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Interventional radiology procedures expose individuals to ionizing radiation. However, existing dosimetry methods do not provide the dose effectively absorbed to the skin, and do not consider the patient’s individual response to irradiation. To resolve this lack of dosimetry data, we developed a new external irradiation biodosimetry device, DosiKit, based on the dose-dependent relationship between irradiation dose and radiation-induced H2AX protein phosphorylation in hair follicles. This new biological method was tested in Clermont-Ferrand University Hospital to evaluate the assay performances in the medical field and to estimate DosiKit sensitivity threshold. DosiKit was tested over 95 patients treated with neuroradiological interventions. For each intervention, lithium fluoride thermoluminescent dosimeters (TLD) were used to measure total dose received at each hair collection point (lateral and occipital skull areas), and conventional indirect dosimetry parameters were collected with a Dosimetry Archiving and Communication System (DACS). Quantitative measurement of radiation-induced H2AX protein phosphorylation was performed on 174 hair samples before and after the radiation exposure and 105 samples showed a notable induction of gammaH2AX protein after the radiological procedure. According to a statistical analysis, the threshold sensitivity of the DosiKit immunoassay was estimated around 700 mGy. With this study, we showed that DosiKit provides a useful way for mapping the actually absorbed doses, allowing to identify patients overexposed in interventional radiology procedures, and thus for anticipating risk of developing dermatitis. • DosiKit is a new external irradiation biodosimetry device, based on the dose-dependent relationship between irradiation dose and radiation-induced H2AX protein phosphorylation in hair follicles. • DosiKit was tested over 95 patients treated with neuroradiological interventions. • The threshold sensitivity of the DosiKit immunoassay was estimated around 700 mGy and DosiKit provides a useful way for mapping the actually absorbed doses.

International audience; Cancer cells can use a telomerase-independent mechanism, known as alternative lengthening of telomeres (ALT), to elongate their telomeres. General control non-derepressible 5 (GCN5) and P300/CBP-associated factor (PCAF) are two homologous acetyltransferases that are mutually exclusive subunits in SAGA-like complexes. Here, we reveal that down regulation of GCN5 and PCAF had differential effects on some phenotypic characteristics of ALT cells. Our results suggest that GCN5 is present at telomeres and opposes telomere recombination, in contrast to PCAF that may indirectly favour them in ALT cells.

We previously identified two highly discriminating and predictive radiation-induced transcriptomic signatures by comparing series of sporadic and postradiotherapy thyroid tumors (322-gene signature), and by reanalyzing a previously published data set of sporadic and post-Chernobyl thyroid tumors (106-gene signature). The aim of the present work was (i) to compare the two signatures in terms of gene expression deregulations and molecular features/pathways, and (ii) to test the capacity of the postradiotherapy signature in classifying the post-Chernobyl series of tumors and reciprocally of the post-Chernobyl signature in classifying the postradiotherapy-induced tumors.We now explored if postradiotherapy and post-Chernobyl papillary thyroid carcinomas (PTC) display common molecular features by comparing molecular pathways deregulated in the two tumor series, and tested the potential of gene subsets of the postradiotherapy signature to classify the post-Chernobyl series (14 sporadic and 12 post-Chernobyl PTC), and reciprocally of gene subsets of the post-Chernobyl signature to classify the postradiotherapy series (15 sporadic and 12 postradiotherapy PTC), by using conventional principal component analysis.We found that the five genes common to the two signatures classified the learning/training tumors (used to search these signatures) of both the postradiotherapy (seven PTC) and the post-Chernobyl (six PTC) thyroid tumor series as compared with the sporadic tumors (seven sporadic PTC in each series). Importantly, these five genes were also effective for classifying independent series of postradiotherapy (five PTC) and post-Chernobyl (six PTC) tumors compared to independent series of sporadic tumors (eight PTC and six PTC respectively; testing tumors). Moreover, part of each postradiotherapy (32 genes) and post-Chernobyl signature (16 genes) cross-classified the respective series of thyroid tumors. Finally, several molecular pathways deregulated in post-Chernobyl tumors matched those found to be deregulated in postradiotherapy tumors.Overall, our data suggest that thyroid tumors that developed following either external exposure or internal (131)I contamination shared common molecular features, related to DNA repair, oxidative and endoplasmic reticulum stresses, allowing their classification as radiation-induced tumors in comparison with sporadic counterparts, independently of doses and dose rates, which suggests there may be a "general" radiation-induced signature of thyroid tumors.

