Three-kinase inhibitor combination recreates multipathway effects of a geldanamycin analogue on hepatocellular carcinoma cell death

A dynamic signaling time course reveals differences between Hep3B and Huh7. A, a signaling time course in Hep3B and Huh7 cells depicts mean fold changes in phosphoprotein signaling in response to 1 μmol/L 17AAG relative to the vehicle only (0.1% methanol) control. B, the integral (discussed in Materials and Methods) from 0 to 4 h of 17AAG-induced signaling shows large cumulative differences in early signaling between Huh7 and Hep3B cells.

A PCA reduces data complexity and provides testable hypotheses. A, percentage of the total variance captured by a model consisting of one, two, or three principal components. There is a marginal increase in the benefit of including principal component 3, indicating an obvious cutoff criterion. B, percentage of total variance explained by two-component models that are built on 1,000 perturbed data matrices (see Materials and Methods). A histogram plots the data from the empirical 1,000 matrix sampling. A normal distribution was fit to the histogram data, and our model fit was calculated to have a highly significant P value of 0.0002. C, a PCA yielded a two-component model that accurately explains 91% of the cumulative variance. PC1 strongly captures variation at early time points and in the 0- to 4-h integral metric. PC2 captures variation at 24 h. These results from the loadings plot are summarized in the upper right-hand corner of the plot. The ellipse represents Hotelling's outlier criteria at a 95% confidence level. The original signaling measurements are plotted in the principal components space. PC1 visually seems to capture cell line variation. The colored ellipses are simply a visualization tool used to bring the readers attention to the distinct clusters in the scores plot. D, contributions vectors describe how signals vary in principal components space and are derived computationally by measuring the latent variable distance in terms of the Euclidean distance of the measured variables between Huh7 and Hep3B for a given signal and then comparing that distance to an average distance of all the distances between the cell lines (in units of SD). This plot asks the question of how distinct are two signals between Huh7 and Hep3B cells relative to the average distance between lines. Quantitatively, D affirms qualitative observations made in C.

Adding signaling data from another HCC cell line (FOCUS) to the PCA correctly clusters FOCUS cells with sensitive Hep3B cells. A, mean of triplicate measurements of the percentage of double-positive FOCUS cells in response to 1 μmol/L 17AAG at 48 h. The gating strategy was the same as in Fig. 1A. B, signaling time course of FOCUS cells in response to 1 μmol/L 17AAG. Time point measurements are represented as mean signaling fold change relative to vehicle only controls. C, a principal components scores plot, as in Fig. 3, correctly classifies FOCUS cell phosphoprotein signaling measurements as homologous to 17AAG-sensitive Hep3B cells in the two-component model.

Where inhibition of singular nodes fails, pretreatment with a combination therapy sensitizes Huh7 cells to 17AAG and works as well or better than 17AAG in all cell lines tested. A, double-positive populations of Huh7 cells (mean of triplicate ± SE as gated in Fig. 1A) in response to different treatments at 48 h. The IKK inhibitor BMS-345541 was used at 15 μmol/L, the PI3K inhibitor PI103 was used at 5 μmol/L, and the JAK inhibitor JAK inhibitor 1, pyridone 6, was used at 3 μmol/L. The P values were obtained by a t test. B, double-positive populations for the listed treatments of Hep3B and FOCUS cells at 48 h. Columns, mean of triplicates; bars, SE. The P values were obtained by a t test. The drug combination is the same as in A.