A new design of nanocrystalline silicon optical devices based on 3-dimensional photonic crystal structures

We propose a new design of nanocrystalline silicon optical devices which are based on control of electromagnetic fields, electronic states, as well as the phonon dispersion of size-controlled silicon quantum dots

Meta-analysis of gene expression microarrays with missing replicates

<p>Abstract</p> <p>Background</p> <p>Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combined using meta-analysis, in order to increase the overall sample size. However, some genes are not measured in all experiments, hence they cannot be included or their statistical significance cannot be appropriately estimated in traditional meta-analysis. Nonetheless, these genes, which we refer to as <it>incomplete genes</it>, may also be informative and useful.</p> <p>Results</p> <p>We propose a meta-analysis framework, called "Incomplete Gene Meta-analysis", which can include incomplete genes by imputing the significance of missing replicates, and computing a meta-score for every gene across all datasets. We demonstrate that the incomplete genes are worthy of being included and our method is able to appropriately estimate their significance in two groups of experiments. We first apply the <it>Incomplete Gene Meta-analysis </it>and several comparable methods to five breast cancer datasets with an identical set of probes. We simulate incomplete genes by randomly removing a subset of probes from each dataset and demonstrate that our method consistently outperforms two other methods in terms of their false discovery rate. We also apply the methods to three gastric cancer datasets for the purpose of discriminating diffuse and intestinal subtypes.</p> <p>Conclusions</p> <p>Meta-analysis is an effective approach that identifies more robust sets of differentially expressed genes from multiple studies. The incomplete genes that mainly arise from the use of different platforms may also have statistical and biological importance but are ignored or are not appropriately involved by previous studies. Our Incomplete Gene Meta-analysis is able to incorporate the incomplete genes by estimating their significance. The results on both breast and gastric cancer datasets suggest that the highly ranked genes and associated GO terms produced by our method are more significant and biologically meaningful according to the previous literature.</p

Galectin-3 Facilitates Cell Motility in Gastric Cancer by Up-Regulating Protease-Activated Receptor-1(PAR-1) and Matrix Metalloproteinase-1(MMP-1)

BACKGROUND: Galectin-3 is known to regulate cancer metastasis. However, the underlying mechanism has not been defined. Through the DNA microarray studies after galectin-3 silencing, we demonstrated here that galectin-3 plays a key role in up-regulating the expressions of protease-activated receptor-1 (PAR-1) and matrix metalloproteinase-1 (MMP-1) PAR-1 thereby promoting gastric cancer metastasis. METHODOLOGY/PRINCIPAL FINDINGS: We examined the expression levels of Galectin-3, PAR-1, and MMP-1 in gastric cancer patient tissues and also the effects of silencing these proteins with specific siRNAs and of over-expressing them using specific lenti-viral constructs. We also employed zebrafish embryo model for analysis of in vivo gastric cancer cell invasion. These studies demonstrated that: a) galectin-3 silencing decreases the expression of PAR-1. b) galectin-3 over-expression increases cell migration and invasion and this increase can be reversed by PAR-1 silencing, indicating that galectin-3 increases cell migration and invasion via PAR-1 up-regulation. c) galectin-3 directly interacts with AP-1 transcriptional factor, and this complex binds to PAR-1 promoter and drives PAR-1 transcription. d) galectin-3 also amplifies phospho-paxillin, a PAR-1 downstream target, by increasing MMP-1 expression. MMP-1 silencing blocks phospho-paxillin amplification and cell invasion caused by galectin-3 over-expression. e) Silencing of either galectin-3, PAR-1 or MMP-1 significantly reduced cell migration into the vessels in zebrafish embryo model. f) Galectin-3, PAR-1, and MMP-1 are highly expressed and co-localized in malignant tissues from gastric cancer patients. CONCLUSIONS/SIGNIFICANCE: Galectin-3 plays the key role of activating cell surface receptor through production of protease and boosts gastric cancer metastasis. Galectin-3 has the potential to serve as a useful pharmacological target for prevention of gastric cancer metastasis

