Application of Oligonucleotides Arrays for Coincident Comparative Genomic Hybridization, Ploidy Status and Loss of Heterozygosity Studies in Human Cancers

  • John K. Cowell
  • Ken C. Lo
Part of the Methods in Molecular Biology™ book series (MIMB, volume 556)


Many oligonucleotide arrays comprise of spotted short oligonucleotides from throughout the genome under study. Hybridization of tumor DNA samples to these arrays will provide copy number estimates at each reference point with varying degrees of accuracy. In addition to copy number changes, however, tumors often undergo loss of heterozygosity for specific regions of the genome without copy number changes and these genetic changes can only be identified using arrays that identify polymorphic alleles at each reference point. In addition, because the hybridization intensity can be measured at each of the allelic variants, allelic ratios can be established which give indications of ploidy status in the tumor which is not generally possible using most other oligonucleotide array designs. The only arrays currently available that simultaneously report copy number, ploidy, and loss of heterozygosity are the Affymetrix SNP mapping arrays.

In this review, the features of the SNP mapping arrays are described and computational tools explored which allow the maximum genetic information to be extracted from the experiment. Although the methodologies to generate the SNP data are now well established, approaches to interpret the data are only just being developed. From our experience using these arrays, we provide insights into how to evaluate the SNP data to report copy number changes, loss of heterozygosity, and ploidy in the same tumor samples using a single array.

Key words

SNP mapping arrays comparative genome hybridization loss of heterozygosity allelic ratios CGH visualization tools oligonucleotide arrays 


