title: Computational challenges of tumor spheroid modeling.
abstract: The speed and the versatility of today's computers open up new opportunities to simulate complex biological systems. Here we review a computational approach recently proposed by us to model large tumor cell populations and spheroids, and we put forward general considerations that apply to any fine-grained numerical model of tumors. We discuss ways to bypass computational limitations and discuss our incremental approach, where each step is validated by experimental observations on a quantitative basis. We present a few results on the growth of tumor cells in closed and open environments and of tumor spheroids. This study suggests new ways to explore the initial growth phase of solid tumors and to optimize antitumor treatments.
authors.affiliation: Dipartimento di Biotecnologie, Università di Verona, and INFN - Sezione di Trieste, Strada le Grazie 15-CV1, I-37134 Verona, Italia. roberto.chignola@univr.it
authors.forename: Roberto
authors.initials: R
authors.lastname: Chignola
authors.forename: Alessio Del
authors.initials: AD
authors.lastname: Fabbro
authors.forename: Marcello
authors.initials: M
authors.lastname: Farina
authors.forename: Edoardo
authors.initials: E
authors.lastname: Milotti
mesh_terms: D000818:Animals; D049109:Cell Proliferation; D019295:Computational Biology; D006801:Humans; D053858:Metabolic Networks and Pathways; D008954:Models, Biological; D009369:Neoplasms / Q000378:metabolism / Q000473:pathology*; D018874:Spheroids, Cellular / Q000378:metabolism / Q000473:pathology*; D049490:Systems Biology; D014407:Tumor Cells, Cultured; D059016:Tumor Microenvironment