Biomedical subjects

Ryo Matoba

Publications and source records attributed to Ryo Matoba.

16 recordsLinked to original sources

PubMed2006

Dissecting Oct3/4-regulated gene networks in embryonic stem cells by expression profiling.

POU transcription factor Pou5f1 (Oct3/4) is required to maintain ES cells in an undifferentiated state. Here we show that global expression profiling of Oct3/4-manipulated ES cells delineates the downstream target genes of Oct3/4. Combined with data from genome-wide chromatin-immunoprecipitation (ChIP) assays, this analysis identifies not only primary downstream targets of Oct3/4, but also secondary or tertiary targets. Furthermore, the analysis also reveals that downstream target genes are regulated either positively or negatively by Oct3/4. Identification of a group of genes that show both activation and repression depending on Oct3/4 expression levels provides a possible mechanism for the requirement of appropriate Oct3/4 expression to maintain undifferentiated ES cells. As a proof-of-principle study, one of the downstream genes, Tcl1, has been analyzed in detail. We show that Oct3/4 binds to the promoter region of Tcl1 and activates its transcription. We also show that Tcl1 is involved in the regulation of proliferation, but not differentiation, in ES cells. These findings suggest that the global expression profiling of gene-manipulated ES cells can help to delineate the structure and dynamics of gene regulatory networks.

Animals↗

PubMed2006

Klf4 cooperates with Oct3/4 and Sox2 to activate the Lefty1 core promoter in embryonic stem cells.

Although the POU transcription factor Oct3/4 is pivotal in maintaining self renewal of embryonic stem (ES) cells, little is known of its molecular mechanisms. We previously reported that the N-terminal transactivation domain of Oct3/4 is required for activation of Lefty1 expression (H. Niwa, S. Masui, I. Chambers, A. G. Smith, and J. Miyazaki, Mol. Cell. Biol. 22:1526-1536, 2002). Here we test whether Lefty1 is a direct target of Oct3/4. We identified an ES cell-specific enhancer upstream of the Lefty1 promoter that contains binding sites for Oct3/4 and Sox2. Unlike other known Oct3/4-Sox2-dependent enhancers, however, this enhancer element could not be activated by Oct3/4 and Sox2 in differentiated cells. By functional screening of ES-specific transcription factors, we found that Krüppel-like factor 4 (Klf4) cooperates with Oct3/4 and Sox2 to activate Lefty1 expression, and that Klf4 acts as a mediating factor that specifically binds to the proximal element of the Lefty1 promoter. DNA microarray analysis revealed that a subset of putative Oct3/4 target genes may be regulated in the same manner. Our findings shed light on a novel function of Oct3/4 in ES cells.

Animals↗

PubMed2006

Genomic approaches to early embryogenesis and stem cell biology.

Large-scale systematic gene expression analyses of early embryos and stem cells provide useful information to identify genes expressed differentially or uniquely in these cells. We review the current status of various approaches applied to preimplantation embryos and stem cells: expressed sequence tag, serial analysis of gene expression, differential display, massively parallel signature sequencing, DNA microarray (DNA chip) analysis, and chromatin-immunoprecipitation microarrays. We also discuss the biological questions that can only be addressed by the analysis of global gene expression patterns, such as so-called stemness and developmental potency. As the emphasis now shifts from expression profiling to functional studies, we review the genome-scale functional studies of genes: expression cloning, gene trapping, RNA interference, and gene disruptions. Finally, we discuss the future clinical application of such methodologies.

Animals↗

PubMed2005

High-throughput screen for genes predominantly expressed in the ICM of mouse blastocysts by whole mount in situ hybridization.

Mammalian preimplantation embryos provide an excellent opportunity to study temporal and spatial gene expression in whole mount in situ hybridization (WISH). However, large-scale studies are made difficult by the size of the embryos ( approximately 60mum diameter) and their fragility. We have developed a chamber system that allows parallel processing of embryos without the aid of a microscope. We first selected 91 candidate genes that were transcription factors highly expressed in blastocysts, and more highly expressed in embryonic (ES) than in trophoblast (TS) stem cells. We then used the WISH to identify 48 genes expressed predominantly in the inner cell mass (ICM) and to follow several of these genes in all seven preimplantation stages. The ICM-predominant expressions of these genes suggest their involvement in the pluripotency of embryonic cells. This system provides a useful tool to a systematic genome-scale analysis of preimplantation embryos.

