British Journal of Radiology (2005) Supplement_27, 114-122
© 2005 British Institute of Radiology
doi: 10.1259/bjr/29577159
British Journal of Radiology Supplement_27 (2005),114-122 © 2005 The British Institute of Radiology
The search for mRNA biomarkers: global quantification of transcriptional and translational responses to ionising radiation
N Dainiak, MD1,
S K Schreyer, PhD2 and
J Albanese, PhD3
1 Bridgeport Hospital, Bridgeport, and Yale University School of Medicine, New Haven, CT, USA, 2 Chemical Computing Group, Montreal, Quebec, Canada and 3 Yale New Haven Health System Center for Emergency Preparedness and Disaster Response, New Haven, CT, USA
Correspondence: Nicholas Dainiak, MD, Department of Medicine, Bridgeport Hospital, 267 Grant Street, Bridgeport, CT 06610, USA. E-mail: pndain@bpthosp.org
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Abstract
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Since the discovery of X-rays and the subsequent realisation that ionising radiation (IR) can provide a curative mode of therapy to treat tumours, there has been a concerted effort to discover the mechanisms by which IR induces cells to die or to become resistant to radiotherapy. Classical genetic analyses and biochemical techniques have been used to identify an ever-expanding number of genes whose activation directly or indirectly influences DNA repair, cell cycle progression and apoptosis. The advent of cDNA microarrays provides an opportunity to explore further the biological processes fundamental to the radiation response by permitting a comprehensive assessment of a cell's transcriptional landscape. The capacity to study the expression patterns of thousands of genes simultaneously may lead to (i) an increased understanding of how IR-responsive genes from seemingly mutually exclusive pathways (i.e. DNA repair and apoptosis) interact to determine the fate of irradiated cells and (ii) the discovery of new biomarkers for radiation exposure. Still in its infancy, protein microarray technology provides a complementary approach to cDNA microarray techniques for studying protein expression following exposure to IR. Analysis of microarrays requires a basic understanding of hierarchical clustering methodologies. Projection pursuit is one such method that shows promise in analysis of the non-linear data that are often generated from microarrays.
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Introduction
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A decade ago, Cowan et al [1] observed that the karyotypes of radiation-resistant and radiation-sensitive human squamous carcinoma cells differed following irradiation, and they proposed that certain genes which are responsible for these differences might be used as biomarkers for predicting response to radiation therapy. Since then, the application of traditional molecular and genetic techniques has yielded a copious amount of data that have identified and characterised many genes involved in radiation-induced alterations in cell cycle arrest, DNA repair and apoptosis. The mechanistic details of the pathways activated in response to ionising radiation (IR) are undefined. Furthermore, much of the information currently available regarding the IR response has been generated from studies in which a high dose of radiation was employed to induce cellular changes. It is not clear to what extent the data from these studies are relevant in the context of therapeutic or environmental doses.
Traditional technologies for quantifying transcriptional and translational responses to IR include the reverse transcriptase polymerase chain reaction (RT-PCR), quantitative PCR, Western blotting and the yeast two-hybrid system. Whilst these methods are based on a reductionist approach to discerning responses, new technologies take a global approach to assess biological response. Recently, cDNA and protein microarray systems have been developed that have prompted radiation biologists to re-visit the radiation response in established and primary cell lines treated with low dose radiation. Here, we briefly review the pathways activated in response to IR, and highlight the findings from recent studies that have employed cDNA and protein arrays to examine the genotoxic stress response to low dose IR treatment. In addition, we compare commonly used statistical methodologies used to analyse data generated by cDNA microarrays. It is likely that these statistical techniques can also be applied to analyse data generated by protein microarrays.
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IR-induced gene expression
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The interaction of IR with DNA results in various genetic lesions that include single-strand breaks and double-strand breaks (DSBs) [2]. Single-strand breaks are of lesser consequence to cell survival, since DNA polymerase, a component of the DNA repair mechanism, readily mends the damage using information stored in the opposite strand. However, when both strands of DNA are broken, the molecule is effectively cleaved into two pieces. This type of lesion is more difficult to repair and often results in erroneous rejoining of the broken ends, which consequently is responsible for mutations [3], chromosomal aberrations [4] and/or cell death [5].
