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Joel Greshock

Publications and source records attributed to Joel Greshock.

9 recordsLinked to original sources

STAC: A method for testing the significance of DNA copy number aberrations across multiple array-CGH experiments.

Regions of gain and loss of genomic DNA occur in many cancers and can drive the genesis and progression of disease. These copy number aberrations (CNAs) can be detected at high resolution by using microarray-based techniques. However, robust statistical approaches are needed to identify nonrandom gains and losses across multiple experiments/samples. We have developed a method called Significance Testing for Aberrant Copy number (STAC) to address this need. STAC utilizes two complementary statistics in combination with a novel search strategy. The significance of both statistics is assessed, and P-values are assigned to each location on the genome by using a multiple testing corrected permutation approach. We validate our method by using two published cancer data sets. STAC identifies genomic alterations known to be of clinical and biological significance and provides statistical support for 85% of previously reported regions. Moreover, STAC identifies numerous additional regions of significant gain/loss in these data that warrant further investigation. The P-values provided by STAC can be used to prioritize regions for follow-up study in an unbiased fashion. We conclude that STAC is a powerful tool for identifying nonrandom genomic amplifications and deletions across multiple experiments. A Java version of STAC is freely available for download at http://cbil.upenn.edu/STAC.

Algorithms↗

microRNAs exhibit high frequency genomic alterations in human cancer.

MicroRNAs (miRNAs) are endogenous noncoding RNAs, which negatively regulate gene expression. To determine genomewide miRNA DNA copy number abnormalities in cancer, 283 known human miRNA genes were analyzed by high-resolution array-based comparative genomic hybridization in 227 human ovarian cancer, breast cancer, and melanoma specimens. A high proportion of genomic loci containing miRNA genes exhibited DNA copy number alterations in ovarian cancer (37.1%), breast cancer (72.8%), and melanoma (85.9%), where copy number alterations observed in >15% tumors were considered significant for each miRNA gene. We identified 41 miRNA genes with gene copy number changes that were shared among the three cancer types (26 with gains and 15 with losses) as well as miRNA genes with copy number changes that were unique to each tumor type. Importantly, we show that miRNA copy changes correlate with miRNA expression. Finally, we identified high frequency copy number abnormalities of Dicer1, Argonaute2, and other miRNA-associated genes in breast and ovarian cancer as well as melanoma. These findings support the notion that copy number alterations of miRNAs and their regulatory genes are highly prevalent in cancer and may account partly for the frequent miRNA gene deregulation reported in several tumor types.

Breast Neoplasms↗

High resolution genomic analysis of sporadic breast cancer using array-based comparative genomic hybridization.

INTRODUCTION: Genomic aberrations in the form of subchromosomal DNA copy number changes are a hallmark of epithelial cancers, including breast cancer. The goal of the present study was to analyze such aberrations in breast cancer at high resolution. METHODS: We employed high-resolution array comparative genomic hybridization with 4,134 bacterial artificial chromosomes that cover the genome at 0.9 megabase resolution to analyze 47 primary breast tumors and 18 breast cancer cell lines. RESULTS: Common amplicons included 8q24.3 (amplified in 79% of tumors, with 5/47 exhibiting high level amplification), 1q32.1 and 16p13.3 (amplified in 66% and 57% of tumors, respectively). Moreover, we found several positive correlations between specific amplicons from different chromosomes, suggesting the existence of cooperating genetic loci. Queried by gene, the most frequently amplified kinase was PTK2 (79% of tumors), whereas the most frequently lost kinase was PTK2B (hemizygous loss in 34% of tumors). Amplification of ERBB2 as measured by comparative genomic hybridization (CGH) correlated closely with ERBB2 DNA and RNA levels measured by quantitative PCR as well as with ERBB2 protein levels. The overall frequency of recurrent losses was lower, with no region lost in more than 50% of tumors; the most frequently lost tumor suppressor gene was RB1 (hemizygous loss in 26% of tumors). Finally, we find that specific copy number changes in cell lines closely mimicked those in primary tumors, with an overall Pearson correlation coefficient of 0.843 for gains and 0.734 for losses. CONCLUSION: High resolution CGH analysis of breast cancer reveals several regions where DNA copy number is commonly gained or lost, that non-random correlations between specific amplicons exist, and that specific genetic alterations are maintained in breast cancer cell lines despite repeat passage in tissue culture. These observations suggest that genes within these regions are critical to the malignant phenotype and may thus serve as future therapeutic targets.

Breast Neoplasms↗

Measurement and relevance of neuroblastoma DNA copy number changes in the post-genome era.

The completion of the human genome sequence and the development of high throughput technology present exciting opportunities for the study of cancer cells. High-resolution analysis of chromosomal aberrations provides a global framework for understanding complex patterns in cancer cells, allowing us to ask hypothesis-driven questions. Genome-wide analysis of amplification and deletion of genomic regions is a critical step to resolving the mechanisms of neuroblastoma tumorigenesis. We used a high-resolution aCGH system that has over 4000 human BAC clones, resulting in an average coverage of 1Mb across the genome, to define whole genome copy number aberrations (CNAs) in a panel of human neuroblastoma-derived cell lines. By combining the aCGH data with meticulous regional validation studies, we showed that array CGH could reliably detect known aberrations including single copy gain or loss, that data correlate well with standard techniques used for the detection of these genetic changes, and that this technique can be used to identify novel regions of genomic imbalance.

