Microarray analysis of hepatic-regulated gene expression: specific applications and nonspecific problems.
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Humans↗
Biomedical subjects
David N Stivers
Publications and source records attributed to David N Stivers.
Identifying and quantifying sources of variation in microarray data using high-density cDNA membrane arrays.
Microarray experiments involve many steps, including spotting cDNA, extracting RNA, labeling targets, hybridizing, scanning, and analyzing images. Each step introduces variability, confounding our ability to obtain accurate estimates of the biological differences between samples. We ran repeated experiments using high-density cDNA microarray membranes (Research Genetics Human GeneFilters Microarrays Version I) and 33P-labeled targets. Total RNA was extracted from a Burkitt lymphoma cell line (GA-10). We estimated the components of variation coming from: (1) image analysis, (2) exposure time to PhosphorImager screens, (3) differences in membranes, (4) reuse of membranes, and (5) differences in targets prepared from two independent RNA extractions. Variation was assessed qualitatively using a clustering algorithm and quantitatively using a version of ANOVA adapted to multivariate microarray data. The largest contribution to variation came from reusing membranes, which contributed 38% of the total variation. Differences in membranes and in exposure time each contributed about 10%. Differences in target preparations contributed less than 5%. The effect of image quantification was negligible. Much of the effect from reusing membranes was attributable to increasing levels of background radiation and can be reduced by using membranes at most four times. The effects of exposure time, which were partly attributable to variation in the scanning process, can be minimized by using the same exposure time for all experiments.
Algorithms↗
Global gene expression changes during neoadjuvant chemotherapy for human breast cancer.
PURPOSE: The purpose of this study was to analyze global gene expression changes in serial tumor core biopsy specimens taken during neoadjuvant chemotherapy for primary breast cancer. PATIENTS AND METHODS: Core biopsy specimens from tumors were obtained before treatment and 24 and/or 48 hours after treatment from 21 women who were beginning chemotherapy for breast cancer. RNA was extracted, and radiolabeled complementary DNA was synthesized. The complementary DNA probes were hybridized to high-density microarray membranes that contained more than 25,000 human sequence clones. Hierarchical cluster analysis was used to compare the degree of similarity between expression profiles. RESULTS: Twenty-five (45%) of the 56 available core specimens yielded sufficient quantity and quality RNA for microarray analysis. Microarray profiles were performed only on samples from patients with pretreatment and posttreatment specimens, resulting in serial data sets for five patients (14 specimens). The serial samples from individual patients clustered more closely than the samples taken from different patients. Analyses of the variance of individual gene expression showed that there were significantly fewer genes with fivefold differences in expression in an individual tumor at different times (average, 359 genes) versus pretreatment samples of different tumors (average, 732 genes). Patients with a good pathological response to treatment had gene patterns that clustered distinctly from those of poor responders. Significant transcriptional response occurred in all patients during therapy. Surprisingly, all patients had different genes change after chemotherapy, with no single gene having a significant expression change in all five patients. DISCUSSION: This is the first report to show global gene expression changes during chemotherapy in a human solid tumor. Comprehensive gene expression profiles of more than 25,000 genes can be obtained from core biopsy specimens. A remarkable diversity in transcriptional response was observed for individual cases. Further data are needed to determine whether gene profiling can predict response to chemotherapy.
Analysis of Variance↗