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David Petersen

Publications and source records attributed to David Petersen.

7 recordsLinked to original sources

Changes in gene expression during the development of mammary tumors in MMTV-Wnt-1 transgenic mice.

BACKGROUND: In human breast cancer normal mammary cells typically develop into hyperplasia, ductal carcinoma in situ, invasive cancer, and metastasis. The changes in gene expression associated with this stepwise progression are unclear. Mice transgenic for mouse mammary tumor virus (MMTV)-Wnt-1 exhibit discrete steps of mammary tumorigenesis, including hyperplasia, invasive ductal carcinoma, and distant metastasis. These mice might therefore be useful models for discovering changes in gene expression during cancer development. RESULTS: We used cDNA microarrays to determine the expression profiles of five normal mammary glands, seven hyperplastic mammary glands and 23 mammary tumors from MMTV-Wnt-1 transgenic mice, and 12 mammary tumors from MMTV-Neu transgenic mice. Adipose tissues were used to control for fat cells in the vicinity of the mammary glands. In these analyses, we found that the progression of normal virgin mammary glands to hyperplastic tissues and to mammary tumors is accompanied by differences in the expression of several hundred genes at each step. Some of these differences appear to be unique to the effects of Wnt signaling; others seem to be common to tumors induced by both Neu and Wnt-1 oncogenes. CONCLUSION: We described gene-expression patterns associated with breast-cancer development in mice, and identified genes that may be significant targets for oncogenic events. The expression data developed provide a resource for illuminating the molecular mechanisms involved in breast cancer development, especially through the identification of genes that are critical in cancer initiation and progression.

Animals↗

Three microarray platforms: an analysis of their concordance in profiling gene expression.

BACKGROUND: Microarrays for the analysis of gene expression are of three different types: short oligonucleotide (25-30 base), long oligonucleotide (50-80 base), and cDNA (highly variable in length). The short oligonucleotide and cDNA arrays have been the mainstay of expression analysis to date, but long oligonucleotide platforms are gaining in popularity and will probably replace cDNA arrays. As part of a validation study for the long oligonucleotide arrays, we compared and contrasted expression profiles from the three formats, testing RNA from six different cell lines against a universal reference standard. RESULTS: The three platforms had 6430 genes in common. In general, correlation of gene expression levels across the platforms was good when defined by concordance in the direction of expression difference (upregulation or downregulation), scatter plot analysis, principal component analysis, cell line correlation or quantitative RT-PCR. The overall correlations (r values) between platforms were in the range 0.7 to 0.8, as determined by analysis of scatter plots. When concordance was measured for expression ratios significant at p-values of <0.05 and at expression threshold levels of 1.5 and 2-fold, the agreement among the platforms was very high, ranging from 93% to 100%. CONCLUSION: Our results indicate that the long oligonucleotide platform is highly suitable for expression analysis and compares favorably with the cDNA and short oligonucleotide varieties. All three platforms can give similar and reproducible results if the criterion is the direction of change in gene expression and minimal emphasis is placed on the magnitude of change.

Cell Line↗

Multiple-laboratory comparison of microarray platforms.

Microarray technology is a powerful tool for measuring RNA expression for thousands of genes at once. Various studies have been published comparing competing platforms with mixed results: some find agreement, others do not. As the number of researchers starting to use microarrays and the number of cross-platform meta-analysis studies rapidly increases, appropriate platform assessments become more important. Here we present results from a comparison study that offers important improvements over those previously described in the literature. In particular, we noticed that none of the previously published papers consider differences between labs. For this study, a consortium of ten laboratories from the Washington, DC-Baltimore, USA, area was formed to compare data obtained from three widely used platforms using identical RNA samples. We used appropriate statistical analysis to demonstrate that there are relatively large differences in data obtained in labs using the same platform, but that the results from the best-performing labs agree rather well.

Baltimore↗

Gene expression correlating with response to paclitaxel in ovarian carcinoma xenografts.

