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Journal articles on the topic 'Gene expression and cDNA microarray'

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Published: 4 June 2021

Last updated: 4 February 2022

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Pérez-Enciso, Miguel, Miguel A. Toro, Michel Tenenhaus, and Daniel Gianola. "Combining Gene Expression and Molecular Marker Information for Mapping Complex Trait Genes: A Simulation Study." Genetics 164, no. 4 (2003): 1597–606. http://dx.doi.org/10.1093/genetics/164.4.1597.

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Abstract A method for mapping complex trait genes using cDNA microarray and molecular marker data jointly is presented and illustrated via simulation. We introduce a novel approach for simulating phenotypes and genotypes conditionally on real, publicly available, microarray data. The model assumes an underlying continuous latent variable (liability) related to some measured cDNA expression levels. Partial least-squares logistic regression is used to estimate the liability under several scenarios where the level of gene interaction, the gene effect, and the number of cDNA levels affecting liability are varied. The results suggest that: (1) the usefulness of microarray data for gene mapping increases when both the number of cDNA levels in the underlying liability and the QTL effect decrease and when genes are coexpressed; (2) the correlation between estimated and true liability is large, at least under our simulation settings; (3) it is unlikely that cDNA clones identified as significant with partial least squares (or with some other technique) are the true responsible cDNAs, especially as the number of clones in the liability increases; (4) the number of putatively significant cDNA levels increases critically if cDNAs are coexpressed in a cluster (however, the proportion of true causal cDNAs within the significant ones is similar to that in a no-coexpression scenario); and (5) data reduction is needed to smooth out the variability encountered in expression levels when these are analyzed individually.

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Lonnstedt, I. "Hierarchical Bayes models for cDNA microarray gene expression." Biostatistics 6, no. 2 (2005): 279–91. http://dx.doi.org/10.1093/biostatistics/kxi009.

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Skotheim, Rolf I., Anne Kallioniemi, Bodil Bjerkhagen та ін. "Topoisomerase-IIα Is Upregulated in Malignant Peripheral Nerve Sheath Tumors and Associated With Clinical Outcome". Journal of Clinical Oncology 21, № 24 (2003): 4586–91. http://dx.doi.org/10.1200/jco.2003.07.067.

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Purpose: To identify target genes of clinical significance for patients with malignant peripheral-nerve sheath tumor (MPNST), an aggressive cancer for which no consensus therapy exists. Materials and Methods: Biopsies and clinical data from 51 patients with MPNST were included in this study. Based on our previous research implicating chromosome arm 17q amplification in MPNST, we performed gene expression analyses of 14 MPNSTs using chromosome 17–specific cDNA microarrays. Copy numbers of selected gene probes and centromere probes were then determined by interphase fluorescence in situ hybridization in 16 MPNSTs. Finally, we generated a tissue microarray containing 79 samples from 44 MPNSTs, on which in situ protein expressions of candidate genes were examined and related to clinical end points. Results: Among several deregulated genes found by cDNA microarray analyses, topoisomerase IIα (TOP2A) was the most overexpressed gene in MPNSTs compared with benign neurofibromas. Excess copies of the TOP2A were also seen at the DNA level in 10 of 16 cases, and high expression of the TOP2A protein was seen in 83% of the tumors on the tissue microarray. The TOP2A-expressing tumors were associated with poor cancer-specific survival and presence of metastases. Conclusion: We have identified TOP2A as a target gene in MPNST, using a focused gene expression profiling followed by a DNA copy number evaluation and clinical validation of the encoded protein using a tissue microarray. This study is the first to suggest that TOP2A expression may be a predictive factor for adverse outcome in MPNST.

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Ghazizadeh, Mohammad, Oichi Kawanami, and Tsutomu Araki. "Assessment of Gene Expression Profile by cDNA Microarray Analysis." Journal of Nippon Medical School 68, no. 6 (2001): 460–61. http://dx.doi.org/10.1272/jnms.68.460.

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Schofield, Deborah, and Timothy J. Triche. "cDNA microarray analysis of global gene expression in sarcomas." Current Opinion in Oncology 14, no. 4 (2002): 406–11. http://dx.doi.org/10.1097/00001622-200207000-00007.

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Aittokallio, Tero, Markus Kurki, Olli Nevalainen, Tuomas Nikula, Anne West, and Riitta Lahesmaa. "Computational Strategies for Analyzing Data in Gene Expression Microarray Experiments." Journal of Bioinformatics and Computational Biology 01, no. 03 (2003): 541–86. http://dx.doi.org/10.1142/s0219720003000319.

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Microarray analysis has become a widely used method for generating gene expression data on a genomic scale. Microarrays have been enthusiastically applied in many fields of biological research, even though several open questions remain about the analysis of such data. A wide range of approaches are available for computational analysis, but no general consensus exists as to standard for microarray data analysis protocol. Consequently, the choice of data analysis technique is a crucial element depending both on the data and on the goals of the experiment. Therefore, basic understanding of bioinformatics is required for optimal experimental design and meaningful interpretation of the results. This review summarizes some of the common themes in DNA microarray data analysis, including data normalization and detection of differential expression. Algorithms are demonstrated by analyzing cDNA microarray data from an experiment monitoring gene expression in T helper cells. Several computational biology strategies, along with their relative merits, are overviewed and potential areas for additional research discussed. The goal of the review is to provide a computational framework for applying and evaluating such bioinformatics strategies. Solid knowledge of microarray informatics contributes to the implementation of more efficient computational protocols for the given data obtained through microarray experiments.

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Dumur, Catherine I., Suhail Nasim, Al M. Best, et al. "Evaluation of Quality-Control Criteria for Microarray Gene Expression Analysis." Clinical Chemistry 50, no. 11 (2004): 1994–2002. http://dx.doi.org/10.1373/clinchem.2004.033225.

