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Journal articles on the topic 'Genome-wide copy number analysis'

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Published: 9 March 2023

Last updated: 10 March 2023

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1

Baslan, Timour, Jude Kendall, Linda Rodgers, Hilary Cox, Mike Riggs, Asya Stepansky, Jennifer Troge, et al. "Genome-wide copy number analysis of single cells." Nature Protocols 7, no. 6 (May 3, 2012): 1024–41. http://dx.doi.org/10.1038/nprot.2012.039.

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2

SUN, Yu-Lin, Fei LIU, and Xiao-Hang ZHAO. "Genome-wide Association Analysis Based on Copy Number Variations*." PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS 36, no. 8 (October 16, 2009): 968–77. http://dx.doi.org/10.3724/sp.j.1206.2008.00881.

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3

Liu, Xiling, Zhenmin Zhao, Qiannan Xu, Zheng Wang, Yingnan Bian, Suhua Zhang, and Chengtao Li. "Genome-wide copy number variation analysis in monozygotic twins." Forensic Science International: Genetics Supplement Series 6 (December 2017): e218-e220. http://dx.doi.org/10.1016/j.fsigss.2017.09.075.

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4

Ueno, Takayuki, Mitsuru Emi, Hidenori Sato, Noriko Ito, Mariko Muta, Katsumasa Kuroi, and Masakazu Toi. "Genome-wide copy number analysis in primary breast cancer." Expert Opinion on Therapeutic Targets 16, sup1 (February 8, 2012): S31—S35. http://dx.doi.org/10.1517/14728222.2011.636739.

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5

Lin, Chien-hsing, Mei-chu Huang, Ling-hui Li, Jer-yuarn Wu, Yuan-tsong Chen, and Cathy S. J. Fann. "Genome-wide copy number analysis using copy number inferring tool (CNIT) and DNA pooling." Human Mutation 29, no. 8 (August 2008): 1055–62. http://dx.doi.org/10.1002/humu.20760.

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6

Michael Rothenberg, S., and Jeff Settleman. "Discovering Tumor Suppressor Genes Through Genome-Wide Copy Number Analysis." Current Genomics 11, no. 5 (August 1, 2010): 297–310. http://dx.doi.org/10.2174/138920210791616734.

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7

Baslan, Timour, Jude Kendall, Linda Rodgers, Hilary Cox, Mike Riggs, Asya Stepansky, Jennifer Troge, et al. "Erratum: Corrigendum: Genome-wide copy number analysis of single cells." Nature Protocols 11, no. 3 (February 25, 2016): 616. http://dx.doi.org/10.1038/nprot0316.616b.

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8

Smadbeck, James B., Sarah H. Johnson, Stephanie A. Smoley, Athanasios Gaitatzes, Travis M. Drucker, Roman M. Zenka, Farhad Kosari, et al. "Copy number variant analysis using genome-wide mate-pair sequencing." Genes, Chromosomes and Cancer 57, no. 9 (July 30, 2018): 459–70. http://dx.doi.org/10.1002/gcc.5.

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9

Lee, Il-Kwon, Nan Young Kim, Hee Nam Kim, Dong Kyun Han, Hee-Jo Baek, Tai Ju Hwang, Hoon Kook, and Hyeoung Joon Kim. "Genome-Wide Screening of Copy Number Variation In Childhood Neuroblastoma." Blood 116, no. 21 (November 19, 2010): 4454. http://dx.doi.org/10.1182/blood.v116.21.4454.4454.

