Preclinical Magnetic Resonance Imaging and Systems Biology in Cancer Research

Biologically accurate mouse models of human cancer have become important tools for the study of human disease. The anatomical location of various target organs, such as brain, pancreas, and prostate, makes determination of disease status difficult. Imaging modalities, such as magnetic resonance imaging, can greatly enhance diagnosis, and longitudinal imaging of tumor progression is an important source of experimental data. Even in models where the tumors arise in areas that permit visual determination of tumorigenesis, longitudinal anatomical and functional imaging can enhance the scope of studies by facilitating the assessment of biological alterations, (such as changes in angiogenesis, metabolism, cellular invasion) as well as tissue perfusion and diffusion. One of the challenges in preclinical imaging is the development of infrastructural platforms required for integrating in vivo imaging and therapeutic response data with ex vivo pathological and molecular data using a more systems-based multiscale modeling approach. Further challenges exist in integrating these data for computational modeling to better understand the pathobiology of cancer and to better affect its cure. We review the current applications of preclinical imaging and discuss the implications of applying functional imaging to visualize cancer progression and treatment. Finally, we provide new data from an ongoing preclinical drug study demonstrating how multiscale modeling can lead to a more comprehensive understanding of cancer biology and therapy. Biologically accurate mouse models of human cancer have become important tools for the study of human disease. The anatomical location of various target organs, such as brain, pancreas, and prostate, makes determination of disease status difficult. Imaging modalities, such as magnetic resonance imaging, can greatly enhance diagnosis, and longitudinal imaging of tumor progression is an important source of experimental data. Even in models where the tumors arise in areas that permit visual determination of tumorigenesis, longitudinal anatomical and functional imaging can enhance the scope of studies by facilitating the assessment of biological alterations, (such as changes in angiogenesis, metabolism, cellular invasion) as well as tissue perfusion and diffusion. One of the challenges in preclinical imaging is the development of infrastructural platforms required for integrating in vivo imaging and therapeutic response data with ex vivo pathological and molecular data using a more systems-based multiscale modeling approach. Further challenges exist in integrating these data for computational modeling to better understand the pathobiology of cancer and to better affect its cure. We review the current applications of preclinical imaging and discuss the implications of applying functional imaging to visualize cancer progression and treatment. Finally, we provide new data from an ongoing preclinical drug study demonstrating how multiscale modeling can lead to a more comprehensive understanding of cancer biology and therapy. CME Accreditation Statement: This activity (“ASIP 2013 AJP CME Program in Pathogenesis”) has been planned and implemented in accordance with the Essential Areas and policies of the Accreditation Council for Continuing Medical Education (ACCME) through the joint sponsorship of the American Society for Clinical Pathology (ASCP) and the American Society for Investigative Pathology (ASIP). ASCP is accredited by the ACCME to provide continuing medical education for physicians. The ASCP designates this journal-based CME activity (“ASIP 2013 AJP CME Program in Pathogenesis”) for a maximum of 48 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.CME Disclosures: The authors of this article and the planning committee members and staff have no relevant financial relationships with commercial interests to disclose. The extensive pharmacological studies that have been aimed at developing and testing new anti-neoplastic compounds have clearly established the need for both highly accurate preclinical models, as well as the methods to longitudinally assess therapeutic response. These translational studies have driven significant technological advances in both anatomical and functional imaging and have resulted in the engineering of small animal imaging platforms, including luminescence, fluorescence, positron emission tomography, and magnetic resonance imaging (MRI). Currently, significant needs exist related to enhancing our ability to use quantitative anatomical, metabolic, and functional imaging, integrated into a systems approach to clinical medicine, to expand our understanding of cancer biology and to identify early markers of effective therapeutic intervention. Genetically engineered (GE) mice, since their introduction more than 30 years ago, have become increasingly important to our understanding of the interrelationship between genes, the organism, its environment, and the efficacy of new and existing treatment régimes. The early GE models were relatively simple, primarily relying on the integration of a promoter and transgene into the mouse genome, although technological advances such as inducible gene expression (eg, tetracycline, tamoxifen, or steroid hormones) and the Cre:LoxP gene ablation/modification systems have lead to more biologically relevant models with increased fidelity to the cellular and molecular basis for many human cancers.1Albanese C. Rodriguez O. Johnson M.D. Fricke S. Models of Prostate cancer.Drug Discov Today Dis Models. 