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.

Repression of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) but not its receptors during oral cancer progression.

BACKGROUND: TRAIL plays an important role in host immunosurveillance against tumor progression, as it induces apoptosis of tumor cells but not normal cells, and thus has great therapeutic potential for cancer treatment. TRAIL binds to two cell-death-inducing (DR4 and DR5) and two decoy (DcR1, and DcR2) receptors. Here, we compare the expression levels of TRAIL and its receptors in normal oral mucosa (NOM), oral premalignancies (OPM), and primary and metastatic oral squamous cell carcinomas (OSCC) in order to characterize the changes in their expression patterns during OSCC initiation and progression. METHODS: DNA microarray, immunoblotting and immunohistochemical analyses were used to examine the expression levels of TRAIL and its receptors in oral epithelial cell lines and in archival tissues of NOM, OPM, primary and metastatic OSCC. Apoptotic rates of tumor cells and tumor-infiltrating lymphocytes (TIL) in OSCC specimens were determined by cleaved caspase 3 immunohistochemistry. RESULTS: Normal oral epithelia constitutively expressed TRAIL, but expression was progressively lost in OPM and OSCC. Reduction in DcR2 expression levels was noted frequently in OPM and OSCC compared to respective patient-matched uninvolved oral mucosa. OSCC frequently expressed DR4, DR5 and DcR1 but less frequently DcR2. Expression levels of DR4, DR5 and DcR1 receptors were not significantly altered in OPM, primary OSCC and metastatic OSCC compared to patient-matched normal oral mucosa. Expression of proapoptotic TRAIL-receptors DR4 and DR5 in OSCC seemed to depend, at least in part, on whether or not these receptors were expressed in their parental oral epithelia. High DR5 expression in primary OSCC correlated significantly with larger tumor size. There was no significant association between TRAIL-R expression and OSSC histology grade, nodal status or apoptosis rates of tumor cells and TIL. CONCLUSION: Loss of TRAIL expression is an early event during oral carcinogenesis and may be involved in dysregulation of apoptosis and contribute to the molecular carcinogenesis of OSCC. Differential expressions of TRAIL receptors in OSCC do not appear to play a crucial role in their apoptotic rate or metastatic progression.