Whilst the consequences of IR exposure have traditionally been studied in the context of genetic alterations and apoptosis, these events represent late end-points of DNA damage. A more immediate response to IR-induced DNA damage is the upregulation of an ever-expanding number of genes. This early transcriptional response may define the later fate of the cell. Genes that are induced by IR are those that modulate not only DNA repair but also cell cycle arrest and apoptosis. Despite the certainty that activation of these genes is a direct result of IR-mediated DNA damage, the mechanisms and components through which gene transcription is activated remain unknown, and their clarification constitutes an area of intense investigation.
Current evidence suggests that, in response to DSBs, DNA sensors, including ataxia telangiectasia mutated (ATM), ataxia telangiectasia RAD3-related (ATR) protein and DNA protein kinases, phosphorylate downstream transducer proteins (see Figure 1
) resulting in G1/S and G2/M cell cycle arrest [6]. Arrest of the cell cycle is apparently necessary for prevention of the propagation of IR-induced genomic lesions to cellular progeny. To further enforce faithful propagation of the genome, programmed cell death pathways are integrated into the DNA damage sensing and checkpoint activation mechanisms so that if genomic integrity cannot be restored by the DNA repair machinery, apoptosis ensues [5, 7].
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Figure 1. Cellular response to ionising radiation (IR)-induced DNA damage. In response to IR-induced DNA lesions, DNA sensor proteins convey DNA damage signals to transducer molecules through phosphorylation. In turn, transducer proteins activate effector molecules that are responsible for modulating cell cycle progression, DNA repair and apoptosis. Modified from Belli et al [10] with permission.
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A principal initiator of the G1/S checkpoint, the tumour suppressor protein and transcription factor TP53 is a known substrate of the ATM, ATR and chk2 kinases. Upon its phosphorylation, TP53 binds the promoter regions of TP53-responsive genes, including Bax and p21, to trigger upregulation of their respective gene products. Increased levels of p21 inhibit the activities of cyclin-dependent kinase 2 (CDK2) [8] as well as proliferating-cell nuclear antigen [9], both of which are required for progression through the G1 phase of the cell cycle [8].
Whilst G1/S cycle arrest prevents replication of damaged DNA, G2/M phase arrest permits detection of DNA damage and repair of DNA prior to the segregation of chromosomes to daughter cells [10, 11]. Evidence suggests that inactivation of the phosphatase Cdc25C by ATM-activated chk2 kinase prevents dephosphorylation and stimulation of Cdc2 kinase [12]. Inactivation of Cdc2 kinase blocks the initiation of mitosis and allows time for DNA repair to occur.
Concurrent with cell cycle arrest, homologous and non-homologous end-joining DNA repair mechanisms are initiated through the concerted recruitment of the Rad50/Mre11/NBS1 nuclease complex and DNA protein kinase to the DNA damage sites [13]. Unless DSB repair occurs free of errors, apoptotic pathways are activated, which in turn lead to elimination of the damaged cell.
Whilst the exact mechanism by which apoptosis is initiated in response to DNA damage is not known, upregulation by p53 of two pro-apoptotic proteins, Bax and Noxa, points to these as prime candidates for triggers of IR-induced apoptosis. Bax is a member of the Bcl-2 family of proteins, which contains both repressors and effectors of apoptosis. Bax has been shown to promote cell death by releasing cytochrome c from mitochondria [14]. Cytochrome c then functions to activate intracellular caspases [15], the ultimate triggers of apoptosis. Schuler et al [16] have recently published evidence to suggest that Noxa protein may function to assist Bax translocation to the mitochondria.
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Transcriptional activation of cytokines and pro-apoptotic molecules by IR
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The resolution to IR-induced DNA damage (i.e. activation of apoptotic pathways or successful DNA repair followed by re-entry into mitosis) appears to be universal to all cells. Nevertheless, some cells, including intestinal crypt and haematopoietic cells, are more inclined to undergo apoptosis than to initiate pathways leading to restoration of the genome [17, 18]. Upregulated transcription of genes encoding cytokines, including granulocyte–macrophage colony-stimulating factor (GM-CSF) [19], granulocyte colony-stimulating factor (G-CSF) [20], stem cell factor (SCF) [21], basic fibroblast growth factor (bFGF) [22] and interleukin-1 (IL-1) [23], in response to irradiation may provide radioprotection and permit prolonged survival of those cells that are particularly sensitive to IR [23, 24]. This supposition is supported by results in canine, murine and human models demonstrating that administration of GM-CSF, G-CSF, SCF, bFGF and IL-1 has a favourable effect on outcome [24–26].
