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Regional Copy Number–Independent Deregulation of Transcription in Cancer

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Regional Copy Number–Independent Deregulation of Transcription in Cancer A R T I C L E S Regional copy number–independent deregulation enetics of transcription in cancer Nicolas Stransky1,13, Ce´line Vallot1,13, Fabien Reyal1, Isabelle Bernard-Pierrot1, Sixtina Gil Diez de Medina1,2, 3 4 5 5 5 5 .com/natureg Rick Segraves , Yann de Rycke , Paul Elvin , Andrew Cassidy , Carolyn Spraggon , Alexander Graham , Jennifer Southgate6, Bernard Asselain4, Yves Allory2,7, Claude C Abbou2,8, Donna G Albertson3,9, Jean Paul Thiery1,10,11, Dominique K Chopin2,8,12, Daniel Pinkel3 & Franc¸ois Radvanyi1 .nature Genetic and epigenetic alterations have been identified that lead to transcriptional deregulation in cancers. Genetic mechanisms may affect single genes or regions containing several neighboring genes, as has been shown for DNA copy number changes. It http://www was recently reported that epigenetic suppression of gene expression can also extend to a whole region; this is known as long- range epigenetic silencing. Various techniques are available for identifying regional genetic alterations, but no large-scale analysis oup has yet been carried out to obtain an overview of regional epigenetic alterations. We carried out an exhaustive search for regions Gr susceptible to such mechanisms using a combination of transcriptome correlation map analysis and array CGH data for a series of bladder carcinomas. We validated one candidate region experimentally, demonstrating histone methylation leading to the loss of expression of neighboring genes without DNA methylation. lishing Pub Changes to gene expression patterns are an important feature of second approach involves trying to identify groups of neighboring cancer cells. These alterations are caused directly or indirectly by genes with correlated expression levels. This approach was initially 15,16 Nature genetic or epigenetic events. DNA copy number changes are one of the used in yeast and Drosophila melanogaster . Building on this 8 key genetic mechanisms responsible for changes in gene expression. approach, we recently developed a new method for transcriptome 200 Comparative genomic hybridization on DNA microarrays now analysis in human tumors: the transcriptome correlation map 17 © allow precise scanning of the entire genome for changes in DNA (TCM) . All studies based on transcriptome maps have shown that copy number1,2. the chromosomal regions of gene expression bias are mostly due to Analyses of the expression of genes located in regions of gains or changes in copy number8–12,14,17,18, with very few discrepancies losses have shown that for a significant fraction of these genes, reported11,12. However, such discrepancies are of particular interest, expression level varies consistently with gene copy number3–7. For as they may result from important new mechanisms of tumor example, comparisons of comparative genomic hybridization (CGH) progression, such as long-range epigenetic mechanisms. Such mechan- array and transcriptome data have shown that 40%–60% of the genes isms, involving DNA methylation and histone modification over a in highly amplified regions are overexpressed4,5,7. large chromosomal region, have recently been experimentally char- Conversely, many recent studies have suggested that copy number acterized in colon cancer19, highlighting the biological existence of changes are responsible for the gene expression biases inferred from regions of transcriptome bias not due to copy number changes. transcriptome maps8–13. These maps are obtained by analyzing the Here, by combining transcriptome correlation maps and genomic transcriptome as a function of the position of genes on chromosomes. alterations assessed by array CGH for a series of 57 bladder tumors, we Two main approaches have been used to establish these transcriptome identified, in a systematic manner, those regions of transcriptome bias maps. In the first, levels of gene expression in tumor samples are that were independent of DNA copy number changes. Moreover, compared with those in normal samples, and regions containing comparison of these ‘nongenetic’ regions with the ‘genetic’ regions mostly upregulated or downregulated genes are identified8–14. The (regions of coordinated expression directly accounted for by DNA 1UMR 144 Centre National de la Recherche Scientifique (CNRS)/Institut Curie, 75248 Paris Cedex 05, France. 2EMI Institut National de la Sante´ et de la Recherche Me´dicale (INSERM) 03-37, Hoˆpital Henri Mondor, 94010 Cre´teil Cedex, France. 3Comprehensive Cancer Center, University of California San Francisco (UCSF), San Francisco, California 94143, USA. 4Department of Biostatistics, Institut Curie, 75248 Paris Cedex 05, France. 5Cancer and Infection Research Area, AstraZeneca, Mereside, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK. 6Jack Birch Unit of Molecular Carcinogenesis, Department of Biology, University of York, Heslington YO10 5DD, York, UK. 7Department of Pathology, Hoˆpital Henri Mondor, 94010 Cre´teil Cedex, France. 