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Abstract Background: Development of quality-control criteria to ensure reproducibility of microarray results for potential clinical application is still in its infancy. Methods: In the present studies we developed quality-control criteria and evaluated their effect in microarray data analysis using total RNA from cell lines, frozen tumors, and a commercially available reference RNA. Quality-control criteria such as A260/A280 ratios, percentage of rRNA, and median size of cDNA and cRNA synthesis products were evaluated for robustness in microarray analysis. Furthermore, precision studies using a reference material were performed on the Affymetrix® HG-U133A high-density oligonucleotide microarrays. The same reference RNA sample was examined in 16 different chips run on 2 different days in the four different modules of the Affymetrix fluidics workstation. Fresh and frozen fragmented cRNAs were also compared. An ANOVA model was fit to identify the main sources of variation. Results: Good-quality samples showed &gt;30% rRNA in the electropherograms and cDNA and cRNA synthesis products with median sizes of 2.0 and 3.0 kb, respectively. Precision studies showed that the main source of variation was the day-to-day variability, minimally affecting hybridization exogenous control genes. Altogether, the results showed that the Affymetrix Genechip® system is highly reproducible when RNA that meet the quality-control criteria are used (overall P &gt;0.01). Conclusions: These results confirm the need to establish defined quality-control criteria for sample quality to distinguish between analytical and biological variability.

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Magbanua, M. M., J. E. Lang, J. Scott, et al. "Gene expression profiling of circulating tumor cells from breast cancer patients." Journal of Clinical Oncology 24, no. 18_suppl (2006): 10769. http://dx.doi.org/10.1200/jco.2006.24.18_suppl.10769.

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10769 Background: Levels of circulating tumor cells (CTC) have prognostic and predictive significance in metastatic breast cancer. However, since CTCs are extremely rare, little is known about the actual phenotype of these cells. In order to characterize these cells, we performed cDNA microarray analyses of CTC isolated from peripheral blood (PB) of breast cancer patients. Methods: CTCs were directly isolated via immunomagnetic enrichment (IE) followed by fluorescence activated cell sorting (FACS). Total RNA was then subjected to two rounds of linear amplification and hybridized to cDNA microarrays (∼40,000 cDNAs). Validation studies used spiked BT474 cells. Clinical studies used PB (10–20 ml) from patients with metastatic breast cancer. Results: Rare spiked tumor cells (e.g., 320 cells in 10 mL PB) were efficiently recovered by IE/FACS (50% yield). Expression profiles of recovered cells, both by TaqMan of a 37 gene panel as well as by global gene expression analysis, matched that of BT474 cells in culture. In contrast, these profiles were clearly distinct from that of normal PB, ruling out significant contamination from blood elements. In clinical studies, IE/FACS isolated small numbers of CTCs (10–1000 cells). Expression profiles of CTCs were compared to that of normal blood, primary breast tumors, and normal epithelial samples. Unsupervised hierarchical clustering revealed that CTC profiles were readily distinguished from that of normal blood and normal epithelium; and further analysis revealed that CTC cluster with a subset of primary breast tumors, particularly the basal-like phenotype. Candidate genes associated with the CTC phenotype were also identified. Conclusions: We have developed and validated a method to isolate rare CTCs and profile them via cDNA microarray analysis. In addition, our gene expression analyses of CTC further provide evidence to the malignant nature of these cells. Further expression profiling of CTC may yield insights into their phenotype, pathophysiology and potential as biomarkers. [Table: see text]

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Eckel, Jeanette E., Antje Hoering, and Irene Ghobrial. "Experimental Design & Analysis of Protein Array Data: Applying Methods from cDNA Arrays." Blood 104, no. 11 (2004): 4280. http://dx.doi.org/10.1182/blood.v104.11.4280.4280.

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Abstract It appears that a number of recent manuscripts using protein microarray technology are using equivalent analysis procedures that the gene-expression microarray community implemented in their infancy. That is, utilizing a classic reference design such that the ratio of the sample of interest to a reference sample is the response of interest and assessing fold change to determine differential expression. For example, recent publications have concluded that proteins with a fold change less than 0.7 or greater than 1.3 demonstrate significant down- or up-regulated differential expression, respectively. However, fold change is an unreliable measure of differential expression and statistical models that distinguish true signal from random noise should be utilized instead of fold changes. Over the last half decade a tremendous amount of research has been devoted to gene-expression microarrays to vastly improve on the areas of experimental design, normalization and statistical analyses to assess differential expression and classification and these methods are directly applicable to protein microarray technology. Thus, the objective is to review the statistical methodology that has been developed for two-color cDNA arrays that is directly applicable to protein arrays. Examples are provided from a mantle-cell lymphoma protein-array experiment.

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Lau, W.-y., P. B. S. Lai, M.-f. Leung, et al. "Differential Gene Expression of Hepatocellular Carcinoma Using cDNA Microarray Analysis." Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics 12, no. 2 (2001): 59–69. http://dx.doi.org/10.3727/096504001108747530.

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Weinstein, J. N., U. Scherf, D. Ross, et al. "A cDNA microarray gene expression database for cancer drug discovery." Nature Genetics 23, S3 (1999): 81. http://dx.doi.org/10.1038/14426.

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Kan, Takatsugu, Yutaka Shimada, Fumiaki Sato, et al. "Gene Expression Profiling in Human Esophageal Cancers Using cDNA Microarray." Biochemical and Biophysical Research Communications 286, no. 4 (2001): 792–801. http://dx.doi.org/10.1006/bbrc.2001.5400.

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Chen, Yidong, Hongen Zhang, Sujatha Panavally, et al. "cDNA microarray analysis using both gene expression ratios and intensities." Nature Genetics 27, S4 (2001): 46–47. http://dx.doi.org/10.1038/87032.

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Park, In-Kyung, Yaqin He, Fangming Lin, et al. "Differential gene expression profiling of adult murine hematopoietic stem cells." Blood 99, no. 2 (2002): 488–98. http://dx.doi.org/10.1182/blood.v99.2.488.