However, not all cytokines that are expressed in response to IR support cell survival. IL-6, transforming growth factor-
(TGF-) and interferon-
(IFN-), for example, increase radiosensitivity in whole-body-irradiated mice [25]. We have reported that irradiated cells overexpress several members of the tumour necrosis factor (TNF) superfamily of receptors and ligands at their cell surface, including Fas [27] and its cognate ligand, Fas ligand [28] (see Figure 2), whilst Sheikh et al [29] reported that TNF-related apoptosis-inducing ligand (TRAIL) DR5 death receptor is overexpressed. These three pro-apoptotic molecules are released from the cell surface on extracellular, plasma membrane-derived vesicles [30, 31]. Belka et al [32] have shown that apoptosis in lymphocytes resulting from IR exposure requires the interaction between Fas and its ligand. Consequently, IR-induced cell death may proceed via activation of overexpressed death receptors at the cell surface that, in turn, activate intracellular caspase-8 to initiate apoptosis [33, 34] (see Figure 3).
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Figure 2. Ionising radiation induces the expression of Fas ligand (Fas L) on the cell surface. Plasma membranes were purified from control and irradiated (4 Gy or 10 Gy) colorectal carcinoma cells (SW620) and subjected to Western blot analysis for FasL (TNFSF6) protein (panel A). mRNA for FasL was assessed by reverse transcriptase polymerase chain reaction (RT-PCR) (panel B). Whole cells (2 x 105) were treated with 0 Gy, 4 Gy or 10 Gy, sequentially labelled with rabbit anti-FasL antibody and fluorescein-conjugated anti-rabbit IgG, and analysed by flow cytometry (panel C). Note that both protein and message levels are increased in a dose-dependent manner. Reproduced from Albanese and Dainiak [28] with permission.
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Figure 3. Ionising radiation (IR)-induced transcription of pro-apoptotic receptor mRNAs. Sublethal doses of IR induce upregulation of mRNA coding for "death" receptors (Fas, DR4, DR5). The gene products accumulate at the cell surface where their encounter with death ligand (Fas ligand and TRAIL) triggers the assembly of cytoplastic proteins (FADD and pro-caspase 8) at the plasma membrane, leading to the activation of caspase-8 and caspase-3, with subsequent apoptosis.
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Global gene expression responses to IR
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The identification of genes coding for DNA repair, cell cycle arrest, cell death and cytokine proteins, as well as their respective mRNA transcripts and gene products has provided the starting point for our current understanding of molecular pathways involved in the IR-induced stress response. Much of these data have been obtained through traditional biochemical approaches that have been used to monitor the activation of a single gene, or a few genes at the same time. However, it is increasingly evident that this reductionist approach becomes restrictive as a means for understanding the mounting complexity of the IR stress response.
It is possible that additional genes are expressed as part of the radiation response. The advent of cDNA microarray allows quantification of the entire transcriptome in a single experiment. The promise that extends from the ability to gauge expression levels of thousands of genes simultaneously is a comprehensive understanding of how DNA repair, cell cycle arrest and apoptotic pathways converge to decide the fate of irradiated cells. In due course, understanding the interrelationships that exist between the various IR stress response pathways may provide new therapeutic modalities for radiation toxicity (i.e. targeted therapy).
To date, microarray technology has confirmed previously known transcriptional responses and has identified several new biomarkers for IR exposure. Amundson and co-workers [35–37], for example, have successfully applied microarray techniques to quantify levels of mRNA transcripts for the previously characterised DNA repair genes (CDKN1A, GADD45, MDM2 and Bax) and several cytokine genes (IL-1 and IL-6). Their studies revealed a dose-dependent increase in mRNA transcripts for these genes in ML-1 myeloid human cells irradiated with doses of 0.02–20 Gy [35, 36]. They also showed that, in contrast to the ML-1 and other cell lines, where maximum transcription of CDKN1A occurs at 4 h post irradiation [36], peak induction of CDNK1A as well as DDB2 (a gene that codes for a subunit of the XPE protein known to play a critical role in repairing DNA damage induced by ultraviolet light) and XPC occurs 24 h following ex vivo irradiation (2 Gy) in human peripheral blood lymphocytes (PBLs) [37]. According to the authors, this temporal discrepancy in gene activation may be explained by the fact that rapidly proliferating cells (i.e. established cell lines) respond to IR-induced genotoxic damage faster than quiescent cell populations (i.e. PBLs). Consistent with this hypothesis, the authors were able to show that whole body irradiation in mice results in increased mRNA levels for a number of genes, and that these levels are maintained in thymus, spleen and liver in vivo for at least 24 h post exposure to doses as low as 0.2 Gy [36]. Interestingly, whilst numerous genes were identified as IR-responsive in these organs, elevated levels of mRNA transcripts for the majority of genes were observed to be tissue-specific (Figure 4).
