stereotactic radiosurgery. J Neurooncol, 110(3), 381-8 (2012)

  • [59]D. N. Ayala-Peacock, A. M. Peiffer, J. T. Lucas, S. Isom, J. G. Kuremsky, J. J. Urbanic, J. D. Bourland, A. W. Laxton, S. B. Tatter, E. G. Shaw and M. D. Chan: A nomogram for predicting distant brain failure in patients treated with gamma knife stereotactic radiosurgery without whole brain radiotherapy. Neuro Oncol, 16(9), 1283-8 (2014)

  • [60]J. T. Lucas, H. G. Colmer, L. White, N. Fitzgerald, S. Isom, J. D. Bourland, A. W. Laxton, S. B. Tatter and M. D. Chan: Competing risk analysis of neurologic versus nonneruologic death in patients undergoing radiosurgical salvage after whole-brain radiation therapy failure: who actually dies of their brain metastases? Int J Radiation Oncol Biol Phys, 92(5), 1008-1015 (2015)

  • [61]B. Makond, K. J. Wang and K. M. Wang: Probabilistic modeling of short survivability in patients with brain metastasis from lung cancer. Comput Methods Programs Biomed, 119(3), 142-62 (2015)

  • [62]O. Freedman, E. Amir, G. Dranitsaris, J. Napolskikh, R. Kumar, M. Fralick, S. Chia, T. Petrella, S. Dent, K. Tonkin, I. Ahmad, D. Rayson and M. Clemons: Predicting benefit from fulvestrant in pretreated metastatic breast cancer patients. Breast Cancer Res Treat, 118(2), 377-83 (2009)

  • [63]M. Jung, J. B. Ahn, J. H. Chang, C. O. Suh, S. Hong, J. K. Roh, S. J. Shin and S. Y. Rha: Brain metastases from colorectal carcinoma: prognostic factors and outcome. J Neurooncol, 101 (1), 49-55 (2011)

  • [64]L. S. Kim, S. Huang, W. Lu, D. C. Lev and J. E. Price: Vascular endothelial growth factor expression promotes the growth of breast cancer brain metastases in nude mice. Clin Exp Metastasis, 21(2), 107-18 (2004)

  • [65]G. Schackert and I. J. Fidler: Site-Specific Metastasis of Mouse Melanomas and a Fibro-Sarcoma in the Brain or Meninges of Syngeneic Animals. Cancer Res, 48(12), 3478-84 (1988)

  • [66]J. Wang, I. Daphu, P. H. Pedersen, H. Miletic, R. Hovland, S. Mork, R. Bjerkvig, C. Tiron, E. McCormack, D. Micklem, J. B. Lorens, H. Immervoll and F. Thorsen: A novel brain metastases model developed in immunodeficient rats closely mimics the growth of metastatic brain tumours in patients. Neuropathol Appl Neurobiol, 37(2), 189-205 (2011)

  • [67]Y. W. Zang, X. D. Gu, J. B. Xiang and Z. Y. Chen: Brain Metastases from Colorectal Cancer: Microenvironment and Molecular Mechanisms. Int J Mol Sci, 13(12), 15784-800 (2012)

  • [68]N. Saito, T. Hatori, N. Murata, Z. A. Zhang, H. Nonaka, K. Aoki, S. Iwabuchi and M. Ueda: Comparison of metastatic brain tumour models using three different methods: the morphological role of the pia mater. Int J Exp Pathol, 89(1), 38-44 (2008)

  • [69]I. Daphu, T. Sundstrom, S. Horn, P. C. Huszthy, S. P. Niclou, P. O. Sakariassen, H. Immervoll, H. Miletic, R. Bjerkvig and F. Thorsen: In vivo animal models for studying brain metastasis: value and limitations. Clin Exp Metastasis, 30(5), 695-710 (2013)

  • [70]G. W. Brodland and J. H. Veldhuis: The Mechanics of Metastasis: Insights from a Computational Model. Plos One, 7(9), e44281 (2012)

  • [71]J. G. Scott, P. Gerlee, D. Basanta, A. G. Fletcher, P. K. Maini and A. R. Anderson: Mathematical modelling of the metastatic process. In: Experimental Metastasis: Modeling and Analysis. Ed: A. Malek, New York: Springer (2013)

  • [72]A. R. A. Anderson and V. Quaranta: Integrative mathematical oncology. Nat Rev Cancer, 8(3), 227-34 (2008)

  • [73]F. Michor, M. A. Nowak and Y. Iwasa: Stochastic dynamics of metastasis formation. J Theor Biol, 240(4), 521-30 (2006)