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Abstract Hematopoietic stem cells (HSCs) have self-renewal capacity and multilineage developmental potentials. The molecular mechanisms that control the self-renewal of HSCs are still largely unknown. Here, a systematic approach using bioinformatics and array hybridization techniques to analyze gene expression profiles in HSCs is described. To enrich mRNAs predominantly expressed in uncommitted cell lineages, 54 000 cDNA clones generated from a highly enriched population of HSCs and a mixed population of stem and early multipotent progenitor (MPP) cells were arrayed on nylon membranes (macroarray or high-density array), and subtracted with cDNA probes derived from mature lineage cells including spleen, thymus, and bone marrow. Five thousand cDNA clones with very low hybridization signals were selected for sequencing and further analysis using microarrays on glass slides. Two populations of cells, HSCs and MPP cells, were compared for differential gene expression using microarray analysis. HSCs have the ability to self-renew, while MPP cells have lost the capacity for self-renewal. A large number of genes that were differentially expressed by enriched populations of HSCs and MPP cells were identified. These included transcription factors, signaling molecules, and previously unknown genes.

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Agca, Cansu, James E. Ries, Sarah J. Kolath, et al. "Luteinization of porcine preovulatory follicles leads to systematic changes in follicular gene expression." Reproduction 132, no. 1 (2006): 133–45. http://dx.doi.org/10.1530/rep.1.01163.

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The LH surge initiates the luteinization of preovulatory follicles and causes hormonal and structural changes that ultimately lead to ovulation and the formation of corpora lutea. The objective of the study was to examine gene expression in ovarian follicles (n= 11) collected from pigs (Sus scrofa domestica) approaching estrus (estrogenic preovulatory follicle;n= 6 follicles from two sows) and in ovarian follicles collected from pigs on the second day of estrus (preovulatory follicles that were luteinized but had not ovulated;n= 5 follicles from two sows). The follicular status within each follicle was confirmed by follicular fluid analyses of estradiol and progesterone ratios. Microarrays were made from expressed sequence tags that were isolated from cDNA libraries of porcine ovary. Gene expression was measured by hybridization of fluorescently labeled cDNA (preovulatory estrogenic or -luteinized) to the microarray. Microarray analyses detected 107 and 43 genes whose expression was decreased or increased (respectively) during the transition from preovulatory estrogenic to -luteinized (P<0.01). Cells within preovulatory estrogenic follicles had a gene-expression profile of proliferative and metabolically active cells that were responding to oxidative stress. Cells within preovulatory luteinized follicles had a gene-expression profile of nonproliferative and migratory cells with angiogenic properties. Approximately, 40% of the discovered genes had unknown function.

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Ang, Sunny, Cha-Ze Lee, Konan Peck, et al. "Acid-Induced Gene Expression in Helicobacter pylori: Study in Genomic Scale by Microarray." Infection and Immunity 69, no. 3 (2001): 1679–86. http://dx.doi.org/10.1128/iai.69.3.1679-1686.2001.

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ABSTRACT To understand the RNA expression in response to acid stress ofHelicobacter pylori in genomic scale, a microarray membrane containing 1,534 open reading frames (ORFs) from strain 26695 was used. Total RNAs of H. pylori under growth conditions of pH 7.2 and 5.5 were extracted, reverse transcribed into cDNA, and labeled with biotin. Each microarray membrane was hybridized with cDNA probe from the same strain under two different pH conditions and developed by a catalyzed reporter deposition method. Gene expression of all ORFs was measured by densitometry. Among the 1,534 ORFs, 53 ORFs were highly expressed (≧30% of rRNA control in densitometry ratios). There were 445 ORFs which were stably expressed (<30% of rRNA in densitometry) under both pH conditions without significant variation. A total of 80 ORFs had significantly increased expression levels at low pH, while expressions of 4 ORFs were suppressed under acidic condition. The remaining 952 ORFs were not detectable under either pH condition. These data were highly reproducible and comparable to those obtained by the RNA slot blot method. Our results suggest that microarray can be used in monitoring prokaryotic gene expression in genomic scale.

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Thomson, S. A. M., E. Kennerly, N. Olby, et al. "Microarray Analysis of Differentially Expressed Genes of Primary Tumors in the Canine Central Nervous System." Veterinary Pathology 42, no. 5 (2005): 550–58. http://dx.doi.org/10.1354/vp.42-5-550.

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The pathophysiologic similarities of many human and canine cancers support the role of the domestic dog as a model for brain tumor research. Here we report the construction of a custom canine brain-specific cDNA microarray and the analysis of gene expression patterns of several different types of canine brain tumor The microarray contained 4000 clones from a canine brain specific cDNA library including 2161 clones that matched known genes or expressed sequence tags (ESTs) and 25 cancer-related genes. Our study included 16 brain tumors (seven meningiomas, five glial tumors, two ependymomas, and two choroid plexus papillomas) from a variety of different dog breeds. We identified several genes previously found to be differentially expressed in human brain tumors. This suggests that human and canine brain tumors share a common pathogenesis. In addition, we also found differentially expressed genes unique to either meningiomas or the glial tumors. This report represents the first global gene expression analysis of different types of canine brain tumors by cDNA microarrays and might aid in the identification of potential candidate genes involved in tumor formation and progression.

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Madsen, Sally A., Ling-Chu Chang, Mary-Clare Hickey, Guilherme J. M. Rosa, Paul M. Coussens, and Jeanne L. Burton. "Microarray analysis of gene expression in blood neutrophils of parturient cows." Physiological Genomics 16, no. 2 (2004): 212–21. http://dx.doi.org/10.1152/physiolgenomics.00121.2003.

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It is well documented that blood neutrophils from parturient dairy cows do not perform as well as neutrophils from nonparturient cows in laboratory assays of adhesion, migration, or phagocytosis-induced respiratory burst. However, little is known about the possible molecular basis for parturition-induced changes in neutrophils. cDNA microarray analysis was used in the current study to explore parturition-induced changes in gene expression profiles in bovine blood neutrophils. Total RNA from isolated blood neutrophils of four parturient Holstein cows was obtained before, during, and after parturition, reverse transcribed into cDNA, and sequentially labeled with Cy3 or Cy5 dyes prior to paired hybridizations to 1,056 member bovine total leukocyte (BOTL-3) microarrays in a loop design. Resulting gene expression data were LOWESS normalized by array and analyzed using a mixed model approach. Results showed that expression profiles for 302 BOTL-3 genes were influenced by parturition. BLASTn analysis and preliminary clustering of affected genes by biological function indicated that the largest proportion (14%) of changed genes encode proteins critical to regulation of apoptosis. Independent confirmation of altered expression for 16 of these genes was achieved using quantitative real-time RT-PCR (Q-RT-PCR). A predominantly survival phenotype inferred from the microarray and Q-RT-PCR results was substantiated by monitoring apoptosis status of blood neutrophils from castrated male cattle cultured in the presence of sera from parturient cows. Thus our combined gene expression and apoptosis phenotyping results suggest that bovine parturition may induce prolonged survival in normally short-lived blood neutrophils.

