Hodge JC, Park PJ, Dreyfuss JM, Assil-Kishawi I, Somasundaram P, Semere LG, Quade BJ, Lynch AM, Stewart EA, Morton CC.
Identifying the molecular signature of the interstitial deletion 7q subgroup of uterine leiomyomata using a paired analysis. Genes Chromosomes Cancer 2009;48(10):865-85.
Abstract
Uterine leiomyomata (UL), the most common neoplasm in reproductive-age women, have recurrent cytogenetic abnormalities including interstitial deletion of 7q. To develop a molecular signature, matched del(7q) and non-del(7q) tumors identified by FISH or karyotyping from 11 women were profiled with expression arrays. Our analysis using paired t tests demonstrates this matched design is critical to eliminate the confounding effects of genotype and environment that underlie patient variation. A gene list ordered by genome-wide significance showed enrichment for the 7q22 target region. Modification of the gene list by weighting each sample for percent of del(7q) cells to account for the mosaic nature of these tumors further enhanced the frequency of 7q22 genes. Pathway analysis revealed two of the 19 significant functional networks were associated with development and the most represented pathway was protein ubiquitination, which can influence tumor development by stabilizing oncoproteins and destabilizing tumor suppressor proteins. Array CGH (aCGH) studies determined the only consistent genomic imbalance was deletion of 9.5 megabases from 7q22-7q31.1. Combining the aCGH data with the del(7q) UL mosaicism-weighted expression analysis resulted in a list of genes that are commonly deleted and whose copy number is correlated with significantly decreased expression. These genes include the proliferation inhibitor HPB1, the loss of expression of which has been associated with invasive breast cancer, as well as the mitosis integrity-maintenance tumor suppressor RINT1. This study provides a molecular signature of the del(7q) UL subgroup and will serve as a platform for future studies of tumor pathogenesis.
pdf Park PJ, Manjourides J, Bonetti M, Pagano M.
A permutation test for determining significance of clusters with applications to spatial and gene expression data. Comput Stat Data Anal 2009;53(12):4290-4300.
Abstract
Hierarchical clustering is a common procedure for identifying structure in a data set, and this is frequently used for organizing genomic data. Although more advanced clustering algorithms are available, the simplicity and visual appeal of hierarchical clustering has made it ubiquitous in gene expression data analysis. Hence, even minor improvements in this framework would have significant impact. There is currently no simple and systematic way of assessing and displaying the significance of various clusters in a resulting dendrogram without making certain distributional assumptions or ignoring gene-specific variances. In this work, we introduce a permutation test based on comparing the within-cluster structure of the observed data with those of sample datasets obtained by permuting the cluster membership. We carry out this test at each node of the dendrogram using a statistic derived from the singular value decomposition of variance matrices. The p-values thus obtained provide insight into the significance of each cluster division. Given these values, one can also modify the dendrogram by combining non-significant branches. By adjusting the cut-off level of significance for branches, one can produce dendrograms with a desired level of detail for ease of interpretation. We demonstrate the usefulness of this approach by applying it to illustrative data sets.
pdf Pihlajamäki J, Boes T, Kim E-Y, Dearie F, Kim BW, Schroeder J, Mun E, Nasser I, Park PJ, Bianco AC, Goldfine AB, Patti ME.
Thyroid hormone-related regulation of gene expression in human fatty liver. J Clin Endocrinol Metab 2009;94(9):3521-9.
Abstract
CONTEXT: Fatty liver is an important complication of obesity; however, regulatory mechanisms mediating altered gene expression patterns have not been identified. OBJECTIVE: The aim of the study was to identify novel transcriptional changes in human liver that could contribute to hepatic lipid accumulation and associated insulin resistance, type 2 diabetes, and nonalcoholic steatohepatitis. DESIGN: We evaluated gene expression in surgical liver biopsies from 13 obese (nine with type 2 diabetes) and five control subjects using Affymetrix U133A microarrays. PCR validation was performed in liver biopsies using an additional 16 subjects. We also tested thyroid hormone responses in mice fed chow or high-fat diet. SETTING: Recruitment was performed in an academic medical center. PARTICIPANTS: Individuals undergoing elective surgery for obesity or gallstones participated in the study. RESULTS: The top-ranking gene set, down-regulated in obese subjects, was comprised of genes previously demonstrated to be positively regulated by T(3) in human skeletal muscle (n = 399; P < 0.001; false discovery rate = 0.07). This gene set included genes related to RNA metabolism (SNRPE, HNRPH3, TIA1, and SFRS2), protein catabolism (PSMA1, PSMD12, USP9X, IBE2B, USP16, and PCMT1), and energy metabolism (ATP5C1, COX7C, UQCRB). We verified thyroid hormone regulation of these genes in the liver after injection of C57BL/6J mice with T(3) (100 microg/100 g body weight); furthermore, T(3)-induced increases in expression of these genes were abolished by high-fat diet. In agreement, expression of these genes inversely correlated with liver fat content in humans. CONCLUSIONS: These data suggest that impaired thyroid hormone action may contribute to altered patterns of gene expression in fatty liver.
pdf Yoon SS, Stangenberg L, Lee Y-J, Rothrock C, Dreyfuss JM, Baek K-H, Waterman PR, Nielsen PG, Weissleder R, Mahmood U, Park PJ, Jacks T, Dodd RD, Fisher CJ, Ryeom S, Kirsch DG.
Efficacy of sunitinib and radiotherapy in genetically engineered mouse model of soft-tissue sarcoma. Int J Radiat Oncol Biol Phys 2009;74(4):1207-16.
Abstract
PURPOSE: Sunitinib (SU) is a multitargeted receptor tyrosine kinase inhibitor of the vascular endothelial growth factor and platelet-derived growth factor receptors. The present study examined SU and radiotherapy (RT) in a genetically engineered mouse model of soft tissue sarcoma (STS). METHODS AND MATERIALS: Primary extremity STSs were generated in genetically engineered mice. The mice were randomized to treatment with SU, RT (10 Gy x 2), or both (SU+RT). Changes in the tumor vasculature before and after treatment were assessed in vivo using fluorescence-mediated tomography. The control and treated tumors were harvested and extensively analyzed. RESULTS: The mean fluorescence in the tumors was not decreased by RT but decreased 38-44% in tumors treated with SU or SU+RT. The control tumors grew to a mean of 1378 mm(3) after 12 days. SU alone or RT alone delayed tumor growth by 56% and 41%, respectively, but maximal growth inhibition (71%) was observed with the combination therapy. SU target effects were confirmed by loss of target receptor phosphorylation and alterations in SU-related gene expression. Cancer cell proliferation was decreased and apoptosis increased in the SU and RT groups, with a synergistic effect on apoptosis observed in the SU+RT group. RT had a minimal effect on the tumor microvessel density and endothelial cell-specific apoptosis, but SU alone or SU+RT decreased the microvessel density by >66% and induced significant endothelial cell apoptosis. CONCLUSION: SU inhibited STS growth by effects on both cancer cells and tumor vasculature. SU also augmented the efficacy of RT, suggesting that this combination strategy could improve local control of STS.
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