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ABSTRACT: Human neuroblastoma is the most commonly diagnosed solid tumor in children. The existence and development of S-type cells
is important for the prognosis and malignant properties in neuroblastoma patients. However, their origin is controversial
and the relationship between S- and N-type cells in neuroblastoma has not yet been clarified. To investigate the feasibility
of inter-conversion and characteristic features between S-type cells lacking malignant potential and N-type cells having metastatic
potential, the genomic profiles of neuroblastoma SH-EP (S-type) and SH-SY5Y (N-type) cells were compared at high resolution.
Common gain segments (>10 Mb) between SH-EP and SH-SY5Y cells were observed at 1q21.1–q44 and 17q21.32–q25.3. The results
of the fluorescent in situ hybridization (FISH) analysis showed good agreement with the array-CGH data. Genome-wide inspection of SH-EP and SH-SY5Y
cells successfully identified not only common chromosomal aberrations but also genomic variations, suggesting that interconversion
could not take place between S- and Ntype cells. The identified differences between less aggressive S-type cells (SH-EP) and
highly aggressive neuroblastic N-type cells (SH-SY5Y) might be useful for understanding tumorigenicity and discovery of potential
new markers in neuroblastoma. This is the first effort to compare genomic profiles between less aggressive S-type cells (SH-EP)
and highly aggressive neuroblastic N-type cells (SH-SY5Y) at high resolution.
KeywordsCopy number variation–Neuroblastoma SH-EP and SH-SY5Y–Array-based comparative genomic hybridization (array-CGH)–Inter-conversion
BioChip journal 04/2012; 5(2):165-174. · 0.86 Impact Factor
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ABSTRACT: Glutathione peroxidase 3 (GPX3) is a member of glutathione peroxidase family, exerting one of the most important cellular defense mechanisms against stress signals, including oxidative damage. In this study, the expression of GPX3 mRNA and protein was analyzed for ovarian cancer tissues to test its applicability as a biomarker that can distinguish the four major histologic types of epithelial ovarian cancer. A public microarray dataset containing 99 ovarian cancer and 4 normal ovary samples was downloaded, and GPX3 mRNA expression was analyzed. The expression of GPX3 protein was measured by immunohistochemical staining in 40 epithelial ovarian cancer tissues, 10 for each of the serous, endometrioid, mucinous, and clear cell type. Histoscores were made from the immunohistostaining, and analysis of variance (ANOVA) was performed to quantitate the differences in protein level. Analysis of genomic dataset confirms a GPX3 overexpression in clear cell type ovarian adenocarcinoma compared with normal ovary and 3 other subtypes of epithelial ovarian cancer at mRNA level. GPX3 also shows the highest average antibody staining intensities in clear cell type ovarian adenocarcinomas over the other 3 types in immunostaining on tissue arrays. This is the first validation of GPX3 as a clear cell type-specific biomarker in ovarian cancer patients' tissues by immunostaining. GPX3 may serve as an important molecular marker for the diagnosis and molecular understanding of clear cell carcinoma of the ovary.
Medical Oncology 12/2011; 28 Suppl 1:S522-7. · 2.14 Impact Factor
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ABSTRACT: Since persistent infection with high-risk human papillomavirus (HPV) is a known cause of high-grade cervical intraepithelial neoplasia and cervical cancer, several HPV DNA detection methods have been developed during the last decade. The Hybrid Capture II (HCII) assay, which allows detection of 13 high-risk HPVs, has been well validated; however, it does not provide any genotype-specific information. The oncogenic activity of HPV is dependent on its genotype. The prophylactic effects of HPV vaccines are based on L1 virus-like particles and are limited mainly to infections corresponding to the HPV type used to develop the immunogen. Therefore, accurate detection and genotyping are important for treatment as well as screening. A newly developed HPV genotyping system using a liquid bead array was evaluated with 286 cervical samples and the results were compared to two commercially available methods, i.e. the HCII and HPV DNA chip assays, and sequencing. The sensitivity for detection of high-risk HPV was 85.3 % (HCII), 94.7 % (DNA chip) and 99.0 % (liquid bead array). The liquid bead array showed almost perfect agreement (κ=0.95) with genotype information confirmed by sequencing, while substantial agreement (κ=0.8) was observed between DNA chip and sequencing. Furthermore, the liquid bead array had superior detection of 26 HPVs (16 high-risk and 10 low-risk types) and has proven to be as accurate as sequencing in identifying individual HPV types, even in cases with multiple HPV infections.
Journal of Medical Microbiology 10/2010; 60(Pt 2):162-71. · 2.50 Impact Factor
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ABSTRACT: Most patients with ovarian cancer are diagnosed with advanced stage disease (i.e., stage III-IV), which is associated with a poor prognosis. Differentially expressed genes (DEGs) in stage III serous ovarian carcinoma compared to normal tissue were screened by a new differential display method, the annealing control primer (ACP) system. The potential targets for markers that could be used for diagnosis and prognosis, for stage III serous ovarian cancer, were found by cluster and survival analysis.