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Hwang, Juey-Jen, Paul D. Allen, George C. Tseng, et al. "Microarray gene expression profiles in dilated and hypertrophic cardiomyopathic end-stage heart failure." Physiological Genomics 10, no. 1 (2002): 31–44. http://dx.doi.org/10.1152/physiolgenomics.00122.2001.

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Despite similar clinical endpoints, heart failure resulting from dilated cardiomyopathy (DCM) or hypertrophic cardiomyopathy (HCM) appears to develop through different remodeling and molecular pathways. Current understanding of heart failure has been facilitated by microarray technology. We constructed an in-house spotted cDNA microarray using 10,272 unique clones from various cardiovascular cDNA libraries sequenced and annotated in our laboratory. RNA samples were obtained from left ventricular tissues of precardiac transplantation DCM and HCM patients and were hybridized against normal adult heart reference RNA. After filtering, differentially expressed genes were determined using novel analyzing software. We demonstrated that normalization for cDNA microarray data is slide-dependent and nonlinear. The feasibility of this model was validated by quantitative real-time reverse transcription-PCR, and the accuracy rate depended on the fold change and statistical significance level. Our results showed that 192 genes were highly expressed in both DCM and HCM (e.g., atrial natriuretic peptide, CD59, decorin, elongation factor 2, and heat shock protein 90), and 51 genes were downregulated in both conditions (e.g., elastin, sarcoplasmic/endoplasmic reticulum Ca2+-ATPase). We also identified several genes differentially expressed between DCM and HCM (e.g., αB-crystallin, antagonizer of myc transcriptional activity, β-dystrobrevin, calsequestrin, lipocortin, and lumican). Microarray technology provides us with a genomic approach to explore the genetic markers and molecular mechanisms leading to heart failure.

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Han, Wonshik, Ki Wook Chung, Soo Jung Ahn, et al. "Gene Expression Profiles of Primary Breast Cancer Tissue Using cDNA Microarray." Journal of Korean Breast Cancer Society 5, no. 4 (2002): 284. http://dx.doi.org/10.4048/jkbcs.2002.5.4.284.

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Tan, Zhi-Jun. "Analysis of gene expression profile of pancreatic carcinoma using cDNA microarray." World Journal of Gastroenterology 9, no. 4 (2003): 818. http://dx.doi.org/10.3748/wjg.v9.i4.818.

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Lee, Suman, Jung Hoon Park, Kye-Sung Kim, Hyun-Joo Kim, Kwang Yul Cha, and Sook-Hwan Lee. "Gene expression profiles during mouse spermatogenesis by 8.0K cDNA microarray experiment." Fertility and Sterility 80 (September 2003): 31. http://dx.doi.org/10.1016/s0015-0282(03)01883-1.

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Kim, Chul Wook, Kyu Tae Chang, Yeon Hee Hong, et al. "cDNA Microarray Analysis of the Gene Expression Profile of Swine Muscle." Asian-Australasian Journal of Animal Sciences 18, no. 8 (2005): 1080–87. http://dx.doi.org/10.5713/ajas.2005.1080.

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Yoon, Joo Hee, Joon Mo Lee, Sung Eun Namkoong, et al. "cDNA Microarray Analysis of Gene Expression Profiles Associated with Cervical Cancer." Cancer Research and Treatment 35, no. 5 (2003): 451–59. http://dx.doi.org/10.4143/crt.2003.35.5.451.

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Wang, Kai, Lu Gan, Eric Jeffery, et al. "Monitoring gene expression profile changes in ovarian carcinomas using cDNA microarray." Gene 229, no. 1-2 (1999): 101–8. http://dx.doi.org/10.1016/s0378-1119(99)00035-9.

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Davis, Daniel P., Piyush M. Patel, Satoki Inoue, Paul J. Kelly, and John M. Drummond. "Gene Expression Profiling Using cDNA Microarray Analysis To Investigate Ischemic Preconditioning." Anesthesiology 96, Sup 2 (2002): A756. http://dx.doi.org/10.1097/00000542-200209002-00756.

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Airik, Rannar, Martin Kärner, Alar Karis, and Jüri Kärner. "Gene expression analysis of Gata3−/− mice by using cDNA microarray technology." Life Sciences 76, no. 22 (2005): 2559–68. http://dx.doi.org/10.1016/j.lfs.2004.10.054.

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Tomioka, Hirofumi, Kei-ichi Morita, Shogo Hasegawa, and Ken Omura. "Gene expression analysis by cDNA microarray in oral squamous cell carcinoma." Journal of Oral Pathology and Medicine 35, no. 4 (2006): 206–11. http://dx.doi.org/10.1111/j.1600-0714.2006.00410.x.

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Wolfinger, Russell D., Greg Gibson, Elizabeth D. Wolfinger, et al. "Assessing Gene Significance from cDNA Microarray Expression Data via Mixed Models." Journal of Computational Biology 8, no. 6 (2001): 625–37. http://dx.doi.org/10.1089/106652701753307520.

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Pellagatti, Andrea, Noor Esoof, Fiona Watkins, et al. "Gene expression profiling in the myelodysplastic syndromes using cDNA microarray technology." British Journal of Haematology 125, no. 5 (2004): 576–83. http://dx.doi.org/10.1111/j.1365-2141.2004.04958.x.

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Hsieh, Sun-Yuan, and Yu-Chun Chou. "A Faster cDNA Microarray Gene Expression Data Classifier for Diagnosing Diseases." IEEE/ACM Transactions on Computational Biology and Bioinformatics 13, no. 1 (2016): 43–54. http://dx.doi.org/10.1109/tcbb.2015.2474389.

