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Detection limits of DNA copy number alterations in heterogeneous cell populations

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Abstract

Background

Array Comparative Genomic Hybridization (aCGH) is a widely used technique to assess chromosomal copy number alterations. Chromosomal content, however, is often not uniform throughout cell populations. Here we evaluated to what extent aCGH can detect DNA copy number alterations in heterogeneous cell populations. A systematic evaluation is currently lacking, despite its importance in diagnostics and research. The detection limits reported are a compound of analytical software and laboratory techniques and do not account for the number of probes in relation to sample homogeneity.

Methods

Detection limits were explored with DNA isolated from a patient with intellectual disability (ID) and from tumor cell line BT474. Both were diluted with increasing amounts of normal DNA to simulate different levels of cellularity. Samples were hybridized on microarrays containing 180,880 oligonucleotides evenly distributed over the genome (spacing ~17 kb).

Results

Single copy number alterations, represented by down to 249 probes (4 Mb) and present in 10 % of a cell population, could be detected. Alterations encompassing as few as 14 probes (~238 Kb) could also be detected, but for this a 35 % mosaic level was required.

Conclusions

DNA copy number alterations can be detected in cell populations containing 10 % abnormal cells. Detection of sub-megabase alterations requires a higher percentage of abnormal cells or microarrays with a higher probe density.

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Abbreviations

aCGH:

Array comparative genome hybridization

WCP:

Whole chromosome paint

CEP:

Centromere probe

FISH:

Fluorescence in situ hybridization

GEO:

Gene expression omnibus

CNV:

Copy number variation

ID:

Intellectual disability

References

  1. A.E. Oostlander, G.A. Meijer, B. Ylstra, Microarray-based comparative genomic hybridization and its applications in human genetics. Clin. Genet. 66, 488–495 (2004)

    Article  PubMed  CAS  Google Scholar 

  2. L.E. Vissers, B.B. de Vries, J.A. Veltman, Genomic microarrays in mental retardation: from copy number variation to gene, from research to diagnosis. J Med Genet. 47(5), 289–297 (2010)

    Article  PubMed  CAS  Google Scholar 

  3. D. Pinkel, D.G. Albertson, Array comparative genomic hybridization and its applications in cancer. Nat. Genet. 37(Suppl), S11–S17 (2005)

    Article  PubMed  CAS  Google Scholar 

  4. K. Wang, J. Li, S. Li, L. Bolund, C. Wiuf, Estimation of tumor heterogeneity using CGH array data. BMC Bioinforma. 10, 12 (2009)

    Article  Google Scholar 

  5. C. Curtis, A.G. Lynch, M.J. Dunning, I. Spiteri, J.C. Marioni, J. Hadfield, S.F. Chin, J.D. Brenton, S. Tavaré, C. Caldas, The pitfalls of platform comparison: DNA copy number array technologies assessed. BMC Genomics. 10, 588 (2009)

    Article  PubMed  Google Scholar 

  6. B.C. Ballif, E.A. Rorem, K. Sundin, M. Lincicum, S. Gaskin, J. Coppinger, C.D. Kashork, L.G. Shaffer, B.A. Bejjani, Detection of low-level mosaicism by array CGH in routine diagnostic specimens. Am J Med Genet Part A 140A, 2757–2767 (2006)

    Article  Google Scholar 

  7. S.W. Cheung, C.A. Shaw, D.A. Scott, A. Patel, T. Sahoo, C.A. Bacino, A. Pursley, J. Li, R. Erickson, A.L. Gropman, D.T. Miller, M.R. Seashore, A.M. Summers, P. Stankiewicz, A.C. Chinault, J.R. Lupski, A.L. Beaudet, V.R. Sutton et al., Microarray-based CGH detects chromosomal mosaicism not revealed by conventional cytogenetics. Am J Med Genet Part A 143A, 1679–1686 (2007)

    Article  PubMed  Google Scholar 

  8. C. Garnis, B.P. Coe, S.L. Lam, C. MacAulay, W.L. Lam, High-resolution array CGH increases heterogeneity tolerance in the analysis of clinical samples. Genomics 85(6), 790–793 (2005)

    Article  PubMed  CAS  Google Scholar 

  9. N.A. Johnson, R.A. Hamoudi, K. Ichimura, L. Liu, D.M. Pearson, V.P. Collins, M.Q. Du, Application of array CGH on archival formalin-fixed paraffin-embedded tissues including small numbers of microdissected cells. Lab Invest 86, 968–978 (2006)

