MicroRNA Expression Array Identifies Novel Diagnostic Markers for Conventional and Oncocytic Follicular Thyroid Carcinomas

Objective:The most difficult thyroid tumors to be diagnosed by cytology and histology are conventional follicular carcinomas (cFTCs) and oncocytic follicular carcinomas (oFTCs). Several microRNAs (miRNAs) have been previously found to be consistently deregulated in papillary thyroid carcinomas; however, very limited information is available for cFTC and oFTC. The aim of this study was to explore miRNA deregulation and find candidate miRNA markers for follicular carcinomas that can be used diagnostically.Design:Thirty-eight follicular thyroid carcinomas (21 cFTCs, 17 oFTCs) and 10 normal thyroid tissue samples were studied for expression of 381 miRNAs using human microarray assays. Expression of deregulated miRNAs was confirmed by individual RT-PCR assays in all samples. In addition, 11 follicular adenomas, two hyperplastic nodules (HNs), and 19 fine-needle aspiration samples were studied for expression of novel miRNA markers detected in this study.Results:The unsupervised hierarchical clustering analysis demonstrated individual clusters for cFTC and oFTC, indicating the difference in miRNA expression between these tumor types. Both cFTCs and oFTCs showed an up-regulation of miR-182/-183/-221/-222/-125a-3p and a down-regulation of miR-542-5p/-574-3p/-455/-199a. Novel miRNA (miR-885-5p) was found to be strongly up-regulated (>40-fold) in oFTCs but not in cFTCs, follicular adenomas, and HNs. The classification and regression tree algorithm applied to fine-needle aspiration samples demonstrated that three dysregulated miRNAs (miR-885-5p/-221/-574-3p) allowed distinguishing follicular thyroid carcinomas from benign HNs with high accuracy.Conclusions:In this study we demonstrate that different histopathological types of follicular thyroid carcinomas have distinct miRNA expression profiles. MiR-885-5p is highly up-regulated in oncocytic follicular carcinomas and may serve as a diagnostic marker for these tumors. A small set of deregulated miRNAs allows for an accurate discrimination between follicular carcinomas and hyperplastic nodules and can be used diagnostically in fine-needle aspiration biopsies.

Performance Modeling Of Reconfigurable Distributed Systems Based On The Opensparc Fpga Board And The Sirc Communication Framewor

This thesis explores system performance for reconfigurable distributed systems and provides an analytical model for determining throughput of theoretical systems based on the OpenSPARC FPGA Board and the SIRC Communication Framework. This model was developed by studying a small set of variables that together determine a system¿s throughput. The importance of this model is in assisting system designers to make decisions as to whether or not to commit to designing a reconfigurable distributed system based on the estimated performance and hardware costs. Because custom hardware design and distributed system design are both time consuming and costly, it is important for designers to make decisions regarding system feasibility early in the development cycle. Based on experimental data the model presented in this paper shows a close fit with less than 10% experimental error on average. The model is limited to a certain range of problems, but it can still be used given those limitations and also provides a foundation for further development of modeling reconfigurable distributed systems.

SNP array profiling of childhood adrenocortical tumors reveals distinct pathways of tumorigenesis and highlights candidate driver genes

Childhood adrenocortical tumors (ACT) are rare malignancies, except in southern Brazil, where a higher incidence rate is associated to a high frequency of the founder R337H TP53 mutation. To date, copy number alterations in these tumors have only been analyzed by low-resolution comparative genomic hybridization.

Transient rhythmic network activity in the somatosensory cortex evoked by distributed input in vitro

The initiation and maintenance of physiological and pathophysiological oscillatory activity depends on the synaptic interactions within neuronal networks. We studied the mechanisms underlying evoked transient network oscillation in acute slices of the adolescent rat somatosensory cortex and modeled its underpinning mechanisms. Oscillations were evoked by brief spatially distributed noisy extracellular stimulation, delivered via bipolar electrodes. Evoked transient network oscillation was detected with multi-neuron patch-clamp recordings under different pharmacological conditions. The observed oscillations are in the frequency range of 2-5 Hz and consist of 4-12 mV large, 40-150 ms wide compound synaptic events with rare overlying action potentials. This evoked transient network oscillation is only weakly expressed in the somatosensory cortex and requires increased [K+]o of 6.25 mM and decreased [Ca2+]o of 1.5 mM and [Mg2+]o of 0.5 mM. A peak in the cross-correlation among membrane potential in layers II/III, IV and V neurons reflects the underlying network-driven basis of the evoked transient network oscillation. The initiation of the evoked transient network oscillation is accompanied by an increased [K+]o and can be prevented by the K+ channel blocker quinidine. In addition, a shift of the chloride reversal potential takes place during stimulation, resulting in a depolarizing type A GABA (GABAA) receptor response. Blockade of alpha-amino-3-hydroxy-5-methyl-4-isoxazole-proprionate (AMPA), N-methyl-D-aspartate (NMDA), or GABA(A) receptors as well as gap junctions prevents evoked transient network oscillation while a reduction of AMPA or GABA(A) receptor desensitization increases its duration and amplitude. The apparent reversal potential of -27 mV of the evoked transient network oscillation, its pharmacological profile, as well as the modeling results suggest a mixed contribution of glutamatergic, excitatory GABAergic, and gap junctional conductances in initiation and maintenance of this oscillatory activity. With these properties, evoked transient network oscillation resembles epileptic afterdischarges more than any other form of physiological or pathophysiological neocortical oscillatory activity.