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Rosenzweig, Barry A., P. Scott Pine, Olen E. Domon, Suzanne M. Morris, James J. Chen, and Frank D. Sistare. "Dye bias correction in dual-labeled cDNA microarray gene expression measurements." Environmental Health Perspectives 112, no. 4 (2004): 480–87. http://dx.doi.org/10.1289/ehp.6694.

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LEE, Gyoung-Jae, Wan-Seon LEE, Ki-Seon JEON, et al. "cDNA Microarray Gene Expression Analysis and Toxicological Phenotype for Anticancer Drug." Journal of Veterinary Medical Science 66, no. 11 (2004): 1339–45. http://dx.doi.org/10.1292/jvms.66.1339.

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Farah, Raymond, Rola Khamisy-Farah, Tamar Amit, Moussa B. H. Youdim, and Zaher Arraf. "Lithium’s Gene Expression Profile, Relevance to Neuroprotection A cDNA Microarray Study." Cellular and Molecular Neurobiology 33, no. 3 (2013): 411–20. http://dx.doi.org/10.1007/s10571-013-9907-x.

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Fouad, Islam A., Mai S. Mabrouk, and Amr A. Sharawy. "A Fully Automated Method for Noisy cDNA Microarray Image Quantification." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 3 (2013): 2330–40. http://dx.doi.org/10.24297/ijct.v11i3.1170.

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DNA microarray is an innovative tool for gene studies in biomedical research, and its applications can vary from cancer diagnosis to human identification. Image processing is an important aspect of microarray experiments, the primary purpose of the image analysis step is to extract numerical foreground and background intensities for the red and green channels for each spot on the microarray. The background intensities are used to correct the foreground intensities for local variation on the array surface, resulting in corrected red and green intensities for each spot that can be considered as a primary data for subsequent analysis. Most techniques divide the overall microarray image processing into three steps: gridding, segmentation, and quantification. In this paper, aÂ Â simple automated gridding technique is developed with a great effect on noisy microarray images. A segmentation technique based on â€˜edge-detectionâ€™ is applied to identify the spots and separate the foreground from the background is known as microarray image segmentation. Finally, a quantification technique is used to calculate the gene expression level from the intensity values of the red and green components of the image. Results revealed that the developed methods can deal with various kinds of noisy microarray images, with high Â griddingaccuracy of 92.2% for low quality images and 100% for high quality images resulting in better spot quantification to getÂ more accurate gene expression values.Â

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Rim, Kyung Taek, Kun Koo Park, Jae Hyuck Sung, et al. "Gene-expression profiling using suppression-subtractive hybridization and cDNA microarray in rat mononuclear cells in response to welding-fume exposure." Toxicology and Industrial Health 20, no. 1-5 (2004): 77–88. http://dx.doi.org/10.1191/0748233704th200oa.

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Welders with radiographic pneumoconiosis abnormalities have shown a gradual clearing of the X-ray identified effects following removal from exposure. In some cases, the pulmonary fibrosis associated with welding fumes appears in a more severe form in welders. Accordingly, for the early detection of welding-fume-exposure-induced pulmonary fibrosis, the gene expression profiles of peripheral mononuclear cells from rats exposed to welding fumes were studied using suppression-subtractive hybridization (SSH) and a cDNA microarray. As such, Sprague-Dawley rats were exposed to a stainless steel arc welding fume for 2 h/day in an inhalation chamber with a 107.59 / 2.6 mg/m3 concentration of total suspended particulate (TSP) for 30 days. Thereafter, the total RNA was extracted from the peripheral blood mononuclear cells, the cDNA synthesized from the total RNA using the SMARTTM PCR cDNA method, and SSH performed to select the welding-fume-exposure-regulated genes. The cDNAs identified by the SSH were then cloned into a plasmid miniprep, sequenced and the sequences analysed using the NCBI BLAST programme. In the SSH cloned cDNA microarray analysis, five genes were found to increase their expression by 1.9-fold or more, including Rgs 14, which plays an important function in cellular signal transduction pathways; meanwhile 36 genes remained the same and 30 genes decreased their expression by more than 59%, including genes associated with the immune response, transcription factors and tyrosine kinases. Among the 5200 genes analysed, 256 genes (5.1%) were found to increase their gene expression, while 742 genes (15%) decreased their gene expression in response to the welding-fume exposure when tested using a commercial 5.0k DNA microarray. Therefore, unlike exposure to other toxic substances, prolonged welding-fume exposure was found to substantially downregulate many genes.

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Zhang, X., J. Feng, Y. Cheng, et al. "Characterization of differentially expressed genes in ovarian cancer by cDNA microarrays." International Journal of Gynecologic Cancer 15, no. 1 (2005): 50–57. http://dx.doi.org/10.1136/ijgc-00009577-200501000-00009.

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The molecular events leading to the development and progression of ovarian carcinoma are not completely understood. We performed a large-scale survey for the identification of differentially expressed genes between ovarian carcinoma and normal ovarian tissue by using cDNA microarray analysis. We utilized 512 member human novel putative oncogene and tumor suppressor gene cDNA microarrays to study the differences in gene expression between ovarian carcinoma and normal ovarian tissues. Some differentially expressed genes have been further confirmed by immunohistochemical analysis. A total of 39 differentially expressed genes were identified, of which 16 and 23 were specifically expressed in ovarian cancer and normal ovarian tissue, respectively. The comparison of average signal of differentially expressed genes exhibited at least a twofold difference in expression. The differentially expressed genes may be related to the carcinogenesis and progression of the malignant growth. The use of cDNA microarrays allows simultaneous monitor of the expression of many genes, thereby it speeds up the identification of differentially expressed genes. It is essential for further exploration of the mechanisms of the disease.

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Feng, Xu, Yuan Jiang, Paul Meltzer, and Paul M. Yen. "Thyroid Hormone Regulation of Hepatic Genes in Vivo Detected by Complementary DNA Microarray." Molecular Endocrinology 14, no. 7 (2000): 947–55. http://dx.doi.org/10.1210/mend.14.7.0470.

