Biomedical subjects

I-Ping Tu

Publications and source records attributed to I-Ping Tu.

4 recordsLinked to original sources

PubMed2006

Comprehensive analysis of 19q12 amplicon in human gastric cancers.

Amplification at 19q12 has been observed in multiple tumor types, while cyclin E1 (CCNE1) has been considered to be the key oncogene within this amplicon. We have previously applied cDNA microarray analysis to systematically characterize gene expression patterns of gastric tumor and nontumor samples. We identified a cluster of five tightly coregulated genes all located at chromosome 19q12, including CCNE1. We found that the 19q12 gene cluster is highly expressed in gastric tumors compared to nontumor gastric samples. Array based comparative genomic hybridization and real-time PCR was used to define the boundary of the 19q12 amplicon to a region of approximately 200 kb. Interestingly, we found that in some cases amplification at 19q12 was not associated with DNA copy number gain at CCNE1, suggesting that some other genes within the 19q12 amplicon may also have important function during gastric tumorigenesis. We found high expression of the 19q12 gene cluster to be statistically correlated with the cell proliferation gene signature. Using the SAM software, we identified a set of 577 genes whose expression levels positively correlated with the 19q12 gene cluster. GO term analysis revealed that this genelist is enriched with genes involved in cell cycle regulation and cell proliferation. In conclusion, expression array analysis combined with array comparative genomic hybridization and real-time PCR provides a new and powerful tool to identify clusters of genes which may be regulated by genomic DNA aberrations. In addition, our study indicates that amplification at 19q12 is associated with cell proliferation in vivo.

Adenocarcinoma↗

PubMed2004

A method for detecting and correcting feature misidentification on expression microarrays.

BACKGROUND: Much of the microarray data published at Stanford is based on mouse and human arrays produced under controlled and monitored conditions at the Brown and Botstein laboratories and at the Stanford Functional Genomics Facility (SFGF). Nevertheless, as large datasets based on the Stanford Human array began to accumulate, a small but significant number of discrepancies were detected that required a serious attempt to track down the original source of error. Due to a controlled process environment, sufficient data was available to accurately track the entire process leading to up to the final expression data. In this paper, we describe our statistical methods to detect the inconsistencies in microarray data that arise from process errors, and discuss our technique to locate and fix these errors. RESULTS: To date, the Brown and Botstein laboratories and the Stanford Functional Genomics Facility have together produced 40,000 large-scale (10-50,000 feature) cDNA microarrays. By applying the heuristic described here, we have been able to check most of these arrays for misidentified features, and have been able to confidently apply fixes to the data where needed. Out of the 265 million features checked in our database, problems were detected and corrected on 1.3 million of them. CONCLUSION: Process errors in any genome scale high throughput production regime can lead to subsequent errors in data analysis. We show the value of tracking multi-step high throughput operations by using this knowledge to detect and correct misidentified data on gene expression microarrays.

Animals↗

PubMed2003

Gene expression patterns in ovarian carcinomas.

We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A comparison of the gene expression patterns in the ovarian cancers to published data of gene expression in breast cancers revealed a large number of differentially expressed genes. We identified a group of 62 genes that correctly classified all 125 breast and ovarian cancer specimens. Among the best discriminators more highly expressed in the ovarian carcinomas were PAX8 (paired box gene 8), mesothelin, and ephrin-B1 (EFNB1). Although estrogen receptor was expressed in both the ovarian and breast cancers, genes that are coregulated with the estrogen receptor in breast cancers, including GATA-3, LIV-1, and X-box binding protein 1, did not show a similar pattern of coexpression in the ovarian cancers.

Adenocarcinoma↗

PubMed2002

Phospholipase A2 group IIA expression in gastric adenocarcinoma is associated with prolonged survival and less frequent metastasis.

We analyzed gene expression patterns in human gastric cancers by using cDNA microarrays representing approximately equal 30,300 genes. Expression of PLA2G2A, a gene previously implicated as a modifier of the Apc(Min/+) (multiple intestinal neoplasia 1) mutant phenotype in the mouse, was significantly correlated with patient survival. We confirmed this observation in an independent set of patient samples by using quantitative RT-PCR. Beyond its potential diagnostic and prognostic significance, this result suggests the intriguing possibility that the activity of PLA2G2A may suppress progression or metastasis of human gastric cancer.

Adenocarcinoma↗