Skip to main content
Springer Nature Link
Log in

Single Nucleotide Polymorphism Microarray Analysis of Genetic Alterations in Cancer

  • Protocol
  • First Online:
Cancer Cytogenetics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 730))

  • 2299 Accesses

Abstract

The identification of structural genetic alterations, including DNA amplifications, deletions, and loss of heterozygosity (LOH), using single nucleotide polymorphism (SNP) microarrays has provided important insights into the pathogenesis of a number of hematologic malignancies. Currently available SNP arrays comprise over a million SNP and copy number oligonucleotide probes that interrogate the genome at sub-kilobase resolution. The accurate detection of DNA copy number abnormalities and LOH is critically dependent on the use of high-quality DNA, the use of matched reference samples wherever possible, optimal normalization of raw microarray data, and computational algorithms to detect copy number alterations sensitively and robustly. This chapter provides methods and guidelines for preparing samples, processing and analyzing data, and validation of novel lesions. Specific examples are provided for Affymetrix SNP arrays in acute lymphoblastic leukemia.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Protocol
USD 49.95
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (Canada)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (Canada)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (Canada)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Pui CH, Robison LL, Look AT. Acute lymphoblastic leukaemia. Lancet 2008;371:1030–43.

    Article  PubMed  CAS  Google Scholar 

  2. Harrison CJ. Cytogenetics of paediatric and adolescent acute lymphoblastic leukaemia. Br J Haematol 2009;144:147–56.

    Article  PubMed  Google Scholar 

  3. Albertson DG, Pinkel D. Genomic microarrays in human genetic disease and cancer. Hum Mol Genet 2003;12(Spec No 2):R145–52.

    Article  PubMed  CAS  Google Scholar 

  4. Carter NP. Methods and strategies for analyzing copy number variation using DNA microarrays. Nat Genet 2007;39:S16–21.

    Article  PubMed  CAS  Google Scholar 

  5. Matsuzaki H, Dong S, Loi H, et al. Genotyping over 100,000 SNPs on a pair of oligonucleotide arrays. Nat Methods 2004;1:109–11.

    Article  PubMed  CAS  Google Scholar 

  6. Dutt A, Beroukhim R. Single nucleotide polymorphism array analysis of cancer. Curr Opin Oncol 2007;19:43–9.

    Article  PubMed  CAS  Google Scholar 

  7. Mullighan CG, Downing JR. Genome-wide profiling of genetic alterations in acute lymphoblastic leukemia: recent insights and future directions. Leukemia 2009;23(7):1209–18.

    Article  PubMed  CAS  Google Scholar 

  8. LaFramboise T. Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances. Nucleic Acids Res 2009;37:4181–93.

    Article  PubMed  CAS  Google Scholar 

  9. Mullighan CG, Downing JR. Global genomic characterization of acute lymphoblastic leukemia. Semin Hematol 2009;46:3–15.

    Article  PubMed  CAS  Google Scholar 

  10. Gunderson KL, Steemers FJ, Lee G, Mendoza LG, Chee MS. A genome-wide scalable SNP genotyping assay using microarray technology. Nat Genet 2005;37:549–54.

    Article  PubMed  CAS  Google Scholar 

  11. Affymetrix Technical Manuals. (Accessed at http://www.affymetrix.com/support/technical/manuals.affx.)

  12. Genome-Wide Human SNP Array 5.0. (Accessed at http://www.affymetrix.com/support/technical/datasheets/500k_datasheet.pdf.)

  13. McCarroll SA, Kuruvilla FG, Korn JM, et al. Integrated detection and population-genetic analysis of SNPs and copy number variation. Nat Genet 2008;40:1166–74.

    Article  PubMed  CAS  Google Scholar 

  14. Mullighan CG, Phillips LA, Su X, et al. Genomic analysis of the clonal origins of relapsed acute lymphoblastic leukemia. Science 2008;322:1377–80.

    Article  PubMed  CAS  Google Scholar 

  15. Mullighan CG, Collins-Underwood JR, Phillips LAA, et al. Rearrangement of CRLF2 in B-progenitor and Down syndrome associated acute lymphoblastic leukemia. Nat Genet 2009;41:1243–6.