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Abstract Abstract 4454 Background Structural genetic variation, including copy-number variation (CNV), constitutes a substantial fraction of total genetic variability and the importance of structural variants in modulating human disease is increasingly being recognized. Recent studies showed that chromosomal aberrations are detectable in childhood cancers and can be associated with susceptibility to childhood cancers. However its relationship with neuroblosatoma in particular is not fully understood. To gain insight into the incidence of the chromosomal aberrations in neuroblastoma in children, we examined Korean childhood neuroblastoma genomes using high-resolution single-nucleotide polymorphism (SNP) array-based analysis. Patients and Methods 13 cases analyzed had been diagnosed with neuroblastoma (5 male, 8 female). 620,901 SNP markers were considered on these samples using Human610Quad v1.0 DNA analysis BeadChip (Illumina). Fragmented DNAs were hybridized on bead chips. Data analysis was carried out with GenomeStudio v2009.1, Genotyping 1.1.9, cnvPartition_v2.4.4 softwares. Overall call rate were more than 99.8%. Genome-wide CNV, genotyping of markers including 7,577 non-synonymous SNPs, loss of heterozygosity (LOH) analyses were performed using the GenomeStudio v2010.1. Linkage disequilibrium was analyzed by Haploview 4.2. The gene set enrichment analysis was performed using GO software, Panther. Results The average call rates were 99.8 %. In total 343 CNVs were identified across the whole genome. Average number of CNVs per genome in this study (17.15) is higher than that of CNVs called in the recent studies using lower-resolution SNP- or CNV arrays. The median size of CNVs was 30,056 (range 569 ~ 1,260,297 bp). The largest portion of CNVs (235 calls) were found to be 10 kb~500 kb in length. Gain/loss of CNV was 2.05/4.90 having 2.4 fold higher frequencies in loss calls. We defined CNV regions (CNVRs) by merging overlapping CNVs (30% of overlap threshold) detected in two or more genomes. In total 155 CNVRs identified. The median size of CNVR was 27,482 (range 806 ~ 1,270,815 bp). Like CNVs, CNVRs-losses were more frequent than CNVR-gains. Defined CNVRs encompassing 13.4Mb accounted for ~0.5% of the human genome. Total of 1029 NM numbered transcripts were located near or within the 155 CNVRs. Through gene ontology (GO) analysis, putative target genes within the commonly gained or deleted region were categorized. Gene functions significantly enriched in the identified CNVRs include receptors for signal transduction pathways, transcription factors with nucleic acid binding proteins, transporters and regulatory molecule related functions involved in developmental processes. Genotype distributions for 7,577 non-synonymous SNPs in neuroblastoma were also examined and compared to two lab-specific as well as 90 Korean HapMap samples as control reference. Conclusions High-resolution single-nucleotide polymorphism (SNP) array-based analysis allowed us a high incidence of gains and losses in childhood neuroblastoma. Many of those detectable legions were found to be previously unidentified cryptic chromosomal aberrations. Those CNVRs could be potentially Korean-specific novel CNVRs indicating that previous CNV coverage of the human genome is incomplete and there is human genome diversity among different ethnic populations. Although results reveals high degrees of heterogeneity in the genomic alterations detectable in neuroblastoma, genes of the signal transduction pathway and transcriptional regulatory members were the most frequently altered targets whose deregulation may play a role in the pathogenesis of neuroblastoma in children. CNVs/CNVRs identified in the study will be solid resources for investigating chromosomal aberrations in childhood cancer and its potential association with childhood neuroblastoma. Further studies on larger sample size, as well as functional analyses will define their role in the pathogenesis of neuroblastoma in children. Disclosures: No relevant conflicts of interest to declare.

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10

Huang, Yen-Tsung, Thomas Hsu, and David C. Christiani. "TEGS-CN: A Statistical Method for Pathway Analysis of Genome-wide Copy Number Profile." Cancer Informatics 13s4 (January 2014): CIN.S13978. http://dx.doi.org/10.4137/cin.s13978.

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The effects of copy number alterations make up a significant part of the tumor genome profile, but pathway analyses of these alterations are still not well established. We proposed a novel method to analyze multiple copy numbers of genes within a pathway, termed Test for the Effect of a Gene Set with Copy Number data (TEGS-CN). TEGS-CN was adapted from TEGS, a method that we previously developed for gene expression data using a variance component score test. With additional development, we extend the method to analyze DNA copy number data, accounting for different sizes and thus various numbers of copy number probes in genes. The test statistic follows a mixture of X 2 distributions that can be obtained using permutation with scaled X 2 approximation. We conducted simulation studies to evaluate the size and the power of TEGS-CN and to compare its performance with TEGS. We analyzed a genome-wide copy number data from 264 patients of non-small-cell lung cancer. With the Molecular Signatures Database (MSigDB) pathway database, the genome-wide copy number data can be classified into 1814 biological pathways or gene sets. We investigated associations of the copy number profile of the 1814 gene sets with pack-years of cigarette smoking. Our analysis revealed five pathways with significant P values after Bonferroni adjustment (<2.8 x 10-5), including the PTEN pathway (7.8 x 10-7), the gene set up-regulated under heat shock (3.6 x 10-6), the gene sets involved in the immune profile for rejection of kidney transplantation (9.2 x 10-6) and for transcriptional control of leukocytes (2.2 x 10-5), and the ganglioside biosynthesis pathway (2.7 x 10-5). In conclusion, we present a new method for pathway analyses of copy number data, and causal mechanisms of the five pathways require further study.

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11

Grayson, Britney L., Mary Ellen Smith, James W. Thomas, Lily Wang, Phil Dexheimer, Joy Jeffrey, Pamela R. Fain, Priyaanka Nanduri, George S. Eisenbarth, and Thomas M. Aune. "Genome-Wide Analysis of Copy Number Variation in Type 1 Diabetes." PLoS ONE 5, no. 11 (November 15, 2010): e15393. http://dx.doi.org/10.1371/journal.pone.0015393.

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12

Sulovari, A., Z. Liu, Z. Zhu, and D. Li. "Genome-wide meta-analysis of copy number variations with alcohol dependence." Pharmacogenomics Journal 18, no. 3 (July 11, 2017): 398–405. http://dx.doi.org/10.1038/tpj.2017.35.

