To study cancer, very powerful modern experimental methods ~ including high-throughput approaches ~, and modern statistics/computer-science methods are now used. Mechanistic quantitative models of cancer timedevelopment, from very early stages to clinical disease, have been somewhat less well explored. A highly interdisciplinary, unusually closely interacting team of cancer biologists, molecular biologists, mathematicians, physicists, and computer scientists has been assembled to work toward dynamic, mechanistic carcinogenesis models so parsimoniously parameterized they have predictive capability. The overriding goal is to make the models more realistic and credible by taking into account the influence of intercellular interactions during carcinogenesis. The time-course of effects involving a diverse, interacting cell population and/or of tumor progression, a comparatively late stage in the lengthy cancer latency period, will be emphasized. The phenomena of microscopic tumor dormancy, recently found to be almost ubiquitous in humans, and of emergence from dormancy due to "switching on" of blood supply recruitment will be one main focus. The team will work under an iterative paradigm: experiments a mathematical/computational model a experiments, etc. Data will be gathered from various sources: in vitro experiments, including modern high throughput results and in depth studies of particular proteins;experiments using genetically engineered mice;highly developed imaging approaches;and results in the literature on human cancer incidence or mortality. Several ofthe individual projects will involve ionizing radiation, a carcinogen whose action has been unusually well characterized at very small time and length scales, as well as over a whole human lifetime and for whole organisms, so that it is highly informative about cancer development in general. Mathematical methods will include the following: classic mathematical biology approaches with systems of ordinary or partial differential equations;modern discrete and hybrid discrete-continuous models based on treating many cells, each represented as an entity which can interact with other cells and with its microenvironment according to comparatively simple rules, with complicated wholesystem behavior arising from those rules;probabilistic "stochastic-process" models, needed since most new stages of cancer evolution putatively originate with a single cell, at risk for eradication or accidental extinction;and multi time-scale computational modeling, in which effects governed by comparatively very short time scales influence much longer time-scale cancer evolution and vice-versa.
With about 1.5 million new cancer cases per year in the U.S. preventing, curing, or managing cancer has high priority. The approach most promising in the long run is to develop quantitative, mechanistic, predictive human carcinogenesis models. It is now clear that such models require more attention to intercellular interactions and to systems biology than has been given in earlier approaches emphasizing time-development of a single somatic cell lineage evolving almost autonomously toward cancer. The proposed ICBP team, due to its comprehensive interdisciplinary nature and longstanding expertise in the specific areas needed to develop such models is well placed to help carry out that task.
|Gao, Xuefeng; Sishc, Brock J; Nelson, Christopher B et al. (2016) Radiation-Induced Reprogramming of Pre-Senescent Mammary Epithelial Cells Enriches Putative CD44(+)/CD24(-/low) Stem Cell Phenotype. Front Oncol 6:138|
|Benzekry, Sebastien; Beheshti, Afshin; Hahnfeldt, Philip et al. (2015) Capturing the Driving Role of Tumor-Host Crosstalk in a Dynamical Model of Tumor Growth. Bio Protoc 5:|
|Wage, Justin; Ma, Lili; Peluso, Michael et al. (2015) Proton irradiation impacts age-driven modulations of cancer progression influenced by immune system transcriptome modifications from splenic tissue. J Radiat Res 56:792-803|
|Kareva, Irina; Waxman, David J; Lakka Klement, Giannoula (2015) Metronomic chemotherapy: an attractive alternative to maximum tolerated dose therapy that can activate anti-tumor immunity and minimize therapeutic resistance. Cancer Lett 358:100-6|
|Radivoyevitch, Tomas; Siranart, Nopphon; Hlatky, Lynn et al. (2015) Stochastic process pharmacodynamics: dose timing in neonatal gentamicin therapy as an example. AAPS J 17:447-56|
|Beheshti, Afshin; Wage, Justin; McDonald, J Tyson et al. (2015) Tumor-host signaling interaction reveals a systemic, age-dependent splenic immune influence on tumor development. Oncotarget 6:35419-32|
|Benzekry, Sebastian; Tuszynski, Jack A; Rietman, Edward A et al. (2015) Design principles for cancer therapy guided by changes in complexity of protein-protein interaction networks. Biol Direct 10:32|
|Pellicciotta, Ilenia; Marciscano, Ariel E; Hardee, Matthew E et al. (2015) Development of a novel multiplexed assay for quantification of transforming growth factor-Î² (TGF-Î²). Growth Factors 33:79-91|
|Beheshti, Afshin; Benzekry, SÃ©bastien; McDonald, J Tyson et al. (2015) Host age is a systemic regulator of gene expression impacting cancer progression. Cancer Res 75:1134-43|
|Beheshti, Afshin; Peluso, Michael; Lamont, Clare et al. (2014) Proton irradiation augments the suppression of tumor progression observed with advanced age. Radiat Res 181:272-83|
Showing the most recent 10 out of 50 publications