    Article  PubMed  CAS  Google Scholar 

  10. J.R. Vermeesch, C. Melotte, G. Froyen, V.S. Van, B. Dutta, N. Maas, S. Vermeulen, B. Menten, F. Speleman, M.B. De, H.P. Van, P. Marynen, J.P. Fryns, K. Devriendt, Molecular karyotyping: array CGH quality criteria for constitutional genetic diagnosis. J. Histochem. Cytochem. 53, 413–422 (2005)

    Article  PubMed  CAS  Google Scholar 

  11. B. Ylstra, P. van den Ijssel, B. Carvalho, R.H. Brakenhoff, G.A. Meijer, BAC to the future! or oligonucleotides: a perspective for micro array comparative genomic hybridization (array CGH). Nucleic Acids Res. 34(2), 445–450 (2006)

    Article  PubMed  CAS  Google Scholar 

  12. D. Pinto, K. Darvishi, X. Shi, D. Rajan, D. Rigler, T. Fitzgerald, A.C. Lionel, B. Thiruvahindrapuram, J.R. Macdonald, R. Mills, A. Prasad, K. Noonan, S. Gribble, E. Prigmore, P.K. Donahoe, R.S. Smith, J.H. Park, M.E. Hurles, N.P. Carter, C. Lee, S.W. Scherer, L. Feuk, Comprehensive assessment of array-based platforms and calling algorithms for detection of copy number variants. Nat. Biotechnol. 29(6), 512–520 (2011)

    Article  PubMed  CAS  Google Scholar 

  13. J.R. González, B. Rodríguez-Santiago, A. Cáceres, R. Pique-Regi, N. Rothman, S.J. Chanock, L. Armengol, L.A. Pérez-Jurado, A fast and accurate method to detect allelic genomic imbalances underlying mosaic rearrangements using SNP array data. BMC Bioinforma. 12, 166 (2011)

    Article  Google Scholar 

  14. S.A. Scott, N. Cohen, T. Brandt, G. Toruner, R.J. Desnick, L. Edelmann, Detection of low-level mosaicism and placental mosaicism by oligonucleotide array comparative genomic hybridization. Genet Med. 12(2), 85–92 (2010)

    Article  PubMed  CAS  Google Scholar 

  15. R. Valli, C. Marletta, B. Pressato, G. Montalbano, F. Lo Curto, F. Pasquali, E. Maserati, Comparative genomic hybridization on microarray (a-CGH) in constitutional and acquired mosaicism may detect as low as 8% abnormal cells. Mol. Cytogenet. 4, 13 (2011)

    Article  PubMed  Google Scholar 

  16. K. Szuhai, I. Jennes, D. de Jong, J.V. Bovée, M. Wiweger, W. Wuyts, P.C. Hogendoorn, Tiling resolution array-CGH shows that somatic mosaic deletion of the EXT gene is causative in EXT gene mutation negative multiple osteochondromas patients. Hum. Mutat. 32(2), E2036–E2049 (2011). doi:10.1002/humu.21423

    Article  PubMed  CAS  Google Scholar 

  17. E.S. Venkatraman, A.B. Olshen, A faster circular binary segmentation algorithm for the analysis of array CGH data. Bioinformatics 23(6), 657–663 (2007)

    Article  PubMed  CAS  Google Scholar 

  18. O. Krijgsman, D. Israeli, J.C. Haan, H.F. van Essen, S.J. Smeets, P.P. Eijk, M. Steenbergen RD, K. Kok, S. Tejpar, G.A. Meijer, B. Ylstra, CGH arrays compared for DNA isolated from formalin-fixed, paraffin-embedded material. Gene. Chromosome. Canc. 51(4), 344–352 (2012). doi:10.1002/gcc.21920

    Article  CAS  Google Scholar 

  19. T.E. Buffart, D. Israeli, M. Tijssen, S.J. Vosse, A. Mrsić, G.A. Meijer, B. Ylstra, Across array comparative genomic hybridization: a strategy to reduce reference channel hybridizations. Gene. Chromosome. Canc. 47(11), 994–1004 (2008)

    Article  CAS  Google Scholar 

  20. K. Jong, E. Marchiori, A. van der Vaart, S.F. Chin, B. Carvalho, M. Tijssen, P.P. Eijk, P. van den Ijssel, H. Grabsch, P. Quirke, J.J. Oudejans, G.A. Meijer, C. Caldas, B. Ylstra, Cross-platform array comparative genomic hybridization meta-analysis separates hematopoietic and mesenchymal from epithelial tumors. Oncogene 26(10), 1499–1506 (2007)

