Uterine tumours are a phenotypic manifestation of the hyperparathyroidism-jaw tumour syndrome

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74672/1/j.1365-2796.2004.01421.x.pd

Heritability and major gene effects on left ventricular mass in the Chinese population: a family study

BACKGROUND: Genetic components controlling for echocardiographically determined left ventricular (LV) mass are still unclear in the Chinese population. METHODS: We conducted a family study from the Chin-San community, Taiwan, and a total of 368 families, 1145 subjects, were recruited to undergo echocardiography to measure LV mass. Commingling analysis, familial correlation, and complex segregation analysis were applied to detect component distributions and the mode of inheritance. RESULTS: The two-component distribution model was the best-fitting model to describe the distribution of LV mass. The highest familial correlation coefficients were mother-son (0.379, P < .0001) and father-son (0.356, P < .0001). Genetic heritability (h(2)) of LV mass was estimated as 0.268 ± 0.061 (P < .0001); it decreased to 0.153 ± 0.052 (P = .0009) after systolic blood pressure adjustment. Major gene effects with polygenic components were the best-fitting model to explain the inheritance mode of LV mass. The estimated allele frequency of the gene was 0.089. CONCLUSION: There were significant familial correlations, heritability and a major gene effect on LV mass in the population-based families

Gene expression profile of cervical and skin tissues from human papillomavirus type 16 E6 transgenic mice

<p>Abstract</p> <p>Background</p> <p>Although K14E6 transgenic mice develop spontaneous tumors of the skin epithelium, no spontaneous reproductive tract malignancies arise, unless the transgenic mice were treated chronically with 17β-estradiol. These findings suggest that E6 performs critical functions in normal adult cervix and skin, highlighting the need to define E6-controlled transcriptional programs in these tissues.</p> <p>Methods</p> <p>We evaluated the expression profile of 14,000 genes in skin or cervix from young K14E6 transgenic mice compared with nontransgenic. To identify differentially expressed genes a linear model was implemented using R and the LIMMA package. Two criteria were used to select the set of relevant genes. First a set of genes with a Log-odds ≥ 3 were selected. Then, a hierarchical search of genes was based on Log Fold Changes.</p> <p>Results</p> <p>Microarray analysis identified a total of 676 and 1154 genes that were significantly up and down-regulated, respectively, in skin from K14E6 transgenic mice. On the other hand, in the cervix from K14E6 transgenic mice we found that only 97 and 252 genes were significantly up and down-regulated, respectively. One of the most affected processes in the skin from K14E6 transgenic mice was the cell cycle. We also found that skin from transgenic mice showed down-regulation of pro-apoptotic genes and genes related to the immune response. In the cervix of K14E6 transgenic mice, we could not find affected any gene related to the cell cycle and apoptosis pathways but did observe alterations in the expression of immune response genes. Pathways such as angiogenesis, cell junction and epidermis development, also were altered in their gene expression profiles in both tissues.</p> <p>Conclusion</p> <p>Expression of the HPV16 E6 oncoprotein in our model alters expression of genes that fell into several functional groups providing insights into pathways by which E6 deregulate cell cycle progression, apoptosis, the host resistance to infection and immune function, providing new opportunities for early diagnostic markers and therapeutic drug targets.</p

Risk factor screening to identify women requiring oral glucose tolerance testing to diagnose gestational diabetes : a systematic review and meta-analysis and analysis of two pregnancy cohorts

BACKGROUND: Easily identifiable risk factors including: obesity and ethnicity at high risk of diabetes are commonly used to indicate which women should be offered the oral glucose tolerance test (OGTT) to diagnose gestational diabetes (GDM). Evidence regarding these risk factors is limited however. We conducted a systematic review (SR) and meta-analysis and individual participant data (IPD) analysis to evaluate the performance of risk factors in identifying women with GDM. METHODS: We searched MEDLINE, Medline in Process, Embase, Maternity and Infant Care and the Cochrane Central Register of Controlled Trials (CENTRAL) up to August 2016 and conducted additional reference checking. We included observational, cohort, case-control and cross-sectional studies reporting the performance characteristics of risk factors used to identify women at high risk of GDM. We had access to IPD from the Born in Bradford and Atlantic Diabetes in Pregnancy cohorts, all pregnant women in the two cohorts with data on risk factors and OGTT results were included. RESULTS: Twenty nine published studies with 211,698 women for the SR and a further 14,103 women from two birth cohorts (Born in Bradford and the Atlantic Diabetes in Pregnancy study) for the IPD analysis were included. Six studies assessed the screening performance of guidelines; six examined combinations of risk factors; eight evaluated the number of risk factors and nine examined prediction models or scores. Meta-analysis using data from published studies suggests that irrespective of the method used, risk factors do not identify women with GDM well. Using IPD and combining risk factors to produce the highest sensitivities, results in low specificities (and so higher false positives). Strategies that use the risk factors of age (>25 or >30) and BMI (>25 or 30) perform as well as other strategies with additional risk factors included. CONCLUSIONS: Risk factor screening methods are poor predictors of which pregnant women will be diagnosed with GDM. A simple approach of offering an OGTT to women 25 years or older and/or with a BMI of 25kg/m2 or more is as good as more complex risk prediction models. Research to identify more accurate (bio)markers is needed. Systematic Review Registration: PROSPERO CRD42013004608

Desmoglein 3, via an Interaction with E-cadherin, Is Associated with Activation of Src

Desmoglein 3 (Dsg3), a desmosomal adhesion protein, is expressed in basal and immediate suprabasal layers of skin and across the entire stratified squamous epithelium of oral mucosa. However, increasing evidence suggests that the role of Dsg3 may involve more than just cell-cell adhesion.To determine possible additional roles of Dsg3 during epithelial cell adhesion we used overexpression of full-length human Dsg3 cDNA, and RNAi-mediated knockdown of this molecule in various epithelial cell types. Overexpression of Dsg3 resulted in a reduced level of E-cadherin but a colocalisation with the E-cadherin-catenin complex of the adherens junctions. Concomitantly these transfected cells exhibited marked migratory capacity and the formation of filopodial protrusions. These latter events are consistent with Src activation and, indeed, Src-specific inhibition reversed these phenotypes. Moreover Dsg3 knockdown, which also reversed the decreased level of E-cadherin, partially blocked Src phosphorylation.Our data are consistent with the possibility that Dsg3, as an up-stream regulator of Src activity, helps regulate adherens junction formation

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe