Detecting cell growth and drug response in heterogeneous populations: A dynamic imaging approach
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2016 IEEE. Tumor heterogeneity has been increasingly recognized as one of the potentially contributing factors in explaining drug resistance. In order to gain better understanding of heterogeneous cancer cell populations and different cells' responses to various drugs, we use fluorescent proteins to mark the cells and a live-cell dynamic imaging platform to collect cell-by-cell measurements. After addressing the issue of fluorescent reporter variance in a Bayesian inference framework, we decompose the different cell types in the mixture and calculate their proportions and counts over time responding to different drug treatments. Additionally, the drug response as characterized by the cell death rate was also computed for these cells, and their different sensitivity was demonstrated. Overall, this work represents an important advancement toward evaluating cancer heterogeneity and drug responses in heterogeneous cancer cell populations.
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2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)