Transcriptional responses to radiation exposure facilitate the discovery of biomarkers functioning as radiation biodosimeters

The development of new methods for a retrospective quantification of the radiation dose of exposed individuals is of widespread interest. To this end, I developed a computational framework for biomarker discovery and radiation dose prediction and successfully identified gene signatures with which low and medium to high radiation doses can be accurately quantified. To enhance our understanding of the radiation-induced transcriptional response, I additionally analyzed microarray data of human PBLs after ex vivo gamma-irradiation and characterized affected functional processes and pathways

Integration of new biological and physical retrospective dosimetry methods into EU emergency response plans : joint RENEB and EURADOS inter-laboratory comparisons

Purpose: RENEB, 'Realising the European Network of Biodosimetry and Physical Retrospective Dosimetry,' is a network for research and emergency response mutual assistance in biodosimetry within the EU. Within this extremely active network, a number of new dosimetry methods have recently been proposed or developed. There is a requirement to test and/or validate these candidate techniques and inter-comparison exercises are a well-established method for such validation. Materials and methods: The authors present details of inter-comparisons of four such new methods: dicentric chromosome analysis including telomere and centromere staining; the gene expression assay carried out in whole blood; Raman spectroscopy on blood lymphocytes, and detection of radiation induced thermoluminescent signals in glass screens taken from mobile phones. Results: In general the results show good agreement between the laboratories and methods within the expected levels of uncertainty, and thus demonstrate that there is a lot of potential for each of the candidate techniques. Conclusions: Further work is required before the new methods can be included within the suite of reliable dosimetry methods for use by RENEB partners and others in routine and emergency response scenarios

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks

Comparable dose estimates of blinded whole blood samples are obtained independently of culture conditions and analytical approaches. Second RENEB gene expression study

PURPOSE:This collaboration of five established European gene expression labs investigated the potential impact of culture conditions on the transcriptional response of peripheral blood to radiation exposure.MATERIALS AND METHODS:Blood from one healthy donor was exposed ex vivo to a Cobalt 60 source to produce a calibration curve in addition to four unknown doses. After exposure, the blood samples were either diluted with RPMI medium or left untouched. After 24-h incubation at 37 °C the diluted blood samples were lysed, while the undiluted samples were mixed with the preservative RNALater and all samples were shipped frozen to the participating labs. Samples were processed by each lab using microarray (one lab) and QRT-PCR (four labs).RESULTS:We show that although culture conditions affect the total amount of RNA recovered (p 0.5 Gy) measurements (p = .6).CONCLUSION:This study confirms the robustness of gene expression as a method for biological dosimetry

Integration of new biological and physical retrospective dosimetry methods into EU emergency response plans – joint RENEB and EURADOS inter-laboratory comparisons

PURPOSE:RENEB, 'Realising the European Network of Biodosimetry and Physical Retrospective Dosimetry,' is a network for research and emergency response mutual assistance in biodosimetry within the EU. Within this extremely active network, a number of new dosimetry methods have recently been proposed or developed. There is a requirement to test and/or validate these candidate techniques and inter-comparison exercises are a well-established method for such validation.MATERIALS AND METHODS:The authors present details of inter-comparisons of four such new methods: dicentric chromosome analysis including telomere and centromere staining; the gene expression assay carried out in whole blood; Raman spectroscopy on blood lymphocytes, and detection of radiation-induced thermoluminescent signals in glass screens taken from mobile phones.RESULTS:In general the results show good agreement between the laboratories and methods within the expected levels of uncertainty, and thus demonstrate that there is a lot of potential for each of the candidate techniques.CONCLUSIONS:Further work is required before the new methods can be included within the suite of reliable dosimetry methods for use by RENEB partners and others in routine and emergency response scenarios