Array Comparative Genomic Hybridization in Pathology

  • Reinhard Ullmann
Part of the Molecular Pathology Library book series (MPLB, volume 2)


Comparative genomic hybridization (CGH) is a molecular cytogenetic method for the detection and mapping of chromosomal gains and losses.1 It is based on the cohybridization of differentially labeled test and reference DNA onto metaphase spreads, which usually have been prepared from peripheral blood lymphocytes of a healthy donor. The signal intensity ratios of the two labels along the chromosomes then reflect DNA copy number changes in the test genome relative to the reference genome. Although CGH has tremendously contributed to our knowledge of chromosomal aberrations, its resolution, unfortunately, is limited to about 3–10 Mb.2 Resolution of CGH has significantly improved when samples were no longer hybridized to metaphase spreads but to DNA targets that have been arrayed on a glass substrate. This modification to the original technique has been named array CGH3 or matrix CGH,4 respectively. In theory, resolution of array CGH is only limited by the number and quality of DNA targets arrayed on the slide. The principle of array CGH is illustrated in Fig. 10.1.


Bacterial Artificial Chromosome Comparative Genomic Hybridization Array Comparative Genomic Hybridization Whole Genome Amplification Array Comparative Genomic Hybridization Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Kallioniemi A, Kallioniemi OP, Sudar D, et al Comparative genomic hybridization for molecular cytogenetic analysis of solid tumors. Science. 1992;258:818–821.CrossRefPubMedGoogle Scholar
  2. 2.
    Kirchhoff M, Gerdes T, Maahr J, et al Deletions below 10 megabase pairs are detected in comparative genomic hybridization by standard reference intervals. Genes Chromosomes Cancer. 1999;25:410–413.CrossRefPubMedGoogle Scholar
  3. 3.
    Pinkel D, Segraves R, Sudar D, et al High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat Genet. 1998;20:207–211.CrossRefPubMedGoogle Scholar
  4. 4.
    Solinas-Toldo S, Lampel S, Stilgenbauer S, et al Matrix-based comparative genomic hybridization: biochips to screen for genomic imbalances. Genes Chromosomes Cancer. 1997;20:399–407.CrossRefPubMedGoogle Scholar
  5. 5.
    Pollack JR, Perou CM, Alizadeh AA, et al Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat Genet. 1999;23:41–46.CrossRefPubMedGoogle Scholar
  6. 6.
    Pollack JR, Sorlie T, Perou CM, et al Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc Natl Acad Sci USA. 2002;99:12963–12968.CrossRefPubMedGoogle Scholar
  7. 7.
    Monni O, Barlund M, Mousses S, et al Comprehensive copy number and gene expression profiling of the 17q23 amplicon in human breast cancer. Proc Natl Acad Sci USA. 2001;98:5711–5716.CrossRefPubMedGoogle Scholar
  8. 8.
    Fiegler H, Carr P, Douglas EJ, et al DNA microarrays for comparative genomic hybridization based on DOP-PCR amplification of BAC and PAC clones. Genes Chromosomes Cancer. 2003;36:361–374.CrossRefPubMedGoogle Scholar
  9. 9.
    Snijders AM, Nowak N, Segraves R, et al Assembly of microarrays for genome-wide measurement of DNA copy number. Nat Genet. 2001;29:263–264.CrossRefPubMedGoogle Scholar
  10. 10.
    Krzywinski M, Bosdet I, Smailus D, et al A set of BAC clones spanning the human genome. Nucleic Acids Res. 2004;32:3651–3660.CrossRefPubMedGoogle Scholar
  11. 11.
    Osoegawa K, Mammoser AG, Wu C, et al A bacterial artificial chromosome library for sequencing the complete human genome. Genome Res. 2001;11:483–496.CrossRefPubMedGoogle Scholar
  12. 12.
