DNA methylation profiles delineate epigenetic heterogeneity in seminoma and non-seminoma

Background: It remains important to understand the biology and identify biomarkers for less studied cancers like testicular cancer. The purpose of this study was to determine the methylation frequency of several cancer-related genes in different histological types of testicular cancer and normal testis tissues (NT). Methods: DNA was isolated from 43 seminomas (SEs), 14 non-SEs (NSEs) and 23 NT, and was assayed for promoter methylation status of 15 genes by quantitative methylation-specific PCR. The methylation status was evaluated for an association with cancer, and between SEs and NSEs. Results: We found differential methylation pattern in SEs and NSEs. MGMT, VGF, ER-Β and FKBP4 were predominately methylated in NSEs compared with SEs. APC and hMLH1 are shown to be significantly more methylated in both subtypes in comparison with NT. When combining APC, hMLH1, ER-Β and FKBP4, it is possible to identify 86% of the NSEs, whereas only 7% of the SEs. Conclusions: Our results indicate that the methylation profile of cancer-associated genes in testicular cancer correlates with histological types and show cancer-specific pattern for certain genes. Further methylation analysis, in a larger cohort is needed to elucidate their role in testicular cancer development and potential for therapy, early detection and disease monitoring

Expression in Aneuploid Drosophila S2 Cells

Analysis of the relationship between gene copy number and gene expression in aneuploid male Drosophila cells reveals a global compensation mechanism in addition to X chromosome-specific dosage compensation

Demographic variation in incidence of adult glioma by subtype, United States, 1992-2007

<p>Abstract</p> <p>Background</p> <p>We hypothesized that race/ethnic group, sex, age, and/or calendar period variation in adult glioma incidence differs between the two broad subtypes of glioblastoma (GBM) and non-GBM. Primary GBM, which constitute 90-95% of GBM, differ from non-GBM with respect to a number of molecular characteristics, providing a molecular rationale for these two broad glioma subtypes.</p> <p>Methods</p> <p>We utilized data from the Surveillance, Epidemiology, and End Results Program for 1992-2007, ages 30-69 years. We compared 15,088 GBM cases with 9,252 non-GBM cases. We used Poisson regression to calculate adjusted rate ratios and 95% confidence intervals.</p> <p>Results</p> <p>The GBM incidence rate increased proportionally with the 4^thpower of age, whereas the non-GBM rate increased proportionally with the square root of age. For each subtype, compared to non-Hispanic Whites, the incidence rate among Blacks, Asians/Pacific Islanders, and American Indians/Alaskan Natives was substantially lower (one-fourth to one-half for GBM; about two-fifths for non-GBM). Secondary to this primary effect, race/ethnic group variation in incidence was significantly less for non-GBM than for GBM. For each subtype, the incidence rate was higher for males than for females, with the male/female rate ratio being significantly higher for GBM (1.6) than for non-GBM (1.4). We observed significant calendar period trends of increasing incidence for GBM and decreasing incidence for non-GBM. For the two subtypes combined, we observed a 3% decrease in incidence between 1992-1995 and 2004-2007.</p> <p>Conclusions</p> <p>The substantial difference in age effect between GBM and non-GBM suggests a fundamental difference in the genesis of primary GBM (the driver of GBM incidence) versus non-GBM. However, the commonalities between GBM and non-GBM with respect to race/ethnic group and sex variation, more notable than the somewhat subtle, albeit statistically significant, differences, suggest that within the context of a fundamental difference, some aspects of the complex process of gliomagenesis are shared by these subtypes as well. The increasing calendar period trend of GBM incidence coupled with the decreasing trend of non-GBM incidence may at least partly be due to a secular trend in diagnostic fashion, as opposed to real changes in incidence of these subtypes.</p

Transmembrane protein 50b (C21orf4), a candidate for Down syndrome neurophenotypes, encodes an intracellular membrane protein expressed in the rodent brain

Transmembrane protein 50b, Tmem50b, previously referred to as C21orf4, encodes a predicted transmembrane protein and is one of few genes significantly over-expressed during cerebellar development in a Down syndrome mouse model, Ts1Cje. In order to assess potential mechanisms by which Tmem50b could contribute to Down syndrome–related phenotypes, we determined the expression patterns of Tmem50b mRNA, as well as Tmem50b protein distribution, expression and subcellular localization. In situ hybridization in mice at embryonic day 14.5 showed cortical plate and spinal cord mRNA expression. By postnatal day 7, strong mRNA expression was seen in the cerebellum, hippocampus and olfactory bulb, with diffuse cortical expression. Quantitative PCR of adult mouse tissue showed Tmem50b mRNA expression in the brain, heart and testis. A rabbit polyclonal antibody was generated against Tmem50b and rat and mouse tissue screening by Western blot, and immunohistochemistry showed that protein expression concurred with mRNA expression. Double immunofluorescence revealed that Tmem50b is highly expressed in rat and mouse glial fibrillary acidic protein–positive cells in vivo and in vitro, but less so in neuronal MAP2- or β-tubulin II-positive cells in vitro. Tmem50b is invariably expressed in cultured mouse neural precursor cells. In adult mouse cerebellum sections, Tmem50b immunoreactivity was found in Purkinje and Golgi cell somata and in Bergmann glial processes. Electron microscopy confirmed that Tmem50b was present on endoplasmic reticulum (ER) and Golgi apparatus membranes. Results indicate that Tmem50b is a developmentally-regulated intracellular ER and Golgi apparatus membrane protein that may prove important for correct brain development through functions associated with precursor cells and glia

Comparative analysis of two 14-3-3 homologues and their expression pattern in the root-knot nematode Meloidogyne incognita.

International audience14-3-3 proteins are highly conserved ubiquitous proteins found in all eukaryotic organisms. They are involved in various cellular processes including signal transduction, cell-cycle control, apoptosis, stress response and cytoskeleton organisation. We report here the cloning of two genes encoding 14-3-3 isoforms from the plant parasitic root-knot nematode Meloidogyne incognita, together with an analysis of their expression. Both genes were shown to be transcribed in unhatched second stage larvae, infective second stage larvae, adult males and females. The Mi-14-3-3-a gene was shown to be specifically transcribed in the germinal primordium of infective larvae, whereas Mi-14-3-3-b was transcribed in the dorsal oesophageal gland in larvae of this stage. The MI-14-3-3-B protein was identified by mass spectrometry in in vitro-induced stylet secretions from infective larvae. The stability and distribution of MI-14-3-3 proteins in host plant cells was assessed after stable expression of the corresponding genes in tobacco BY2 cells

IRIT at TREC’2002: Web Track

The tests we performed for TREC’2002 web track focus on the web distillation part. The aim of our participation is to experiment our method for topic distillation combined with a new version of our system Mercure and to validate our system on a large collection of web pages: 18 Go of data. This year, three runs were submitted to NIST. 2 Mercure model Mercure is an information retrieval system based on a connexionist approach and modeled by a multi-layered network. The network is composed of a query layer (set of query terms), a term layer (representing the indexing terms) and a document layer [Boughanem99]. Mercure includes the implementation of a retrieval process based on spreading activation forward and backward through the weighted links. Queries and documents can be used either as inputs or outputs. The links between layers are symmetric and their weights are based on tfidf measure inspired from OKAPI [Robertson00] and SMART term weighting.- the query-term links (at stage s) are weighted as follows: q � n