Biomedical subjects

Sigeo Ihara

Publications and source records attributed to Sigeo Ihara.

7 recordsLinked to original sources

PubMed2006

Genome-wide detection of human copy number variations using high-density DNA oligonucleotide arrays.

Recent reports indicate that copy number variations (CNVs) within the human genome contribute to nucleotide diversity to a larger extent than single nucleotide polymorphisms (SNPs). In addition, the contribution of CNVs to human disease susceptibility may be greater than previously expected, although a complete understanding of the phenotypic consequences of CNVs is incomplete. We have recently reported a comprehensive view of CNVs among 270 HapMap samples using high-density SNP genotyping arrays and BAC array CGH. In this report, we describe a novel algorithm using Affymetrix GeneChip Human Mapping 500K Early Access (500K EA) arrays that identified 1203 CNVs ranging in size from 960 bp to 3.4 Mb. The algorithm consists of three steps: (1) Intensity pre-processing to improve the resolution between pairwise comparisons by directly estimating the allele-specific affinity as well as to reduce signal noise by incorporating probe and target sequence characteristics via an improved version of the Genomic Imbalance Map (GIM) algorithm; (2) CNV extraction using an adapted SW-ARRAY procedure to automatically and robustly detect candidate CNV regions; and (3) copy number inference in which all pairwise comparisons are summarized to more precisely define CNV boundaries and accurately estimate CNV copy number. Independent testing of a subset of CNVs by quantitative PCR and mass spectrometry demonstrated a >90% verification rate. The use of high-resolution oligonucleotide arrays relative to other methods may allow more precise boundary information to be extracted, thereby enabling a more accurate analysis of the relationship between CNVs and other genomic features.

Algorithms↗

PubMed2006

Packet traffic analysis of scale-free networks for large-scale network-on-chip design.

Recent progress in integrated circuit technologies requires precise evaluation between dynamic characteristics and topological architecture design. In this paper, we have investigated the performance evaluation of network-on-chip (NoC) architectures constructed with diverse scale-free network topologies by dynamic packet traffic simulation and theoretical network analysis. Topological differences of scale-free networks are evaluated by the degree-degree correlations that indicate topological tendency between the degree of a node and that of the nearest neighbors. Our simulation results quantitatively show that the NoC architecture constructed with the topology where hubs mostly connect to lower-degree nodes is found to achieve short latency and low packet loss ratio since it can disperse traffic load and avoid the extreme concentration of load on hubs.

Journal Article↗

PubMed2006

Noise reduction from genotyping microarrays using probe level information.

Genomic copy number change is one of the important phenomenon observed in cancer and other genetic disorders. Recently oligonucleotide microarrays have been used to analyze changes in the copy number. Although high density microarrays provide genome wide useful data on copy number, they are often associated with substantial amount of experimental noise that could affect the performance of the analyses. We used the high density oligonucleotide genotyping microarrays in our experiments that uses redundant probe tiling approach for individual SNPs. We found that the noise in the genotyping microarray data is associated with several experimental steps during target preparation and devised an algorithm that takes into account those experimental parameters. Additionally, defective probes that do not hybridize well to the target and therefore could not be modified inherently were detected and omitted automatically by using the algorithm. When we applied the algorithm to actual datasets, we could reduce the noise substantially without compressing the dynamic range. Additionally, combinatorial use of our noise reduction algorithm and conventional breakpoint detection algorithm successfully detected a microamplification of c-myc which was overlooked in the raw data. The algorithm described here is freely available with the software upon request to all non-profit researchers.

Adenocarcinoma↗

PubMed2005

Analysis of mechanism for human gammadelta T cell recognition of nonpeptide antigens.

Whereas human gammadelta T cells respond to nonpeptide antigens like pyrophosphomonoesters and alkyl amines in the primary reactions, only pyrophosphomonoesters provoke proliferative responses in the secondary responses. To elucidate the differences in stimulatory activity between the two groups of nonpeptide antigens, we systematically analyzed time courses of gene expressions by microarray analyses. While 253 genes were induced by stimulation with 2-methyl-3-butenyl-1-pyrophosphate (2M3B1PP), only 35 genes were detected after stimulation with isobutyl amine. Then, gammadelta T cells expressed various cytokines like XCL1-2, CCL3-4, TNF-alpha, and IFN-gamma in response to 2M3B1PP in a time-dependent manner, while transient expressions were observed in IBA during the time period. The differences in such responsiveness are likely to originate from the activation state of NFAT, which is involved in the expression of transcription factors, EGR1-3 and NR4A1-2, and might play a crucial role in effector functions of gammadelta T cells.

