Gene expression arrays as a tool to unravel mechanisms of normal tissue radiation injury and prediction of response

Kruse, Jacqueline J C M; Stewart, Fiona

doi:10.3748/wjg.v13.i19.2669

Cited by 30 publications

(16 citation statements)

References 52 publications

(46 reference statements)

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“…Currently, much work is focused on the use of microarray technology as a way to generate genetic signature profiles which will indicate the probable response of a tumour to radiation [reviewed in (21)]; this approach represents promising and revolutionary technology. However, the implementation of this technology in predictive radiation biology has yet to be validated and there are still some important limitations with regards to interpretation of gene expression data, complications raised by cell heterogeneity and expense.…”

Section: Prediction Of Tumour Radiosensitivitymentioning

confidence: 99%

Potential use of the comet assay in the clinical management of cancer

2008

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Section: Prediction Of Tumour Radiosensitivitymentioning

confidence: 99%

Potential use of the comet assay in the clinical management of cancer

2008

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“…Using subcutaneous fibroblasts from breast cancer patients, Rodningen et al (2007) identified a set of 18 radiation-responsive genes, which may provide a predictive assay for late normal tissue reactions after radiotherapy. The amount of information available on gene expression responses to radiation has been increasing considerably in recent years (Kruse and Stewart, 2007). These studies of altered gene expression have been useful for elucidating the molecular mechanisms underlying cellular radiation response and a few have been able to identify genes as potential indicators of severe reactions to radiotherapy treatment.…”

mentioning

confidence: 99%

Aberrant CDKN1A transcriptional response associates with abnormal sensitivity to radiation treatment

Badie¹,

Dziwura²,

Raffy³

et al. 2008

Br J Cancer

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Normal tissue reactions to radiation therapy vary in severity among patients and cannot be accurately predicted, limiting treatment doses. The existence of heritable radiosensitivity syndromes suggests that normal tissue reaction severity is determined, at least in part, by genetic factors and these may be revealed by differences in gene expression. To test this hypothesis, peripheral blood lymphocyte cultures from 22 breast cancer patients with either minimal (11) or very severe acute skin reactions (11) have been used to analyse gene expression. Basal and post-irradiation expression of four radiation-responsive genes (CDKN1A, GADD45A, CCNB1, and BBC3) was determined by quantitative real-time PCR in T-cell cultures established from the two patient groups before radiotherapy. Relative expression levels of BBC3, CCNB1, and GADD45A 2 h following 2 Gy X-rays did not discriminate between groups. However, post-irradiation expression response was significantly reduced for CDKN1A (Po0.002) in severe reactors compared to normal. Prediction of reaction severity of B91% of individuals sampled was achieved using this end point. Analysis of TP53 Arg72Pro and CDKN1A Ser31Arg single nucleotide polymorphisms did not show any significant association with reaction sensitivity. Although these results require confirmation and extension, this study demonstrates the possibility of predicting the severity of acute skin radiation toxicity in simple tests.

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“…An example to this is the study from Ichimura et al who identified the gene with most significant change in the postischemic rat kidney, KIM-1, and confirmed its viability for use as a biomarker by subsequent immunoblot, immunostaining, and RNA in situ hybridization [9]. Examples to other similar studies in which analysis of microarray data is used to find markers and changed gene expression levels for damage due to radiation toxicity [11], hemolytic anemia induced by drugs [12], nephrotoxicity induced by cisplatin [13], identification of glutathione depletion-responsive genes in rat liver [14], and many more. This approach is powerful, and pharmaceutical and biotechnology companies even created panels of biomarkers that detect drugs causing hepatotoxicity upon in vitro exposure to rat hepatocytes or in vivo dosing in rats [15].…”

Section: Related Workmentioning

confidence: 97%

Discovery of Biomarkers for Hexachlorobenzene Toxicity Using Population Based Methods on Gene Expression Data

Meydan

Küçükural

Yörükoğlu

et al. 2008

Pattern Recognition in Bioinformatics

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Abstract. Discovering toxicity biomarkers is important in drug discovery to safely evaluate possible toxic effects of a substance in early phases. We tried evolutionary classification methods for selecting the important classifier genes in hexachlorobenzene toxicity using microarray data. Using modified genetic algorithms for selection of minimum number of features for classification of gene expression data, we discovered a number of gene sets of size 4 that were able to discriminate between the control and the hexachlorobenzene (HCB) exposed group of Brown-Norway rats with >99% accuracy in 5-fold crossvalidation tests, whereas classification using all of the genes with SVM and other methods yielded results that vary between 48.48% to 81.81%. Making use of this small number of genes as biomarkers may allow us to detect toxicity of substances with mechanisms of toxicity similar to HCB in a fast and cost efficient manner when there are no emerging symptoms.

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Gene expression arrays as a tool to unravel mechanisms of normal tissue radiation injury and prediction of response

Abstract: Over the past 5 years there has been a rapid increase in the use of microarray technology in the field of cancer research.

Cited by 30 publications

References 52 publications

Potential use of the comet assay in the clinical management of cancer

Potential use of the comet assay in the clinical management of cancer

Aberrant CDKN1A transcriptional response associates with abnormal sensitivity to radiation treatment

Discovery of Biomarkers for Hexachlorobenzene Toxicity Using Population Based Methods on Gene Expression Data

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