Gene expression analysis with an integrated CMOS microarray by time-resolved fluorescence detection

Huang, T.-c.D.; Paul, Sunirmal; Gong, Ping; Levicky, Rastislav; Kymissis, John; Amundson, Sally A.; Shepard, Kenneth L.

doi:10.1016/j.bios.2010.03.001

Cited by 21 publications

(14 citation statements)

References 24 publications

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“…Because some of them are induced in isolated peripheral blood cells after exposure to doses as low as 5-25 mGy (Knops et al 2012;Riecke et al 2012;Manning et al 2013;Nosel et al 2013), it can be stated that in terms of sensitivity to low doses gene expression equals the DCA method. As a result, the development of a biodosimetry gene signature and associated assays which can be configured as devices suitable for low-cost, 'point-of-care' measurements make an appealing strategy (Brengues et al 2010;Huang et al 2011;Joiner et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Gene expression-based biodosimetry for radiological incidents: assessment of dose and time after radiation exposure

Macaeva

Mysara

Vos

et al. 2018

International Journal of Radiation Biology

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Purpose: In order to ensure efficient use of medical resources following a radiological incident, there is an urgent need for high-throughput time-efficient biodosimetry tools. In the present study, we tested the applicability of a gene expression signature for the prediction of exposure dose as well as the time elapsed since irradiation. Materials and methods: We used whole blood samples from seven healthy volunteers as reference samples (X-ray doses: 0, 25, 50, 100, 500, 1000, and 2000 mGy; time points: 8, 12, 24, 36 and 48 h) and samples from seven other individuals as 'blind samples' (20 samples in total). Results: Gene expression values normalized to the reference gene without normalization to the unexposed controls were sufficient to predict doses with a correlation coefficient between the true and the predicted doses of 0.86. Importantly, we could also classify the samples according to the time since exposure with a correlation coefficient between the true and the predicted time point of 0.96. Because of the dynamic nature of radiation-induced gene expression, this feature will be of critical importance for adequate gene expression-based dose prediction in a real emergency situation. In addition, in this study we also compared different methodologies for RNA extraction available on the market and suggested the one most suitable for emergency situation which does not require on-spot availability of any specific reagents or equipment. Conclusions: Our results represent an important advancement in the application of gene expression for biodosimetry purposes.

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Section: Introductionmentioning

confidence: 99%

Gene expression-based biodosimetry for radiological incidents: assessment of dose and time after radiation exposure

Macaeva

Mysara

Vos

et al. 2018

International Journal of Radiation Biology

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“…Several groups are developing gene expression signatures as an approach for emergency biodosimetry (7–9), while others are developing devices for implementing low-cost, rapid measurements in the field (18–21). Because of the diversity of gene expression responses to stresses such as ionizing radiation, it may be possible to develop such signatures to discriminate between acute and LDR exposures, either as part of a complete gene expression-based solution, or as an adjunct to a separate dose-determining approach such as high-throughput cytogenetics (22) or electron paramagnetic resonance measurements (23).…”

Section: Introductionmentioning

confidence: 99%

Radiation Dose-Rate Effects on Gene Expression in a Mouse Biodosimetry Model

et al. 2015

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In the event of a nuclear accident or radiological terrorist attack, there will be a pressing need for biodosimetry to triage a large, potentially exposed population and to assign individuals to appropriate treatment. Exposures from fallout are likely, resulting in protracted dose delivery that would, in turn, impact the extent of injury. Biodosimetry approaches that can distinguish such low-dose-rate (LDR) exposures from acute exposures have not yet been developed. In this study, we used the C57BL/6 mouse model in an initial investigation of the impact of low-dose-rate delivery on the transcriptomic response in blood. While a large number of the same genes responded to LDR and acute radiation exposures, for many genes the magnitude of response was lower after LDR exposures. Some genes, however, were differentially expressed (P < 0.001, false discovery rate < 5%) in mice exposed to LDR compared with mice exposed to acute radiation. We identified a set of 164 genes that correctly classified 97% of the samples in this experiment as exposed to acute or LDR radiation using a support vector machine algorithm. Gene expression is a promising approach to radiation biodosimetry, enhanced greatly by this first demonstration of its potential for distinguishing between acute and LDR exposures. Further development of this aspect of radiation biodosimetry, either as part of a complete gene expression biodosimetry test or as an adjunct to other methods, could provide vital triage information in a mass radiological casualty event.

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“…The choice of indicator RNA is essential for establishing the methodology to measure cellular damage. In this study, we used mRNAs of the well-known genes Bax , Bbc3 and Cdkn1a , which are considered biodosimetric indicators following low-dose irradiation in human [ 7 , 8 , 10 , 12 , 16 , 17 , 33 , 34 ] and mouse [ 20 ] cells. DNA damage by radiation in proliferative cells activates p53 protein via ATM signals, and then the p53 activates the growth-arrest protein CDKN1A and proapoptotic proteins BAX and BBC3 [ 35 ].…”

Section: Discussionmentioning

confidence: 99%

Quantification of damage due to low-dose radiation exposure in mice: construction and application of a biodosimetric model using mRNA indicators in circulating white blood cells

Ishiguro¹,

Tanaka²,

Yakumaru³

et al. 2015

J Radiat Res

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Biodosimetry, the measurement of radiation damage in a biologic sample, is a reliable tool for increasing the accuracy of dose estimation. Although established chromosome analyses are suitable for estimating the absorbed dose after high-dose irradiation, biodosimetric methodology to measure damage following low-dose exposure is underdeveloped. RNA analysis of circulating blood containing radiation-sensitive cells is a candidate biodosimetry method. Here we quantified RNA from a small amount of blood isolated from mice following low-dose body irradiation (<0.5 Gy) aimed at developing biodosimetric tools for situations that are difficult to study in humans. By focusing on radiation-sensitive undifferentiated cells in the blood based on Myc RNA expression, we quantified the relative levels of RNA for DNA damage-induced (DDI) genes, such as Bax , Bbc3 and Cdkn1a . The RNA ratios of DDI genes/ Myc in the blood increased in a dose-dependent manner 4 h after whole-body irradiation at doses ranging from 0.1 to 0.5 Gy (air-kerma) of X-rays, regardless of whether the mice were in an active or resting state. The RNA ratios were significantly increased after 0.014 Gy (air-kerma) of single X-ray irradiation. The RNA ratios were directly proportional to the absorbed doses in water ranging from 0.1 to 0.5 Gy, based on gamma-irradiation from 137 Cs. Four hours after continuous irradiation with gamma-rays or by internal contamination with a beta-emitter, the increased RNA ratios resembled those following single irradiation. These findings indicate that the RNA status can be utilized as a biodosimetric tool to estimate low-dose radiation when focusing on undifferentiated cells in blood.

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Gene expression analysis with an integrated CMOS microarray by time-resolved fluorescence detection

Cited by 21 publications

References 24 publications

Gene expression-based biodosimetry for radiological incidents: assessment of dose and time after radiation exposure

Gene expression-based biodosimetry for radiological incidents: assessment of dose and time after radiation exposure

Radiation Dose-Rate Effects on Gene Expression in a Mouse Biodosimetry Model

Quantification of damage due to low-dose radiation exposure in mice: construction and application of a biodosimetric model using mRNA indicators in circulating white blood cells

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