A functional and transcriptomic analysis of NET1 bioactivity in gastric cancer

<p>Abstract</p> <p>Background</p> <p>NET1, a RhoA guanine exchange factor, is up-regulated in gastric cancer (GC) tissue and drives the invasive phenotype of this disease. In this study, we aimed to determine the role of NET1 in GC by monitoring the proliferation, motility and invasion of GC cells in which NET1 has been stably knocked down. Additionally, we aimed to determine NET1-dependent transcriptomic events that occur in GC.</p> <p>Methods</p> <p>An in vitro model of stable knockdown of NET1 was achieved in AGS human gastric adenocarcinoma cells via lentiviral mediated transduction of short-hairpin (sh) RNA targeting NET1. Knockdown was assessed using quantitative PCR. Cell proliferation was assessed using an MTS assay and cell migration was assessed using a wound healing scratch assay. Cell invasion was assessed using a transwell matrigel invasion assay. Gene expression profiles were examined using affymetrix oligonucleotide U133A expression arrays. A student's t test was used to determine changes of statistical significance.</p> <p>Results</p> <p>GC cells were transduced with NET1 shRNA resulting in a 97% reduction in NET1 mRNA (p < 0.0001). NET1 knockdown significantly reduced the invasion and migration of GC cells by 94% (p < 0.05) and 24% (p < 0.001) respectively, while cell proliferation was not significantly altered following NET1 knockdown. Microarray analysis was performed on non-target and knockdown cell lines, treated with and without 10 μM lysophosphatidic acid (LPA) allowing us to identify NET1-dependent, LPA-dependent and NET1-mediated LPA-induced gene transcription. Differential gene expression was confirmed by quantitative PCR. Shortlisted NET1-dependent genes included STAT1, TSPAN1, TGFBi and CCL5 all of which were downregulatd upon NET1 downregulation. Shortlisted LPA-dependent genes included EGFR and PPARD where EGFR was upregulated and PPARD was downregulated upon LPA stimulation. Shortlisted NET1 and LPA dependent genes included IGFR1 and PIP5K3. These LPA induced genes were downregulated in NET1 knockdown cells.</p> <p>Conclusions</p> <p>NET1 plays an important role in GC cell migration and invasion, key aspects of GC progression. Furthermore, the gene expression profile further elucidates the molecular mechanisms underpinning NET1-mediated aggressive GC cell behaviour.</p

Large-scale integration of cancer microarray data identifies a robust common cancer signature

<p>Abstract</p> <p>Background</p> <p>There is a continuing need to develop molecular diagnostic tools which complement histopathologic examination to increase the accuracy of cancer diagnosis. DNA microarrays provide a means for measuring gene expression signatures which can then be used as components of genomic-based diagnostic tests to determine the presence of cancer.</p> <p>Results</p> <p>In this study, we collect and integrate ~ 1500 microarray gene expression profiles from 26 published cancer data sets across 21 major human cancer types. We then apply a statistical method, referred to as the <it>T</it>op-<it>S</it>coring <it>P</it>air of <it>G</it>roups (TSPG) classifier, and a repeated random sampling strategy to the integrated training data sets and identify a common cancer signature consisting of 46 genes. These 46 genes are naturally divided into two distinct groups; those in one group are typically expressed less than those in the other group for cancer tissues. Given a new expression profile, the classifier discriminates cancer from normal tissues by ranking the expression values of the 46 genes in the cancer signature and comparing the average ranks of the two groups. This signature is then validated by applying this decision rule to independent test data.</p> <p>Conclusion</p> <p>By combining the TSPG method and repeated random sampling, a robust common cancer signature has been identified from large-scale microarray data integration. Upon further validation, this signature may be useful as a robust and objective diagnostic test for cancer.</p

Integration of DNA Copy Number Alterations and Transcriptional Expression Analysis in Human Gastric Cancer

Background: Genomic instability with frequent DNA copy number alterations is one of the key hallmarks of carcinogenesis. The chromosomal regions with frequent DNA copy number gain and loss in human gastric cancer are still poorly defined. It remains unknown how the DNA copy number variations contributes to the changes of gene expression profiles, especially on the global level. Principal Findings: We analyzed DNA copy number alterations in 64 human gastric cancer samples and 8 gastric cancer cell lines using bacterial artificial chromosome (BAC) arrays based comparative genomic hybridization (aCGH). Statistical analysis was applied to correlate previously published gene expression data obtained from cDNA microarrays with corresponding DNA copy number variation data to identify candidate oncogenes and tumor suppressor genes. We found that gastric cancer samples showed recurrent DNA copy number variations, including gains at 5p, 8q, 20p, 20q, and losses at 4q, 9p, 18q, 21q. The most frequent regions of amplification were 20q12 (7/72), 20q12-20q13.1 (12/72), 20q13.1-20q13.2 (11/72) and 20q13.2-20q13.3 (6/72). The most frequent deleted region was 9p21 (8/72). Correlating gene expression array data with aCGH identified 321 candidate oncogenes, which were overexpressed and showed frequent DNA copy number gains; and 12 candidate tumor suppressor genes which were down-regulated and showed frequent DNA copy number losses in human gastric cancers. Three networks of significantly expressed genes in gastric cancer samples were identified by ingenuity pathway analysis. Conclusions: This study provides insight into DNA copy number variations and their contribution to altered gene expression profiles during human gastric cancer development. It provides novel candidate driver oncogenes or tumor suppressor genes for human gastric cancer, useful pathway maps for the future understanding of the molecular pathogenesis of this malignancy, and the construction of new therapeutic targets. © 2012 Fan et al.published_or_final_versio