8Department of Urology, Hoˆpital Henri Mondor, 94010 Cre´teil Cedex, France. 9Cancer Research Institute, UCSF, San Francisco, California 94143, USA. 10Department of Translational Research, Institut Curie, 75248 Paris Cedex 05, France. 11Institute of Molecular and Cell Biology, Proteos, 138673 Singapore. 12Deceased. 13These authors contributed equally to this work. Correspondence should be addressed to F.R. ([email protected]). Received 9 August 2006; accepted 13 October 2006; published online 12 November 2006; corrected after print 27 February 2008; doi:10.1038/ng1923 1 3 8 6 VOLUME 38 [ NUMBER 12 [ DECEMBER 2006 NATURE GENETICS A R T I C L E S Probe set position (Mb) Figure 1 Transcriptome correlation map of chromosome 8 for the 57 bladder 0 20 40 60 80 100 120 140 carcinomas. Each dot represents the transcriptome correlation score for a 7 given gene, indicating the strength of the correlation between the expression 8-1 profile of this gene and the expression profiles of the 14 neighboring genes. 6 The transcriptome correlation map shows scores for the various genes as a 8-5 function of their position along the chromosome. The dashed green line 5 represents the significance threshold, calculated by taking the 499th 8-2 8-3 quantile of the distribution of the transcriptome correlation scores obtained 4 8-4 from randomly ordered datasets. Genes above the dashed line have a high 3 transcriptome correlation score (42.64) and are considered to be significantly correlated with their neighbors. Black lines above the dots 2 indicate the five different TCM regions found on chromosome 8. These regions (8-1 to 8-5) contained 17, 8, 3, 6 and 15 genes and were 10.7, Transcriptome correlation score 1 enetics 7.0, 3.8, 8.6 and 2.0 Mb in size, respectively. 0 8p23.1 8p22 8p12 8q12.1 8q21.11 8q21.3 8q23.3 8q24.13 8q24.3 of neighboring genes with correlated expression patterns. We calcu- lated the transcriptome correlation score for each gene using a moving .com/natureg window of 14 genes around each gene. This score is the sum of copy number changes) showed marked differences in terms of the correlation values, for the tumor samples, between the RNA levels of proportion of downregulated genes and chromosomal location. We the gene of interest and those of each of its neighbors (seven telomeric .nature studied one of the copy number–independent regions in detail and genes and seven centromeric genes). We established a significance found that epigenetic abnormalities were responsible for a coordinated threshold (the score above which a gene is considered to have an loss of gene expression. Indeed, we showed that this loss of expression expression pattern correlated with that of its neighbors) using random http://www in a whole region was due to cancer-specific aberrant histone methyla- data sets obtained by randomly ordering the 8,555 genes in the tion, with no associated DNA methylation. Genes showing correlated genome. We generated transcriptome correlation maps for all the oup expression in the nongenetic regions provide new candidates for chromosomes of the 57 bladder tumors (Fig. 1 and Supplementary Gr involvement in tumor progression through epigenetic mechanisms. a Region 7-1 Region 8-1 Region 10-4 lishing RESULTS 50 50 50 Generation of transcriptome correlation Pub 40 40 40 maps = 57) n We determined mRNA levels for a series of 57 30 30 30 20 20 20 Nature bladder tumor samples, using Affymetrix Samples ( 8 U95A or U95Av2 GeneChips. Of the 12,533 10 10 10 probe sets common to the U95A and U95Av2 200 0 20 40 60 80 0 20 40 60 80 0 10 20 30 40 50 60 70 © chips, we retained 8,555 probe sets, each BAC clones BAC clones BAC clones corresponding to a single gene, for the estab- b Probe set position (Mb) Probe set position (Mb) Probe set position (Mb) lishment of transcriptome correlation maps 0 20 40 60 0 20 40 60 80 100 120 (see Methods). These maps highlight groups 7 4 5 6 4 Figure 2 Comparison of CGH array data and 3 5 transcriptome correlation maps: identification of 4 3 regions of correlation due to DNA copy number 2 3 changes. (a) CGH BAC array results for 2 2 57 bladder carcinomas, analyzed with a 1 1 segmentation algorithm (see Methods) for 1 chromosomes 7, 8 and 10 (yellow, no change in Transcriptome correlation score 0 0 DNA copy number; green, loss; red, gain; purple, 0 amplification). The shading indicates which BAC 7p21.3 7p21.1 7p14.1 7p11.2 7q23.1 8p23.1 8p22 8p12 8q12.1 10q22.3 10q25.1 10q26.3 clones are located near the correlated genes from c 0 20 40 60 0 20 40 60 80 100 120 the three TCM regions on the second row. 5 (b) Transcriptome correlation map for 4 5 chromosomes 7, 8 and 10 for 57 bladder 4 carcinomas. The correlated genes of regions 7-1, 4 8-1 and 10-4 are circled. (c) Transcriptome 3 3 correlation maps for a subset of bladder 3 carcinoma samples presenting no DNA copy 2 2 2 number changes around the genes from the three TCM regions.
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