• Bioinformatics and Biosystems
• /
• v.1 no.1
• /
• pp.28-37
• /
• 2006

Recent studies in molecular biology and proteomics have identified a significant number of novel diagnostic, prognostic, and therapeutic disease markers. However, validation of these markers in clinical specimens with traditional histopathological techniques involves low throughput and is time consuming and labor intensive. Tissue microarrays (TMAs) offer a means of combining tens to hundreds of specimens of tissue onto a single slide for simultaneous analysis. This capability is particularly pertinent in the field of cancer for target verification of data obtained from cDNA micro arrays and protein expression profiling of tissues, as well as in epidemiology-based investigations using histochemical/immunohistochemical staining or in situ hybridization. In combination with automated image analysis, TMA technology can be used in the global cellular network analysis of tissues. In particular, this potential has generated much excitement in cardiovascular disease research. The following review discusses recent advances in the construction and application of TMAs and the opportunity for developing novel, highly sensitive diagnostic tools for the early detection of cardiovascular disease.

• Asian Pacific Journal of Cancer Prevention
• /
• v.13 no.11
• /
• pp.5433-5438
• /
• 2012

Background: Hepatocellular carcinoma (HCC) is a common and aggressive malignancy. Despite of the improvements in its treatment, HCC prognosis remains poor due to its recurrence after resection. This study provides complete genetic profile for Egyptian HCC. Genome-wide analyses were performed to identify the predictive signatures. Patients and Methods: Liver tissue was collected from 31 patients with diagnosis of HCC and gene expression levels in the tumours and their adjacent non-neoplastic tissues samples were studied by analyzing changes by microarray then correlate these with the clinico-pathological parameters. Genes were validated in an independent set by qPCR. The genomic profile was associated with genetic disorders and cancer focused on gene expression, cell cycle and cell death. Molecular profile analysis revealed cell cycle progression and arrest at G2/M, but progression to mitosis; unregulated DNA damage check-points, and apoptosis. Result: Nine hundred fifty eight transcripts out of the 25,000 studied cDNAs were differentially expressed; 503 were up-regulated and 455 were down-regulated. A total of 19 pathways were up-regulated through 27 genes and 13 pathways were down-regulated through 19 genes. Thirty-seven genes showed significant differences in their expression between HCC cases with high and low Alpha Feto Protein ($AFP{\geq}600$ IU/ml). The validation for the microarray was done by real time PCR assay in which PPP3CA, ATG-5, BACE genes showed down-regulation and ABCG2, RXRA, ELOVL2, CXR3 genes showed up-regulation. cDNA microarrays showed that among the major upregulated genes in HCC are sets. Conclusion: The identified genes could provide a panel of new diagnostic and prognostic aids for HCC.

• Korean Journal of Oriental Medicine
• /
• v.6 no.1
• /
• pp.89-98
• /
• 2000

Cerebral ischemia, the most prevalent form of clinical stroke, is a medical problem of the first magnitude. Substantial efforts are being made to develop drugs which will protect the brain from the neurodegeneration followed by an ischemic stroke. A key factor in this process is the development of animal models that mimic the neuropathological consequences of stroke. Recently, there is increasing an evidence that free radical is involved in the mechanisms of ischemic brain damage. We investigated the macro scale gene expression analysis on the global ischemia induced by 4-vessel occlusion in Wister rats. The recent availability of microarrays provides an attractive strategy for elaborating an unbiased molecular profile of large number of genes during ischemic injury. This experimental approach offers the potential to identify molecules or cellular pathways not previously associated with ischemia. Ischemia was induced by 4-vessel occlusion for 10 minutes and reperfused again. RNA from sham control brain and time-dependent ischemed brain were hybridized to microarrays containing 4,000 rat genes. 589 genes were found to be at least 2 fold regulated at one or more time points. These survey data provide the foundation studies that should provide convincing proof for ischemia and oxidative stress on gene expression.

• Journal of Microbiology and Biotechnology
• /
• v.18 no.9
• /
• pp.1510-1517
• /
• 2008

Expresssed sequence tag (EST) analysis was developed from three cDNA libraries constructed from cells of the digestive tract, gonad, and liver of sea squirt. Randomly selected cDNA clones were partially sequenced to generate a total of 922 ESTs, in which 687 unique ESTs were identified respectively. Results of BLASTX search showed that 612 ESTs (89%) have homology to genes of known function whereas 75 ESTs (11%) were unidentified or novel. Based on the major function of their encoded proteins, the identified clones were classified into ten broad categories. We also identified several kinds of immune-related genes as identifying novel genes. Sequence analysis of ESTs revealed the presence of microsatellite-containing genes that may be valuable for further gene mapping studies. The accumulation of a large number of identified cDNA clones is invaluable for the study of sea squirt genetics and developmental biology. Further studies using cDNA microarrays are needed to identify the differentially expressed transcripts after disease infection.

