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Molecular Cancer Therapeutics
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Research Articles: Therapeutics, Targets, and Development

High-content imaging characterization of cell cycle therapeutics through in vitro and in vivo subpopulation analysis

Jonathan Low, Shuguang Huang, Wayne Blosser, Michele Dowless, John Burch, Blake Neubauer and Louis Stancato
Jonathan Low
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Shuguang Huang
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Wayne Blosser
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Michele Dowless
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John Burch
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Blake Neubauer
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Louis Stancato
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DOI: 10.1158/1535-7163.MCT-08-0328 Published August 2008
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    Figure 1.

    Well-level analysis of HeLa cell cycle progression. HeLa cells were synchronized by blocking DNA replication in early S phase. The cells were released from arrest and followed as they progressed through the cell cycle. The changes in the well-level averages of six phenotypic markers as the cells progressed through one replication cycle are displayed. All values are expressed as a ratio compared with HeLa cells arrested at the G1-S transition. Right, BrdUrd incorporation ratio; left, all others.

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    Figure 2.

    Multiparametric analysis defines subpopulations in each cell cycle compartment. The panels above were generated from the same experiment using the six variables shown in Fig. 1. The heatmaps above were created by clustering the data from each individual cell and sorting each cluster based on the total DNA intensity of the nucleus. The numbers on the left side of each heatmap denote the fraction of cells in each cluster. Distinct phenotypic fingerprints for asynchronous cells (A) and synchronized cells containing a major subpopulation showing a phenotype of cells at G1-S (B), S phase (C), G2 (D), mitosis (E), or G1 (F) are illustrated. Total, average, and variation represent total DNA intensity, average DNA intensity, and variation of DNA intensity, respectively. Red lines to the side of each heatmap denote the cluster of interest.

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    Figure 3.

    Subclustering major cell cycle compartments. Subclustering subpopulations formed from the initial analysis further distinguishes phenotypic populations. Two major S-phase clusters were detected on clustering cells with a S-phase phenotype corresponding to early and late S phase (A). All four major mitotic clusters were distinguished by subclustering two mitotic clusters (B). Prophase, metaphase, anaphase, and telophase were easily differentiated with distinct phenotypes.

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    Figure 4.

    Key of cell cycle phenotypes and subpopulation heatmaps. Images were taken of each major cell cycle and mitotic phase at ×80 under standard HCI staining conditions (A). Green fluorescence, BrdUrd incorporation; red fluorescence, pHH3 expression. Heatmaps for cells at each stage of the cell cycle quantify the phenotypic differences found in these images (B).

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    Figure 5.

    Compound treatments generate distinct and distinguishable phenotypes. HeLa cells were treated with the well-characterized agents nocodazole (125 nmol/L), paclitaxel (31 nmol/L), gemcitabine (62 nmol/L), and doxorubicin (125 nmol/L) to determine if arrest caused by compounds generated phenotypes similar to those in untreated cells (A). Cells were exposed to compounds for 48 h before exposure to BrdUrd, fixation, and marker detection. Nocodazole and paclitaxel generated phenotypes matching mitosis, whereas gemcitabine and doxorubicin produced S-phase phenotypes. HeLa cells were treated as above with the commercially available herboxidiene (1.67 μmol/L), methotrexate (185 nmol/L), raltitrexed (185 nmol/L), and TAS-102 (1.67 μmol/L; B). All four of these compounds created S-phase arrest phenotypes but can be distinguished phenotypically due to differences in arrest mechanism. p388 cells were treated with the mitotic agent vincristine in culture (20 nmol/L) or 72 h after inoculation into BDF1 mice (3.75 mg/kg). Cells were treated with vincristine or vehicle alone for 24 h before exposure to BrdUrd, fixation, and cell cycle marker detection (C). Treatment with vincristine generates similar phenotypes under both conditions.

Tables

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  • Table 1.

    Effects of 310 potential oncology compounds on the stage of cell cycle arrest

    PhenotypeNo. treatments with phenotype
    Death21
    Death-S10
    Death-G21
    Death-M5
    G1-S1
    S25
    M10
    No effect237
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Molecular Cancer Therapeutics: 7 (8)
August 2008
Volume 7, Issue 8
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High-content imaging characterization of cell cycle therapeutics through in vitro and in vivo subpopulation analysis
Jonathan Low, Shuguang Huang, Wayne Blosser, Michele Dowless, John Burch, Blake Neubauer and Louis Stancato
Mol Cancer Ther August 1 2008 (7) (8) 2455-2463; DOI: 10.1158/1535-7163.MCT-08-0328

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High-content imaging characterization of cell cycle therapeutics through in vitro and in vivo subpopulation analysis
Jonathan Low, Shuguang Huang, Wayne Blosser, Michele Dowless, John Burch, Blake Neubauer and Louis Stancato
Mol Cancer Ther August 1 2008 (7) (8) 2455-2463; DOI: 10.1158/1535-7163.MCT-08-0328
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Molecular Cancer Therapeutics
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