Gene Expression Profiling and Pathway Network Analysis Predicts a Novel Antitumor Function for a Botanical-Derived Drug, PG2

Figure 2

Scatter-plot matrix and correlation map with hierarchical clustering analysis show similarities between PG2 samples. (a) Scatter-plot matrix using all 54,675 probe sets for the gene expression profiles of HL-60 cells treated with PG2, 15-delta prostaglandin J2 (15d-PGJ2), clopidogrel, Vitis ficifolia var. taiwaniana (EH), Antrodia Camphorata (Ac9), and etoposide. All of the PG2 samples have very similar gene expression profiles because most of the data points fall very close to the 45° line. (b) The Pearson product-moment correlation matrix between the 16 samples, using relative expression for all 54,675 probe sets, is displayed by the GAP environment and sorted by the HCT_R2E algorithm. Both the sorted correlation matrix map and the dendrogram branching structure clearly indicate that all of the 11 PG2 samples form a cluster relative to the other samples. (c) The correlation plot of the first two components from the principal component analysis (PCA) of the same data reconfirms the findings in (b). (d) Three matrix maps (expression profile matrix (i), sample correlation matrix (ii), and gene correlation matrix (iii)) were calculated for the relative expression profile of 14 samples (3 vehicles and 11 PG2) with 646 upregulated genes and 465 downregulated genes, sorted and displayed by the GAP environment with the R2E (rank-two elliptical seriation) algorithm. The interaction pattern of the two sample groups (vehicle and PG2) on the two clear gene clusters (up- and downregulated genes) suggests that the PG2 signature is a well-defined gene set that can be used to analyze PG2.

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