    Ishkanian AS, Malloff CA, Watson SK, et al A tiling resolution DNA microarray with complete coverage of the human genome. Methods for high throughput validation of amplified fragment pools of BAC DNA for constructing high resolution CGH arrays. Nat Genet. 2004;36:299–303. [Epub 2004 Feb 2015.]CrossRefPubMedGoogle Scholar
  13. 13.
    Garnis C, Lockwood WW, Vucic E, et al High resolution analysis of non-small cell lung cancer cell lines by whole genome tiling path array CGH. Int J Cancer. 2006;118:1556–1564.CrossRefPubMedGoogle Scholar
  14. 14.
    Mantripragada KK, Tapia-Paez I, Blennow E, Nilsson P, Wedell A, Dumanski JP. DNA copy-number analysis of the 22q11 deletion-syndrome region using array-CGH with genomic and PCR-based targets. Int J Mol Med. 2004;13:273–279.PubMedGoogle Scholar
  15. 15.
    Dhami P, Coffey AJ, Abbs S, et al Exon array CGH: detection of copy-number changes at the resolution of individual exons in the human genome. Am J Hum Genet. 2005;76:750–762.CrossRefPubMedGoogle Scholar
  16. 16.
    Carvalho B, Ouwerkerk E, Meijer GA, Ylstra B. High resolution microarray comparative genomic hybridisation analysis using spotted oligonucleotides. J Clin Pathol. 2004;57:644–646.CrossRefPubMedGoogle Scholar
  17. 17.
    Peiffer DA, Le JM, Steemers FJ, et al High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping. Genome Res. 2006;16:1136–1148.CrossRefPubMedGoogle Scholar
  18. 18.
    Bignell GR, Huang J, Greshock J, et al High-resolution analysis of DNA copy number using oligonucleotide microarrays. Genome Res. 2004;14:287–295.CrossRefPubMedGoogle Scholar
  19. 19.
    Srinivasan M, Sedmak D, Jewell S. Effect of fixatives and tissue processing on the content and integrity of nucleic acids. Am J Pathol. 2002;161:1961–1971.PubMedGoogle Scholar
  20. 20.
    Hernandez S, Lloreta J. Manual versus laser micro-dissection in molecular biology. Ultrastruct Pathol. 2006;30:221–228.CrossRefPubMedGoogle Scholar
  21. 21.
    Ullmann R, Bongiovanni M, Halbwedl I, et al Bronchiolar columnar cell dysplasia: genetic analysis of a novel preneoplastic lesion of peripheral lung. Virchows Arch. 2003;442:429–436.PubMedGoogle Scholar
  22. 22.
    Telenius H, Pelmear AH, Tunnacliffe A, et al Cytogenetic analysis by chromosome painting using DOP-PCR amplified flow-sorted chromosomes. Genes Chromosomes Cancer. 1992;4:257–263.CrossRefPubMedGoogle Scholar
  23. 23.
    Klein CA, Schmidt-Kittler O, Schardt JA, Pantel K, Speicher MR, Riethmuller G. Comparative genomic hybridization, loss of heterozygosity, and DNA sequence analysis of single cells. Proc Natl Acad Sci USA. 1999;96:4494–4499.CrossRefPubMedGoogle Scholar
  24. 24.
    Ludecke HJ, Senger G, Claussen U, Horsthemke B. Cloning defined regions of the human genome by microdissection of banded chromosomes and enzymatic amplification. Nature. 1989;338:348–350.CrossRefPubMedGoogle Scholar
  25. 25.
    Saunders RD, Glover DM, Ashburner M, et al PCR amplification of DNA microdissected from a single polytene chromosome band: a comparison with conventional microcloning. Nucleic Acids Res. 1989;17:9027–9037.CrossRefPubMedGoogle Scholar
  26. 26.
    Tanabe C, Aoyagi K, Sakiyama T, et al Evaluation of a whole-genome amplification method based on adaptor-ligation PCR of randomly sheared genomic DNA. Genes Chromosomes Cancer. 2003;38:168–176.CrossRefPubMedGoogle Scholar
  27. 27.
