Biomedical subjects

Sakae Saito

Publications and source records attributed to Sakae Saito.

6 recordsLinked to original sources

PubMed2006

Prediction of peritoneal metastasis in advanced gastric cancer by gene expression profiling of the primary site.

Peritoneal metastasis is the most common cause of tumour progression in advanced gastric cancer. Clinicopathological findings including cytologic examination of peritoneal lavage have been applied to assess the risk of peritoneal metastasis, but are sometimes inadequate for predicting peritoneal metastasis in individuals. Hence, we tried to construct a new prediction system for peritoneal metastasis by using a PCR-based high throughput array with 2304 genes. The prediction system, constructed from the learning set comprised of 30 patients with the most informative 18 genes, classified each case into a 'good signature group' or 'poor signature group'. Then, we confirmed the predictive performance in an additional validation set comprised of 24 patients, and the prediction accuracy for peritoneal metastasis was 75%. Kaplan-Meier analysis with peritoneal metastasis revealed significant difference between these two groups (P=0.0225). By combining our system with conventional clinicopathological factors, we can identify high risk cases for peritoneal metastasis more accurately.

Aged↗

PubMed2005

Prediction of recurrence in advanced gastric cancer patients after curative resection by gene expression profiling.

The prognosis of patients with advanced gastric cancer remains unfavorable. Even after curative resection, 40% of patients with advanced gastric cancer die of recurrence. Conventional clinicopathlogic findings are sometimes inadequate for predicting recurrence in individuals. Hence, we tried to construct a new diagnostic system, which predicts recurrence in patients with advanced gastric cancer after curative resection based on molecular analysis. Gastric cancer progression is a function of multiple genetic events that may affect the expression of large number of genes. We performed gene expression profiling with 2,304 genes in 60 advanced gastric cancer patients who underwent curative resection using a PCR array technique, a high-throughput quantitative RT-PCR technique. The diagnostic system, which was constructed from the learning set comprised of 40 patients with the most informative 29 genes, classified each case into a good-signature or poor-signature group. Then, we confirmed the predictive performance in an additional test set comprised of 20 patients, and the prediction accuracy for recurrence was 75%. Kaplan-Meier analysis revealed significant difference between the good-signature and the poor-signature group (p = 0.0125). Especially in patients with smaller tumor (< or = 5 cm), less developed LN metastasis (N(0,1)), or earlier stage (stages I and II), the prediction accuracy was high (88.9%, 84.6%, or 81.8%, respectively). Our diagnostic system based on systematic analysis of gene expression profiling can predict the recurrence at clinically meaningful level. By combining our system with conventional clinicopathologic factors, we can improve the prediction of recurrence in patients with advanced gastric cancer who underwent curative surgery.

Aged↗

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↗

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↗