Differential determinants of cancer cell insensitivity to anti-mitotic drugs discriminated by a one-step cell imaging assay
Yangzhong Tang1,5, Tiao Xie1,2,5, Stefan Florian1, Nathan Moerke1, Caroline Shamu1,3, Cyril Benes4, and Timothy J. Mitchison1
1 HMS LINCS Center, Harvard Medical School, Boston, MA; 2 Image and Data analysis Core (IDAC), Harvard Medical School, Boston, MA; 3 ICCB-Longwood Screening Facility, Harvard Medical School, Boston, MA; 4 Massachusetts General Hospital Cancer Center, Harvard Medical School, Charlestown MA; 5 These authors contributed equally.
Discriminating different mechanisms that compromise drug sensitivity in cells in culture requires multiplexed readout of response, which is often accomplished using mRNA profiling, multiplexed gene expression reporters, and high-content imaging assays. These assays can be highly informative but typically are costly and complex. Furthermore, it can be difficult to infer alternative mechanistic effects on drug response pathways from gene expression and other multiplex readouts where the relationship between readout and drug response pathway is complex. Here, we describe a new one-step, no-wash imaging assay that uses three dyes (Hoechst33342, LysoTracker-Red, and DEVD-NucView488) to stain living cells and enables measurement of multiple physiological changes in cells related to mitotic and apoptotic status following treatment with anti-mitotic small molecule drugs. A step-by-step description of the assay also was published in Tang (2014)1.
- A new one-step, no-wash imaging assay scores mitotic arrest and apoptotic state in live cells following perturbagen treatment.
- The assay is considerably more accurate for scoring weakly adherent mitotic and apoptotic cells than conventional antibody-based assays.
- The response profiles generated by this assay for 33 cell lines treated with 8 anti-mitotic drugs at multiple concentrations and time points are publicly available in the HMS LINCS Database.
- Together these data comprise a pharmacological response signature that discriminates alternative mechanisms of compromised drug sensitivity to Paclitaxel and reveal an unexpected dose-response profile for a Polo-like kinase inhibitor.
Cancer cells can be drug resistant due to genetic variation at multiple steps in the drug response pathway, including drug efflux pumping, target mutation, and blunted apoptotic response. These are not discriminated by conventional cell survival assays. Here, we report a rapid and convenient high-content cell-imaging assay that measures multiple physiological changes in cells responding to antimitotic small-molecule drugs. Our one-step, no-wash assay uses three dyes to stain living cells and is much more accurate for scoring weakly adherent mitotic and apoptotic cells than conventional antibody-based assays. We profiled responses of 33 cell lines to 8 antimitotic drugs at multiple concentrations and time points using this assay and deposited our data and assay protocols into a public database (http://lincs.hms.harvard.edu/). Our data discriminated between alternative mechanisms that compromise drug sensitivity to paclitaxel and revealed an unexpected bell-shaped dose-response curve for BI2536, a highly selective inhibitor of Polo-like kinases. Our approach can be generalized, is scalable, and should therefore facilitate identification of molecular biomarkers for mechanisms of drug insensitivity in high-throughput screens and other assays.
Explore the data
We encourage readers to explore the findings and the data underlying this study as well as data from several related studies that use similar imaging-based methodologies to measure cell proliferation and mitotic and apoptotic state. Through the links below, readers can access the original datasets containing raw images and cell state metrics as well as the software for the image-analysis algorithm used in this study.
Available data and software
|Data||All raw imaging data and mitotic and apoptotic metrics reported in this study and measured using a 3-dye imaging assay across 12 doses for 8 drugs in 33 cell lines at 3 timepoints (HMS Dataset #20003).||Details||Download (.xls)|
|Software||A link to Tiao Xie’s GitHub to download the custom MATLAB image-analysis algorithm used in this study.||algorithm at GitHub|
|Data||Related dataset: All raw imaging data and proliferation and mitotic metrics measured using an EdU- and antibody-based imaging assay across 13 doses for 8 drugs in 17 cell lines at 3 timepoints (HMS Dataset #20004).||Details||Download (.xls)|
|Data||Related dataset: All raw imaging data and apoptotic metrics measured using a 2-color imaging assay across 13 doses for 8 drugs in 12 cell lines at 3 timepoints (HMS Dataset #20001).||Details||Download (.xls)|
|Data||Related dataset: All raw imaging data and apoptotic metrics measured using a 3-color imaging assay across 13 doses for 8 drugs in 12 cell lines at 3 timepoints (HMS Dataset #20002).||Details||Download (.xls)|
NIH LINCS grant U54 HG006097
1. Tang, Y. (2014) A one-step imaging assay to monitor cell cycle state and apoptosis in mammalian cells. Curr Protoc Chem Biol 6(1):1-5. doi:10.1002/9780470559277.ch130140 PMID:24652619 PMCID:PMC4016950