• Genomics & Informatics
• /
• v.5 no.2
• /
• pp.83-87
• /
• 2007

The analysis of DNA microarray data is a rapidly evolving area of bioinformatics, and various types of microarray are emerging as some of the most exciting technologies for use in biological and clinical research. In recent years, microarray technology has been utilized in various applications such as the profiling of mRNAs, assessment of DNA copy number, genotyping, and detection of methylated sequences. However, the analysis of these heterogeneous microarray platform experiments does not need to be performed separately. Rather, these platforms can be co-analyzed in combination, for cross-validation. There are a number of separate laboratory information management systems (LIMS) that individually address some of the needs for each platform. However, to our knowledge there are no unified LIMS systems capable of organizing all of the information regarding multi-platform microarray experiments, while additionally integrating this information with tools to perform the analysis. In order to address these requirements, we developed a web-based LIMS system that provides an integrated framework for storing and analyzing microarray information generated by the various platforms. This system enables an easy integration of modules that transform, analyze and/or visualize multi-platform microarray data.

• BMB Reports
• /
• v.37 no.1
• /
• pp.1-10
• /
• 2004

DNA and RNA quantifications are widely used in biological and biomedical research. In the last ten years, many technologies have been developed to enable automated and high-throughput analyses. In this review, we first give a brief overview of how DNA and RNA quantifications are carried out. Then, five technologies (microarrays, SAGE, differential display, real time PCR and real competitive PCR) are introduced, with an emphasis on how these technologies can be applied and what their limitations are. The technologies are also evaluated in terms of a few key aspects of nucleic acids quantification such as accuracy, sensitivity, specificity, cost and throughput.

• Proceedings of the Korean Society of Toxicology Conference
• /
• 2003.05a
• /
• pp.36-37
• /
• 2003

The potential application of toxicogenomics to predictive toxicology has been discussed widely, but the utility of the approach remains largely unproven. Using cDNA microarrays, we have compared the gene expression profiles produced in mouse lymphoma cells by three genotoxic compounds, hydroxyurea (a carcino- gen), p-anisidine (a noncarcinogen) and paclitaxel (carcinogenicity unknown). (omitted)

• Genomics & Informatics
• /
• v.12 no.4
• /
• pp.145-150
• /
• 2014

Recent technical advances, such as chromatin immunoprecipitation combined with DNA microarrays (ChIp-chip) and chromatin immunoprecipitation-sequencing (ChIP-seq), have generated large quantities of high-throughput data. Considering that epigenomic datasets are arranged over chromosomes, their analysis must account for spatial or temporal characteristics. In that sense, simple clustering or classification methodologies are inadequate for the analysis of multi-track ChIP-chip or ChIP-seq data. Approaches that are based on hidden Markov models (HMMs) can integrate dependencies between directly adjacent measurements in the genome. Here, we review three HMM-based studies that have contributed to epigenetic research, from a computational perspective. We also give a brief tutorial on HMM modelling-targeted at bioinformaticians who are new to the field.

• Journal of Microbiology and Biotechnology
• /
• v.16 no.11
• /
• pp.1773-1777
• /
• 2006

We evaluated the usefulness of DNA microarray as a comparative genomics tool, and tested the validity of the cutoff values for defining absent genes in test genomes. Three genome-sequenced E. coli strains (K-12, EDL933, and CFT073) were subjected to comparative genomic hybridization with DNA microarrays covering almost all ORFs of the reference strain K-12, and the microarray results were compared with the results obtained from in silico analyses of genome sequences. For defining the K-12 ORFs absent in test genomes (reference strain-specific ORFs), we applied and evaluated the cutoff level of -1. The average sequence similarity between ORFs, to which corresponding spots showed a log-ratio of>-1, was $96.9{\pm}4.8$. The numbers of spots showing a log-ratio of <-1 (P<0.05, t-test) were 90 (2.5%) and 417 (10.6%) for the EDL933 genome and the CFT073 genome, respectively. Frequency of false negatives (FN) was ca. 0.2, and the cutoff level of -1.3 was required to achieve the FN of 0.1. The average sequence similarity of the false negative ORFs was $77.8{\pm}14.8$, indicating that the majority of the false negatives were caused by highly divergent genes. We concluded that the microarray is useful for identifying missing or divergent ORFs in closely related prokaryotic genomes.

• Genomics & Informatics
• /
• v.1 no.2
• /
• pp.87-93
• /
• 2003

DNA microarray is currently the most prominent tool for investigating large-scale gene expression data. Different algorithms for measuring gene expression levels from scanned images of microarray experiments may significantly impact the following steps of functional genomic analyses. $Affymetrix^{(R)}$ recently introduced high-density microarrays and new statistical algorithms in Microarray Suit (MAS) version 5.0$^{(R)}$. Very high correlations (0.92 - 0.97) between the new algorithms and the old algorithms (MAS 4.0) across several species and conditions were reported. We found that the column-wise array correlations had a tendency to be much higher than the row-wise gene correlations, which may be much more meaningful in the following higher-order data analyses including clustering and pattern analyses. In this paper, not only the detailed comparison of the two sets of algorithms is illustrated, but the impact of the introducing new algorithms on the further clustering analysis of microarray data and of possible pitfalls in mixing the old and the new algorithms were also described.