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Abstract The liver is an important target organ of thyroid hormone. However, only a limited number of hepatic target genes have been identified, and little is known about the pattern of their regulation by thyroid hormone. We used a quantitative fluorescent cDNA microarray to identify novel hepatic genes regulated by thyroid hormone. Fluorescent-labeled cDNA prepared from hepatic RNA of T3-treated and hypothyroid mice was hybridized to a cDNA microarray, representing 2225 different mouse genes, followed by computer analysis to compare relative changes in gene expression. Fifty five genes, 45 not previously known to be thyroid hormone-responsive genes, were found to be regulated by thyroid hormone. Among them, 14 were positively regulated by thyroid hormone, and unexpectedly, 41 were negatively regulated. The expression of 8 of these genes was confirmed by Northern blot analyses. Thyroid hormone affected gene expression for a diverse range of cellular pathways and functions, including gluconeogenesis, lipogenesis, insulin signaling, adenylate cyclase signaling, cell proliferation, and apoptosis. This is the first application of the microarray technique to study hormonal regulation of gene expression in vivo and should prove to be a powerful tool for future studies of hormone and drug action.

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Ma, Xianyong, Tupur Husain, Hui Peng, et al. "Development of a murine hematopoietic progenitor complementary DNA microarray using a subtracted complementary DNA library." Blood 100, no. 3 (2002): 833–44. http://dx.doi.org/10.1182/blood.v100.3.833.

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Abstract With the goal of creating a resource for in-depth study of myelopoiesis, we have executed a 2-pronged strategy to obtain a complementary DNA (cDNA) clone set enriched in hematopoietic genes. One aspect is a library subtraction to enrich for underrepresented transcripts present at early stages of hematopoiesis. For this, a hematopoietic cDNA library from primary murine bone marrow cells enriched for primitive progenitors was used as tester. The subtraction used 10 000 known genes and expressed sequence tags (ESTs) as driver. The 2304 randomly picked clones from the subtracted cDNA libraries represent 1255 distinct genes, of which 622 (50%) are named genes, 386 (30%) match uncharacterized ESTs, and 247 (20%) are novel. The second aspect of our strategy was to complement this subtracted library with genes known to be involved in myeloid cell differentiation and function. The resulting cDNAs were arrayed on polylysine-coated glass slides. The microarrays were used to analyze gene expression in primary and cultured murine bone marrow–derived progenitors. We found expression of various types of genes, including regulatory cytokines and their receptors, signal transduction genes, and transcription factors. To assess gene expression during myeloid differentiation, we examined patterns of change during induced differentiation of EML cells. Several hundred of the genes underwent fluctuations in expression level during myeloid cell differentiation. The complete database, accessible on the World Wide Web at http://yale130132115135.med.yale.edu/, allows for retrieval of information regarding these genes. Our microarray allows for genomewide expression analysis of myeloid stem cells, which will help in defining the regulatory mechanisms of stem cell differentiation.

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Kim, Kyu-Tae, Kristin Baird, Sean Davis, et al. "Constitutive FLT3 Activation Results in Specific Changes in Gene Expression in Myeloid Leukemic Cells." Blood 104, no. 11 (2004): 1115. http://dx.doi.org/10.1182/blood.v104.11.1115.1115.

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Abstract Constitutively activating internal tandem duplication (ITD) mutations of the receptor tyrosine kinase FLT3 play an important role in leukemogenesis. They are the most common genetic alteration in AML and their presence is associated with poor prognosis. To better understand FLT3 signaling in leukemogenesis, we have examined the changes in gene expression induced by FLT3/ITD or constitutively activated wild type FLT3 signaling by cDNA microarray analysis. In order to minimize gene expression changes that might be drug specific and not related to FLT3 inhibition or might be cell-type specific, we used three different FLT3 inhibitors, CEP-701, CEP-5214, and AG1296, and three different constitutively activated FLT3-expressing leukemia-derived cell lines, EOL-1, MOLM-14 and MV4-11. We considered to be FLT3 responsive only those genes whose expression consistently changed in response to FLT3 inhibition by each of the three FLT3 inhibitors in all of the cell lines. RNA for hybridization to the microarrays was harvested from cells both before and after increasing times of FLT3 inhibition to determine genes which decreased or increased in response to FLT3 signaling. In addition, because the inhibitors are all reversible, RNA was also harvested from the cells at increasing times after release from FLT3 inhibition. This enabled us to confirm that, for example, genes whose expression appeared FLT3 dependent and were thus down-regulated by FLT3 inhibition, returned towards normal levels after FLT3 signaling was allowed to resume. Statistical analysis of the microarray results indicated a limited set of genes are highly and consistently affected by FLT3 inhibition and return toward pretreatment levels after release from inhibitor. We confirmed the cDNA microarray data using quantitative real-time PCR. Several of the most significantly affected genes are involved in the Ras/MAPK pathway including DUSP6, DUSP7, MAPK6, TNF, and cMyc. Other sets of genes are involved in JAK/STAT or Wnt signaling pathways including Pim-1, cMyc, Cyclin D3, IL4 receptor, and CISH. These genes are all consistently down-regulated after FLT3 inhibition. These data further confirm the role of constitutively activating FLT3 in mediating multiple signal transduction pathways. We also found several transcriptional factors (RUNX1/AML1, MAFG, XBP1, TGFBI4, and BRD8), several genes involved in receptor-mediated signaling (IL1RAP, CDC42EP3, PLAUR, LY64), and several genes involved in cell proliferation, metabolism, or structure (BCL7A, APTX, GHRH, SET7, ATAD2, CLIC1, CRIP2, MRPL12, VIM) to be consistently differentially expressed. In summary, we have found by cDNA microarray analysis and confirmed by QPCR, a consistent pattern of FLT3 dependent gene expression. The alteration of the gene expression profile in these cells is likely the mechanism of FLT3-mediated leukemogenisis.

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Liu, Zhi-Fang, Chun-Yan Chen, Wei Tang, Jian-Ye Zhang, Yao-Qin Gong, and Ji-Hui Jia. "Gene-expression profiles in gastric epithelial cells stimulated with spiral and coccoid Helicobacter pylori." Journal of Medical Microbiology 55, no. 8 (2006): 1009–15. http://dx.doi.org/10.1099/jmm.0.46456-0.

