Biomedical subjects

Vincent Detours

Publications and source records attributed to Vincent Detours.

5 recordsLinked to original sources

PubMed2005

Gene expression in human thyrocytes and autonomous adenomas reveals suppression of negative feedbacks in tumorigenesis.

The cAMP signaling pathway regulates growth of many cell types, including somatotrophs, thyrocytes, melanocytes, ovarian follicular granulosa cells, adrenocortical cells, and keratinocytes. Mutations of partners from the cAMP signaling cascade are involved in tumor formation. Thyroid-stimulating hormone (TSH) receptor and Gsalpha activating mutations have been detected in thyroid autonomous adenomas, Gsalpha mutations in growth hormone-secreting pituitary adenomas, and PKAR1A mutations in Carney complex, a multiple neoplasia syndrome. To gain more insight into the role of cAMP signaling in tumor formation, human primary cultures of thyrocytes were treated for different times (1.5, 3, 16, 24, and 48 h) with TSH to characterize modulations in gene expression using cDNA microarrays. This kinetic study showed a clear difference in expression, early (1.5 and 3 h) and late (16-48 h) after the onset of TSH stimulation. This result suggests a progressive sequential process leading to a change of cell program. The gene expression profile of the long-term stimulated cultures resembled the autonomous adenomas, but not papillary carcinomas. The molecular phenotype of the adenomas thus confirms the role of long-term stimulation of the TSH-cAMP cascade in the pathology. TSH induced a striking up-regulation of different negative feedback modulators of the cAMP cascade, presumably insuring the one-shot effect of the stimulus. Some were down- or nonregulated in adenomas, suggesting a loss of negative feedback control in the tumors. These results suggest that in tumorigenesis, activation of proliferation pathways may be complemented by suppression of multiple corresponding negative feedbacks, i.e., specific tumor suppressors.

Adenoma↗

PubMed2005

Gene expression in thyroid autonomous adenomas provides insight into their physiopathology.

The purpose of this study was to use the microarray technology to define expression profiles characteristic of thyroid autonomous adenomas and relate these findings to physiological mechanisms. Experiments were performed on a series of separated adenomas and their normal counterparts on Micromax cDNA microarrays covering 2400 genes (analysis I), and on a pool of adenomatous tissues and their corresponding normal counterparts using microarrays of 18,000 spots (analysis II). Results for genes present on the two arrays corroborated and several gene regulations previously determined by Northern blotting or microarrays in similar lesions were confirmed. Five overexpressed and 24 underexpressed genes were also confirmed by real-time RT-PCR in some of the samples used for microarray analysis, and in additional tumor specimens. Our results show: (1) a change in the cell populations of the tumor, with a marked decrease in lymphocytes and blood cells and an increase in endothelial cells. The latter increase would correspond to the establishment of a close relation between thyrocytes and endothelial cells and is related to increased N-cadherin expression. It explains the increased blood flow in the tumor; (2) a homogeneity of tumor samples correlating with their common physiopathological mechanism: the constitutive activation of the thyrotropin (TSH)/cAMP cascade; (3) a low proportion of regulated genes consistent with the concept of a minimal deviation tumor; (4) a higher expression of genes coding for specific functional proteins, consistent with the functional hyperactivity of the tumors; (5) an increase of phosphodiesterase gene expression which explains the relatively low cyclic AMP levels measured in these tumors; (6) an overexpression of antiapoptotic genes and underexpression of proapoptotic genes compatible with their low apoptosis rate; (7) an overexpression of N-cadherin and downregulation of caveolins, which casts doubt about the use of these expressions as markers for malignancy.

Adenoma↗

PubMed2003

Integration and cross-validation of high-throughput gene expression data: comparing heterogeneous data sets.

Data analysis--not data production--is becoming the bottleneck in gene expression research. Data integration is necessary to cope with an ever increasing amount of data, to cross-validate noisy data sets, and to gain broad interdisciplinary views of large biological data sets. New Internet resources may help researchers to combine data sets across different gene expression platforms. However, noise and disparities in experimental protocols strongly limit data integration. A detailed review of four selected studies reveals how some of these limitations may be circumvented and illustrates what can be achieved through data integration.

Animals↗

PubMed2002

Prediction of proteasome cleavage motifs by neural networks.

We present a predictive method that can simulate an essential step in the antigen presentation in higher vertebrates, namely the step involving the proteasomal degradation of polypeptides into fragments which have the potential to bind to MHC Class I molecules. Proteasomal cleavage prediction algorithms published so far were trained on data from in vitro digestion experiments with constitutive proteasomes. As a result, they did not take into account the characteristics of the structurally modified proteasomes--often called immunoproteasomes--found in cells stimulated by gamma-interferon under physiological conditions. Our algorithm has been trained not only on in vitro data, but also on MHC Class I ligand data, which reflect a combination of immunoproteasome and constitutive proteasome specificity. This feature, together with the use of neural networks, a non-linear classification technique, make the prediction of MHC Class I ligand boundaries more accurate: 65% of the cleavage sites and 85% of the non-cleavage sites are correctly determined. Moreover, we show that the neural networks trained on the constitutive proteasome data learns a specificity that differs from that of the networks trained on MHC Class I ligands, i.e. the specificity of the immunoproteasome is different than the constitutive proteasome. The tools developed in this study in combination with a predictor of MHC and TAP binding capacity should give a more complete prediction of the generation and presentation of peptides on MHC Class I molecules. Here we demonstrate that such an approach produces an accurate prediction of the CTL the epitopes in HIV Nef. The method is available at www.cbs.dtu.dk/services/NetChop/.

Algorithms↗

PubMed2002

Clustering patterns of cytotoxic T-lymphocyte epitopes in human immunodeficiency virus type 1 (HIV-1) proteins reveal imprints of immune evasion on HIV-1 global variation.

The human cytotoxic T-lymphocyte (CTL) response to human immunodeficiency virus type 1 (HIV-1) has been intensely studied, and hundreds of CTL epitopes have been experimentally defined, published, and compiled in the HIV Molecular Immunology Database. Maps of CTL epitopes on HIV-1 protein sequences reveal that defined epitopes tend to cluster. Here we integrate the global sequence and immunology databases to systematically explore the relationship between HIV-1 amino acid sequences and CTL epitope distributions. CTL responses to five HIV-1 proteins, Gag p17, Gag p24, reverse transcriptase (RT), Env, and Nef, have been particularly well characterized in the literature to date. Through comparing CTL epitope distributions in these five proteins to global protein sequence alignments, we identified distinct characteristics of HIV amino acid sequences that correlate with CTL epitope localization. First, experimentally defined HIV CTL epitopes are concentrated in relatively conserved regions. Second, the highly variable regions that lack epitopes bear cumulative evidence of past immune escape that may make them relatively refractive to CTLs: a paucity of predicted proteasome processing sites and an enrichment for amino acids that do not serve as C-terminal anchor residues. Finally, CTL epitopes are more highly concentrated in alpha-helical regions of proteins. Based on amino acid sequence characteristics, in a blinded fashion, we predicted regions in HIV regulatory and accessory proteins that would be likely to contain CTL epitopes; these predictions were then validated by comparison to new sets of experimentally defined epitopes in HIV-1 Rev, Tat, Vif, and Vpr.

Amino Acid Sequence↗