Several studies have demonstrated the deleterious effect of aging on the capacity of cells to repair their DNA. However, current existing assays aimed at measuring DNA repair address only a specific repair step dedicated to the correction of a specific DNA lesion type. Consequently they provide no information regarding the repair pathways that handle other types of lesions. In addition to aging, consequences of photo-exposure on these repair processes remain elusive. In this study we evaluated the consequence of aging and of chronic and/or acute photo-exposure on DNA repair in human skin fibroblasts using a multiplexed approach, which provided detailed information on several repair pathways at the same time. The resulting data were analyzed with adapted statistics/bioinformatics tools. We showed that, irrespective of the repair pathway considered, excision/synthesis was less efficient in non-exposed cells from elderly compared to cells from young adults and that photo-exposure disrupted this very clear pattern. Moreover, it was evidenced that chronic sun-exposure induced changes in DNA repair properties. Finally, the identification of a specific signature at the level of the NER pathway in cells repeatedly exposed to sun revealed a cumulative effect of UVB exposure and chronic sun irradiation. The uses of bioinformatics tools in this study was essential to fully take advantage of the large sum of data obtained with our multiplexed DNA repair assay and unravel the effects of environmental exposure on DNA repair pathways.

Oncogenic mechanisms of human papillomavirus (HPV)-positive oropharyngeal cancer are still poorly characterized. Analysis of their microRNA expression profile might provide valuable information.The microRNA expression profiles were analyzed by micro-arrays in 26 oropharyngeal cancers. A microRNA signature specific to HPV-status was identified by analyzing a learning/training set consisting of 16 oropharyngeal cancers. The robustness of this signature was further confirmed by blind case-by-case classification of a validation set composed of 10 independent tumors. Putative targeted molecular pathways were proposed using DIANA miRPath online software (http://microrna.gr/mirpath).We have identified 25 miRNA signatures, which discriminates HPV16-positive oropharyngeal cancer from their HPV-negative counterparts. These 25 microRNAs play a potential role in Wnt and PI3K-pathways, cell-adhesion/cell-polarity, and the cytoskeleton regulation.Our study contributes to a better understanding of pathogenic mechanisms involved in the development of HPV-positive oropharyngeal cancer and in the identification of potential therapeutic molecular targets. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1708-1716, 2016.

Experiments were designed to compare the transcriptional response to ionizing radiation (IR) of wild-type (WT) and ataxia telangiectasia (AT) cells. mRNA levels were assessed 2, 4 and 24 h after exposure to equitoxic doses using cDNA microarrays. Data reveal distinct patterns of gene expression between AT and WT cells since IR-responsive genes were mostly cell-type specific, this group representing 87 and 94% of the responding genes in WT and AT cells, respectively. In both cell lines, transcriptional alterations of genes associated with proliferation correlated with the observed cell cycle and growth data. Deregulated genes involved in apoptosis suggest that wild-type cells were more prone to cell death by apoptosis than AT cells. Furthermore, genes associated with the response to oxidative stress were particularly deregulated in wild-type cells whereas alterations of genes related to unexpected pathways including RNA processing, protein synthesis and lipid metabolism were specifically found in irradiated AT cells. These data suggest that under radiation conditions leading to a similar survival of WT and AT cells, the mechanisms triggered after radiation were mainly dependent on ATM status and thus on the intrinsic radiosensitivity.

DosiKit is a new field-radiation biodosimetry immunoassay for rapid triage of individuals exposed to external total-body irradiation. Here, we report on the validation of this immunoassay in human blood cell extracts 0.5 h after in vitro exposure to 137Cs gamma rays, using γ-H2AX analysis. First, calibration curves were established for five donors at doses ranging from 0 to 10 Gy and dose rates ranging from ∼0.8 to ∼3 Gy/min. The calibration curves, together with a γ-H2AX peptide scale, enabled the definition of inter-experimental correction factors. Using previously calculated correction factors, blind dose estimations were performed at 0.5 h postirradiation, and DosiKit performance was compared against concomitant dicentric chromosome assay (DCA), the current gold standard for external irradiation biodosimetry. A prototype was then assembled and field tested. We show that, despite significant inter-individual variations, DosiKit can estimate total-body irradiation doses from 0.5 to 10 Gy with a strong l...

Summary Objective Human-papillomaviruses (HPV) type 16 is a causative agent in an increasing subset of oropharyngeal squamous cell carcinomas (OPSCCs). These tumors have distinct oncogenic mechanisms and a more favorable prognosis than tobacco-induced OPSCCs. Although these differences emphasize the need for a specific therapeutic approach, HPV status is still not used to guide treatment. A better characterization of the molecular profile related to HPV16-induced OPSCC might help to develop personalized treatments. Patients and methods Using a human whole-genome DNA-microarray, we have examined the gene expression profiles in 15 HPV-negative and 15 transcriptionally-active HPV-positive OPSCCs. The study was conducted in two steps. Firstly, a learning/training-set consisting of 8 HPV16-positive and 8 HPV16-negative OPSCCs was analyzed to identify a specific signature. Potentially confounding factors (stage, sex and tobacco) were equally distributed in both groups. Subsequently the robustness of this signature was confirmed by blind case-by-case classification of a validation-set composed of the 14 remaining tumors. Results We have identified a signature composed of 224 genes, which discriminates HPV16-induced OPSCC from their HPV-negative counterparts. After the blind classification of the 14 tumours, the viral status was revealed: 13 out of 14 tumors were correctly classified according to tumor etiology, 1/14 was not determined and none were misclassified. Several of the differentially expressed genes were involved in cell-cycle regulation, DNA replication and repair, transcription regulation, immune response and apoptosis. Conclusion Our study contributes to a better understanding of pathogenic mechanisms involved in the development of HPV-positive OPSCCs and in the identification of potential therapeutic targets.

Exposure to ionizing radiation is a known risk factor for cancer. However, up to now, rigorously defined scientific criteria that could establish case-by-case the radiation-induced (RI) origin of a tumour have been lacking. To identify genes that could constitute a RI signature, we compared the transcriptome of 12 sarcomas arising in the irradiation field of a primary tumour following radiotherapy with the transcriptome of 12 sporadic sarcomas. This learning/training set contained four leiomyosarcomas, four osteosarcomas and four angiosarcomas in each subgroup. We identified a signature of 135 genes discriminating RI from sporadic sarcomas. The robustness of this signature was tested by the blind case-by-case classification of an independent set of 36 sarcomas of various histologies. Thirty-one sarcomas were classified as RI or sporadic; it was not possible to propose an aetiology for the five others. After the code break, it was found that one sporadic sarcoma was misclassified as RI. Thus, the signature is robust with a sensitivity of 96%, a positive and a negative predictive value of 96 and 100%, respectively and a specificity of 62%. The functions of the genes of the signature suggest that RI sarcomas were subject to chronic oxidative stress probably due to mitochondrial dysfunction.