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13

Forer, Lukas, Sebastian Schönherr, Hansi Weissensteiner, Florian Haider, Thomas Kluckner, Christian Gieger, Heinz-Erich Wichmann, Günther Specht, Florian Kronenberg, and Anita Kloss-Brandstätter. "CONAN: copy number variation analysis software for genome-wide association studies." BMC Bioinformatics 11, no. 1 (2010): 318. http://dx.doi.org/10.1186/1471-2105-11-318.

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14

Tang, Clara Sze-Man, Guo Cheng, Man-Ting So, Benjamin Hon-Kei Yip, Xiao-Ping Miao, Emily Hoi-Man Wong, Elly Sau-Wai Ngan, et al. "Genome-Wide Copy Number Analysis Uncovers a New HSCR Gene: NRG3." PLoS Genetics 8, no. 5 (May 10, 2012): e1002687. http://dx.doi.org/10.1371/journal.pgen.1002687.

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15

Royo, Félix. "Genome-Wide Analysis of DNA Copy Number Changes in Liver Steatosis." British Journal of Medicine and Medical Research 3, no. 4 (January 10, 2013): 1773–85. http://dx.doi.org/10.9734/bjmmr/2013/2543.

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16

Vincenten, Julien P. L., Hendrik F. van Essen, Birgit I. Lissenberg-Witte, Nicole W. J. Bulkmans, Oscar Krijgsman, Daoud Sie, Paul P. Eijk, Egbert F. Smit, Bauke Ylstra, and Erik Thunnissen. "Clonality analysis of pulmonary tumors by genome-wide copy number profiling." PLOS ONE 14, no. 10 (October 16, 2019): e0223827. http://dx.doi.org/10.1371/journal.pone.0223827.

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17

Pollack, Jonathan R., Charles M. Perou, Ash A. Alizadeh, Michael B. Eisen, Alexander Pergamenschikov, Cheryl F. Williams, Stefanie S. Jeffrey, David Botstein, and Patrick O. Brown. "Genome-wide analysis of DNA copy-number changes using cDNA microarrays." Nature Genetics 23, no. 1 (September 1999): 41–46. http://dx.doi.org/10.1038/12640.

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18

Lynn, Miriam, Yuexiang Wang, Jaime Slater, Naisha Shah, Judith Conroy, Sean Ennis, Thomas Morris, David R. Betts, Jonathan A. Fletcher, and Maureen J. O’Sullivan. "High-resolution Genome-wide Copy-number Analyses Identify Localized Copy-number Alterations in Ewing Sarcoma." Diagnostic Molecular Pathology 22, no. 2 (June 2013): 76–84. http://dx.doi.org/10.1097/pdm.0b013e31827a47f9.

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19

Rucker, J. J. H., G. Breen, D. Pinto, I. Pedroso, C. M. Lewis, S. Cohen-Woods, R. Uher, et al. "Genome-wide association analysis of copy number variation in recurrent depressive disorder." Molecular Psychiatry 18, no. 2 (November 1, 2011): 183–89. http://dx.doi.org/10.1038/mp.2011.144.

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20

Bae, Joon Seol, Hyun Sub Cheong, Byung Lae Park, Lyoung Hyo Kim, Tae Joon Park, Jason Yongha Kim, Charisse Flerida A. Pasaje, et al. "Genome-wide association analysis of copy number variations in subarachnoid aneurysmal hemorrhage." Journal of Human Genetics 55, no. 11 (August 12, 2010): 726–30. http://dx.doi.org/10.1038/jhg.2010.97.

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21

Oldridge, Derek A., Samprit Banerjee, Sunita R. Setlur, Andrea Sboner, and Francesca Demichelis. "Optimizing copy number variation analysis using genome-wide short sequence oligonucleotide arrays." Nucleic Acids Research 38, no. 10 (February 15, 2010): 3275–86. http://dx.doi.org/10.1093/nar/gkq073.

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22

Scharf, Jeremiah, Dongmei Yu, Alden Huang, Fotis Tsetsos, Peristera Paschou, Giovanni Coppola, and Carol Mathews. "Collaborative Genome-Wide Association and Copy Number Variation Analysis of Tourette Syndrome." European Neuropsychopharmacology 29 (2019): S736—S737. http://dx.doi.org/10.1016/j.euroneuro.2017.06.064.

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23

Vincenten, Julien P. L., Hendrik F. van Essen, Birgit I. Lissenberg-Witte, Nicole W. J. Bulkmans, Oscar Krijgsman, Daoud Sie, Paul P. Eijk, Egbert F. Smit, Bauke Ylstra, and Erik Thunnissen. "Correction: Clonality analysis of pulmonary tumors by genome-wide copy number profiling." PLOS ONE 14, no. 11 (November 19, 2019): e0225733. http://dx.doi.org/10.1371/journal.pone.0225733.