Animals↗

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

Prediction of docetaxel response in human breast cancer by gene expression profiling.

PURPOSE: Docetaxel is one of the most effective anticancer drugs available in the treatment of breast cancer. Nearly half of the treated patients, however, do not respond to chemotherapy and suffer from side effects. The ability to reliably predict a patient's response based on tumor gene expression will improve therapeutic decision making and save patients from unnecessary side effects. PATIENTS AND METHODS: A total of 44 breast tumor tissues were sampled by biopsy before treatment with docetaxel, and the response to therapy was clinically evaluated by the degree of reduction in tumor size. Gene expression profiling of the biopsy samples was performed with 2,453 genes using a high-throughput reverse transcriptase polymerase chain reaction technique. Using genes differentially expressed between responders and nonresponders, a diagnostic system based on the weighted-voting algorithm was constructed. RESULTS: This system predicted the clinical response of 26 previously unanalyzed samples with over 80% accuracy, a level promising for clinical applications. Diagnostic profiles in nonresponders were characterized by elevated expression of genes controlling the cellular redox environment (ie, redox genes, such as thioredoxin, glutathione-S-transferase, and peroxiredoxin). Overexpression of these genes protected cultured mammary tumor cells from docetaxel-induced cell death, suggesting that enhancement of the redox system plays a major role in docetaxel resistance. CONCLUSION: These results suggest that the clinical response to docetaxel can be predicted by gene expression patterns in biopsy samples. The results also suggest that one of the molecular mechanisms of the resistance is activation of a group of redox genes.

Adult↗

PubMed2005

Cancer gene expression database (CGED): a database for gene expression profiling with accompanying clinical information of human cancer tissues.

Gene expression profiling of cancer tissues is expected to contribute to our understanding of cancer biology as well as developments of new methods of diagnosis and therapy. Our collaborative efforts in Japan have been mainly focused on solid tumors such as breast, colorectal and hepatocellular cancers. The expression data are obtained by a high-throughput RT-PCR technique, and patients are recruited mainly from a single hospital. In the cancer gene expression database (CGED), the expression and clinical data are presented in a way useful for scientists interested in specific genes or biological functions. The data can be retrieved either by gene identifiers or by functional categories defined by Gene Ontology terms or the Swiss-Prot annotation. Expression patterns of multiple genes, selected by names or similarity search of the patterns, can be compared. Visual presentation of the data with sorting function enables users to easily recognize of relationships between gene expression and clinical parameters. Data for other cancers such as lung and thyroid cancers will be added in the near future. The URL of CGED is http://cged.hgc.jp.

Databases, Genetic↗

PubMed2004

Molecular prediction of response to 5-fluorouracil and interferon-alpha combination chemotherapy in advanced hepatocellular carcinoma.

PURPOSE: The prognosis of hepatocellular carcinoma (HCC) is very poor, particularly in patients with tumors that have invaded the major branches of the portal vein. Combination chemotherapy with intra-arterial 5-fluorouracil and subcutaneous interferon-alpha has shown promising results for such advanced HCC, but it is important to develop the ability to accurately predict chemotherapeutic responses. EXPERIMENTAL DESIGN: We analyzed the expression of 3,080 genes using a polymerase chain reaction-based array in 20 HCC patients who were treated with combination chemotherapy after reduction surgery. After unsupervised analyses, a supervised classification method for predicting chemotherapeutic responses was constructed. To minimize the number of predictive genes, we used a random permutation test to select only significant (P < 0.01) genes. A leave-one-out cross-validation confirmed the gene selection. We also prepared an additional 11 cases for validation of predictive performance. RESULTS: Hierarchical clustering analysis and principal component analysis with all 3,080 genes revealed distinct gene expression patterns in responders (those with complete response or partial response) and nonresponders (those with stable disease or progressive disease) to the combination chemotherapy. Using a weighted-voting classification method with either all genes or only significant genes as assessed by permutation testing, the objective responses to treatment were correctly predicted in 17 of 20 cases (accuracy, 85%; positive predictive value, 100%; negative predictive value, 80%). Moreover, patients in the validation dataset could be classified into two distinct prognostic groups using 63 predictive genes. CONCLUSIONS: Molecular analysis of 63 genes can predict the response of patients with advanced HCC and major portal vein tumor thrombi to combination chemotherapy with 5-fluorouracil and interferon-alpha.

