(180c) Combined Experimental and Computational Approach to Elucidating the Effects of Cellular Proliferation On Gene Transfer Efficiency

Cellular proliferation plays determining roles in gene delivery and it has been speculated that transfecting (or transducing) actively dividing cells by most gene vectorswould be much more efficient than quiescent cells. For example, retroviral vectors can transduce only actively dividing (mitotic) cells, which makes them a poor gene carrier in vivo where cells do not rapidly proliferate. Quantitative gene transfer efficiency of both viral and nonviral vectors to the cells under heterogeneous proliferation conditions (like in the body) has not been fully elucidated. In addition, usually gene transfer efficiency cannot be quantified until cells express transgene, requiring post-transfection (or transduction) incubation; therefore, overall gene delivery efficiency at a certain post-transfection (or transduction) time could be highly over- or under-estimated. Quantitatively understanding the above-mentioned parameters cannot be achieved by experiments alone. A431 human epithelial carcinoma and T98G human glioblastoma cells were cultured to form colonies where different levels of contact inhibition forces are applied, depending on locations. The cells toward the center of the colony no longer are able to divide in the confined area, while the cells in periphery actively spread and proliferate. A computer-simulated stochastic cell growth model was utilized to fit experimental cell growth kinetics. By employing gene expression rates collected at various post-tranfection (or transduction) time points as well as the simulated model, the specific gene transfer rate to actively dividing and non-dividing cells at the time of transfection (or transduction) were also determined. The results demonstrated that contact inhibition did have a dramatic effect on the level of gene transfer efficiency of retroviral, lentiviral, adenoviral, adeno-associated viral, and nonviral vectors; however, this effect varied significantly among the various vectors. For example, surprisingly, adenovirus transduced the non-dividing cells more efficiently than dividing ones. The results of this study indicate that a stochastic cell growth model in combination with experimentally determined gene transfer efficiencies is a useful tool in obtaining insightful findings that could provide new paradigms in developing efficient vectors for gene therapy.