A Faster Circular Binary Segmentation Algorithm for the Analysis of Array CGH Data

Motivation: Array CGH technologies enable the simultaneous measurement of DNA copy number for thousands of sites on a genome. We developed the circular binary segmentation (CBS) algorithm to divide the genome into regions of equal copy number (Olshen {\it et~al}, 2004). The algorithm tests for change-points using a maximal $t$-statistic with a permutation reference distribution to obtain the corresponding $p$-value. The number of computations required for the maximal test statistic is $O(N^2),$ where $N$ is the number of markers. This makes the full permutation approach computationally prohibitive for the newer arrays that contain tens of thousands markers and highlights the need for a faster. algorithm. Results: We present a hybrid approach to obtain the $p$-value of the test statistic in linear time. We also introduce a rule for stopping early when there is strong evidence for the presence of a change. We show through simulations that the hybrid approach provides a substantial gain in speed with only a negligible loss in accuracy and that the stopping rule further increases speed. We also present the analysis of array CGH data from a breast cancer cell line to show the impact of the new approaches on the analysis of real data. Availability: An R (R Development Core Team, 2006) version of the CBS algorithm has been implemented in the ``DNAcopy'' package of the Bioconductor project (Gentleman {\it et~al}, 2004). The proposed hybrid method for the $p$-value is available in version 1.2.1 or higher and the stopping rule for declaring a change early is available in version 1.5.1 or higher.

Detection of erythropoietin in exhaled breath condensate of nonhypoxic subjects using a multiplex bead array

As a noninvasive method, exhaled breath condensate (EBC) has gained importance to improve monitoring of lung diseases and to detect biomarkers. The aim of the study was to investigate, whether erythropoietin (EPO) is detectable in EBC. EBC was collected from 22 consecutive patients as well as from healthy individuals. Using a multiplex fluorescent bead immunoassay, we detected EPO in EBC, as well as tumour necrosis factor-alpha (TNF-alpha) in 13 out of 22 patients simultaneously (EPO 0.21 +/- 0.03 in U/mL and TNF-alpha 34.6 +/- 4.2 in pg/mL, mean +/- SEM). No significant differences for EPO levels or correlation between EPO and TNF-alpha were found but TNF-alpha was significantly higher in patients with chronic obstructive pulmonary disease (COPD) than in non-COPD (obstructive sleep apnoea, OSA, and lung healthy patients). This is the first report of detection of EPO in EBC. Due to the small study size more data is needed to clarify the role of EPO in EBC.

Bayesian Hidden Markov Modeling of Array CGH Data

Genomic alterations have been linked to the development and progression of cancer. The technique of Comparative Genomic Hybridization (CGH) yields data consisting of fluorescence intensity ratios of test and reference DNA samples. The intensity ratios provide information about the number of copies in DNA. Practical issues such as the contamination of tumor cells in tissue specimens and normalization errors necessitate the use of statistics for learning about the genomic alterations from array-CGH data. As increasing amounts of array CGH data become available, there is a growing need for automated algorithms for characterizing genomic profiles. Specifically, there is a need for algorithms that can identify gains and losses in the number of copies based on statistical considerations, rather than merely detect trends in the data. We adopt a Bayesian approach, relying on the hidden Markov model to account for the inherent dependence in the intensity ratios. Posterior inferences are made about gains and losses in copy number. Localized amplifications (associated with oncogene mutations) and deletions (associated with mutations of tumor suppressors) are identified using posterior probabilities. Global trends such as extended regions of altered copy number are detected. Since the posterior distribution is analytically intractable, we implement a Metropolis-within-Gibbs algorithm for efficient simulation-based inference. Publicly available data on pancreatic adenocarcinoma, glioblastoma multiforme and breast cancer are analyzed, and comparisons are made with some widely-used algorithms to illustrate the reliability and success of the technique.