    Article  PubMed  CAS  Google Scholar 

  16. Genome-Wide Human SNP Nsp/Sty 6.0 User Guide. (Accessed at http://www.affymetrix.com/support/downloads/manuals/genomewidesnp6_manual.pdf.)

  17. Genome-Wide Human SNP Nsp/Sty Assay 5.0. (Accessed at http://www.affymetrix.com/support/downloads/manuals/genome_wide_snp_5_0_manual.pdf.)

  18. Huang J, Wei W, Zhang J, et al. Whole genome DNA copy number changes identified by high density oligonucleotide arrays. Hum Genomics 2004;1:287–99.

    PubMed  CAS  Google Scholar 

  19. Huang J, Wei W, Chen J, et al. CARAT: a novel method for allelic detection of DNA copy number changes using high density oligonucleotide arrays. BMC Bioinform 2006;7:83.

    Article  Google Scholar 

  20. Lin M, Wei LJ, Sellers WR, Lieberfarb M, Wong WH, Li C. dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data. Bioinformatics 2004;20:1233–40.

    Article  PubMed  CAS  Google Scholar 

  21. dChip. (Accessed at http://biosun1.harvard.edu/complab/dchip/.)

  22. Partek. (Accessed at http://www.partek.org.)

  23. Nannya Y, Sanada M, Nakazaki K, et al. A robust algorithm for copy number detection using high-density oligonucleotide single nucleotide polymorphism genotyping arrays. Cancer Res 2005;65:6071–9.

    Article  PubMed  CAS  Google Scholar 

  24. CNAG. (Accessed at http://www.genome.umin.jp/CNAGtop2.html.)

  25. Yamamoto G, Nannya Y, Kato M, et al. Highly sensitive method for genomewide detection of allelic composition in nonpaired, primary tumor specimens by use of affymetrix single-nucleotide-polymorphism genotyping microarrays. Am J Hum Genet 2007;81:114–26.

    Article  PubMed  CAS  Google Scholar 

  26. Ishikawa S, Komura D, Tsuji S, et al. Allelic dosage analysis with genotyping microarrays. Biochem Biophys Res Commun 2005;333:1309–14.

    Article  PubMed  CAS  Google Scholar 

  27. Rigaill G, Hupe P, Almeida A, et al. ITALICS: an algorithm for normalization and DNA copy number calling for Affymetrix SNP arrays. Bioinformatics 2008;24:768–74.

    Article  PubMed  CAS  Google Scholar 

  28. Nexus. (Accessed at http://www.biodiscovery.com/index/nexus.)

  29. Wang K, Li M, Hadley D, et al. PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data. Genome Res 2007;17:1665–74.

    Article  PubMed  CAS  Google Scholar 

  30. LaFramboise T, Weir BA, Zhao X, et al. Allele-specific amplification in cancer revealed by SNP array analysis. PLoS Comput Biol 2005;1:e65.

    Article  PubMed  Google Scholar 

  31. Mullighan CG, Goorha S, Radtke I, et al. Genome-wide analysis of genetic alterations in acute lymphoblastic leukaemia. Nature 2007;446:758–64.

    Article  PubMed  CAS  Google Scholar 

  32. Mullighan CG, Miller CB, Radtke I, et al. BCR-ABL1 lymphoblastic leukaemia is characterized by the deletion of Ikaros. Nature 2008;453:110–4.

    Article  PubMed  CAS  Google Scholar 

  33. Mullighan CG, Su X, Zhang J, et al. Deletion of IKZF1 and Prognosis in Acute Lymphoblastic Leukemia. N Engl J Med 2009;360:470–80.

    Article  PubMed  CAS  Google Scholar 

  34. Radtke I, Mullighan CG, Ishii M, et al. Genomic analysis reveals few genetic alterations in pediatric acute myeloid leukemia. Proc Natl Acad Sci USA 2009;106:12944–9.

