Development of an in vitro three-dimensional model for colon cancer study and drug efficacy analysis.

摘要

Colon cancer is the second most deadly cancer with 56,000 deaths estimated in the United States for 2005. The staggering average cost of developing drug therapies to the market exceeds ;The preparation of the cancer model included scaffold treatment, cell counting method analyses, and cell seeding optimization. The fibrous scaffold, poly(ethylene terephthalate) (PET), was compressed, producing scaffold porosities ranging from 0.94 to 0.84, and treated to reduce surface hydrophobicity. The direct counting method of enzymatic detachment of cells was useful for relative counts, but the developed fluorescent model was optimal, providing accurate and noninvasive counts in the 3-D environment. Dynamic and filter seeding provided superior cell distributions and seeding rates compared to static seeding. High porosity (0.94) and treated PET had the highest attachment rate.;The colon cancer cell line, HT-29, was grown in plates on PET of four combinations of two porosities (0.94 and 0.88) and pretreatment status. Whereas cell growth was fastest in high porosity and treated PET, the low porosity and treated PET culture showed significant population growth and developed a 3-D morphology due to smaller interfiber distances. Growth within mixed spinner flask and perfusion bioreactor environments improved the aerobic conditions within the PET and sustained higher cell densities.;Two anti-cancer drugs were utilized to determine the effectiveness of the 3-D colon cancer model in predicting drug efficacy. The 3-D, low porosity PET model was more and less sensitive to 5-fluorouracil and gemcitabine, respectively, than 3-D high porosity and currently-utilized 2-D cultures were, accurately predicting their actual colon cancer efficacies. A 3-D model with transfected green fluorescent protein correlated fluorescence signals with cytotoxic effects, providing a convenient and fast method for screening drug cytotoxicity. Application of the 3-D model can be expanded to other candidate drug therapies.