Distinguishing between genotoxic and non-genotoxic hepatocarcinogens by gene expression profiling and bioinformatic pathway analysis

Abstract

A rapid and sensitive method to determine the characteristics of carcinogens is needed. In this study, we used a microarray-based genomics approach, with a short-term in vivo model, in combination with insights from statistical and mechanistic analyses to determine the characteristics of carcinogens. Carcinogens were evaluated based on the different mechanisms involved in the responses to genotoxic carcinogens and non-genotoxic carcinogens. Gene profiling was performed at two time points after treatment with six training and four test carcinogens. We mapped the DEG (differentially expressed gene)-related pathways to analyze cellular processes, and we discovered significant mechanisms that involve critical cellular components. Classification results were further supported by Comet and Micronucleus assays. Mechanistic studies based on gene expression profiling enhanced our understanding of the characteristics of different carcinogens. Moreover, the efficiency of this study was demonstrated by the short-term nature of the animal experiments that were conducted.

Figure 1. Schematic outline of the research protocol.

Figure 2. PCA (Principal Component Analysis).

The results are depicted 3-dimensionally with PC1 (35%), PC2 (12%) and PC3 (7%) as the X, Y and Z axes, respectively. Each color represents a different compound in single and multiple treatments, and one chip data are shown as a large circle, with 41 training data points on the graph. The data before the statistical analysis show no gathering between the GTX and NGTX groups; therefore, a selection process to detect the significant gene is needed. Only DL-ethionine (multiple), light blue, showed a different PC2 value from the other data; this was found when interpreting the results after the statistical analysis.

Figure 3. DEG (differentially expressed gene) heat map and hierarchical clustering results distinguishing GTX from NGTX compounds.

These data are from the training set of three GTX (G; 2-AAF, DEN, MeDAB), three NGTX (N; clofibrate, dioxane, DL-ethionine) carcinogens and the test set of four unknown carcinogens (T; DCP, methyleugenol, sodium nitrite, urethane). The expression patterns for the DEGs selected from the overall heat map on the left side are shown in color. The red color represents high expression and the blue color low expression, within the −2.9~2.9 (Figure 3A) and −3.5~3.5 (Figure 3B) ranges, respectively. The magnified section on the right shows parts of DEG lists and hierarchical clustering results of the upper part. (a): single-treatment results, (b): multiple-treatment results.

Figure 4. Pathway mapping among DEGs.

Each entity represents a protein transcribed from the selected DEG, and the arrows indicate the connections. (a) DEG pathway analysis results between GTX carcinogens and NGTX carcinogens in single treatment. (b) DEG pathway analysis results between GTX carcinogens and NGTX carcinogens in multiple treatments.