  1. 1.
    Cowell, J. K., Barnett, G. and Nowak N. J. (2004) Characterization of the 1p/19q chromosomal loss in oligodendrogliomas using CGHa. J. Neuropathol. Exp. Neurol. 63, 151–158.PubMedGoogle Scholar
  2. 2.
    Lo, K. C., Ma, C., Bundy, B. N., Pomeroy, S. L., Eberhart, C. G. and Cowell, J. K. (2007) Gain of 1q is a univariate negative prognostic marker for survival in medulloblastoma. Clin. Cancer Res. 13, 7022–7028.PubMedCrossRefGoogle Scholar
  3. 3.
    Cavenee, W. K., Dryja, T. P., Phillips, R. A., Benedict, W. F., Godbout, R., Gallie, B. L., Murphree, A. L., Strong, L. C. and White, R. L. (1983) Expression of recessive alleles by chromosomal mechanisms in retinoblastoma. Nature 305, 779–784.PubMedCrossRefGoogle Scholar
  4. 4.
    Cowell, J. K. and Hawthorn, L. (2007) The application of microarray technology to the analysis of the cancer genome. Curr. Mol. Med. 7, 103–120.PubMedCrossRefGoogle Scholar
  5. 5.
    Nannya, Y., Sanada, M., Nakazaki, K., Hosoya, N., Wang, L., Hangaishi, A., Kurokawa, M., Chiba, S., Bailey, D. K., Kennedy, G. C. and others. (2005) A robust algorithm for copy number detection using high-density oligonucleotide single nucleotide polymorphism genotyping arrays. Cancer Res. 65, 6071–6079.Google Scholar
  6. 6.
    Lo, K. C., Bailey, D., Burkhardt, T., Gardina, P., Turpaz, Y. and Cowell, J. K. (2008) Comprehensive analysis of loss of heterozygosity events in glioblastoma using the 100 K SNP mapping arrays and comparison with copy number abnormalities defined by BAC array comparative genomic hybridization. Genes Chromosomes Cancer 47, 221–237.PubMedCrossRefGoogle Scholar
  7. 7.
    Gardina, P. J., Lo, K. C., Lee, W., Cowell, J. K. and Turpaz, Y. (2008) Ploidy status and copy number aberrations in primary glioblastomas defined by integrated analysis of allelic ratios, signal ratios and loss of heterozygosity on 500 K SNP mapping arrays. BMC Genomics In press.Google Scholar
  8. 8.
    Shankar, G., Rossi, M. R., McQuaid, D., Conroy, J. M., Gaile, D. G., Cowell, J. K., Nowak, N. J. and Liang, P. (2006) aCGH viewer: A generic visualization tool for aCGH data. Cancer Inform. 2, 36–43.PubMedGoogle Scholar
  9. 9.
    Fridlyand, J., Snijders, A. M., Pinkel, D., Albertson, D. G. and Jain A. N. (2004) Hidden Markov models approach to the analysis of array CGH data. J. Multivariate Anal. 90, 132–153.CrossRefGoogle Scholar
  10. 10.
    Lai, W. R., Johnson, M. D., Kucherlapati, R. and Park, P. J. (2005) Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data. Bioinformatics 21, 3763–3770.PubMedCrossRefGoogle Scholar
  11. 11.
    Mitelman, F., Johansson, B. and Mertens, F. (Eds.) (2008). Mitelman Database of Chromosome Aberrations in Cancer.
  12. 12.
    Rossi, M. R., Gaile, D., LaDuca, J., Matsui, S. I, Conroy, J., McQuaid, D., Chervinsky, D., Eddy, R., Chen, H-S., Barnett, G., Nowak, N. J. and Cowell, J. K. (2005) Identification of consistent novel megabase deletions in low-grade oligodendrogliomas using array-based comparative genomic hybridization. Genes Chromosomes Cancer 44, 85–96.PubMedCrossRefGoogle Scholar
  13. 13.
    Lo, K. C., Rossi, M. R., LaDuca, J., Hicks, D. G., Turpaz, Y. and Hawthorn, L. (2007) Candidate gliobastoma development gene identification using concordance between copy number abnormalities and gene expression level changes. Genes Chromosomes Cancer 46, 875–894.PubMedCrossRefGoogle Scholar
  14. 14.
    Cowell, J. K. (1982) Double minutes and homogeneously staining regions: Gene amplification in mammalian cells. Ann. Rev. Genet. 16, 21–59.PubMedCrossRefGoogle Scholar
  15. 15.
    Stark, G. R. (1993) Regulation and mechanisms of mammalian gene amplification. Adv. Cancer Res. 61, 87–113.PubMedCrossRefGoogle Scholar
  16. 16.
    Lockwood, W. W., Chari, R., Chi, B. and Lam, W. L. (2006) Recent advances in array comparative genomic hybridization technologies and their applications in human genetics. Eur. Hum. Genet. 14, 139–148.CrossRefGoogle Scholar
  17. 17.
    Knudson, A. G. (1971) Mutation and cancer: Statistical study of retinoblastoma. Proc. Natl. Acad. Sci. USA 68, 820–823.PubMedCrossRefGoogle Scholar
  18. 18.
    Cowell, J. K., LaDuca, J., Rossi, M. R., Burkhardt, T., Nowak, N. J. and Matsui, S-I. (2005) Molecular characterization of the t(3;9) translocation associated with immortalization in the MCF10A cell line. Cancer Genet. Cytogenet. 163, 23–29.PubMedCrossRefGoogle Scholar
  19. 19.
    Rossi, M. R., LaDuca, J., Matsui, S-I., Nowak, N. J., Hawthorn, L. and Cowell, J. K. (2005) Novel amplicons on the short arm of chromosome 7 identified using high resolution array CGH contain over expressed genes in addition to EGFR in glioblastoma multiforme. Genes Chromosomes Cancer 44, 392–404.PubMedCrossRefGoogle Scholar
  20. 20.
    Lo, K. C., Shankar, G., Turpaz, Y., Bailey, D., Rossi, M. R., Burkhardt, T., Liang, P and Cowell, J. K. (2007) Overlay tool for aCGHviewer: An analysis module built for aCGHViewer used to combine different microarray platforms for visualization. Cancer Inform. 3, 307–319.PubMedGoogle Scholar

Copyright information

© Humana Press, a part of Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • John K. Cowell
    • 1
  • Ken C. Lo
    • 2
  1. 1.School of MedicineMedical College of Georgia Cancer CenterAugustaUSA
  2. 2.Roche NimbleGen, Inc.MadisonUSA

Personalised recommendations