Single cell analysis is crucial for understanding how cancer cells respond to drugs because drug responses are inherently asynchronous and transformed cells are both genetically and epigenetically heterogeneous. While single cell RNA-Seq is emerging as a high-dimensional and increasingly scalable tool for assessing phenotypic heterogeneity, many aspects of cellular phenotype cannot be inferred from the transcriptome alone. However, if we can combine single cell imaging and RNA-Seq on a large-scale, then we can take advantage of high-content imaging assays with access to numerous phenotypic observables for cellular metabolism, protein localization, translation, cell cycle, and cell signalng with single cell resolution. Existing tools for merging single cell imaging and sequencing are expensive, low-throughput, and incompatible with short-term cell culture and stimulation. Here, we will address this issue by combining our highly scalable microfluidic platform for single cell RNA-Seq and imaging with a novel barcoding strategy that will allow us to associate sequence barcodes in a pooled library with optical barcodes in our device. Quantitative studies will be carried out to validate our integrated platform for single cell drug stimulation, imaging, and RNA-Seq on several cancer cell lines with compounds used in both targeted and cytotoxic therapies.
Cancer cells respond heterogeneously to drugs, and as a result, targeted and cytotoxic therapies cannot completely eliminate tumor cells in many types of cancer. We are developing a platform for large-scale imaging and expression profiling of individual cancer cells so that we can better understand the mechanisms underlying drug resistance.
| Yuan, Jinzhou; Sheng, Jenny; Sims, Peter A (2018) SCOPE-Seq: a scalable technology for linking live cell imaging and single-cell RNA sequencing. Genome Biol 19:227 |
| Yuan, Jinzhou; Sims, Peter A (2016) An Automated Microwell Platform for Large-Scale Single Cell RNA-Seq. Sci Rep 6:33883 |