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24

Meyer, Kacie J., Lea K. Davis, Emily I. Schindler, John S. Beck, Danielle S. Rudd, A. Jason Grundstad, Todd E. Scheetz, et al. "Genome-wide analysis of copy number variants in age-related macular degeneration." Human Genetics 129, no. 1 (October 28, 2010): 91–100. http://dx.doi.org/10.1007/s00439-010-0904-6.

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25

Langdon, Jacqueline A., Jayne M. Lamont, Debbie K. Scott, Sara Dyer, Emma Prebble, Nick Bown, Richard G. Grundy, David W. Ellison, and Steven C. Clifford. "Combined genome-wide allelotyping and copy number analysis identify frequent genetic losses without copy number reduction in medulloblastoma." Genes, Chromosomes and Cancer 45, no. 1 (January 2006): 47–60. http://dx.doi.org/10.1002/gcc.20262.

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26

Sanada, Masashi, Yasuhito Nannya, Kumi Nakazaki, Go Yamamoto, Lili Wang, Noriko Hosoya, Akira Hangaishi, Mineo Kurokawa, Shigeru Chiba, and Seishi Ogawa. "Genome-Wide Analysis of Copy Number Analysis of Myelodysplastic Syndromes Using High-Density SNP-Genotyping Microarrays." Blood 106, no. 11 (November 16, 2005): 3420. http://dx.doi.org/10.1182/blood.v106.11.3420.3420.

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Abstract Myelodysplastic syndromes (MDS) are clonal disorders of hematopoietic progenitors characterized by impaired blood cell production due to ineffective hematopoiesis and high propensity to acute myeloid leukemias. One of the prominent features of MDS is the high frequency of unbalanced chromosomal abnormalities that result in genetic imbalances and copy number alterations. Although the chromosomal segments involved in these abnormalities are thought to contain relevant genes to the pathogenesis of MDS, conventional analyses including FISH have failed to identify critical regions small enough to pinpoint their target genes. Affymetrix® GeneChip® 100K/500K mapping arrays were originally developed for large-scale genotyping of more than 100,000/500,000 SNPs in two separate arrays, but the quantitative nature of the preparative whole-genome amplification and array hybridization thereafter also allows for accurate copy number estimate of the genome using these platforms at the resolutions of 21.3 kb and 5.4 kb with 116,204 and 520,000 oligonucleotide probes, respectively. Here we developed robust algorithms (CNAG) for copy number detection using 100K and/or 500K arrays and analyzed 88 MDS samples on these platforms in order to identify relevant genes for development of MDS. With these huge numbers of uniformly distributed SNP probes, numerous copy number alterations were sensitively detected in cases with MDS with more numbers of abnormalities found in advanced diseases (RAEB and RAEB-t). In addition to large-scale alterations of various chromosomal segments previously reported in these syndromes, a number of small cryptic chromosomal abnormalities were identified that would escape conventional cytogenetic analysis or array CGH analysis. Minimum overlapping deletions in 5q, 7q, 12p, 13q, and 20q were precisely defined, although no pinpoint homozygous deletions were detected within these regions. A common 20q deletion spans a 400 kb segment harboring five transcriptomes and the common 12p deletion defines a 1.3 Mb region that contains the ETV6 gene. Other common overlapping abnormalities include deletions in 21q22, 17q13, and gains of 11q25. Genome-wide analysis of copy number changes using high-density oligonucleotide arrays provides valuable information about genetic abnormalities in MDS.

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27

Li, Wenli, and Michael Olivier. "Current analysis platforms and methods for detecting copy number variation." Physiological Genomics 45, no. 1 (January 2013): 1–16. http://dx.doi.org/10.1152/physiolgenomics.00082.2012.

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Copy number variation (CNV), generated through duplication or deletion events that affect one or more loci, is widespread in the human genomes and is often associated with functional consequences that may include changes in gene expression levels or fusion of genes. Genome-wide association studies indicate that some disease phenotypes and physiological pathways might be impacted by CNV in a small number of characterized genomic regions. However, the pervasiveness and full impact of such variation remains unclear. Suitable analytic methods are needed to thoroughly mine human genomes for genomic structural variation, and to explore the interplay between observed CNV and disease phenotypes, but many medical researchers are unfamiliar with the features and nuances of recently developed technologies for detecting CNV. In this article, we evaluate a suite of commonly used and recently developed approaches to uncovering genome-wide CNVs and discuss the relative merits of each.

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28

Wang, Jian, Tsz-Kwong Man, Kwong Kwok Wong, Pulivarthi H. Rao, Hon-Chiu Eastwood Leung, Rudy Guerra, and Ching C. Lau. "Genome-Wide Analysis of Copy Number Variations in Normal Population Identified by SNP Arrays." Open Biology Journal 2, no. 1 (July 8, 2009): 54–65. http://dx.doi.org/10.2174/1874196700902010054.