    Article  PubMed  CAS  Google Scholar 

  35. Flotho C, Coustan-Smith E, Pei D, et al. A set of genes that regulate cell proliferation predicts treatment outcome in childhood acute lymphoblastic leukemia. Blood 2007;110:1271–7.

    Article  PubMed  CAS  Google Scholar 

  36. Loh ML, Sakai DS, Flotho C, et al. Mutations in CBL occur frequently in juvenile myelomonocytic leukemia. Blood 2009;114:1859–63.

    Article  PubMed  CAS  Google Scholar 

  37. Pounds S, Cheng C, Mullighan C, Raimondi SC, Shurtleff S, Downing JR. Reference alignment of SNP microarray signals for copy number analysis of tumors. Bioinformatics 2009;25:315–21.

    Article  PubMed  CAS  Google Scholar 

  38. R Development Core Team. R: A language and environment for statistical computing. 2009. (Accessed at http://www.R-project.org.)

  39. Reference Marker Normalization. (Accessed at http://www.stjuderesearch.org/depts/biostats/refnorm/.)

  40. Bengtsson H, Irizarry R, Carvalho B, Speed TP. Estimation and assessment of raw copy numbers at the single locus level. Bioinformatics 2008;24:759–67.

    Article  PubMed  CAS  Google Scholar 

  41. Bengtsson H, Ray A, Spellman P, Speed TP. A single-sample method for normalizing and combining full-resolution copy numbers from multiple platforms, labs and analysis methods. Bioinformatics 2009;25:861–7.

    Article  PubMed  CAS  Google Scholar 

  42. Bengtsson H, Wirapati P, Speed TP. A single-array preprocessing method for estimating full-resolution raw copy numbers from all Affymetrix genotyping arrays including GenomeWideSNP 5 & 6. Bioinformatics 2009;25:2149–56.

    Article  PubMed  CAS  Google Scholar 

  43. Olshen AB, Venkatraman ES, Lucito R, Wigler M. Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics 2004;5:557–72.

    Article  PubMed  Google Scholar 

  44. Venkatraman ES, Olshen AB. A faster circular binary segmentation algorithm for the analysis of array CGH data. Bioinformatics 2007;23:657–63.

    Article  PubMed  CAS  Google Scholar 

  45. The Integrative Genomics Viewer. (Accessed at http://www.broadinstitute.org/igv/.)

  46. Kent WJ, Sugnet CW, Furey TS, et al. The human genome browser at UCSC. Genome Res 2002;12:996–1006.

    PubMed  CAS  Google Scholar 

  47. Beroukhim R, Lin M, Park Y, et al. Inferring loss-of-heterozygosity from unpaired tumors using high-density oligonucleotide SNP arrays. PLoS Comput Biol 2006;2:e41.

    Article  PubMed  Google Scholar 

  48. Conrad DF, Andrews TD, Carter NP, Hurles ME, Pritchard JK. A high-resolution survey of deletion polymorphism in the human genome. Nat Genet 2006;38:75–81.

    Article  PubMed  CAS  Google Scholar 

  49. Iafrate AJ, Feuk L, Rivera MN, et al. Detection of large-scale variation in the human genome. Nat Genet 2004;36:949–51.

    Article  PubMed  CAS  Google Scholar 

  50. Redon R, Ishikawa S, Fitch KR, et al. Global variation in copy number in the human genome. Nature 2006;444:444–54.

    Article  PubMed  CAS  Google Scholar 

  51. McCarroll SA, Hadnott TN, Perry GH, et al. Common deletion polymorphisms in the human genome. Nat Genet 2006;38:86–92.

    Article  PubMed  CAS  Google Scholar 

  52. Komura D, Shen F, Ishikawa S, et al. Genome-wide detection of human copy number variations using high-density DNA oligonucleotide arrays. Genome Res 2006;16:1575–84.

