Biomedical subjects

Marci Schaner

Publications and source records attributed to Marci Schaner.

2 recordsLinked to original sources

PubMed2005

High-resolution gene copy number and expression profiling of human chromosome 22 in ovarian carcinomas.

Previous low-resolution studies of chromosome 22 in ovarian carcinoma have suggested its involvement in the development of the disease. We report a high-resolution analysis of DNA copy number and gene expression of 22q in 18 ovarian carcinomas using a 22q-specific genomic microarray. We identified aberrations in 67% of the studied tumors, which displayed 3 distinct gene copy number profiles. The majority of the cases (11 of 18) demonstrated heterozygous terminal deletions of various sizes, the smallest of which was 3.5 Mb. The second profile, detected in 3 tumors, revealed the coexistence of heterozygous deletions and different patterns of low-copy-number gain that involved the proximal half of 22q. The latter finding has not been reported previously in ovarian carcinoma. One case displayed a continuous deletion encompassing the entire 22q, consistent with monosomy 22. Furthermore, we compared the results with the available data on these tumors by using cDNA microarrays to define the degree of correlation between abnormalities at the DNA level and variation in mRNA expression. By a comparison with the expression data, we were able to identify 21 deleted genes showing low mRNA levels and 12 amplified genes displaying elevated gene expression, several of which play roles in cell cycle control and the induction of apoptosis. Our results indicated significant correlation between DNA copy number aberrations and variation in mRNA expression. We also identified several regions and candidate genes on 22q that should be studied further to determine their role in the development of ovarian cancer.

Adenocarcinoma, Clear Cell↗

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↗