Adult↗

PubMed2004

Molecular-based prediction of early recurrence in hepatocellular carcinoma.

BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) has a very poor prognosis, due to the high incidence of tumor recurrence. As the current morphological indicators are often insufficient for therapeutic decisions, we sought to identify additional biologic indicators for early recurrence. METHODS: We analyzed gene expression using a PCR-based array of 3,072 genes in 100 HCC patients. Informative genes predicting early intrahepatic recurrence were selected by random permutation testing, and a weighted voting prediction method was constructed. Following estimation of prediction accuracy, a multivariate Cox analysis was performed. RESULTS: By permutation testing, we selected 92 genes demonstrated distinct expression patterns differing significantly between recurrence cases and recurrence-free cases. Our prediction method, using the 20 top-ranked genes, correctly predicted the early intrahepatic recurrence for 29 of 40 cases within the validation group, and the odds ratio was 6.8 (95%CI 1.7-27.5, P = 0.010). The 2-year recurrence rates in the patients with the good signature and those with the poor signature were 29.4 and 73.9%, respectively. Multivariate Cox analysis revealed that molecular-signature was an independent indicator for recurrence (hazard ratio 3.82, 95%CI 1.44-10.10, P = 0.007). CONCLUSIONS: Our molecular-based prediction method using 20 genes is clinically useful to predict early recurrence of HCC.

Aged↗

PubMed2003

Transcriptome analysis of mouse stem cells and early embryos.

Understanding and harnessing cellular potency are fundamental in biology and are also critical to the future therapeutic use of stem cells. Transcriptome analysis of these pluripotent cells is a first step towards such goals. Starting with sources that include oocytes, blastocysts, and embryonic and adult stem cells, we obtained 249,200 high-quality EST sequences and clustered them with public sequences to produce an index of approximately 30,000 total mouse genes that includes 977 previously unidentified genes. Analysis of gene expression levels by EST frequency identifies genes that characterize preimplantation embryos, embryonic stem cells, and adult stem cells, thus providing potential markers as well as clues to the functional features of these cells. Principal component analysis identified a set of 88 genes whose average expression levels decrease from oocytes to blastocysts, stem cells, postimplantation embryos, and finally to newborn tissues. This can be a first step towards a possible definition of a molecular scale of cellular potency. The sequences and cDNA clones recovered in this work provide a comprehensive resource for genes functioning in early mouse embryos and stem cells. The nonrestricted community access to the resource can accelerate a wide range of research, particularly in reproductive and regenerative medicine.

Animals↗

PubMed2003

Identification of expressed genes linked to malignancy of human colorectal carcinoma by parametric clustering of quantitative expression data.

BACKGROUND: Individual human carcinomas have distinct biological and clinical properties: gene-expression profiling is expected to unveil the underlying molecular features. Particular interest has been focused on potential diagnostic and therapeutic applications. Solid tumors, such as colorectal carcinoma, present additional obstacles for experimental and data analysis. RESULTS: We analyzed the expression levels of 1,536 genes in 100 colorectal cancer and 11 normal tissues using adaptor-tagged competitive PCR, a high-throughput reverse transcription-PCR technique. A parametric clustering method using the Gaussian mixture model and the Bayes inference revealed three groups of expressed genes. Two contained large numbers of genes. One of these groups correlated well with both the differences between tumor and normal tissues and the presence or absence of distant metastasis, whereas the other correlated only with the tumor/normal difference. The third group comprised a small number of genes. Approximately half showed an identical expression pattern, and cancer tissues were classified into two groups by their expression levels. The high-expression group had strong correlation with distant metastasis, and a poorer survival rate than the low-expression group, indicating possible clinical applications of these genes. In addition to c-yes, a homolog of a viral oncogene, prognostic indicators included genes specific to glial cells, which gives a new link between malignancy and ectopic gene expression. CONCLUSIONS: The malignancy of human colorectal carcinoma is correlated with a unique expression pattern of a specific group of genes, allowing the classification of tumor tissues into two clinically distinct groups.

Cluster Analysis↗

PubMed2003

Molecular features of non-B, non-C hepatocellular carcinoma: a PCR-array gene expression profiling study.

BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) usually develops following chronic liver inflammation caused by hepatitis C or B virus. Through expression profiling in a rare type of HCC, for which the causes are unknown, we sought to find key genes responsible for each step of hepatocarcinogenesis in the absence of viral influence. METHODS: We used 68 non-B, non-C liver tissues (20 HCC, 17 non-tumor, 31 normal liver) for expression profiling with PCR-array carrying 3072 genes known to be expressed in liver tissues. To select the differentially expressed genes, we performed random permutation testing. A weighted voting classification algorithm was used to confirm the reliability of gene selection. We then compared these genes with the results of previous expression profiling studies. RESULTS: A total of 220 differentially expressed genes were selected by random permutation tests. The classification accuracies using these genes were 91.8, 92.0 and 100.0% by a leave-one-out cross-validation, an additional PCR-array dataset and a Stanford DNA microarray dataset, respectively. By comparing our results with previous reports on virus-infected HCC, four genes (ALB, A2M, ECHS1 and IGFBP3) were commonly selected in some studies. CONCLUSIONS: The 220 differentially expressed genes selected by PCR-array are potentially responsible for hepatocarcinogenesis in the absence of viral influence.

Aged↗

PubMed2003

Adapter-tagged competitive PCR (ATAC-PCR)--a high-throughput quantitative PCR method for microarray validation.

Adapter-tagged competitive PCR (ATAC-PCR) is an advanced version of competitive quantitative PCR that is characterized by the addition of unique adapters to cDNA derived from each sample RNA. Using multiple adapters, we can accurately measure the relative expression ratios of many samples, with a calibration curve obtained from internal standards included in the same reaction. ATAC-PCR can identify differences in gene expression as small as twofold, even from very small amounts of sample RNA. This technique is suitable for confirming results obtained with cDNA microarrays or differential display, and it can process more than a thousand of genes per day when used in conjunction with a capillary DNA sequencer.

Animals↗

PubMed2002

Comparison of gene expression profiling during postnatal development of mouse dentate gyrus and cerebellum.

Both the dentate gyrus of the hippocampus and the cerebellar cortex consist mainly of granule cells and develop postnatally. The granule cells in both tissues are presumed to be similar. Changes in gene expression were analyzed during the postnatal development of the dentate gyrus. Altogether, expression patterns of 1,937 genes were determined by adaptor-tagged competitive PCR. More than 90% of the genes belong to groups characterized by elevated expression either at earlier or later stages of development. A majority of the genes expressed showed marked changes during the developmental process, but there was little correlation between gene function and expression, unlike that observed during mouse postnatal cerebellar development. Despite anatomical and physiological similarities between these two processes, the gene expression profiles are completely different.

Animals↗

PubMed2002

Molecular classification of primary breast tumors possessing distinct prognostic properties.

The natural progression of breast cancer differs greatly between patients; the precise prediction of this disease course will improve the efficacy of therapeutics. Gene expression profiling may elucidate the undiscovered biological variations between seemingly similar cancers, leading to a new cancer classification system valuable in accurate diagnosis. The expression levels of 2412 genes, derived from 98 cancer samples, were precisely recorded by a high throughput RT-PCR technique, adapter-tagged competitive PCR. Subsequent cluster analysis revealed a molecular profile, correlating with estrogen receptor levels and the presence of lymph node metastases. We analyzed 301 cancer samples for the expression patterns of 21 genes critical in this categorization. The classification of the samples into three major groups was verified utilizing principal component analysis. This molecular classification system correlated significantly with early recurrence, independent of lymph node status. This malignant potential is associated with the expression levels of a group of genes, which comprise a set of candidates potentially useful in diagnostic prediction. These genes and the associated control mechanisms may also be effective therapeutic targets.

Breast Neoplasms↗

PubMedDate not supplied

The NIA cDNA project in mouse stem cells and early embryos.

A catalog of mouse genes expressed in early embryos, embryonic and adult stem cells was assembled, including 250000 ESTs, representing approximately 39000 unique transcripts. The cDNA libraries, enriched in full-length clones, were condensed into the NIA 15 and 7.4K clone sets, freely distributed to the research community, providing a standard platform for expression studies using microarrays. They are essential tools for studying mammalian development and stem cell biology, and to provide hints about the differential nature of embryonic and adult stem cells.

Animals↗