We have investigated gene expression profiles of human ovarian carcinomas in vivo during Taxol(R) (paclitaxel) treatment and observed a difference in expression. Nude mice bearing 1A9 or 1A9PTX22 xenografts were given 60 mg/kg of paclitaxel. Therapeutic efficacy was achieved for 1A9, while 1A9PTX22 did not respond. Tumor tissues harvested 4 and 24 h after treatment were evaluated by cDNA microarray against untreated tumors. Paclitaxel caused the modulation of more genes in 1A9 than in 1A9PTX22 tumors, in accordance to their therapeutic response. Most gene expression alterations were detected 24 h after paclitaxel administration and affected genes involved in various biological functions including cell cycle regulation and cell proliferation (CDC2, CDKN1A, PLAB, and TOP2A), apoptosis (BNIP3 and PIG8), signal transduction and transcriptional regulation (ARF1, ATF2, FOS, GNA11, HDAC3, MADH2, SLUG, and SPRY4), fatty acid biosynthesis and sterol metabolism (FDPS, IDI1, LIPA, and SC5D), and IFN-mediated signaling (G1P3, IFI16, IFI27, IFITM1, and ISG15). The modulation of two representative genes, CDKN1A and TOP2A, was validated by Northern analyses on a panel of seven ovarian carcinoma xenograft models undergoing treatment with paclitaxel. We found that the changes in expression level of these genes was strictly associated with the responsiveness to paclitaxel. Our study shows the feasibility of obtaining gene expression profiles of xenografted tumor models as a result of drug exposure. This in turn might provide insights related to the drugs' action in vivo that will anticipate the response to treatment manifested by tumors and could be the basis for novel approaches to molecular pharmacodynamics.

Animals↗

A search for candidate genes for lipodystrophy, obesity and diabetes via gene expression analysis of A-ZIP/F-1 mice.

Genome scans for diabetes have identified many regions of the human genome that correlate with the disease state. To identify candidate genes for type 2 diabetes, we examined the transgenic A-ZIP/F-1 mouse. This mouse model has no white fat, resulting in abnormal levels of glucose, insulin, and leptin, making the A-ZIP/F-1 mice a good model for lipodystrophy and insulin resistance. We used cDNA-based microarrays to find differentially expressed genes in four tissues of these mice. We examined these results in the context of human linkage scans for lipodystrophy, obesity, and type 2 diabetes. We combined 199 known human orthologs of the misregulated mouse genes with 33 published human genome scans on a genome map. Integrating expression data with human linkage results permitted us to suggest and prioritize candidate genes for lipodystrophy and related disorders. These genes include a cluster of 3 S100A genes on chromosome 1 and SLPI1 on chromosome 20.

Animals↗

Prospective molecular profiling of melanoma metastases suggests classifiers of immune responsiveness.

We amplified RNAs from 63 fine needle aspiration (FNA) samples from 37 s.c. melanoma metastases from 25 patients undergoing immunotherapy for hybridization to a 6108-gene human cDNA chip. By prospectively following the history of the lesions, we could correlate transcript patterns with clinical outcome. Cluster analysis revealed a tight relationship among autologous synchronously sampled tumors compared with unrelated lesions (average Pearson's r = 0.83 and 0.7, respectively, P < 0.0003). As reported previously, two subgroups of metastatic melanoma lesions were identified that, however, had no predictive correlation with clinical outcome. Ranking of gene expression data from pretreatment samples identified approximately 30 genes predictive of clinical response (P < 0.001). Analysis of their annotations denoted that approximately half of them were related to T-cell regulation, suggesting that immune responsiveness might be predetermined by a tumor microenvironment conducive to immune recognition.

Adult↗

Core biopsies can be used to distinguish differences in expression profiling by cDNA microarrays.

The primary focus of this work was to determine the feasibility of obtaining representative expression array profiles from clinical core biopsies. For this purpose we performed six 16-gauge needle core biopsies and an excision biopsy on each of two different human xenografts, one from an Ewing's sarcoma cell line and the second from neuroblastoma cell line grown in Beige-Scid mice. Three of the six core biopsies were processed separately and the remaining three were pooled and processed together. As the initial RNA material isolated from the core biopsies was not sufficient for microarray analysis, an amplification procedure using a modified Eberwine protocol was performed, and the amplified products applied onto a 6000-feature human cDNA microarray. Comparisons of the array results from core biopsies (amplified RNA) and surgical specimens (non-amplified RNA) showed maintenance of the expression profile as assessed by hierarchical clustering. Gene expression profiles obtained from microarray analysis clearly differentiated the Ewing's sarcoma from the neuroblastoma with both core and excisional biopsies as starting material. Pooling the core biopsies did not improve the concordance with excisional biopsies. In conclusion, our results suggest that core biopsies can be used as a suitable and reliable material for the determination of tumor genetic profiles.

Animals↗