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RNAi-based molecular computing for cancer cell detection

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If you have a question about this talk, please contact Florian Markowetz .

Engineered biological systems that integrate multi-input sensing, sophisticated information processing, and precisely regulated actuation in living cells could be useful in a variety of applications. For example, anticancer therapies could be engineered to detect and respond to complex cellular conditions in individual cells with high specificity.

A few years ago we proposed a geenral-purpose approach to logic signal integration in mammalian cells using RNA interference. More recently, we applied these ideas to design a scalable transcriptional/posttranscriptional synthetic regulatory circuit-a cell-type “classifier”-that senses expression levels of a customizable set of endogenous microRNAs and triggers a cellular response only if the expression levels match a predetermined profile of interest. We demonstrate that a HeLa cancer cell classifier selectively identifies HeLa cells and triggers apoptosis without affecting non-HeLa cell types. This approach also provides a general platform for programmed responses to other complex cell states.

This talk is part of the Seminars on Quantitative Biology @ CRUK Cambridge Institute series.

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