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Figure 4. Tissue-specific gene expression. Venn diagram showing the number of genes expressed at elevated levels in various mouse tissues harvested 24 h following irradiation with 2 Gy (panel A) or 0.2 Gy (panel B) -rays. The samples were hybridised to microarrays of 4105 murine cDNAs. Note that although a small number of genes responded in all tissues examined, the majority were specific to one tissue. Reproduced from Amundson et al [36] with permission.
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Whilst the possibility of expediting the discovery of new IR-responsive genes or patterns of gene expression is an attractive motive for radiobiologists to employ gene expression profiling, the potential to use newly discovered genes or entire expression profiles as a biomarker or signature for IR exposure, particularly at low dose exposure, provides an added impetus to use this technology. In this context, the goal is to use cDNA methodologies to establish a rapid, precise, high-throughput assay system that is practical for medical triage of individuals in a variety of radiation exposure scenarios [38, 39].
As biomarkers for IR exposure, the CDNKA1, DD2 and XPC genes are of particular interest since these genes are induced in a linear manner at environmentally relevant doses (0.05–2 Gy) [36, 37]. Moreover, transcript levels show little interindividual variation and thus mRNA quantities in non-exposed persons may provide a baseline for comparison purposes for exposed individuals [37, 39]. Recently, Kang et al [40], using cDNA microarray and RT-PCR analysis, identified four genes (TRAIL receptor 2 (DR5), FHL2, cyclin G and the cyclin protein gene) whose expression levels varied linearly with dose (0.5–4 Gy) in irradiated human lymphocytes. Whilst CDNKA1, DD2 and XPC gene transcript levels peak at 24 h post irradiation [35], those for genes described by Kang and colleagues are maximally induced at 12 h following exposure to IR [40]. Nevertheless, DR5, FHL2, cyclin G and cyclin protein gene transcript levels exhibit little interindividual variability in non-irradiated cells [40]. These studies performed using PBLs irradiated ex vivo suggest a potential for cDNA technology to identify a set of genes that can distinguish between irradiated and non-irradiated individuals.
We have published results generated by cDNA microarray analysis of PBLs exposed to low dose IR in vivo donated by Belarusians residing near Chernobyl [41]. The data identified differences in the patterns of mRNA expression for growth factors, cytokine receptors and their cognate ligands as well as for apoptosis-modulating proteins in individuals exposed to greater than 10 mSv compared with those exposed to less than 10 mSv. At doses between 10 mSv and 50 mSv, overexpressed gene transcripts include IL-1, IL-2, IL-8, IL-10, IL-12, IL-10 receptor, macrophage colony-stimulating factor (M-CSF), M-CSF receptor, soluble and membrane-bound Fas, TNF-
/ and the IFN receptor [41]. These findings suggest that it may be possible to assign "signature" patterns of gene expression to recognise individuals who have been exposed to low doses of IR.
cDNA microarrays may be exploited to distinguish between different types of IR. Marko et al [42] have recently employed cDNA microarray technology to investigate the transcriptional response to bioequivalent doses of - and -radiation in HCT-116, a human colorectal cancer cell line. Their results indicate that -radiation triggers the activation of a greater number of genes in addition to a more pronounced level of gene transcription than does -radiation. Whilst both types of radiation induce a common set of genes (including those coding for DNA repair, cell cycle and apoptosis proteins), distinct gene expression profiles are identified for - and -radiation (Figure 5) [42]. Among notable differences in transcriptional responses between the two forms of radiation is the activation by -radiation of a proportionally larger number of genes that regulate transcription, signalling and cell adhesion. In contrast, -radiation preferentially activates genes encoding inflammatory molecules and proteases.
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Analysis of data generated by microarrays
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In addition to being knowledgeable of technical issues involved in performing microarrays (such as appropriate use of controls, performance of replicates and die swapping techniques, and normalisation of data to account for systematic differences in channel intensity), an understanding of bioinformatics is necessary for appropriate analysis of the enormous amount of data generated by microarrays. Data analysis methodologies have been reviewed [41]. We have recently applied projection pursuit as a method to reveal clustering when the within-group variance of principle component analysis (PCA) is large. Projection pursuit uses the significant principle component scores to construct projection space, and obtains the results and projection pursuit factors according to their sequential maximised 
2 index. Figure 6 depicts rotation of the first principle component to obtain optimal separation of groups, as the first projection pursuit is identified.