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Gene copy number change is an essential characteristic of many types of cancer. However, it is important to distinguish copy number variation (CNV) in the human genome of normal individuals from bona fide abnormal copy number changes of genes specific to cancers. Based on Affymetrix 50K single nucleotide polymorphism (SNP) array data, we identified genome-wide copy number variations among 104 normal subjects from three ethnic groups that were used in the HapMap project. Our analysis revealed 155 CNV regions, of which 37% were gains and 63% were losses. About 21% (30) of the CNV regions are concordant with earlier reports. These 155 CNV regions are located on more than 100 cytobands across all 23 chromosomes. The CNVs range from 68bp to 18 Mb in length, with a median length of 86 Kb. Eight CNV regions were selected for validation by quantitative PCR. Analysis of genomic sequences within and adjacent to CNVs suggests that repetitive sequences such as long interspersed nuclear elements (LINEs) and long terminal repeats (LTRs) may play a role in the origin of CNVs by facilitating non-allelic homologous recombination. Thirty-two percent of the CNVs identified in this study are associated with segmental duplications. CNVs were not preferentially enriched in gene-encoding regions. Among the 364 genes that are completely encompassed by these 155 CNVs, genes related to olfactory sensory, chemical stimulus, and other physiological responses are significantly enriched. A statistical analysis of CNVs by ethnic group revealed distinct patterns regarding the CNV location and gain-to-loss ratio. The CNVs reported here will help build a more comprehensive map of genomic variations in the human genome and facilitate the differentiation between copy number variation and somatic changes in cancers. The potential roles of certain repeat elements in CNV formation, as corroborated by other studies, shed light on the origin of CNVs and will improve our understanding of the mechanisms of genomic rearrangements in the human genome.

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29

Jiang, Shuang, Xiaoqing Wang, Chunhui Shi, and Jun Luo. "Genome-Wide Identification and Analysis of High-Copy-Number LTR Retrotransposons in Asian Pears." Genes 10, no. 2 (February 18, 2019): 156. http://dx.doi.org/10.3390/genes10020156.

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A large proportion of the genome of ‘Suli’ pear (Pyrus pyrifolia) contains long terminal repeat retrotransposons (LTR-RTs), which suggests that LTR-RTs have played important roles in the evolution of Pyrus. Further analysis of retrotransposons, particularly of high-copy-number LTR-RTs in different species, will provide new insights into the evolutionary history of Pyrus. A total of 4912 putative LTR-RTs classified into 198 subfamilies were identified in the ‘Suli’ pear genome. Six Asian pear accessions, including cultivars and wild species, were resequenced. The comparison of copy number for each LTR-RT subfamily was evaluated in Pyrus accessions, and data showed up to four-fold differences for some subfamilies. This contrast suggests different fates for retrotransposon families in the evolution of Pyrus. Fourteen high-copy-number subfamilies were identified in Asian pears, and more than 50% of the LTR-RTs in the genomes of all Pyrus accessions were from these 14 identified LTR-RT subfamilies. Their average insertion time was 3.42 million years ago, which suggests that these subfamilies were recently inserted into the genome. Many homologous and specific retrotransposon insertion sites were identified in oriental and occidental pears, suggesting that the duplication of retrotransposons has occurred throughout almost the entire origin and evolution of Pyrus species. The LTR-RTs show high heterogeneity, and their copy numbers vary in different Pyrus species. Thus, our findings suggest that LTR-RTs are an important source of genetic variation among Pyrus species.

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30

Silva, Shobha, Sarah Danson, Dawn Teare, Fiona Taylor, James Bradford, Andrew J. G. McDonagh, Abdulazeez Salawu, et al. "Genome-Wide Analysis of Circulating Cell-Free DNA Copy Number Detects Active Melanoma and Predicts Survival." Clinical Chemistry 64, no. 9 (September 1, 2018): 1338–46. http://dx.doi.org/10.1373/clinchem.2018.290023.

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Abstract BACKGROUND A substantial number of melanoma patients develop local or metastatic recurrence, and early detection of these is vital to maximise benefit from new therapies such as inhibitors of BRAF and MEK, or immune checkpoints. This study explored the use of novel DNA copy-number profiles in circulating cell-free DNA (cfDNA) as a potential biomarker of active disease and survival. PATIENTS AND METHODS Melanoma patients were recruited from oncology and dermatology clinics in Sheffield, UK, and cfDNA was isolated from stored blood plasma. Using low-coverage whole-genome sequencing, we created copy-number profiles from cfDNA from 83 melanoma patients, 44 of whom had active disease. We used scoring algorithms to summarize copy-number aberrations and investigated their utility in multivariable logistic and Cox regression analyses. RESULTS The copy-number aberration score (CNAS) was a good discriminator of active disease (odds ratio, 3.1; 95% CI, 1.5–6.2; P = 0.002), and CNAS above or below the 75th percentile remained a significant discriminator in multivariable analysis for active disease (P = 0.019, with area under ROC curve of 0.90). Additionally, mortality was higher in those with CNASs above the 75th percentile than in those with lower scores (HR, 3.4; 95% CI, 1.5–7.9; P = 0.005), adjusting for stage of disease, disease status (active or resected), BRAF status, and cfDNA concentration. CONCLUSIONS This study demonstrates the potential of a de novo approach utilizing copy-number profiling of cfDNA as a biomarker of active disease and survival in melanoma. Longitudinal analysis of copy-number profiles as an early marker of relapsed disease is warranted.

