Toward an Ising Model of Cancer and Beyond

Theoretical and computational tools that can be used in the clinic to predict neoplastic progression and propose individualized optimal treatment strategies to control cancer growth is desired. To develop such a predictive model, one must account for the complex mechanisms involved in tumor growth. Here we review resarch work that we have done toward the development of an "Ising model" of cancer. The review begins with a description of a minimalist four-dimensional (three in space and one in time) cellular automaton (CA) model of cancer in which healthy cells transition between states (proliferative, hypoxic, and necrotic) according to simple local rules and their present states, which can viewed as a stripped-down Ising model of cancer. This model is applied to model the growth of glioblastoma multiforme, the most malignant of brain cancers. This is followed by a discussion of the extension of the model to study the effect on the tumor dynamics and geometry of a mutated subpopulation. A discussion of how tumor growth is affected by chemotherapeutic treatment is then described. How angiogenesis as well as the heterogeneous and confined environment in which a tumor grows is incorporated in the CA model is discussed. The characterization of the level of organization of the invasive network around a solid tumor using spanning trees is subsequently described. Then, we describe open problems and future promising avenues for future research, including the need to develop better molecular-based models that incorporate the true heterogeneous environment over wide range of length and time scales (via imaging data), cell motility, oncogenes, tumor suppressor genes and cell-cell communication. The need to bring to bear the powerful machinery of the theory of heterogeneous media to better understand the behavior of cancer in its microenvironment is presented.Comment: 55 pages, 21 figures and 3 tables. To appear in Physical Biology. Added reference

Overcoming the blood–brain barrier: the role of nanomaterials in treating neurological diseases

Therapies directed toward the central nervous system remain difficult to translate into improved clinical outcomes. This is largely due to the blood–brain barrier (BBB), arguably the most tightly regulated interface in the human body, which routinely excludes most therapeutics. Advances in the engineering of nanomaterials and their application in biomedicine (i.e., nanomedicine) are enabling new strategies that have the potential to help improve our understanding and treatment of neurological diseases. Herein, the various mechanisms by which therapeutics can be delivered to the brain are examined and key challenges facing translation of this research from benchtop to bedside are highlighted. Following a contextual overview of the BBB anatomy and physiology in both healthy and diseased states, relevant therapeutic strategies for bypassing and crossing the BBB are discussed. The focus here is especially on nanomaterial‐based drug delivery systems and the potential of these to overcome the biological challenges imposed by the BBB. Finally, disease‐targeting strategies and clearance mechanisms are explored. The objective is to provide the diverse range of researchers active in the field (e.g., material scientists, chemists, engineers, neuroscientists, and clinicians) with an easily accessible guide to the key opportunities and challenges currently facing the nanomaterial‐mediated treatment of neurological diseases

The Genomic Analysis of Lactic Acidosis and Acidosis Response in Human Cancers

The tumor microenvironment has a significant impact on tumor development. Two important determinants in this environment are hypoxia and lactic acidosis. Although lactic acidosis has long been recognized as an important factor in cancer, relatively little is known about how cells respond to lactic acidosis and how that response relates to cancer phenotypes. We develop genome-scale gene expression studies to dissect transcriptional responses of primary human mammary epithelial cells to lactic acidosis and hypoxia in vitro and to explore how they are linked to clinical tumor phenotypes in vivo. The resulting experimental signatures of responses to lactic acidosis and hypoxia are evaluated in a heterogeneous set of breast cancer datasets. A strong lactic acidosis response signature identifies a subgroup of low-risk breast cancer patients having distinct metabolic profiles suggestive of a preference for aerobic respiration. The association of lactic acidosis response with good survival outcomes may relate to the role of lactic acidosis in directing energy generation toward aerobic respiration and utilization of other energy sources via inhibition of glycolysis. This “inhibition of glycolysis” phenotype in tumors is likely caused by the repression of glycolysis gene expression and Akt inhibition. Our study presents a genomic evaluation of the prognostic information of a lactic acidosis response independent of the hypoxic response. Our results identify causal roles of lactic acidosis in metabolic reprogramming, and the direct functional consequence of lactic acidosis pathway activity on cellular responses and tumor development. The study also demonstrates the utility of genomic analysis that maps expression-based findings from in vitro experiments to human samples to assess links to in vivo clinical phenotypes