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Human gastric epithelial immortalized GES-1 cells were infected with spiral and coccoid Helicobacter pylori. Scanning electron microscopy was used to determine the ability of the two forms of H. pylori to adhere to GES-1 cells. GES-1 cell apoptosis induced by coccoid and spiral H. pylori was analysed using flow cytometry. A cDNA microarray for 22 000 human genes was used to identify the gene-expression differences in GES-1 cells infected with the two forms of H. pylori, and the gene expression identified by the cDNA microarray was confirmed by RT-PCR. Scanning electron microscope observation showed that both coccoid and spiral bacteria can adhere to GES-1 cells. After 4 h infection, apoptosis induction was 27.4 % for spiral-form infection and 10.2 % for coccoid-form infection. Of 268 differentially expressed genes identified by cDNA microarray, 166 showed higher expression with the spiral H. pylori infection than with the coccoid H. pylori infection. To the best of the authors' knowledge, this is the first report that GES-1 cells infected with spiral H. pylori have higher expression of cxcl10, ccl11, ccl5, groα, TLR5, ATF3, fos, fosl2, gadd45a and myc. The cells infected with coccoid H. pylori had higher expression of survivin. The global profile of gene expression in GES-1 cells infected with coccoid and spiral H. pylori is described for the first time.

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Sarropoulou, Elena, Georgios Kotoulas, Deborah M. Power, and Robert Geisler. "Gene expression profiling of gilthead sea bream during early development and detection of stress-related genes by the application of cDNA microarray technology." Physiological Genomics 23, no. 2 (2005): 182–91. http://dx.doi.org/10.1152/physiolgenomics.00139.2005.

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Large-scale gene expression studies were performed for one of the main European aquaculture species, the gilthead sea bream Sparus auratus L. For this purpose, a cDNA microarray containing 10,176 clones from a cDNA library of mixed embryonic and larval stages was constructed. In addition to its importance for aquaculture, the taxonomic position and the relatively small genome size of sea bream makes it a prospective model for evolutionary biology and comparative genomics. However, so far, no large-scale analysis of gene expression exists for this species. In the present study, gene expression was analyzed in gilthead sea bream during early development, a significant period in the determination of quantitative traits and therefore of considerable interest for aquaculture. Synexpression groups expressed primarily early and late in development were determined and were composed of both known and novel genes. Furthermore, it was possible to identify stress response genes induced by cortisol injections using the cDNA microarray generated. The creation of gene expression profiles for sea bream by microarray hybridization will accelerate identification of candidate genes involved in multifactorial traits and certain regulatory pathways and will also contribute to a better understanding of the genetic background of fish physiology, which may help to improve aquaculture practices.

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Zhao, Baiteng, Robert A. Bowden, Salomon A. Stavchansky, and Phillip D. Bowman. "Human endothelial cell response to gram-negative lipopolysaccharide assessed with cDNA microarrays." American Journal of Physiology-Cell Physiology 281, no. 5 (2001): C1587—C1595. http://dx.doi.org/10.1152/ajpcell.2001.281.5.c1587.

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To assess the feasibility of using cDNA microarrays to understand the response of endothelial cells to lipopolysaccharide (LPS) and to evaluate potentially beneficial agents in treatment of septic shock, human umbilical vein endothelial cells were exposed to Escherichia coli LPS for 1, 4, 7, 12, or 24 h. Total RNA was isolated and reverse-transcribed into33P-labeled cDNA probes that were hybridized to human GeneFilter microarrays containing ∼4,000 genes. The mRNA levels of several genes known to respond to LPS changed after stimulation. In addition, a number of genes not previously implicated in the response of endothelial cells to LPS also appeared to be altered in expression. Nuclear factor-κB (NF-κB) was shown to play an important role in regulating genes identified from the microarray studies. Pretreatment of endothelial cells with a specific NF-κB translocation inhibitor eliminated most of the alterations in gene expression. Quantitative RT-PCR results independently confirmed the microarray results for monocyte chemotactic protein-1 and interleukin-8, and enzyme-linked immunosorbent assays demonstrated that augmented transcription was followed by translation and secretion.

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Imoto, Seiya, Christopher J. Savoie, Sachiyo Aburatani, et al. "Use of Gene Networks for Identifying and Validating Drug Targets." Journal of Bioinformatics and Computational Biology 01, no. 03 (2003): 459–74. http://dx.doi.org/10.1142/s0219720003000290.

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We propose a new method for identifying and validating drug targets by using gene networks, which are estimated from cDNA microarray gene expression profile data. We created novel gene disruption and drug response microarray gene expression profile data libraries for the purpose of drug target elucidation. We use two types of microarray gene expression profile data for estimating gene networks and then identifying drug targets. The estimated gene networks play an essential role in understanding drug response data and this information is unattainable from clustering methods, which are the standard for gene expression analysis. In the construction of gene networks, we use the Bayesian network model. We use an actual example from analysis of the Saccharomyces cerevisiae gene expression profile data to express a concrete strategy for the application of gene network information to drug discovery.

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Inoue, A., N. Yoshida, Y. Omoto, et al. "Development of cDNA microarray for expression profiling of estrogen-responsive genes." Journal of Molecular Endocrinology 29, no. 2 (2002): 175–92. http://dx.doi.org/10.1677/jme.0.0290175.

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Estrogen plays an important role in many physiological events including carcinogenesis and the development of human breast cancer. However, the molecular mechanisms of estrogen signaling in cancers have not been clarified hitherto and accurate therapeutic prediction of breast cancer is earnestly desired. We first carried out estrogen-responsive expression profiling of approximately 9000 genes in estrogen receptor-positive human MCF-7 breast cancer cells. Based on the results, estrogen-responsive genes were selected for production of a custom-made cDNA microarray. Using a microarray consisting of the narrowed-down gene subset, we first analyzed the time course of the estrogen-responsive gene expression profiles in MCF-7 cells, resulting in subdivision of the genes up-regulated by estrogen into early-responsive and late-responsive genes. The expression patterns of several genes were confirmed by Northern blot analysis. We also analyzed the effects of the estrogen antagonists ICI 182780 and 4-hydroxytamoxifen (OHT) on the estrogen-responsive gene expression profiles in MCF-7 cells. While the regulation of most of the genes by estrogen was completely abolished by ICI 182780, some genes were partially regulated by estrogen even in the presence of OHT. Furthermore, the estrogen-responsive gene expression profiles of twelve cancer cell lines derived from the breast, ovary, stomach and other tissues were obtained and analyzed by hierarchical clustering including the profiles in MCF-7 cells. Several genes also showed up-regulation or down-regulation by estrogen in cell lines other than MCF-7 cells. The significance of the estrogen-responsive genes identified in these analyses concerning the nature of cancer is discussed.