  • [74]D. Dingli, F. Michor, T. Antal and J. M. Pacheco: The emergence of tumor metastases. Cancer Biol Ther, 6(3), 383-90 (2007)

  • [75]H. Haeno and F. Michor: The evolution of tumor metastases during clonal expansion. J Theor Biol, 263(1), 30-44 (2010)

  • [76]M. Kimmel and B. J. Flehinger: Nonparametric-Estimation of the Size Metastasis Relationship in Solid Cancers. Biometrics, 47(3), 987-1004 (1991)

  • [77]D. P. Taylor, J. Z. Wells, A. Savol, C. Chennubhotla and A. Wells: Modeling Boundary Conditions for Balanced Proliferation in Metastatic Latency. Clin Cancer Res, 19(5), 1063-70 (2013)

  • [78]A. R. Kansal, S. Torquato, G. I. Harsh, E. A. Chiocca and T. S. Deisboeck: Simulated brain tumor growth dynamics using a three-dimensional cellular automaton. J Theor Biol, 203 (4), 367-82 (2000)

  • [79]L. Norton: A Gompertzian model of human breast cancer growth. Cancer Res, 48(24), 7067-71 (1988)

  • [80]G. J. Bosl, N. L. Geller, C. Cirrincione, N. J. Vogelzang, B. J. Kennedy, W. F. Whitmore, Jr., D. Vugrin, H. Scher, J. Nisselbaum and R. B. Golbey: Multivariate analysis of prognostic variables in patients with metastatic testicular cancer. Cancer Res, 43(7), 3403-7 (1983)

  • [81]K. Iwata, K. Kawasaki and N. Shigesada: Adynamical model for the growth and size distribution of multiple metastatic tumors. J Theor Biol, 203(2), 177-86 (2000)

  • [82]D. Barbolosi, A. Benabdallah, F. Hubert and F. Verga: Mathematical and numerical analysis for a model of growing metastatic tumors. Math Biosci, 218(1), 1-14 (2009)

  • [83]N. Hartung, S. Mollard, D. Barbolosi, A. Benabdallah, G. Chapuisat, G. Henry, S. Giacometti, A. Iliadis, J. Ciccolini, C. Faivre and F. Hubert: Mathematical modeling of tumor growth and metastatic spreading: validation in tumor-bearing mice. Cancer Res, 74(22), 6397-407 (2014)

  • [84]A. R. A. Anderson: A hybrid mathematical model of solid tumour invasion: the importance of cell adhesion. Math Med Biol, 22(2), 163-86 (2005)

  • [85]F. Li, H. Tan, J. Singh, J. Yang, X. Xia, J. Bao, J. Ma, M. Zhan and S. T. Wong: A 3D multiscale model of cancer stem cell in tumor development. BMC Syst Biol, 7(S2), S12 (2013)

  • [86]F. Li, J. Singh, X. Xia, D. Cridebring, J. Yang, M. Zhan, S. T. C. Wong, J. Bao and J. Ma: A 3-dimentional multiscale model to simulate tumor progression in response to interactions between cancer stem cells and tumor microenvironmental factors. IEEE 6th International Conference on Systems Biology (ISB), 297-303 (2012)

  • [87]L. Liu, H. Wang, J. Wen, C. E. Tseng, Y. Zu, C. C. Chang and X. Zhou: Mutated genes and driver pathways involved in myelodysplastic syndromes-a transcriptome sequencing based approach. Mol Biosyst, 11(8), 2158-66 (2015)

  • [88]V. Suresh, L. Liu, D. Adjeroh and X. Zhou: RPI-Pred: predicting ncRNA-protein interaction using sequence and structural information. Nucleic Acids Res, 43(3), 1370-9 (2015)

  • [89]L. Liu, G. Jin and X. Zhou: Modeling the relationship of epigenetic modifications to transcription factor binding. Nucleic Acids Res, 43(8), 3873-85 (2015)

  • [90]X. Chen, L. Liu, J. Mims, E. C. Punska, K. E. Williams, W. Zhao, K. F. Arcaro, A. W. Tsang, X. Zhou and C. M. Furdui: Analysis of DNA methylation and gene expression in radiation-resistant head and neck tumors. Epigenetics, 10(6), 545-61 (2015)

  • [91]H. Peng, J. Wen, H. Li, J. Chang and X. Zhou: Drug inhibition profile prediction for NFkappaB pathway in multiple myeloma. PLoS One, 6(3), e14750 (2011)

  • [92]H. Peng, J. Wen, L. Zhang, H. Li, C. C. Chang, Y. Zu and X. Zhou: A systematic modeling study on the pathogenic role of p38 MAPK activation in myelodysplastic syndromes. Mol Biosyst, 8(4), 1366-74 (2012)