2005; 2: 7-13Crossref Scopus (6) Google Scholar In fact, the use of GE mice and xeno- and allo-grafting models have become the hallmark of translational platforms for the study of human cancers and their treatment. There are inherent difficulties associated with many GE models (eg, brain,2Beauchamp E.M. Ringer L. Bulut G. Sajwan K.P. Hall M.D. Lee Y.C. Peaceman D. Ozdemirli M. Rodriguez O. Macdonald T.J. Albanese C. Toretsky J.A. Uren A. Arsenic trioxide inhibits human cancer cell growth and tumor development in mice by blocking Hedgehog/GLI pathway.J Clin Invest. 2011; 121: 148-160Crossref PubMed Scopus (281) Google Scholar prostate,3Fricke S. Rodriguez O. Vanmeter J. Dettin L. Casimiro M. Chien C. Newell T. Johnson K. Ileva L. Johnson M.D. Albanese C. In vivo magnetic resonance volumetric and spectroscopic analysis of mouse prostate cancer models.Prostate. 2006; 66: 708-717Crossref PubMed Scopus (39) Google Scholar and gastric4Pollock C.B. Rodriguez O. Martin P.L. Albanese C. Li X. Kopelovich L. Glazer R.I. Induction of metastatic gastric cancer by peroxisome proliferator-activated receptor delta activation.PPAR Res 2010,. 2010; : 571783Google Scholar), as in humans, in identifying disease initiation, its progression, and its treatment without invasive surgery or sacrificing the animal. Preclinical imaging modalities have been developed to overcome these limitations and to enable longitudinal studies analogous to clinical imaging and trials. Two of these preclinical imaging modalities (ie, MRI and positron emission tomography) allow for functional and metabolic imaging. Importantly, MRI is unique in its ability to combine high resolution anatomical imaging with functional and metabolic analyses, making it one of the most flexible preclinical/clinical imaging platforms. Imaging data can both define the location of deep tissue tumors and provide data related to cancer progression and regression (response to therapy), because many longitudinal preclinical studies seek to combine in vivo imaging data with ex vivo pathology, as well as with genetic and molecular changes within the target tissue to quantify complex phenotypic traits. The complexity of the data generated, however, which by necessity must include those of the underlying model, requires cross-platform multiscale approaches. These platforms, by definition, must integrate the imaging data for a region of interest (eg, a tumor), which occurs at the organismal and macroscopic scales, with the data from the cellular or microscopic scale (eg, pathology, vascularity) and with data derived at the subcellular or molecular scale (eg, mRNA, proteomics, metabolomics). Currently, there are National Institutes of Health initiatives such as the cancer Biomedical Informatics Grid, and National Cancer Institute initiatives such as The Cancer Genome Atlas that seek to support the groundwork collaborations between cancer imaging laboratories and molecular and bioinformatics/bioengineering groups that are needed to develop these capabilities. Additional innovations, such as the Georgetown Database of Cancer (G-DOC), a systems medicine data integration, analysis, and visualization platform,5Madhavan S. Gusev Y. Harris M. Tanenbaum D.M. Gauba R. Bhuvaneshwar K. Shinohara A. Rosso K. Carabet L.A. Song L. Riggins R.B. Dakshanamurthy S. Wang Y. Byers S.W. Clarke R. Weiner L.M. G-DOC: a systems medicine platform for personalized oncology.Neoplasia. 2011; 13: 771-783Abstract Full Text PDF PubMed Scopus (46) Google Scholar will eventually allow for real-time data analysis. These bioinformatics platforms will allow for correlative data comparisons, such as those available from The Cancer Genome Atlas, and for target validation, as well as for predictive modeling of tumors and their responses to intervention. In this review, recent advances in the use of MRI in preclinical cancer research are highlighted, and we discuss and give an example of the central role that MRI combined with systems biology can fulfill in imaging-based preclinical studies. Many outstanding imaging modalities exist for anatomical imaging (eg, ultrasound was one of the earliest translations of human imaging into preclinical modeling). Ultrasound provides a rapid and sensitive method for the identification of changes in skin architecture, volumetric analyses of surface tumors, such as xenografted human cancer cells, oncogene-induced changes in the mammary gland before palpable tumors arise,6Tilli M.T. Parrish A.R. Cotarla I. Jones L.P. Johnson M.D. Furth P.A. Comparison of mouse mammary gland imaging techniques and applications: reflectance confocal microscopy. GFP imaging, and ultrasound.BMC Cancer. 