Biomedical subjects

Hiroko Kita-Matsuo

Publications and source records attributed to Hiroko Kita-Matsuo.

3 recordsLinked to original sources

PubMed2006

Central genetic alterations common to all HCV-positive, HBV-positive and non-B, non-C hepatocellular carcinoma: a new approach to identify novel tumor markers.

Hepatocellular carcinoma (HCC) is a common malignancy, but the prognosis remains poor due to the lack of sensitive diagnostic markers. To gain insight into the central molecular features common to all types of HCC, and to identify novel diagnostic markers or therapeutic targets for HCC, we performed a gene expression profiling analysis using a high throughput RT-PCR system. After examining the mRNA expression of 3,072 genes in 204 (119 tumor and 85 non-tumor) liver samples, we identified differential gene expression between the HCV group (n=80), HBV group (n=19) and non-B, non-C group (n=20) with a principal component analysis and a correlation spectrum analysis. After selection of genes differentially expressed between tumor and non-tumor tissues (p<0.01) within each HCC group, a total of 51 differentially expressed genes (23 upregulated and 28 downregulated genes) were found to be common to the three HCC groups. Gene Ontology grouping analysis revealed that genes with functions related to cell proliferation or differentiation and genes encoding extracellular proteins were found to be significantly enriched in these 51 common genes. Using an atelocollagen-based cell transfection array for functional analysis of eight upregulated genes, five (CANX, FAM34A, PVRL2, LAMR1, and GBA) significantly inhibited cellular apoptosis by two independent assays. In conclusion, we identified 51 differentially expressed genes, common to all HCC types. Among these genes, there was a high incidence of anti-apoptotic activity. This combination approach with the advanced statistical methods and the bioinformatical analysis may be useful for finding novel molecular targets for diagnosis and therapy.

Apoptosis↗

PubMed2005

Adaptor-tagged competitive polymerase chain reaction: amplification bias and quantified gene expression levels.

Adaptor-tagged competitive polymerase chain reaction (ATAC-PCR) is an advanced version of quantitative competitive PCR characterized by the addition of unique adaptors to different cDNA samples. It is currently the only quantitative PCR technique that enables large-scale gene expression analysis. Multiplex application of ATAC-PCR employs seven adaptors, two or three of which are used as controls to generate a calibration curve. The characteristics of the ATAC-PCR method for large-scale data production, including any adaptor- and gene-dependent amplification biases, were evaluated by using this method to analyze the expression of 384 mouse brain genes. Short adaptors tended to amplify at higher efficiency than did long adaptors. The population of genes with a high amplification bias increased with the use of short adaptors. Subtracting the median value of all adaptor-dependent biases could reduce this bias; the majority of genes displayed a small gene-dependent bias, which facilitated reliable quantification. We modified ATAC-PCR to estimate molecular numbers of transcripts by introducing synthetic standards. This modification demonstrated that gene expression levels in mammalian cells are varied over seven orders of magnitude.

Animals↗

PubMed2005

Gene expression profiling of cerebellar development with high-throughput functional analysis.

We measured the expression levels of 450 genes during mouse postnatal cerebellar development by quantitative PCR using RNA purified from layers of the cerebellar cortex. Principal component analysis of the data matrix demonstrated that the first and second components corresponded to general levels of gene expression and gene expression patterns, respectively. We introduced 288 of the 450 genes into PC12 cells using a high-throughput transfection assay based on atelocollagen and determined the ability of each gene to promote neurite outgrowth or cell proliferation. Five genes induced neurite outgrowth, and seven genes enhanced proliferation. Evaluation of the functional data and gene expression patterns showed that none of these genes exhibited elevated expression at maturation, suggesting that genes characteristic of mature neurons are not likely to participate in neuronal development. These results demonstrate that functional data can facilitate interpretation of expression profiles and identification of new molecules that participate in biological processes.

Animals↗