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31

Liu, Yao-Zhong, Jian Li, Rong Pan, Hui Shen, Qing Tian, Yu Zhou, Yong-Jun Liu, and Hong-Wen Deng. "Genome-Wide Copy Number Variation Association Analyses for Age at Menarche." Journal of Clinical Endocrinology & Metabolism 97, no. 11 (November 2012): E2133—E2139. http://dx.doi.org/10.1210/jc.2012-1145.

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32

Cronin, S., H. M. Blauw, J. H. Veldink, M. A. van Es, R. A. Ophoff, D. G. Bradley, L. H. van den Berg, and O. Hardiman. "Analysis of genome-wide copy number variation in Irish and Dutch ALS populations." Human Molecular Genetics 17, no. 21 (November 1, 2008): 3392–98. http://dx.doi.org/10.1093/hmg/ddn233.

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33

Reid, Brett M., Jennifer B. Permuth, Y. Ann Chen, Brooke L. Fridley, Edwin S. Iversen, Zhihua Chen, Heather Jim, et al. "Genome-wide Analysis of Common Copy Number Variation and Epithelial Ovarian Cancer Risk." Cancer Epidemiology Biomarkers & Prevention 28, no. 7 (April 4, 2019): 1117–26. http://dx.doi.org/10.1158/1055-9965.epi-18-0833.

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34

Frenkel, Svetlana, Charles N. Bernstein, Michael Sargent, Qin Kuang, Wenxin Jiang, John Wei, Bhooma Thiruvahindrapuram, Elizabeth Spriggs, Stephen W. Scherer, and Pingzhao Hu. "Genome-wide analysis identifies rare copy number variations associated with inflammatory bowel disease." PLOS ONE 14, no. 6 (June 11, 2019): e0217846. http://dx.doi.org/10.1371/journal.pone.0217846.

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35

Ramos-Quiroga, Josep-Antoni, Cristina Sánchez-Mora, Miguel Casas, Iris Garcia-Martínez, Rosa Bosch, Mariana Nogueira, Montse Corrales, et al. "Genome-wide copy number variation analysis in adult attention-deficit and hyperactivity disorder." Journal of Psychiatric Research 49 (February 2014): 60–67. http://dx.doi.org/10.1016/j.jpsychires.2013.10.022.

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36

Rodríguez-López, Julio, Gerardo Flórez, Vanessa Blanco, César Pereiro, José Manuel Fernández, Emilio Fariñas, Valentín Estévez, et al. "Genome wide analysis of rare copy number variations in alcohol abuse or dependence." Journal of Psychiatric Research 103 (August 2018): 212–18. http://dx.doi.org/10.1016/j.jpsychires.2018.06.001.

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37

Frenkel, Svetlana, Michael Sargent, Qin Kuang, John Wei, Bhooma Thiruvahindrapuram, Elizabeth Spriggs, Stephen W. Scherer, Charles N. Bernstein, and Pingzhao Hu. "Genome-Wide Analysis Identifies Rare Copy Number Variations Associated with Inflammatory Bowel Disease." Gastroenterology 152, no. 5 (April 2017): S984. http://dx.doi.org/10.1016/s0016-5085(17)33331-0.

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Ambatipudi, Srikant, Moritz Gerstung, Manishkumar Pandey, Tanuja Samant, Asawari Patil, Shubhada Kane, Rajiv S. Desai, Alejandro A. Schäffer, Niko Beerenwinkel, and Manoj B. Mahimkar. "Genome-wide expression and copy number analysis identifies driver genes in gingivobuccal cancers." Genes, Chromosomes and Cancer 51, no. 2 (November 10, 2011): 161–73. http://dx.doi.org/10.1002/gcc.20940.

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39

Luo, Hong, Xiaohan Xu, Jian Yang, Kun Wang, Chen Wang, Ping Yang, and Haoyang Cai. "Genome-wide somatic copy number alteration analysis and database construction for cervical cancer." Molecular Genetics and Genomics 295, no. 3 (January 4, 2020): 765–73. http://dx.doi.org/10.1007/s00438-019-01636-x.