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Li, Zhi Yao, and Gui Rong Weng. "Segmentation of cDNA Microarray Image Using Fuzzy c-Mean Algorithm and Mathematical Morphology." Key Engineering Materials 464 (January 2011): 159–62. http://dx.doi.org/10.4028/www.scientific.net/kem.464.159.

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cDNA microarray technology provides an effectual tool to explore the enormous genome. cDNA microarray consists of thousands of gene sequences which are printed on glass slide and these sequence information can be obtained by forming a microarray image. So image analysis is crucial. However, image segmentation is another key point. How to deal with the gene spots which are always comprised with imperfection such as irregular contours, donut shapes, artifact and spots with low expression is important to the robustness of the segmentation method. The paper proposed a method based on fuzzy c-mean algorithm which can effectively avoid the influence of various types of artifacts through adaptive partitioning.

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Lehnert, S. A., Y. H. Wang, S. H. Tan, and A. Reverter. "Gene expression-based approaches to beef quality research." Australian Journal of Experimental Agriculture 46, no. 2 (2006): 165. http://dx.doi.org/10.1071/ea05226.

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Advances in mammalian genomics have permitted the application of gene expression profiling approaches to gene discovery for meat quality traits in cattle. The first custom cDNA microarray based on the transcriptome of bovine muscle and fat tissue was developed and applied to animal experimentation and cell culture experimentation between 1999 and 2005. Complementary DNA microarray tools for beef quality research were developed in parallel with bioinformatics tools that permit the analysis of microarray data obtained from complex experimental designs commonly encountered in large animal research. In addition, tools were designed to link gene expression data with gene function in the bovine, such as in vitro models of bovine adipogenesis and bioinformatics tools to map gene networks from expression data. The application of these genomics tools to the study of beef quality has yielded novel knowledge of genes and molecules involved in the processes of intramuscular adipogenesis and protein turnover. This review summarises the current state of knowledge and important lessons derived from bovine genomics initiatives in Australia and around the world.

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de la Vega, Enrique, Michael R. Hall, Kate J. Wilson, Antonio Reverter, Rick G. Woods, and Bernard M. Degnan. "Stress-induced gene expression profiling in the black tiger shrimp Penaeus monodon." Physiological Genomics 31, no. 1 (2007): 126–38. http://dx.doi.org/10.1152/physiolgenomics.00068.2007.

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Cultured shrimp are continuously exposed to variable environmental conditions that have been associated with stress and subsequent outbreaks of disease. To investigate the effect of environmental stress on Penaeus monodon gene expression, a 3,853 random cDNA microarray chip was generated with clones originating from six stress-enriched hemocyte libraries generated by suppression subtractive hybridization and a normal hemocyte cDNA library. Changes in temporal gene expression were analyzed from shrimp exposed to hypoxic, hyperthermic, and hypoosmotic conditions; 3.1% of the cDNAs were differentially expressed in response to at least one of the environmental stressors, and 72% of the differentially expressed clones had no significant sequence similarity to previously known genes. Among those genes with high identity to known sequences, the most common functional groups were immune-related genes and non-long terminal repeat retrotransposons. Hierarchical clustering revealed a set of cDNAs with temporal and stress-specific gene expression profiles as well as a set of cDNAs indicating a common stress response between stressors. Hypoxic and hyperthermic stressors induced the most severe short-term response in terms of gene regulation, and the osmotic stress had the least variation in expression profiles relative to the control. These expression data agree with observed differences in shrimp physical appearance and behavior following exposure to stress conditions.

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Yang, Liping, Miqu Wang, Wei Wu, and Louxin Zhang. "Transcriptome Analysis of Cold Syndrome Using Microarray." American Journal of Chinese Medicine 35, no. 04 (2007): 609–20. http://dx.doi.org/10.1142/s0192415x07005107.

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Microarrays are widely used to study changes in gene expression in diseases. In this paper, we use this technology to discover gene expression patterns in the cold syndrome in Chinese medicine. We identify differentially expressed genes and extracted gene modules that are enriched with differentially expressed genes in the cold syndrome by analyzing cDNA samples, which are purified from blood taken from a pedigree. Our results suggest that the cold syndrome might be caused by the physiological imbalance and/or the disorder of metabolite processes. The study confirms the hypotheses about molecular pathways responsible to human metabolic-related diseases.

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LOGUINOV, A. V., L. M. ANDERSON, G. J. CROSBY, and R. Y. YUKHANANOV. "Gene expression following acute morphine administration." Physiological Genomics 6, no. 3 (2001): 169–81. http://dx.doi.org/10.1152/physiolgenomics.2001.6.3.169.

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The long-term response to neurotropic drugs depends on drug-induced neuroplasticity and underlying changes in gene expression. However, alterations in neuronal gene expression can be observed even following single injection. To investigate the extent of these changes, gene expression in the medial striatum and lumbar part of the spinal cord was monitored by cDNA microarray following single injection of morphine. Using robust and resistant linear regression (MM-estimator) with simultaneous prediction confidence intervals, we detected differentially expressed genes. By combining the results with cluster analysis, we have found that a single morphine injection alters expression of two major groups of genes, for proteins involved in mitochondrial respiration and for cytoskeleton-related proteins. RNAs for these proteins were mostly downregulated both in the medial striatum and in lumbar part of the spinal cord. These transitory changes were prevented by coadministration of the opioid antagonist naloxone. Data indicate that microarray analysis by itself is useful in describing the effect of well-known substances on the nervous system and provides sufficient information to propose a potentially novel pathway mediating its activity.

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