  • [93]X. Sun, J. Su, J. Bao, T. Peng, L. Zhang, Y. Zhang, Y. Yang and X. Zhou: Cytokine combination therapy prediction for bone remodeling in tissue engineering based on the intracellular signaling pathway. Biomaterials, 33(33), 8265-76 (2012)

  • [94]X. Sun, Y. Kang, J. Bao, Y. Zhang, Y. Yang and X. Zhou: Modeling vascularized bone regeneration within a porous biodegradable CaP scaffold loaded with growth factors. Biomaterials, 34(21), 4971-81 (2013)

  • [95]T. Peng, H. Peng, D. S. Choi, J. Su, C. C. Chang and X. Zhou: Modeling cell-cell interactions in regulating multiple myeloma initiating cell fate. IEEE J Biomed Health Inform, 18(2), 484-91 (2014)

  • [96]H. Peng, T. Peng, J. Wen, D. A. Engler, R. K. Matsunami, J. Su, L. Zhang, C. C. Chang and X. Zhou: Characterization of p38 MAPK isoforms for drug resistance study using systems biology approach. Bioinformatics, 30(13), 1899-907 (2014)

  • [97]L. Tang, A. L. van de Ven, D. Guo, V. Andasari, V. Cristini, K. C. Li and X. Zhou: Computational modeling of 3D tumor growth and angiogenesis for chemotherapy evaluation. PLoS One, 9(1), e83962 (2014)

  • [98]J. Su, L. Zhang, W. Zhang, D. S. Choi, J. Wen, B. Jiang, C. C. Chang and X. Zhou: Targeting the biophysical properties of the myeloma initiating cell niches: a pharmaceutical synergism analysis using multi-scale agent-based modeling. PLoS One, 9(1), e85059 (2014)

  • [99]H. Peng, X. Zhou, F. Li, X. Xia and S. T. Wong: Integrating Multi-Scale Blob/Curvilinear Detector Techniques and Multi-Level Sets for Automated Segmentation of Stem Cell Images. Proc IEEE Int Symp Biomed Imaging, 2009, 1362-5 (2009)

  • [100]G. M. Saidel, L. A. Liotta and J. Kleinerman: System dynamics of metastatic process from an implanted tumor. J Theor Biol, 56(2), 417-34 (1976)

  • [101]H. Enderling, A. R. Anderson, M. A. Chaplain, A. Beheshti, L. Hlatky and P. Hahnfeldt: Paradoxical dependencies of tumor dormancy and progression on basic cell kinetics. Cancer Res, 69(22), 8814-21 (2009)

  • [102]A. R. A. Anderson and V. Quaranta: Integrative mathematical oncology. Nat Rev Cancer, 8(3), 227-34 (2008)

  • [103]J. G. Scott, P. Gerlee, D. Basanta, A. G. Fletcher, P. K. Maini and A. R. Anderson: Mathematical modelling of the metastatic process. In: Experimental Metastasis: Modeling and Analysis. Ed: A. Malek, NewYork: Springer (2013)

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Frontiers in Bioscience-Scholar (FBS) is published by IMR Press from Volume 13 Issue 1 (2021). Previous articles were published by another publisher on a subscription basis, and they are hosted by IMR Press on imrpress.com as a courtesy and upon agreement with Frontiers in Bioscience.

1 Jan 2016Review

Computational systems biology in cancer brain metastasis

Huiming Peng 1, Hua Tan 1, Weiling Zhao 1, Guangxu Jin 1, Sambad Sharma 2, Fei Xing 2, Kounosuke Watabe 2, Xiaobo Zhou 1,*
Affiliations
Article Info

1 Department of Radiology, Wake Forest School of Medicine, Winston Salem, NC, USA

2 Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC, USA

*Author to whom correspondence should be addressed.

 

Abstract

Brain metastases occur in 20-40% of patients with advanced malignancies. A better understanding of the mechanism of this disease will help us to identify novel therapeutic strategies. In this review, we will discuss the systems biology approaches used in this area, including bioinformatics and mathematical modeling. Bioinformatics has been used for identifying the molecular mechanisms driving brain metastasis and mathematical modeling methods for analyzing dynamics of a system and predicting optimal therapeutic strategies. We will illustrate the strategies, procedures, and computational techniques used for studying systems biology in cancer brain metastases. We will give examples on how to use a systems biology approach to analyze a complex disease. Some of the approaches used to identify relevant networks, pathways, and possibly biomarkers in metastasis will be reviewed into details. Finally, certain challenges and possible future directions in this area will also be discussed.

Keywords

  • Brain metastasis
  • Systems biology
  • Bioinformatics
  • Mathematical model
  • Molecular mechanism
  • Review

References