• 한국데이터정보과학회:학술대회논문집
• /
• 2006.04a
• /
• pp.121-129
• /
• 2006

Two color or cDNA microarrays are extensively used to study relative expression levels of thousands of genes simultaneously. 0かy two tissue samples can be hybridized on a single microarray slide. Thus, a microarray slide necessarily forms an incomplete block design with block size two when more than two tissue samples are under study. We also need to control for variability in gene expression values due to the two dyes. Thus, red and green dyes form the second blocking factor in addition to slides. General design problem for these microarray experiments is discussed in this paper. Designs for factorial cDNA microarrays are also discussed.

• 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.

• International Journal of Oral Biology
• /
• v.40 no.3
• /
• pp.151-159
• /
• 2015

Odontogenic cells express many genes spatiotemporally through complex and intricate processes during tooth formation. Therefore, investigating them during the tooth development has been an important subject for the better understanding of tooth morphogenesis. The present study was performed to identify the genetic profiles which are involved in the morphological changes during the different stages of rat tooth development using the Agilent Rat Oligonucleotide Microarrays. Morphologically, the maxillary 3rd molar germ at 10 days post-partum (dpp) was at the cap/bell stage. In contrast, the maxillary 2nd molar germ showed the root development stage. After microarray analysis, there were a considerable number of up- or down-regulated genes in the 3rd and the 2nd molar germ cells during tooth morphogenesis. Several differentially expressed genes for nerve supply were further studied. Among them, neuroligin 1 (Nlgn 1) was gradually downregulated during tooth development both at the transcription and the translation level. Also, Nlgn 1 was mostly localized in the dental sac, which is an important component yielding the nerve supply. This genetic profiling study proposed that many genes may be implicated in the biological processes for the dental hard tissue formation and, furthermore, may allow the identification of the key genes involved in the nerve supply to the dental sac.

• Clinical and Experimental Reproductive Medicine
• /
• v.29 no.4
• /
• pp.323-335
• /
• 2002

Object: The present study was accomplished to obtain a gene expression profile of the luminal epithelium during embryo apposition in comparison of implantation (1M) and interimplantation (INTER) sites. Material and Method: The mouse uterine luminal epithelium from IM and INTER sites were sampled on day 4.5 (Day of vaginal plug = day 0.5) by Laser Captured Microdissection (LCM). RNA was extracted from LCM captured epithelium, amplified, labeled and hybridized to microarrays. Results from microarray hybridization were analyzed by Significance Analysis of Microarrays (SAM) method. Differential expression of some genes was confirmed by LCM followed by RT-PCR. Results: Comparison of IM and INTER sites by SAM identified 73 genes most highly ranked at IM, while 13 genes at the INTER sites, within the estimated false discovery rate (FDR) of 0.163. Among 73 genes at IM, 20 were EST/unknown function, and the remain 53 were categorized to the structural, cell cycle, gene/protein expression, immune reaction, invasion, metabolism, oxidative stress, and signal transduction. Of the 24 structural genes, 14 were related especially to extracellular matrix and tissue remodeling. Meanwhile, among 13 genes up-regulated at INTER, 8 genes were EST/unknown function, and the rest 5 were related to metabolism, signal transduction, and gene/protein expression. Among these 58 (53+5) genes with known functions, 13 genes (22.4%) were related with $Ca^{2+}$ for their function. Conclusions: Results of the present study suggest that 1) active tissue remodeling is occurring at the IM sites during embryo apposition, 2) the INTER sites are relatively quiescent than IM sites, and 3) the $Ca^{2+}$ may be a crucial for apposition. Search for human homologue of those genes expressed in the mouse luminal epithelium during apposition will help to understand the implantation process and/or implantation failure in humans.

• Korean Journal of Head & Neck Oncology
• /
• v.21 no.2
• /
• pp.121-125
• /
• 2005

Objectives: To investigate the role of MMP-2 and TIMP-2 in the invasion and metastasis of thyroid papillary microcarcinomas. Materials and Methods: We performed immunohistochemical study on MMP-2 and its tissue inhibitor (TIMP-2) using tissue microarrays containing 2 cores of 40 microPTC and 8 non-neoplastic thyroid tissue. The expression intensity was semiquantitatively scored as -, ${\pm}$, +1, +2, and +3. Results: Both MMP-2 and TIMP-2 expression was observed in all tumors(100%) and in 1 of 8 non-neoplastic tissue(12.5%), and the positive staining was restricted to the epithelial cells. In 17 and 23 tumors with or without extrathyroid invasion, respectively, 8(47%) and 10(43%) cases showed moderate to strong(+23) positivity for MMP-2. TIMP-2 expression was moderate to strong in 13 cases(76%) and 16 cases(70%) in each group. In multifocal and solitary tumors, 3 of 6(50%) and 11 of 21(52%) cases showed moderate to strong MMP-2 expression, and 5/6(83%) and 15/21(71%) showed moderate to strong TIMP-2 expression. Conclusion: There is no relationship between MMP-2 or TIMP-2 expression and extrathyroid invasion or tumor multifocality in papillary microcarcinoma of the thyroid gland.

