Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

Cellular dynamic simulator: an event driven molecular simulation environment for cellular physiology.

In this paper, we present the Cellular Dynamic Simulator (CDS) for simulating diffusion and chemical reactions within crowded molecular environments. CDS is based on a novel event driven algorithm specifically designed for precise calculation of the timing of collisions, reactions and other events for each individual molecule in the environment. Generic mesh based compartments allow the creation / importation of very simple or detailed cellular structures that exist in a 3D environment. Multiple levels of compartments and static obstacles can be used to create a dense environment to mimic cellular boundaries and the intracellular space. The CDS algorithm takes into account volume exclusion and molecular crowding that may impact signaling cascades in small sub-cellular compartments such as dendritic spines. With the CDS, we can simulate simple enzyme reactions; aggregation, channel transport, as well as highly complicated chemical reaction networks of both freely diffusing and membrane bound multi-protein complexes. Components of the CDS are generally defined such that the simulator can be applied to a wide range of environments in terms of scale and level of detail. Through an initialization GUI, a simple simulation environment can be created and populated within minutes yet is powerful enough to design complex 3D cellular architecture. The initialization tool allows visual confirmation of the environment construction prior to execution by the simulator. This paper describes the CDS algorithm, design implementation, and provides an overview of the types of features available and the utility of those features are highlighted in demonstrations.

Tumor heterogeneity dictates sensitivity to gefitinib (Iressa(TM)/ZD1839) in solid tumor models

The epidermal growth factor receptor (EGFR) and its ligands are overexpressed in many human tumors, including bladder and pancreas, correlating with a more aggressive tumor phenotype and poor patient prognosis. We initiated the present study to characterize the heterogeneity of gefitinib responsiveness in a panel of human bladder and pancreatic cancer cell lines in order to identify the biological characteristics of EGFR-dependent proliferation that could be used to prospectively identify drug-sensitive tumors. A second objective was to elucidate how to best exploit these results by utilizing gefitinib in combination therapy. To these ends, we examined the effects of the EGFR antagonist gefitinib on proliferation and apoptosis in a panel of 18 human bladder cancer cell lines and 9 human pancreatic cancer cell lines. Our data confirmed the existence of marked heterogeneity in Iressa responsiveness with less than half of the cell lines displaying significant growth inhibition by clinically relevant concentrations of the drug. Gefitinib responsiveness was found to be p27 kip1 dependent as DNA synthesis was restored following exposure to p27siRNA. Unfortunately, Iressa responsiveness was not closely linked to surface EGFR or TGF-α expression in the bladder cancer cells, however, cellular TGF-α expression correlated directly with Iressa sensitivity in the pancreatic cancer cell lines. These findings provide the potential for prospectively identifying patients with drug-sensitive tumors. ^ Further studies aimed at exploiting gefitinib-mediated cell cycle effects led us to investigate if gefitinib-mediated TRAIL sensitization correlated with increased p27kip1 accumulation. We observed that increased TRAIL sensitivity following gefitinib exposure was not dependent on p27 kip1 expression. Additional studies initiated to examine the role(s) of Akt and Erk signaling demonstrated that exposure to PI3K or MEK inhibitors significantly enhanced TRAIL-induced apoptosis at concentrations that block target phosphorylation. Furthermore, combinations of TRAIL and the PI3K or MEK inhibitors increased procaspase-8 processing above levels observed with TRAIL alone, indicating that the effects were exerted at the level of caspase-8 activation, considered the earliest step in the TRAIL pathway. ^

The mechanism of action of a novel benzo[c]phenanthridine alkaloid, NK314 and the cellular responses

NK314 is a novel synthetic benzo[c]phenanthridine alkaloid that is currently in clinical trials as an antitumor compound, based on impressive activities in preclinical models. However, its mechanism of action is unknown. The present investigations were directed at determining the mechanism of action of this agent and cellular responses to NK314. My studies demonstrated that NK314 intercalated into DNA, trapped topoisomerase IIα in its cleavage complex intermediate, and inhibited the ability of topoisomerase IIα to relax super-coiled DNA. CEM/VM1 cells, which are resistant to etoposide due to mutations in topoisomerase IIα, were cross-resistant to NK314. However, CEM/C2 cells, which are resistant to camptothecin due to mutations in topoisomerase I, retained sensitivity. This indicates topoisomerase IIα is the target of NK314 in the cells. NK314 caused phosphorylation of the histone variant, H2AX, which is considered a marker of DNA double-strand breaks. DNA double-strand breaks were also evidenced by pulsed-field gel electrophoresis and visualized as chromosomal aberrations after cells were treated with NK314 and arrested in mitosis. Cell cycle checkpoints are activated following DNA damage. NK314 induced significant G2 cell cycle arrest in several cell lines, independent of p53 status, suggesting the existence of a common mechanism of checkpoint activation. The Chk1-Cdc25C-Cdk1 G2 checkpoint pathway was activated in response to NK314, which can be abrogated by the Chk1 inhibitor UCN-01. Cell cycle checkpoint activation may be a defensive mechanism that provides time for DNA repair. DNA double-strand breaks are repaired either through ATM-mediated homologous recombination or DNA-PK-mediated non-homologous end-joining repair pathways. Clonogenic assays demonstrated a significant decrease of colony formation in both ATM deficient and DNA-PK deficient cells compared to ATM repleted and DNA-PK wild type cells respectively, indicating that both ATM and DNA-PK play important roles in the survival of the cells in response to NK314. The DNA-PK specific inhibitor NU7441 also significantly sensitized cells to NK314. In conclusion, the major mechanism of NK314 is to intercalate into DNA, trap and inhibit topoisomerase IIα, an action that leads to the generation of double-strand DNA breaks, which activate ATM and DNA-PK mediated DNA repair pathways and Chk1 mediated G2 checkpoint pathway. ^