2008; 8: 21Crossref PubMed Scopus (13) Google Scholar and vascular blood flow by Doppler. Ultrasound is limited to some extent by its depth of imaging, its dynamic range, and its lack of contrast in some tissues, and also by its inability to perform functional and metabolic imaging. Similarly, computed tomography is widely used in both clinical and preclinical settings and provides extremely high resolution anatomical imaging, however, the use of computed tomography is limited in its metabolic and functional imaging as a stand-alone modality. Furthermore, computed tomography involves ionizing radiation exposure necessitating judicious use in both research and diagnostic settings. MRI has long been used for anatomical imaging to allow the visualization of changes that occur during disease progression. In addition, magnetic resonance-based chemical imaging using hyperpolarized carbon-14 has shown great promise in visualizing alterations in tissue pH7Gallagher F.A. Kettunen M.I. Brindle K.M. Imaging pH with hyperpolarized 13C.NMR Biomed. 2011; 24: 1006-1015Crossref PubMed Scopus (86) Google Scholar and cellular redox activity,8Keshari K.R. Kurhanewicz J. Bok R. Larson P.E. Vigneron D.B. Wilson D.M. Hyperpolarized 13C dehydroascorbate as an endogenous redox sensor for in vivo metabolic imaging.Proc Natl Acad Sci USA. 2011; 108: 18606-18611Crossref PubMed Scopus (118) Google Scholar and proton magnetic resonance spectroscopy (1H-MRS) is a rapidly developing field of discovery, enabling the measurement of altered energy and metabolic pathways in situ. In combination with anatomical MRI, for example, the measurement of changes in citrate to choline ratios by 1H-MRS have identified cancerous areas of the human prostate.9Zakian K.L. Eberhardt S. Hricak H. Shukla-Dave A. Kleinman S. Muruganandham M. Sircar K. Kattan M.W. Reuter V.E. Scardino P.T. Koutcher J.A. Transition zone prostate cancer: metabolic characteristics at 1H MR spectroscopic imaging–initial results.Radiology. 2003; 229: 241-247Crossref PubMed Scopus (165) Google Scholar Using 1H-MRS, we found that the GE mice we developed that presented with spontaneous prostate cancer, also exhibited an altered choline-to-citrate profile, which was seen in humans.3Fricke S. Rodriguez O. Vanmeter J. Dettin L. Casimiro M. Chien C. Newell T. Johnson K. Ileva L. Johnson M.D. Albanese C. In vivo magnetic resonance volumetric and spectroscopic analysis of mouse prostate cancer models.Prostate. 2006; 66: 708-717Crossref PubMed Scopus (39) Google Scholar These data served to further validate mice as a biologically relevant model amenable to preclinical studies with translational impact on the clinical prostate disease. Importantly, identifying metabolic changes that correlate with cancer progression allows for a possibility of monitoring intervention through dynamic monitoring of tumor chemistry in vivo. The recent of functional magnetic resonance to cancer is also to enhance the preclinical and clinical diagnostic and monitoring of disease progression and treatment efficacy of a of including those of the brain, prostate, and imaging of altered of in tissue and is by the National Cancer Institute as a for imaging cancer A.R. G. D.M. T. A. M. D. P.L. magnetic resonance imaging as a cancer and Full Text PDF PubMed Scopus Google Scholar imaging can identify in for example, between and imaging the of blood which is in with metabolic and blood which is an of J. K. L. J. A. K. imaging of the functional of on tumor cell and blood in an experimental PubMed Scopus Google Scholar imaging imaging, from with such as and will become of enhancing their in and molecular MRI of the 2011; 24: PubMed Scopus Google Scholar M. K. H. H. S. S. T. and imaging in the assessment of at 2010; PubMed Scopus Google Scholar have that the ability to these changes in the tumor can lead to better and tissue to identify and vascular and provides a method for tumor on contrast and S. A. P.L. M. of dynamic MRI in prostate cancer and PubMed Scopus Google Scholar can identify of vascular tumor We that both spectroscopic and imaging great promise for visualizing responses to both chemical and in such as and the such as proteomics, and have our understanding of cancer and progression. 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The of will the ability to therapeutic efficacy and in to identify members of the disease is as in a and functional imaging combined with the promise of such a The development and testing of such a systems-based approach to drug for is using human in the early animal models exist that In an study using MRI as a diagnostic we established that a and therapeutic used for the treatment of was effective in in the GE model of E.M. Ringer L. Bulut G. Sajwan K.P. Hall M.D. Lee Y.C. Peaceman D. Ozdemirli M. Rodriguez O. Macdonald T.J. Albanese C. Toretsky J.A. Uren A. Arsenic trioxide inhibits human cancer cell growth and tumor development in mice by blocking Hedgehog/GLI pathway.J Clin Invest. 2011; 121: 148-160Crossref PubMed Scopus (281) Google Scholar anatomical imaging studies have been on and mice using our MRI, and 1H-MRS was also using a spectroscopy as C. Rodriguez O. Johnson M.D. Fricke S. 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