Genomic aberrations in borderline ovarian tumors

<p>Abstract</p> <p>Background</p> <p>According to the scientific literature, less than 30 borderline ovarian tumors have been karyotyped and less than 100 analyzed for genomic imbalances by CGH.</p> <p>Methods</p> <p>We report a series of borderline ovarian tumors (n = 23) analyzed by G-banding and karyotyping as well as high resolution CGH; in addition, the tumors were analyzed for microsatellite stability status and by FISH for possible 6q deletion.</p> <p>Results</p> <p>All informative tumors were microsatellite stable and none had a deletion in 6q27. All cases with an abnormal karyotype had simple chromosomal aberrations with +7 and +12 as the most common. In three tumors with single structural rearrangements, a common breakpoint in 3q13 was detected. The major copy number changes detected in the borderline tumors were gains from chromosome arms 2q, 6q, 8q, 9p, and 13q and losses from 1p, 12q, 14q, 15q, 16p, 17p, 17q, 19p, 19q, and 22q. The series included five pairs of bilateral tumors and, in two of these pairs, informative data were obtained as to their clonal relationship. In both pairs, similarities were found between the tumors from the right and left side, strongly indicating that bilaterality had occurred via a metastatic process. The bilateral tumors as a group showed more aberrations than did the unilateral ones, consistent with the view that bilaterality is a sign of more advanced disease.</p> <p>Conclusion</p> <p>Because some of the imbalances found in borderline ovarian tumors seem to be similar to imbalances already known from the more extensively studied overt ovarian carcinomas, we speculate that the subset of borderline tumors with detectable imbalances or karyotypic aberrations may contain a smaller subset of tumors with a tendency to develop a more malignant phenotype. The group of borderline tumors with no imbalances would, in this line of thinking, have less or no propensity for clonal evolution and development to full-blown carcinomas.</p

Reduced expression of BAX is associated with poor prognosis in patients with epithelial ovarian cancer: a multifactorial analysis of TP53, p21, BAX and BCL-2

Traditional clinicopathological features do not predict which patients will develop chemotherapy resistance. The TP53 gene is frequently altered in ovarian cancer but its prognostic implications are controversial. Little is known on the impact of TP53-downstream genes on prognosis. Using molecular and immunohistochemical analyses we examined TP53 and its downstream genes p21 BAX and BCL-2 in ovarian tumour tissues and have evaluated the results in relation to clinico-pathological parameters, clinical outcome and response to platinum-based chemotherapy. Associations of tested factors and patient and tumour characteristics were studied by Spearman rank correlation and Pearsons χ2 test. The Cox proportional hazard model was used for univariate and multivariate analysis. The associations of tested factors with response was tested using logistic regression analysis. TP53 mutation, p21 and BCL-2 expression were not associated with increased rates of progression and death. Expression of TP53 was associated with a shorter overall survival only (relative hazard rate [RHR] 2.01 P = 0.03). Interestingly, when combining TP53 mutation and expression data, this resulted in an increased association with overall survival (P = 0.008). BAX expression was found to be associated with both progression-free (RHR 0.44 P = 0.05) and overall survival (RHR 0.42 P = 0.03). Those patients who simultaneously expressed BAX and BCL-2 had a longer progression-free and overall survival compared to patients whose tumours did not express BCL-2 (P = 0.05 and 0.015 respectively). No relations were observed between tested factors and response to platinum-based chemotherapy. We conclude that BAX expression may represent a prognostic indicator for patients with ovarian cancer and that the combined evaluation of BAX and BCL-2 may provide additional prognostic significance.   http://www.bjcancer.com © 2001 Cancer Research Campaig

Bayesian Dynamical Systems Modelling in the Social Sciences

Data arising from social systems is often highly complex, involving non-linear relationships between the macro-level variables that characterize these systems. We present a method for analyzing this type of longitudinal or panel data using differential equations. We identify the best non-linear functions that capture interactions between variables, employing Bayes factor to decide how many interaction terms should be included in the model. This method punishes overly complicated models and identifies models with the most explanatory power. We illustrate our approach on the classic example of relating democracy and economic growth, identifying non-linear relationships between these two variables. We show how multiple variables and variable lags can be accounted for and provide a toolbox in R to implement our approach

Transcriptional Dynamics Reveal Critical Roles for Non-coding RNAs in the Immediate-Early Response

<div><p>The immediate-early response mediates cell fate in response to a variety of extracellular stimuli and is dysregulated in many cancers. However, the specificity of the response across stimuli and cell types, and the roles of non-coding RNAs are not well understood. Using a large collection of densely-sampled time series expression data we have examined the induction of the immediate-early response in unparalleled detail, across cell types and stimuli. We exploit cap analysis of gene expression (CAGE) time series datasets to directly measure promoter activities over time. Using a novel analysis method for time series data we identify transcripts with expression patterns that closely resemble the dynamics of known immediate-early genes (IEGs) and this enables a comprehensive comparative study of these genes and their chromatin state. Surprisingly, these data suggest that the earliest transcriptional responses often involve promoters generating non-coding RNAs, many of which are produced in advance of canonical protein-coding IEGs. IEGs are known to be capable of induction without de novo protein synthesis. Consistent with this, we find that the response of both protein-coding and non-coding RNA IEGs can be explained by their transcriptionally poised, permissive chromatin state prior to stimulation. We also explore the function of non-coding RNAs in the attenuation of the immediate early response in a small RNA sequencing dataset matched to the CAGE data: We identify a novel set of microRNAs responsible for the attenuation of the IEG response in an estrogen receptor positive cancer cell line. Our computational statistical method is well suited to meta-analyses as there is no requirement for transcripts to pass thresholds for significant differential expression between time points, and it is agnostic to the number of time points per dataset.</p></div

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201