Puma and Trail/Dr5 Pathways Control Radiation-Induced Apoptosis in Distinct Populations of Testicular Progenitors

Spermatogonia- stem cells and progenitors of adult spermatogenesis- are killed through a p53-regulated apoptotic process after γ-irradiation but the death effectors are still poorly characterized. Our data demonstrate that both intrinsic and extrinsic apoptotic pathways are involved, and especially that spermatogonia can be split into two main populations, according to apoptotic effectors. Following irradiation both Dr5 and Puma genes are upregulated in the α6-integrin-positive Side Population (SP) fraction, which is highly enriched in spermatogonia. Flow cytometric analysis confirms an increased number of Dr5-expressing SP cells, and Puma-β isoform accumulates in α6-integrin positive cellular extracts, enriched in spermatogonia. Trail−/− or Puma−/− spermatogonia display a reduced sensitivity to radiation-induced apoptosis. The TUNEL kinetics strongly suggest that the extrinsic and intrinsic pathways, via Trail/Dr5 and Puma respectively, could be engaged in distinct subpopulations of spermatogonia. Indeed flow cytometric studies show that Dr5 receptor is constitutively present on more than half of the undifferentiated progenitors (Kit− α6+ SP) and half of the differentiated ones (Kit+ α6+ SP). In addition after irradiation, Puma is not detected in the Dr5-positive cellular fraction isolated by immunomagnetic purification, while Puma is present in the Dr5-negative cell extracts. In conclusion, adult testicular progenitors are divided into distinct sub-populations by apoptotic effectors, independently of progenitor types (immature Kit-negative versus mature Kit-positive), underscoring differential radiosensitivities characterizing the stem cell/progenitors compartment

Gene expression signature discriminates sporadic from post-radiotherapy-induced thyroid tumors

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

Discriminating Gene Expression Signature of Radiation-Induced Thyroid Tumors after Either External Exposure or Internal Contamination

Both external radiation exposure and internal radionuclide contamination are well known risk factors in the development of thyroid epithelial tumors. The identification of specific molecular markers deregulated in radiation-induced thyroid tumors is important for the etiological diagnosis since neither histological features nor genetic alterations can discriminate between sporadic and radiation-induced tumors. Identification of highly discriminating markers in radiation-induced tumors is challenging as it relies on the ability to identify marker deregulation which is associated with a cellular stress that occurred many years before in the thyroid cells. The existence of such a signature is still controversial, as it was not found in several studies while a highly discriminating signature was found in both post-radiotherapy and post-Chernobyl series in other studies. Overall, published studies searching for radiation-induced thyroid tumor specificities, using transcriptomic, proteomic and comparative genomic hybridization approaches, and bearing in mind the analytical constraints required to analyze such small series of tumors, suggest that such a molecular signature could be found. In comparison with sporadic tumors, we highlight molecular similarities and specificities in tumors occurring after high-dose external radiation exposure, such as radiotherapy, and in post-Chernobyl tumors that occurred after internal 131I contamination. We discuss the relevance of signature extrapolation from series of tumors developing after high and low doses in the identification of tumors induced at very low doses of radiation

Strategy to Find Molecular Signatures in a Small Series of Rare Cancers: Validation for Radiation-Induced Breast and Thyroid 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

Abstract 5636: Gene expression signature discriminates sporadic from post-radiotherapy radiation-induced sarcomas

Abstract The purpose of the study is to identify markers that could define a robust signature discriminating case by case radiation-induced tumors from their sporadic counterparts. The rare occurrence of human radiation-induced tumors increases the difficulty of their identification. Nevertheless, in case of sarcomas occurring in the irradiation field after radiotherapy for a primary neoplasm, stringent criteria allow the radiation-induced etiology to be established with a high level of confidence. However, the available series remains limited. Global transcriptome studies are particularly affected by this problem since the methods used for data analysis are generally efficient only for long series. In order to solve this problem, we have developped new methods of classification, based on transcriptome analysis, for the case by case tumor diagnosis. To find a signature we first select a set of candidate genes, using Expectation-Maximisation algorithm, on a learning set of tumors. Second, using a training set of tumors, we select the genes with the higher potential for classifying the tumors. Then, the robustness of the signature was tested by blindly classifying an independent set of tumors. Using a learning/training set of 12 radiation-induced (RI) and 12 sporadic (SP) sarcomas including angiosarcomas, leiomyosarcomas and osteosarcomas, we identified a minimal signature of 143 genes discriminating the sarcomas according to the etiology. A larger signature of 1100 genes, using less stringent criteria of classification was also established. The robustness of these signatures was tested by the blindly case by case classification of an independent set of 22 RI and 14 SP sarcomas of various histologies. After the histology code-break, 28/36 sarcomas were well-classified using the minimal signature, in 6 cases (1 RI and 5 SP) the etiology could not be established whereas 2 SP sarcomas were classified as RI. Using the large signature, the etiology was not determined in 4 cases (1 RI and 3 SP) and the 32 other sarcomas were well-classified. Several pathway were found differentially expressed according to the etiology. Notably, the NRF2-mediated oxidative stress response pathway, the ubiquitination-deubiquitination pathways and several genes coding subunits of the 26S proteasome and heat shock proteins underwent a general up regulation in RI sarcomas. These data suggest that RI sarcomas are submitted to oxidative stress that could generate the formation of mis-folded and oxidated proteins further degradated by the ubiquitination-deubiquitination-proteasome pathway. In this study, we identify a robust signature discriminating radiation-induced from sporadic sarcomas, opening the possibility to recognise, case by case, the implication of ionizing radiation in a tumor formation. Note: This abstract was not presented at the AACR 101st Annual Meeting 2010 because the presenter was unable to attend. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 5636.</jats:p

Gazéifieur optimisé pour la production de dihydrogène avec capture de CO2

La présente invention concerne un dispositif et un procédé de production de dihydrogène à partir de CO et H2O, selon la réaction de gaz à l'eau (a) CO + H2O → CO2 + H2, caractérisé en ce qu’un mélange gazeux comprenant CO et H2O circule dans un tube réactionnel (1) de diamètre compris en 5 mm et 500 mm, d'une longueur comprise entre 50 mm et 10m, disposé dans un réacteur de gazéification, et est soumis à au moins une radiation, choisie parmi une radiation électromagnétique allant des rayons gamma aux ondes radio supérieures à 500 kHz, en passant par les ondes visibles infrarouge et ultraviolet ou radio active gamma, micro-onde, radiation nucléaire telle que alpha, béta, thermique