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40

Jung, Seung-Hyun, Seon-Hee Yim, Hae-Jin Hu, Kyu Hoon Lee, Joo-Hyun Lee, Dong-Hyuk Sheen, Mi-Kyoung Lim, et al. "Genome-Wide Copy Number Variation Analysis Identifies Deletion Variants Associated With Ankylosing Spondylitis." Arthritis & Rheumatology 66, no. 8 (July 28, 2014): 2103–12. http://dx.doi.org/10.1002/art.38650.

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41

Smida, Jan, Hongen Xu, Yanping Zhang, Daniel Baumhoer, Sebastian Ribi, Michal Kovac, Irene von Luettichau, et al. "Genome-wide analysis of somatic copy number alterations and chromosomal breakages in osteosarcoma." International Journal of Cancer 141, no. 4 (May 25, 2017): 816–28. http://dx.doi.org/10.1002/ijc.30778.

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42

Schiffman, Joshua D., Patrick D. Lorimer, Vladimir Rodic, Mona S. Jahromi, Jonathan M. Downie, Michael G. Bayerl, Sherrie L. Perkins, Phillip Barnette, and Rodney R. Miles. "High Resolution Genome-Wide Copy Number Analysis of Pediatric Burkitt Lymphoma Identifies Copy Number Alterations In the Majority of Patients." Blood 116, no. 21 (November 19, 2010): 3123. http://dx.doi.org/10.1182/blood.v116.21.3123.3123.

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Abstract Abstract 3123 Although cure rates are high for pediatric Burkitt lymphoma (BL), a subset of patients relapses and succumbs to the disease. BL is characterized by translocation of the MYC gene with an immunoglobulin gene, but secondary changes including gain of 1q, gain of 13q, loss of 13q, loss of 17p, and others have been described by both conventional cytogenetic and oligo array CGH approaches. Secondary changes may contribute to the clinical heterogeneity of BL as evidenced by the fact that loss of 13q is associated with a worse prognosis in pediatric BL (Poirel et al., Leukemia 23:323, 2009). However, high resolution, genome-wide copy number analysis has not yet been reported in pediatric BL. The objective of this study was to identify copy number alterations (CNAs) in pediatric BL using a genome-wide approach, and to examine the relationship between CNAs and clinical parameters including outcome. After institutional review board approval, we identified 30 pediatric BL patients treated at Primary Children's Medical Center (n=25, Salt Lake City, UT) and Penn State Hershey Medical Center (n=5, Hershey, PA) with available formalin-fixed, paraffin-embedded (FFPE) diagnostic biopsy specimens. Age, site, and gender data were available for all specimens, and 22/24 of the Utah patients were treated according to the COG 5961 protocol with full clinical information and follow-up available. DNA was isolated from FFPE biopsies containing at least 80% tumor. In addition, germline DNA was isolated from negative staging bone marrow clot sections on Utah patients (n=25) to serve as a pooled normal reference and to provide germline copy number variation data on individual patients. Tumor and paired normal DNA was submitted for Molecular Inversion Probe (MIP) assay (330K Cancer Panel, Affymetrix, Santa Clara, CA). The Nexus Copy Number (BioDiscovery, El Segundo, CA) software package was used to analyze the MIP data with the following stringent call criteria: SNPRank segmentation, 5.0E-4 significance threshold, 1000 kb maximum contiguous probe spacing, minimum of 5 probes per segment, gains ≥ 2.7 copy number value, and loss ≤ 1.3 copy number value. Patients included 23 males and 7 females with a mean age of 8.0 years (range 2 – 18). At presentation, lactate dehydrogenase (LDH) levels ranged from 443 – 13851 U/L and uric acid levels ranged from 1.5 – 13 mg/dL. Patients were Murphy stage I (n=1), II (n=9), III (n=13), and IV (n=2). A total of three patients relapsed (one stage II patient and two stage III patients) and three died (the two stage III patients that relapsed and a different stage II patient who did not have a complete clinical response). 27 of the 30 tumor samples and 22/25 paired normals had adequate DNA for MIP analysis. The 3 tumor samples without adequate DNA were clinically similar to the others. We identified a total of 103 CNAs (defined as change seen in the same cytoband in 1 or more patients), which included 63 gains and 40 copy number losses. 23/27 cases (85%) had at least one gain or loss. We identified 21 recurrent CNAs (same cytoband affected in 2 or more patients), which included 14 gains and 7 losses. We found gains of 1q in 10/27 patients (37%), gains of 13q in 4/27 patients (15%) and losses of 17p in 3/27 patients (11%). Despite a relatively small sample size, deletion of 17p13 was significantly associated with relapse (p=0.041). To our knowledge, this is the first report of high-resolution genome-wide copy number analysis of pediatric BL. Furthermore, we show for the first time that FFPE archived materials can be used for high resolution gene copy number analysis in lymphomas. We identified CNAs in 85% of the pediatric BL cases, which include previously described changes of 1q, 13q, and 17p. Although sample size limited statistical power, deletion of the 17p13 locus was associated with relapse. We plan to extend these studies in a larger sample of patients to evaluate the potential prognostic significance of both the 17p13 locus deletion as well as additional recurrent CNAs. Disclosures: No relevant conflicts of interest to declare.