Antigens↗

PubMed2005

Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues.

A critical and difficult part of studying cancer with DNA microarrays is data interpretation. Besides the need for data analysis algorithms, integration of additional information about genes might be useful. We performed genome-wide expression profiling of 36 types of normal human tissues and identified 2503 tissue-specific genes. We then systematically studied the expression of these genes in cancers by reanalyzing a large collection of published DNA microarray datasets. We observed that the expression level of liver-specific genes in hepatocellular carcinoma (HCC) correlates with the clinically defined degree of tumor differentiation. Through unsupervised clustering of tissue-specific genes differentially expressed in tumors, we extracted expression patterns that are characteristic of individual cell types, uncovering differences in cell lineage among tumor subtypes. We were able to detect the expression signature of hepatocytes in HCC, neuron cells in medulloblastoma, glia cells in glioma, basal and luminal epithelial cells in breast tumors, and various cell types in lung cancer samples. We also demonstrated that tissue-specific expression signatures are useful in locating the origin of metastatic tumors. Our study shows that integration of each gene's breadth of expression (BOE) in normal tissues is important for biological interpretation of the expression profiles of cancers in terms of tumor differentiation, cell lineage, and metastasis.

Algorithms↗

PubMed2004

Identification of soluble NH2-terminal fragment of glypican-3 as a serological marker for early-stage hepatocellular carcinoma.

For detection of hepatocellular carcinoma (HCC) in patients with liver cirrhosis, serum alpha-fetoprotein has been widely used, but its sensitivity has not been satisfactory, especially in small, well-differentiated HCC, and complementary serum marker has been clinically required. Glypican-3 (GPC3), a heparan sulfate proteoglycan anchored to the plasma membrane, is a good candidate marker of HCC because it is an oncofetal protein overexpressed in HCC at both the mRNA and protein levels. In this study, we demonstrated that its NH(2)-terminal portion [soluble GPC3 (sGPC3)] is cleaved between Arg(358) and Ser(359) of GPC3 and that sGPC3 can be specifically detected in the sera of patients with HCC. Serum levels of sGPC3 were 4.84 +/- 8.91 ng/ml in HCC, significantly higher than the levels seen in liver cirrhosis (1.09 +/- 0.74 ng/ml; P < 0.01) and healthy controls (0.65 +/- 0.32 ng/ml; P < 0.001). In well- or moderately-differentiated HCC, sGPC3 was superior to alpha-fetoprotein in sensitivity, and a combination measurement of both markers improved overall sensitivity from 50% to 72%. These results indicate that sGPC3 is a novel serological marker essential for the early detection of HCC.

Antibodies, Monoclonal↗

PubMed2003

Identification of gene expression profile in tolerizing murine cardiac allograft by costimulatory blockade.

The induction of specific tolerance would be the ultimate achievement in transplant immunology, but the precise mechanisms of immunologic tolerance remain largely unknown. Here, we investigated global gene expression analysis in tolerizing murine cardiac allografts by means of oligonucleotide microarrays. Tolerance induction was achieved in cardiac allografts from BALB/c to C57BL/6 mice by daily intraperitoneal injection of anti-CD80 and anti-CD86 monoclonal antibodies (mAbs). Comparative analysis revealed 64 genes to be induced more extensively in the tolerizing than in the syngeneic isografts, and 16 genes than in the rejecting allografts. Two genes were specifically upregulated in the tolerizing allografts. In the tolerizing allografts there were induced marked expressions of a number of genes for pro-inflammatory factors, including interferon-gamma-inducible cytokines and chemokines, as well as apoptosis-related genes, which were also upregulated in the rejecting allografts. Moreover, these gene expression patterns continued to be upregulated more than 70 days posttransplant. These results provide evidence that immunologic tolerance can be induced and maintained in the presence of prominent pro-inflammatory gene expression in vivo.

Animals↗