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Figure 6. Projection pursuit (PP). The first principal component (PC1) is rotated to an optimal separation of two groups of data points, thereby defining the first PP. From a random starting plane, two candidate planes are generated. The projection index is evaluated, using the method of Posse, to find the optimal PP index. The plane containing the best PP index is then selected as a new starting plane and the PP axes are identified from projection onto the two best planes.
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We have applied a projection pursuit algorithm to a data set developed from cDNA microarray analysis of PBLs from 19 Chernobyl victims [41]. Comparison of projection pursuit clusters and PCA clusters at the same level of significance revealed only three clusters by PCA and seven separate and clearly defined groups by projection pursuit (see Table 1). These results suggest that projection pursuit maintains the advantages of PCA whilst compensating for non-linearity. Projection pursuit may be valuable in identifying biologically relevant relationships for cDNA microarrays and possibly, protein microarrays.
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Table 1. Comparison of genes expressed in clusters from principal component analysis (PCA) and projection pursuit
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Proteomonic approaches to investigate IR-induced stress responses
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mRNA levels are not only a product of transcription but also of degradation [43]. Consequently, the correlation between the number of mRNA transcripts and protein molecules may not be strong enough to predict protein levels from mRNA levels [44, 45]. Moreover, cDNA microarrays are not capable of differentiating between mRNA splice variants [46]. Accordingly, it is likely that the cDNA microarray data underestimate post-transcriptional modifications and as a result, provide only a partial view of the IR stress response.
Proteomonics provides an alternative and complementary approach to cDNA microarray technology for the identification and validation of proteins, and for global monitoring of IR-induced protein expression alterations. Currently, the most commonly used approach to proteomonics is based on two-dimensional electrophoresis followed by mass spectroscopy and computer-aided identification of the resolved proteins [47]. Whilst this approach has proven successful in separating proteins and in detecting differences in levels of expression of several hundred proteins resulting from external cellular stimuli [48, 49], including X-irradiation [50], this methodology is time consuming. Newer techniques employing protein microarrays may solve this problem [47].
Protein microarrays provide researchers with the ability to catalogue and analyse thousands of proteins at once, and to measure their expression levels with a high degree of sensitivity. One way to compare protein expression levels in complex mixtures is to capture them with antibodies immobilised on a solid support (antibody microarray) [51]. If equal amounts of pre-labelled proteins present in test and reference samples are loaded on an antibody microarray, the relative quantities of proteins in the mixtures can be determined by calculating the ratios of spot intensities (Figure 7) [52]. Sreekumar et al [52] used this two-colour approach to monitor proteomic profiles of LoVo colon cancer cells in response to IR. Analysis of the microarray composed of 146 antibodies specific for proteins that regulate cell cycle arrest and apoptosis revealed increased levels of pro-apoptotic proteins, including TRAIL, DR5 and TP53.
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Figure 7. Schematic representation of an antibody microarray system for monitoring protein profiles. Equal quantities of protein from test and reference cell lysates are labelled with either Cy3- (green) or Cy5- (red) NHS dyes. Unreacted dyes are removed by size exclusion chromatography. The proteins are loaded onto an antibody microarray and the microarray is analysed using a microarray scanner. Proteins are classified as upregulated, downregulated or unchanged, according to the colour intensity ratio of the two dyes. Reproduced from Sreekumar et al [52] with permission.
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Consistent with this observation, irradiated cells displayed an increased incidence of apoptosis. In addition to proteins already known to respond to IR, the authors identified several new proteins, including the TRAIL decoy receptor 2, STAT1a and DFF45/ICAD. Microarray data for protein expression were validated by Western blot analysis [52].
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Conclusions
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The search for mRNA biomarkers of radiation exposure has the potential to generate new knowledge regarding the integration of molecular pathways in response to genotoxic stress. Understanding such pathways may lead to the development of targeted therapy for individuals exposed to IR. Identification of new biomarkers of exposure may be applied to dosimetry, particularly for the low dose range. Microarray studies to date indicate the importance of accounting for not only radiation dose but also for tissue type and cellular phenotype. Owing to the large data sets generated using microarray technology, an understanding of hierarchical clustering methodologies is essential for data analysis.
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Abstract
Introduction