The ACP-based reverse transcriptase polymerase chain reaction (RT PCR) technique was used to identify DEGs in patients with stage III serous ovarian carcinoma. The DEGs identified by the ACP system were confirmed by quantitative real-time PCR. Cluster analysis was performed on the basis of the expression profile produced by quantitative real-time PCR and survival analysis was carried out by the Kaplan-Meier method and Cox proportional hazards multivariate model; the results of gene expression were compared between chemo-resistant and chemo-sensitive groups.
A total of 114 DEGs were identified by the ACP-based RT PCR technique among patients with stage III serous ovarian carcinoma. The DEGs associated with an apoptosis inhibitory process tended to be up-regulated clones while the DEGs associated with immune response tended to be down-regulated clones. Cluster analysis of the gene expression profile obtained by quantitative real-time PCR revealed two contrasting groups of DEGs. That is, a group of genes including: SSBP1, IFI6 DDT, IFI27, C11orf92, NFKBIA, TNXB, NEAT1 and TFG were up-regulated while another group of genes consisting of: LAMB2, XRCC6, MEF2C, RBM5, FOXP1, NUDCP2, LGALS3, TMEM185A, and C1S were down-regulated in most patients. Survival analysis revealed that the up-regulated genes such as DDAH2, RNase K and TCEAL2 might be associated with a poor prognosis. Furthermore, the prognosis of patients with chemo-resistance was predicted to be very poor when genes such as RNase K, FOXP1, LAMB2 and MRVI1 were up-regulated.
The DEGs in patients with stage III serous ovarian cancer were successfully and reliably identified by the ACP-based RT PCR technique. The DEGs identified in this study might help predict the prognosis of patients with stage III serous ovarian cancer as well as suggest targets for the development of new treatment regimens.
BMC Cancer 10/2010; 10:576. · 3.01 Impact Factor
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ABSTRACT: The prespore-specific activation of sigma factor SigF (sigma(F)) in Bacillus subtilis has been explained mainly by two factors, i.e., the transient genetic asymmetry and the volume difference between the mother cell and the prespore. Here, we systematically surveyed the effect of these two factors on sporulation using a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). Considering the fact that the transient genetic asymmetry and the volume difference in sporulation of B. subtilis finally bring about the concentration difference in two proteins SpoIIAB (AB) and SpoIIAA (AA) between the mother cell and the prespore, we have surveyed the effect of AB and AA concentration on the prespore-specific activation of sigma(F) occurring in the early stage of sporulation. Our results show that the prespore-specific activation of sigma(F) could be governed by the ratio of AA to AB rather than their concentrations themselves. Our model also suggests that B. subtilis could maximize the ratio of AA to AB in the prespore and minimize it in the mother cell by employing both the transient genetic asymmetry and the volume difference simultaneously. This might give a good explanation to the co-occurrence of the transient asymmetry and the volume difference during sporulation of B. subtilis. In addition, we suggest for the first time that the sigma(F) activation in the prespore might be switched off by the decrease in the ratio of AA to AB after the transient genetic asymmetry is to an end by completion of DNA translocation into the prespore.
Bio Systems 03/2010; 100(3):178-84. · 1.27 Impact Factor
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ABSTRACT: The thermotolerance of Aspergillus fumigatus plays a critical role in mammalian and avian infections. Thus, the identification of its adaptation mechanism to higher temperature is very important for an efficient anti-fungal drug development as well as fundamental understanding of its pathogenesis. We explored the temporal transcription regulation structure of this pathogenic fungus under heat shock conditions using the time series microarray data reported by Nierman et al. (Nature 2005, 438:1151-1156).
The estimated transcription regulation structure of A. fumigatus shows that the heat shock proteins are strongly negatively associated with central metabolic pathway genes such as the tricarboxylic acid cycle (TCA cycle) and carbohydrate metabolism. It was 60 min and 120 min, respectively, after the growth temperature changes from 30 degrees C (corresponding to environments of tropical soil) to 37 degrees C and 48 degrees C (corresponding to temperatures in the human body and compost, respectively) that some of genes in TCA cycle were started to be upregulated. In these points, most of heat shock proteins showed lowest expression level after heat shocks. Among the heat shock proteins, the HSP30 (AFU6G06470), a single integral plasma membrane heat shock protein, presented most active role in transcription regulation structure in both heat shock conditions of 37 degrees C and 48 degrees C. The metabolic genes associated with multiple genes in the gene regulation network showed a tendency to have opposite expression patterns of heat shock proteins. The role of those metabolic genes was second regulator in the coherent feed-forward loop type of regulation structure having heat shock protein as its first regulator. This type of regulation structure might be very advantageous for the thermal adaptation of A. fumigatus under heat shock because a small amount of heat shock proteins can rapidly magnify their regulation effect on target genes. However, the coherent feed-forward loop type of regulation of heat shock proteins with metabolic genes became less frequent with increasing temperature. This might be the reason for dramatic increase in the expression of heat shock proteins and the number of heat shock response genes at heat shock of 48 degrees C.
