Functional Genomics and a New Era in Radiation Biology and Oncology

Abstract

Ionizing radiation is a ubiquitous stress to which all life is continuously exposed, and thus complex mechanisms have evolved to regulate cellular responses to radiation, including cell cycle arrest, DNA repair, and programmed cell death. Changes in gene expression shape part of the response to radiation, and have historically provided insight into the underlying mechanisms of that response. However, the advent of microarrays, which can measure expression of all the genes in a cell simultaneously, has transformed the study of gene expression, and is beginning to have an impact on both basic mechanistic and clinical studies. This article provides an overview of concepts in gene expression and microarray technology, and highlights their impacts on the study of radiation biology.

Keywords: functional genomics; ionizing radiation; microarray; oncology; p53.

Figure 1

A region of DNA containing a protein-coding gene. A stretch of DNA that may extend several kilobases upstream (before the transcription start site) contains specific DNA sequences (represented by gray boxes on the DNA) where transcription factors, such as p53, NFκB (nuclear factor-kappa B), and AP1, can bind. This area is called the upstream promoter. Binding of transcription factor proteins can either enhance or repress transcription of a gene. The basal promoter is located within about 40 base pairs of the transcription start site, and contains a “TATA box,” a sequence present in all transcribed mammalian genes. The TATA box is bound by TFIID, a complex of many proteins that can recruit other proteins to the site of the gene. The transcription start site is where DNA-dependent RNA polymerase II (pol) binds to the gene and begins transcribing the DNA sequence into messenger RNA (mRNA). The mRNA will then be processed to remove introns (nonprotein coding regions) and the exons (coding sequences, represented by black boxes) will be spliced together. This message can then be translated into protein.

Figure 2

Two-color microarray hybridization. Ribo-nucleic acid (RNA) from two different samples of interest is labeled by carrying out a reverse transcription reaction incorporating a different fluorochrome into each sample. In the example, the control sample is labeled with cyanine-5 (Cy5) and the irradiated sample with cyanine-3 (Cy3). The two samples are hybridized together to the same micro array. After washing and scanning, the brightness of each fluorescent wavelength in the scanned image is compared for each feature (a spot representing an individual gene). In the composite image, genes such as CDKN1A, which are upregulated by radiation exposure, appear as red spots, reflecting the fact that there are more copies of these genes present in the RNA pool that was labeled with the red flurochrome. Similarly, down-regulated genes, such as MYC, appear as green spots, and genes that do not change, such as GAPDH, have equal amounts of both colors and appear yellow.

Figure 3

Single-color microarray hybridization (photolithographic platform). Ribonucleic acid from the samples to be compared is reverse transcribed to complementary DNA (cDNA), then in vitro transcription is carried out in the presence of labeled (in this case bio-tinylated) nucleotides to produce labeled cRNA. The labeled complementary RNA (cRNA) is fragmented to facilitate sequence-specific hybridization, and each sample is hybridized to a separate array. After washing, staining, and scanning, the fluorescent intensity of each feature is compared between arrays, making normalization across experiments extremely important. In the illustrated experiment, features representing genes upregulated by radiation exposure, such as CDKN1A, will have a greater intensity on the array hybridized to the irradiated sample. Downregulated genes, such as MYC, will show a greater intensity in control samples, and unchanged genes, such as GAPDH, will have equal intensity on the two arrays.

Figure 4

Heat map generated by clustering gene-expression ratio data (Amundson et al. 2005). Gene-expression ratios (treated/control) are represented as colors according to the scale at the bottom of the figure, with brighter red indicating more induction of expression, and brighter green indicating more suppression of expression after treatment. Each horizontal row represents the expression pattern of an individual gene across all experiments, and each vertical column represents the expression pattern of all genes within an individual experiment. Clustering has been used to arrange the experiments so that those producing the most similar pattern of gene-expression changes across all genes are closest together. Thus, for instance, all samples treated with metals (arsenite [As] and cadmium chloride [Cd]) appear next to each other, as do all samples treated with 12-O-tetradecanoylphorbol 13-acetate (TPA). The genes have also been clustered, so that those with the most similar response across all experiments are again placed next to each other. This reveals some specific patterns, such as those that have been marked with yellow boxes and discussed in the text. For instance, the genes in cluster A are mostly metallothioneins, which clearly respond much more strongly to metal exposure than to the other stresses studied.