    Hughes S, Arneson N, Done S, Squire J. The use of whole genome amplification in the study of human disease. Prog Biophys Mol Biol. 2005;88:173–189.CrossRefPubMedGoogle Scholar
  28. 28.
    Petzmann S, Ullmann R, Halbwedl I, Popper HH. Analysis of chromosome-11 aberrations in pulmonary and gastrointestinal carcinoids: an array comparative genomic hybridization-based study. Virchows Arch. 2004;445:151–159.CrossRefPubMedGoogle Scholar
  29. 29.
    Moinfar F, Man YG, Arnould L, Bratthauer GL, Ratschek M, Tavassoli FA. Concurrent and independent genetic alterations in the stromal and epithelial cells of mammary carcinoma: implications for tumorigenesis. Cancer Res. 2000;60:2562–2566.PubMedGoogle Scholar
  30. 30.
    Huang Q, Schantz SP, Rao PH, Mo J, McCormick SA, Chaganti RS. Improving degenerate oligonucleotide primed PCR-comparative genomic hybridization for analysis of DNA copy number changes in tumors. Genes Chromosomes Cancer. 2000;28:395–403.CrossRefPubMedGoogle Scholar
  31. 31.
    van Gijlswijk RP, Talman EG, Janssen PJ, et al Universal Linkage System: versatile nucleic acid labeling technique. Expert Rev Mol Diagn. 2001;1:81–91.CrossRefPubMedGoogle Scholar
  32. 32.
    Lucito R, Healy J, Alexander J, et al Representational oligonucleotide microarray analysis: a high-resolution method to detect genome copy number variation. Genome Res. 2003;13:2291–2305.CrossRefPubMedGoogle Scholar
  33. 33.
    Chari R, Lockwood WW, Lam WL. Computational methods in array CGH. Cancer Inform. 2006;2:48–58.Google Scholar
  34. 34.
    Khojasteh M, Lam WL, Ward RK, MacAulay C. A stepwise framework for the normalization of array CGH data. BMC Bioinformatics. 2005;6:274.CrossRefPubMedGoogle Scholar
  35. 35.
    Neuvial P, Hupe P, Brito I, et al Spatial normalization of array-CGH data. BMC Bioinformatics. 2006;7:264.CrossRefPubMedGoogle Scholar
  36. 36.
    Chari R, Lockwood WW, Lam WL. Computational methods for the analysis of array comparative genomic hybridization. Cancer Inform. 2006;2:48–58.Google Scholar
  37. 37.
    Fridlyand J, Snijders AM, Pinkel D, Albertson DG, Jain AN. Application of Hidden Markov models to the analysis of the array CGH data. Special Genomic Issue J Multivariate Anal. 2004;90:132–153.CrossRefGoogle Scholar
  38. 38.
    Marioni JC, Thorne NP, Tavare S. BioHMM: a heterogeneous hidden Markov model for segmenting array CGH data, Bioinformatics. 2006;22:1144–1146.CrossRefPubMedGoogle Scholar
  39. 39.
    Olshen AB, Venkatraman ES, Lucito R, Wigler M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics. 2004;5:557–572.CrossRefPubMedGoogle Scholar
  40. 40.
    Hsu L, Self SG, Grove D, et al Denoising array-based comparative genomic hybridization data using wavelets. Biostatistics. 2005;6:211–226.CrossRefPubMedGoogle Scholar
  41. 41.
    Brazma A, Hingamp P, Quackenbush J, et al Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet. 2001;29:365–371.CrossRefPubMedGoogle Scholar
  42. 42.
    Chen W, Erdogan F, Ropers HH, Lenzner S, Ullmann R. CGHPRO: a comprehensive data analysis tool for array CGH. BMC Bioinformatics. 2005;6:85.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Reinhard Ullmann
    • 1
  1. 1.Department of Human Molecular GeneticsMax Planck Institute for Molecular GeneticsBerlinGermany

Personalised recommendations