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Han, Nayoung, Jung Mi Oh, and In-Wha Kim. "Combination of Genome-Wide Polymorphisms and Copy Number Variations of Pharmacogenes in Koreans." Journal of Personalized Medicine 11, no. 1 (January 7, 2021): 33. http://dx.doi.org/10.3390/jpm11010033.

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For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.

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Han, Nayoung, Jung Mi Oh, and In-Wha Kim. "Combination of Genome-Wide Polymorphisms and Copy Number Variations of Pharmacogenes in Koreans." Journal of Personalized Medicine 11, no. 1 (January 7, 2021): 33. http://dx.doi.org/10.3390/jpm11010033.

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Abstract:

For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.

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Xie, Mian, Chao-sheng He, and Shen-hai Wei. "Integrated analyses of DNA copy number variations and gene expression in inflammatory breast cancer (IBC)." Journal of Clinical Oncology 31, no. 26_suppl (September 10, 2013): 28. http://dx.doi.org/10.1200/jco.2013.31.26_suppl.28.

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28 Background: Inflammatory breast cancer (IBC) is an aggressive form of BC poorly defined at the molecular level. We aim to perform genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with survival in IBC patients. Methods: We performed concurrent genome-wide microarray analyses of copy number variable regions (CNVRs) and gene expression in IBC patients. Fifty-six pairs of breast cancer and normal specimens from IBC patients were analyzed by using Affymetrix SNP 6.0 and Affymetrix U133 plus 2.0 microarrays. To investigate genomic alterations, we used an Affymetrix Genome-Wide Human SNP 6.0 array containing 1.8 million SNP and CNV probes in total. The microarray data were imported into the Partek Genomic Suite to perform CNV analysis. Ingenuity Pathway Analysis was carried out to describe gene-gene interaction networks and canonical pathways. Cox regression model was used to evaluate the association between expression of these CNV-driven genes and survival outcomes. Results: The genomic landscape of frequent copy number variable regions (CNVRs) in at least 35% of samples was revealed. Further statistical analysis for genes located in the CNVRs identified 387 genes differentially expressed between tumor and normal tissues (p < 0.001). We demonstrated the concordance between copy number variations and gene expression changes by elevated Pearson correlation coefficients. Fisher’s exact test identified five canonical pathways that were significantly enriched among the 387 CNV-driven genes. Pathway analysis revealed two major dysregulated functions in IBC: survival regulation via Rac/PAK and PTEN/PI3K/AKT signaling pathway. Further validation using three independent cohorts demonstrated prediction of survival. Conclusions: We identified genes/pathways that may serve as prognostic markers for IBC patients by integrating gene expression profiles and copy number variations.

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Reid, Brett M., and Thomas A. Sellers. "Genome-wide Analysis of Common Copy Number Variation and Epithelial Ovarian Cancer Risk—Response." Cancer Epidemiology Biomarkers & Prevention 29, no. 6 (June 2020): 1279. http://dx.doi.org/10.1158/1055-9965.epi-19-1388.

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Pollack, Jonathan R., Charles M. Perou, Therese Sorlie, Ash A. Alizadeh, Christian Rees, Michael B. Eise, Alexander Pergamenschikov, et al. "Genome-wide analysis of DNA copy number variation in breast cancer using DNA microarrays." Nature Genetics 23, S3 (November 1999): 69. http://dx.doi.org/10.1038/14385.

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48

Selvanayagam, Thanuja, Susan Walker, Matthew J. Gazzellone, Barbara Kellam, Cheryl Cytrynbaum, Dimitri J. Stavropoulos, Ping Li, et al. "Genome-wide copy number variation analysis identifies novel candidate loci associated with pediatric obesity." European Journal of Human Genetics 26, no. 11 (July 5, 2018): 1588–96. http://dx.doi.org/10.1038/s41431-018-0189-0.

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Gessi, Marco, Anja zur Mühlen, Jennifer Hammes, Andreas Waha, Dorota Denkhaus, and Torsten Pietsch. "Genome-Wide DNA Copy Number Analysis of Desmoplastic Infantile Astrocytomas and Desmoplastic Infantile Gangliogliomas." Journal of Neuropathology & Experimental Neurology 72, no. 9 (September 2013): 807–15. http://dx.doi.org/10.1097/nen.0b013e3182a033a0.

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50

Imani, S., Z. Linglin, M. Maghsoudloo, and Q. Wen. "Genome wide copy number analysis of circulating tumour cells in breast cancer liver metastasis." Annals of Oncology 30 (November 2019): ix16. http://dx.doi.org/10.1093/annonc/mdz418.005.

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