    Article  PubMed  CAS  Google Scholar 

  21. D.J. Venter, S.J. Ramus, F.M. Hammet, M. de Silva, A.M. Hutchins, V. Petrovic, G. Price, J.E. Armes, Complex CGH alterations on chromosome arm 8p at candidate tumor suppressor gene loci in breast cancer cell lines. Canc. Genet. Cytogenet. 160(2), 134–140 (2005)

    Article  CAS  Google Scholar 

  22. D. Pinkel, R. Segraves, D. Sudar, S. Clark, I. Poole, D. Kowbel, C. Collins, W.L. Kuo, C. Chen, Y. Zhai, S.H. Dairkee, B.M. Ljung, J.W. Gray, D.G. Albertson, High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat. Genet. 20(2), 207–211 (1998)

    Article  PubMed  CAS  Google Scholar 

  23. M.A. van de Wiel, K.I. Kim, S.J. Vosse, W.N. van Wieringen, S.M. Wilting, B. Ylstra, CGHcall: calling aberrations for array CGH tumor profiles. Bioinformatics 23(7), 892–894 (2007)

    Article  PubMed  Google Scholar 

  24. B.P. Coe, B. Ylstra, B. Carvalho, G.A. Meijer, C. Macaulay, W.L. Lam, Resolving the resolution of array CGH. Genomics 89(5), 647–653 (2007)

    Article  PubMed  CAS  Google Scholar 

  25. N.P. Carter, Methods and strategies for analyzing copy number variation using DNA microarrays. Nat. Genet. 39(7 Suppl), S16–S21 (2007)

    Article  PubMed  CAS  Google Scholar 

  26. R. Beroukhim, C.H. Mermel, D. Porter, G. Wei, S. Raychaudhuri, J. Donovan, J. Barretina, J.S. Boehm, J. Dobson, M. Urashima, K.T. Mc Henry, R.M. Pinchback, A.H. Ligon, Y.J. Cho, L. Haery, H. Greulich, M. Reich, W. Winckler, M.S. Lawrence, B.A. Weir, K.E. Tanaka, D.Y. Chiang, A.J. Bass, A. Loo, C. Hoffman, J. Prensner, T. Liefeld, Q. Gao, D. Yecies, S. Signoretti, E. Maher, F.J. Kaye, H. Sasaki, J.E. Tepper, J.A. Fletcher, J. Tabernero, J. Baselga, M.S. Tsao, F. Demichelis, M.A. Rubin, P.A. Janne, M.J. Daly, C. Nucera, R.L. Levine, B.L. Ebert, S. Gabriel, A.K. Rustgi, C.R. Antonescu, M. Ladanyi, A. Letai, L.A. Garraway, M. Loda, D.G. Beer, L.D. True, A. Okamoto, S.L. Pomeroy, S. Singer, T.R. Golub, E.S. Lander, G. Getz, W.R. Sellers, M. Meyerson, The landscape of somatic copy-number alteration across human cancers. Nature 463(7283), 899–905 (2010)

    Article  PubMed  CAS  Google Scholar 

  27. R.J. Leary, J.C. Lin, J. Cummins, S. Boca, L.D. Wood, D.W. Parsons, S. Jones, T. Sjöblom, B.H. Park, R. Parsons, J. Willis, D. Dawson, J.K. Willson, T. Nikolskaya, Y. Nikolsky, L. Kopelovich, N. Papadopoulos, L.A. Pennacchio, T.L. Wang, S.D. Markowitz, G. Parmigiani, K.W. Kinzler, B. Vogelstein, V.E. Velculescu, Integrated analysis of homozygous deletions, focal amplifications, and sequence alterations in breast and colorectal cancers. Proc. Natl. Acad. Sci. U. S. A. 105(42), 16224–16229 (2008)

    Article  PubMed  CAS  Google Scholar 

  28. R. Redon, S. Ishikawa, K.R. Fitch, L. Feuk, G.H. Perry, T.D. Andrews, H. Fiegler, M.H. Shapero, A.R. Carson, W. Chen, E.K. Cho, S. Dallaire, J.L. Freeman, J.R. González, M. Gratacòs, J. Huang, D. Kalaitzopoulos, D. Komura, J.R. MacDonald, C.R. Marshall, R. Mei, L. Montgomery, K. Nishimura, K. Okamura, F. Shen, M.J. Somerville, J. Tchinda, A. Valsesia, C. Woodwark, F. Yang, J. Zhang, T. Zerjal, J. Zhang, L. Armengol, D.F. Conrad, X. Estivill, C. Tyler-Smith, N.P. Carter, H. Aburatani, C. Lee, K.W. Jones, S.W. Scherer, M.E. Hurles, Global variation in copy number in the human genome. Nature 444(7118), 444–454 (2006)