Both external and internal exposure to ionizing radiation are strong risk factors for the development of thyroid tumors. Until now, the diagnosis of radiation-induced thyroid tumors has been deduced from a network of arguments taken together with the individual history of radiation exposure. Neither the histological features nor the genetic alterations observed in these tumors have been shown to be specific fingerprints of an exposure to radiation. The aim of our work is to define ionizing radiation-related molecular specificities in a series of secondary thyroid tumors developed in the radiation field of patients treated by radiotherapy. To identify molecular markers that could represent a radiation-induction signature, we compared 25K microarray transcriptome profiles of a learning set of 28 thyroid tumors, which comprised 14 follicular thyroid adenomas (FTA) and 14 papillary thyroid carcinomas (PTC), either sporadic or consecutive to external radiotherapy in childhood. We identified a signature composed of 322 genes which discriminates radiation-induced tumors (FTA and PTC) from their sporadic counterparts. The robustness of this signature was further confirmed by blind case-by-case classification of an independent set of 29 tumors (16 FTA and 13 PTC). After the histology code break by the clinicians, 26/29 tumors were well classified regarding tumor etiology, 1 was undetermined, and 2 were misclassified. Our results help shed light on radiation-induced thyroid carcinogenesis, since specific molecular pathways are deregulated in radiation-induced tumors.

Methods of classification using transcriptome analysis for case-by-case tumor diagnosis could be limited by tumor heterogeneity and masked information in the gene expression profiles, especially as the number of tumors is small. We propose a new strategy, EMts_2PCA, based on: 1) The identification of a gene expression signature with a great potential for discriminating subgroups of tumors (EMts stage), which includes: a) a learning step, based on an expectation-maximization (EM) algorithm, to select sets of candidate genes whose expressions discriminate two subgroups, b) a training step to select from the sets of candidate genes those with the highest potential to classify training tumors, c) the compilation of genes selected during the training step, and standardization of their levels of expression to finalize the signature. 2) The predictive classification of independent prospective tumors, according to the two subgroups of interest, by the definition of a validation space based on a two-step principal component analysis (2PCA). The present method was evaluated by classifying three series of tumors and its robustness, in terms of tumor clustering and prediction, was further compared with that of three classification methods (Gene expression bar code, Top-scoring pair(s) and a PCA-based method). Results showed that EMts_2PCA was very efficient in tumor classification and prediction, with scores always better that those obtained by the most common methods of tumor clustering. Specifically, EMts_2PCA permitted identification of highly discriminating molecular signatures to differentiate post-Chernobyl thyroid or post-radiotherapy breast tumors from their sporadic counterparts that were previously unsuccessfully classified or classified with errors.

The purpose of this research was to identify novel genes that can be targeted as diagnostic and clinical markers of differentiated thyroid tumors.Gene expression analysis using microarray platform was performed on 6 pathologically normal thyroid samples and 12 primary follicular and papillary thyroid neoplasms. Microarrays containing probes for 5,760 human full-length cDNAs were used for hybridization with total RNA from normal and tumor thyroid samples labeled with Cy3-dUTP and Cy5-dUTP, respectively. Scanned array images were recorded, and data analysis was performed. Selected sets of differentially expressed genes were analyzed using quantitative real-time reverse transcription-PCR for verification.We identified 155 genes that differentiate histologically normal thyroid tissues from benign and malignant thyroid neoplasms. Of these 75 genes were differentiated between follicular neoplasms (adenoma and carcinoma) and the follicular variant of papillary carcinoma. Purely follicular neoplasms (adenomas and carcinomas) shared many genetic profiles, and only 43 genes were distinctly different between these tumors. Hierarchical cluster analysis also differentiated conventional papillary carcinoma from its follicular variant and follicular tumors. The differentially expressed genes were composed of members of cell differentiation, adhesion, immune response, and proliferation associated pathways. Quantitative real-time reverse transcription-PCR analysis of selected genes corroborated the microarray expression results.Our study show the following: (1) differences in gene expression between tumor and nontumor bearing normal thyroid tissue can be identified, (2) a set of genes differentiate follicular neoplasm from follicular variant of papillary carcinoma, (3) follicular adenoma and carcinoma share many of the differentiated genes, and (4) gene expression differences identify conventional papillary carcinoma from the follicular variant.