We systemically analysed the thermal adaption mechanism of A. fumigatus by state space model with times series microarray data in terms of transcription regulation structure. We suggest for the first time that heat shock proteins might efficiently regulate metabolic genes using the coherent feed-forward loop type of regulation structure. This type of regulation structure would also be efficient for adjustment to the other stresses requiring rapid change of metabolic mode as well as thermal adaptation.
BMC Genomics 02/2009; 10:306. · 4.07 Impact Factor
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ABSTRACT: The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.
Molecules and Cells 05/2008; 25(2):279-88. · 2.18 Impact Factor
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ABSTRACT: Most neuroblastoma cells have chromosomal aberrations such as gains, losses, amplifications and deletions of DNA. Conventional approaches like fluorescence in situ hybridization (FISH) or metaphase comparative genomic hybridization (CGH) can detect chromosomal aberrations, but their resolution is low. In this study we used array-based comparative genomic hybridization to identify the chromosomal aberrations in human neuroblastoma SH-SY5Y cells. The DNA microarray consisting of 4000 bacterial artificial chromosome (BAC) clones was able to detect chromosomal regions with aberrations. The SH-SY5Y cells showed chromosomal gains in 1q12 approximately q44 (Chr1:142188905-246084832), 7 (over the whole chromosome), 2p25.3 approximately p16.3 (Chr2:18179-47899074), and 17q 21.32 approximately q25.3 (Chr17:42153031-78607159), while chromosomal losses detected were the distal deletion of 1p36.33 (Chr1:552910-563807), 14q21.1 approximately q21.3 (Chr14:37666271- 47282550), and 22q13.1 approximately q13.2 (Chr22:36885764-4190 7123). Except for the gain in 17q21 and the loss in 1p36, the other regions of gain or loss in SH-SY5Y cells were newly identified.
Molecules and Cells 09/2007; 24(1):105-12. · 2.18 Impact Factor
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ABSTRACT: DNA microarray is a powerful tool for high-throughput analysis of biological systems. Various computational tools have been created to facilitate the analysis of the large volume of data produced in DNA microarray experiments. Normalization is a critical step for obtaining data that are reliable and usable for subsequent analysis such as identification of differentially expressed genes and clustering. A variety of normalization methods have been proposed over the past few years, but no methods are still perfect. Various assumptions are often taken in the process of normalization. Therefore, the knowledge of underlying assumption and principle of normalization would be helpful for the correct analysis of microarray data. We present a review of normalization techniques from single-labeled platforms such as the Affymetrix GeneChip array to dual-labeled platforms like spotted array focusing on their principles and assumptions.
Molecules and Cells 01/2007; 22(3):254-61. · 2.18 Impact Factor
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ABSTRACT: The problems associated with gene identification and the prediction of gene structure in DNA sequences have been the focus of increased attention over the past few years with the recent acquisition by large-scale sequencing projects of an immense amount of genome data. A variety of prediction programs have been developed in order to address these problems. This paper presents a review of the computational approaches and gene-finders used commonly for gene prediction in eukaryotic genomes. Two approaches, in general, have been adopted for this purpose: similarity-based and ab initio techniques. The information gleaned from these methods is then combined via a variety of algorithms, including Dynamic Programming (DP) or the Hidden Markov Model (HMM), and then used for gene prediction from the genomic sequences.
The Journal of Microbiology 05/2006; 44(2):137-44. · 1.10 Impact Factor
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ABSTRACT: A growing body of evidence suggests that sphingolipids are important bioactive molecules, in addition to being critical structural components of cellular membranes. These molecules have been implicated in regulating cell growth, differentiation, angiogenesis, apoptosis, and senescence. Many of the enzymes involved in sphingolipid biosynthesis are the targets of fungal toxins, thus underscoring the importance of this pathway. An international consortium has made considerable progress in sequencing the genome of Aspergillus fumigatus, one of the most common mold pathogens of humans; however, most genes have not yet been annotated. Here, we have identified genes involved in the sphingolipid pathway of A. fumigatus by comparative analysis with four other fungal species and the gene prediction program GlimmerM. Our results shows that A. fumigatus has most of the sphingolipid pathway genes found in other fungi, except for the CSG2 and IPT1 genes; the former is involved in the mannosylation of inositol phosphorylceramide (IPC) to mannose-inositol-phosphorylceramide and the latter involved in the synthesis of mannose-(inositol-P)(2)-ceramide from mannose-inositol-phosphorylceramide.
Current Genetics 09/2005; 48(2):134-41. · 2.56 Impact Factor