Cell Line, Tumor↗

CGHAnalyzer: a stand-alone software package for cancer genome analysis using array-based DNA copy number data.

SUMMARY: This synopsis provides an overview of array-based comparative genomic hybridization data display, abstraction and analysis using CGHAnalyzer, a software suite, designed specifically for this purpose. CGHAnalyzer can be used to simultaneously load copy number data from multiple platforms, query and describe large, heterogeneous datasets and export results. Additionally, CGHAnalyzer employs a host of algorithms for microarray analysis that include hierarchical clustering and class differentiation. AVAILABILITY: CGHAnalyzer, the accompanying manual, documentation and sample data are available for download at http://acgh.afcri.upenn.edu. This is a Java-based application built in the framework of the TIGR MeV that can run on Microsoft Windows, Macintosh OSX and a variety of Unix-based platforms. It requires the installation of the free Java Runtime Environment 1.4.1 (or more recent) (http://www.java.sun.com).

Algorithms↗

High-resolution detection and mapping of genomic DNA alterations in neuroblastoma.

We used array-based comparative genomic hybridization (aCGH) to measure genomic copy number alterations (CNAs) in 42 neuroblastoma cell lines with known 1p36.3, 2p24 (MYCN), 11q23, and 17q23 allelic status. All cell lines showed CNAs, with an average of 22.0% of the genome of each sample showing evidence of gain (11.6%) or loss (10.4%). MYCN amplification was detected in 81% of cell lines, but other regions with high-level genomic amplification were observed only rarely. Gain of 17q material was present in 75% of the samples, and four discrete genomic regions at 17q23.2-17q25.3 were defined. Novel regions of gain were identified, including a 2.6-Mb subtelomeric region at 5p that includes the telomerase reverse transcriptase gene (TERT), which was found in 45% of the cell lines. Hemizygous deletions were noted at 1p36.23-1p36.32 and 11q23.3-11q25 in 60% and 36%, respectively, of the samples, with other frequent (>25%) regions of deletion localized to 1p32.1, 3p21.31-3p22.1, 5q35.2-5q35.3, 7q31.2, 7q34, 9q22.3-9q24.1, 10q26.11-10q26.12, 16q23.1-16q24.3, 18q21.32-18q23, and 20p11.21-20p11.23. A smallest region of overlap (SRO) for CNAs was mapped across all experiments and in each case was consistent with or refined the published data. A single cell line showed a homozygous deletion at 3p22.3, which was verified, and this location was refined by FISH and PCR. There was outstanding concordance of aCGH with PCR-based CNA detection methods. Several potential cooperating loci were identified, including deletion of 11q23-25, which was highly associated with both regional gain and loss at multiple chromosomal loci but was inversely correlated with the deletion of 1p36. Taking all of this together indicates that aCGH can accurately measure CNAs in the neuroblastoma genome and facilitate gene discovery efforts by high-throughput refinement of candidate loci.

Cell Line, Tumor↗

High-resolution analysis of DNA copy number using oligonucleotide microarrays.

Genomic copy number alterations are a feature of many human diseases including cancer. We have evaluated the effectiveness of an oligonucleotide array, originally designed to detect single-nucleotide polymorphisms, to assess DNA copy number. We first showed that fluorescent signal from the oligonucleotide array varies in proportion to both decreases and increases in copy number. Subsequently we applied the system to a series of 20 cancer cell lines. All of the putative homozygous deletions (10) and high-level amplifications (12; putative copy number >4) tested were confirmed by PCR (either qPCR or normal PCR) analysis. Low-level copy number changes for two of the lines under analysis were compared with BAC array CGH; 77% (n = 44) of the autosomal chromosomes used in the comparison showed consistent patterns of LOH (loss of heterozygosity) and low-level amplification. Of the remaining 10 comparisons that were discordant, eight were caused by low SNP densities and failed in both lines. The studies demonstrate that combining the genotype and copy number analyses gives greater insight into the underlying genetic alterations in cancer cells with identification of complex events including loss and reduplication of loci.

Cell Line↗

1-Mb resolution array-based comparative genomic hybridization using a BAC clone set optimized for cancer gene analysis.

Array-based comparative genomic hybridization (aCGH) is a recently developed tool for genome-wide determination of DNA copy number alterations. This technology has tremendous potential for disease-gene discovery in cancer and developmental disorders as well as numerous other applications. However, widespread utilization of a CGH has been limited by the lack of well characterized, high-resolution clone sets optimized for consistent performance in aCGH assays and specifically designed analytic software. We have assembled a set of approximately 4100 publicly available human bacterial artificial chromosome (BAC) clones evenly spaced at approximately 1-Mb resolution across the genome, which includes direct coverage of approximately 400 known cancer genes. This aCGH-optimized clone set was compiled from five existing sets, experimentally refined, and supplemented for higher resolution and enhancing mapping capabilities. This clone set is associated with a public online resource containing detailed clone mapping data, protocols for the construction and use of arrays, and a suite of analytical software tools designed specifically for aCGH analysis. These resources should greatly facilitate the use of aCGH in gene discovery.

Cell Line, Tumor↗