• Asian-Australasian Journal of Animal Sciences
• /
• v.21 no.1
• /
• pp.11-18
• /
• 2008

We created a cDNA microarray representing approximately 3,500 pig genes for functional genomic studies. The array elements were selected from 6,494 cDNA clones identified in a large-scale expressed sequence tag (EST) project. These cDNA clones came from normalized and subtracted porcine adipose tissue cDNA libraries. Sequence similarity searches of the 3,426 ESTs represented on the array using BLASTN identified 2,790 (81.4%) as putative human orthologs, with the remainder consisting of "novel" genes or highly divergent orthologs. We used the gene microarray to profile transcripts expressed by adipose tissue of fatty Chinese Xiang pig (XP) and muscley Large White (LW). Microarray analysis of RNA extracted from adipose tissue of fatty XP and muscley LW identified 81 genes that were differently expressed two fold or more. Transcriptional differences of four of these genes, adipocyte fatty acid binding protein (aP2), stearyl-CoA desaturase (SCD), sterol regulatory element binding transcription factor 1 (SREBF1) and lipoprotein lipase (LPL) were confirmed using SYBR Green quantitative RT-PCR technology. Our results showed that high expression of SCD and SREBF1 may be one of the reasons that larger fat deposits are observed in the XP. In addition, our findings also illustrate the potential power of microarrays for understanding the molecular mechanisms of porcine development, disease resistance, nutrition, fertility and production traits.

• 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.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.5
• /
• pp.2519-2525
• /
• 2016

There are several existing reports of microarray chip use for assessment of altered gene expression in different diseases. In fact, there have been over 1.5 million assays of this kind performed over the last twenty years, which have influenced clinical and translational research studies. The most commonly used DNA microarray platforms are Affymetrix GeneChip and Quality Control Software along with their GeneChip Probe Arrays. These chips are created using several quality controls to confirm the success of each assay, but their actual impact on gene expression profiles had not been previously analyzed until the appearance of several bioinformatics tools for this purpose. We here performed a data mining analysis, in this case specifically focused on ovarian cancer, as well as healthy ovarian tissue and ovarian cell lines, in order to confirm quality control results and associated variation in gene expression profiles. The microarray data used in our research were downloaded from ArrayExpress and Gene Expression Omnibus (GEO) and analyzed with Expression Console Software using RMA, MAS5 and Plier algorithms. The gene expression profiles were obtained using Partek Genomics Suite v6.6 and data were visualized using principal component analysis, heat map, and Venn diagrams. Microarray quality control analysis showed that roughly 40% of the microarray files were false negative, demonstrating over- and under-estimation of expressed genes. Additionally, we confirmed the results performing second analysis using independent samples. About 70% of the significant expressed genes were correlated in both analyses. These results demonstrate the importance of appropriate microarray processing to obtain a reliable gene expression profile.

• Molecules and Cells
• /
• v.38 no.7
• /
• pp.624-629
• /
• 2015

Since the emergence of proteomics methods, many proteins specific for renal cell carcinoma (RCC) have been identified. Despite their usefulness for the specific diagnosis of RCC, such proteins do not provide spatial information on the diseased tissue. Therefore, the identification of cancer-specific proteins that include information on their specific location is needed. Recently, matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) based imaging mass spectrometry (IMS) has emerged as a new tool for the analysis of spatial distribution as well as identification of either proteins or small molecules in tissues. In this report, surgical tissue sections of papillary RCC were analyzed using MALDI-IMS. Statistical analysis revealed several discriminative cancer-specific m/z-species between normal and diseased tissues. Among these m/z-species, two particular proteins, S100A11 and ferritin light chain, which are specific for papillary RCC cancer regions, were successfully identified using LC-MS/MS following protein extraction from independent RCC samples. The expressions of S100A11 and ferritin light chain were further validated by immunohistochemistry of human tissues and tissue microarrays (TMAs) of RCC. In conclusion, MALDI-IMS followed by LC-MS/MS analysis in human tissue identified that S100A11 and ferritin light chain are differentially expressed proteins in papillary RCC cancer regions.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.4
• /
• pp.1691-1699
• /
• 2016

Ovarian cancer is possibly the sixth most common malignancy worldwide, in Mexico representing the fourth leading cause of gynecological cancer death more than 70% being diagnosed at an advanced stage and the survival being very poor. Ovarian tumors are classified according to histological characteristics, epithelial ovarian cancer as the most common (~80%). We here used high-density microarrays and a systems biology approach to identify tissue-associated deregulated genes. Non-malignant ovarian tumors showed a gene expression profile associated with immune mediated inflammatory responses (28 genes), whereas malignant tumors had a gene expression profile related to cell cycle regulation (1,329 genes) and ovarian cell lines to cell cycling and metabolism (1,664 genes).