    Article  PubMed  CAS  Google Scholar 

  53. McCarroll SA. Extending genome-wide association studies to copy-number variation. Hum Mol Genet 2008;17:R135–42.

    Article  PubMed  CAS  Google Scholar 

  54. The Database of Genomic Variants. (Accessed at http://projects.tcag.ca/variation/.)

  55. UCSC Genome Browser. (Accessed at http://www.genome.ucsc.edu/cgi-bin/hgGateway.)

  56. Beroukhim R, Getz G, Nghiemphu L, et al. Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma. Proc Natl Acad Sci USA 2007;104:20007–12.

    Article  PubMed  CAS  Google Scholar 

  57. Gene Pattern. (Accessed at http://genepattern.broadinstitute.org/gp/pages/index.jsf.)

  58. DNA Blood Mini Kit Technical Manual. (Accessed at http://www1.qiagen.com/products/genomicdnastabilizationpurification/qiaampsystem/qiaampdnabloodminikit.aspx.)

  59. Gentra Puregene Blood Kit Technical Manual. (Accessed at http://www1.qiagen.com/Products/GenomicDnaStabilizationPurification/GentraPuregeneBloodKit.aspx.)

  60. Lovmar L, Syvanen AC. Multiple displacement amplification to create a long-lasting source of DNA for genetic studies. Hum Mutat 2006;27:603–14.

    Article  PubMed  CAS  Google Scholar 

  61. Xing J, Watkins WS, Zhang Y, Witherspoon DJ, Jorde LB. High fidelity of whole-genome ­amplified DNA on high-density single nucleotide polymorphism arrays. Genomics 2008;92:452–6.

    Article  PubMed  CAS  Google Scholar 

  62. Pugh TJ, Delaney AD, Farnoud N, et al. Impact of whole genome amplification on analysis of copy number variants. Nucleic Acids Res 2008;36:e80.

    Article  PubMed  CAS  Google Scholar 

  63. Oosting J, Lips EH, van Eijk R, et al. High-resolution copy number analysis of paraffin-embedded archival tissue using SNP BeadArrays. Genome Res 2007;17:368–76.

    Article  PubMed  CAS  Google Scholar 

  64. Wang Y, Carlton VE, Karlin-Neumann G, et al. High quality copy number and genotype data from FFPE samples using Molecular Inversion Probe (MIP) microarrays. BMC Med Genomics 2009;2:8.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

Work described in this chapter was supported National Cancer Institute Cancer Center Support Grant P30 CA021765, the American Lebanese Syrian Associated Charities of St. Jude Children’s Research Hospital. The author is supported by the National Health and Medical Research Council (Australian), the American Society of Hematology, the American Association for Cancer Research and is a Pew Scholar in the Biomedical Sciences. The author thanks the many collaborators at St Jude Children’s Research Hospital who have contributed to this study, notably James Downing and Sheila Shurtleff (Pathology), Stan Pounds (Biostatistics), Jing Ma (Hartwell Center for Bioinformatics and Biotechnology), Xiaoping Su and Letha Phillips (Pathology), who have supported these studies, and developed and performed the bioinformatic and laboratory procedures described; John Morris, Emily Walker and Geoff Neale of the Clinical Applications of Core Technology laboratory of the Hartwell Center for Bioinformatics and Biotechnology at St Jude, for performing SNP arrays; and Cheng Li, for helpful discussions and development of dChip.

Author information

Authors and Affiliations

  1. Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Charles G. Mullighan

Authors
  1. Charles G. Mullighan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Charles G. Mullighan .

Editor information

Editors and Affiliations

  1. Victorian Cancer Cytogenetics Service, St. Vincent's Hospital Melbourne, 41 Victoria Parade, Fitzroy, 3065, Victoria, Australia

    Lynda J. Campbell

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media, LLC

About this protocol

Cite this protocol

Mullighan, C.G. (2011). Single Nucleotide Polymorphism Microarray Analysis of Genetic Alterations in Cancer. In: Campbell, L. (eds) Cancer Cytogenetics. Methods in Molecular Biology, vol 730. Humana Press. https://doi.org/10.1007/978-1-61779-074-4_17

Download citation

  • DOI: https://doi.org/10.1007/978-1-61779-074-4_17

  • Published:

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-61779-073-7

  • Online ISBN: 978-1-61779-074-4

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation