Studying Multiscale Probabilistic and Deterministic Models for the Annotation of Cellular Networks and Tumor Metastases

Comprehensive modeling of the complex behavior of cellular networks during cellular reprogramming or during tumor metastasis, has become possible by integration of different biological scales into a multiscale model. Typically, these multiscale models combine probabilistic and deterministic aspects of cellular behavior. In this paper, a review is given of modeling studies of the group of NSCLC (non-small cell lung cancers), which has a rather amalgamative appearance. Due to the heterogenous genetic background and poor predictability of divergent pathological processes, the prognosis of NSCLC to date is still very poor. The role of two important phenotypic markers, namely the TTF1 (thyroid trancription factor 1) and EGFR (epidermal growth factor receptor), are discussed with respect to disease progression, migration and metastasis potential. A strategy for introducing the cell survival perspective in tumor expansion modeling is discussed in combination with visualization techniques based on cell-state modeling, similar to cell-state modeling in reprogramming studies.