    Article  PubMed  CAS  Google Scholar 

  29. S.J. Smeets, U. Harjes, W.N. van Wieringen, D. Sie, R.H. Brakenhoff, G.A. Meijer, B. Ylstra, To DNA or not to DNA? That is the question, when it comes to molecular subtyping for the clinic!Clin. Cancer Res. 17(15), 4959–4964 (2011)

    Article  CAS  Google Scholar 

  30. T.E. Buffart, B. Carvalho, T. Mons, R.M. Reis, C. Moutinho, P. Silva, N.C. van Grieken, M. Vieth, M. Stolte, C.J. van de Velde, E. Schrock, A. Matthaei, B. Ylstra, F. Carneiro, G.A. Meijer, DNA copy number profiles of gastric cancer precursor lesions. BMC Genomics. 8, 345 (2007)

    Article  PubMed  Google Scholar 

  31. X.Y. Goh, J.R. Rees, A.L. Paterson, S.F. Chin, J.C. Marioni, V. Save, M. O'Donovan, P.P. Eijk, D. Alderson, B. Ylstra, C. Caldas, R.C. Fitzgerald, Integrative analysis of array-comparative genomic hybridisation and matched gene expression profiling data reveals novel genes with prognostic significance in oesophageal adenocarcinoma. Gut 60(10), 1317–1326 (2011)

    Article  PubMed  CAS  Google Scholar 

  32. H.F. van Essen, B. Ylstra, High-resolution copy number profiling by array CGH using DNA isolated from formalin-fixed, paraffin-embedded tissues. Meth. Mol. Biol. 838, 329–341 (2012)

    Article  Google Scholar 

  33. O. De Wever, M. Mareel, Role of tissue stroma in cancer cell invasion. J. Pathol. 200(4), 429–447 (2003)

    Article  PubMed  Google Scholar 

  34. N.P. West, M. Dattani, P. McShane, G. Hutchins, J. Grabsch, W. Mueller, D. Treanor, P. Quirke, H. Grabsch, The proportion of tumour cells is an independent predictor for survival in colorectal cancer patients. Br. J. Cancer 102(10), 1519–1523 (2010)

    Article  PubMed  CAS  Google Scholar 

  35. W.E. Mesker, J.M. Junggeburt, K. Szuhai, P. de Heer, H. Morreau, H.J. Tanke, R.A. Tollenaar, The carcinoma-stromal ratio of colon carcinoma is an independent factor for survival compared to lymph node status and tumor stage. Cell. Oncol. 29(5), 387–398 (2007)

    PubMed  Google Scholar 

  36. K. Tanaka, D. Yamamoto, M. Yamada, H. Okugawa, Influence of cellularity in human breast carcinoma. Breast 13(4), 334–340 (2004)

    Article  PubMed  Google Scholar 

  37. Y. Wu, H. Grabsch, T. Ivanova, I.B. Tan, J. Murray, C. H. Ooi, A. I. Wright, N. P. West, G. G. Hutchins, J. Wu, M. Lee, J. Lee, J. H. Koo, K. G. Yeoh, N. van Grieken, B. Ylstra, S. Y. Rha, J. A. Ajani, J.H. Cheong, S.H. Noh, K.H. Lim, A. Boussioutas, J.S. Lee, P. Tan. Comprehensive genomic meta-analysis identifies intra-tumoural stroma as a predictor of survival in patients with gastric cancer. Gut. (2012 Jun 26). [Epub ahead of print]

  38. S.F. Chin, A.E. Teschendorff, J.C. Marioni, Y. Wang, N.L. Barbosa-Morais, N.P. Thorne, J.L. Costa, S.E. Pinder, M.A. van de Wiel, A.R. Green, I.O. Ellis, P.L. Porter, S. Tavaré, J.D. Brenton, B. Ylstra, C. Caldas, High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer. Genome Biol. 8(10), R215 (2007)

    Article  PubMed  Google Scholar 

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Acknowledgements

This study was supported by the VUmc Institute for Cancer and Immunology (VUmc CCA/V-ICI) and performed within the framework of CTMM, the Center for Translational Molecular Medicine, DeCoDe project (grant 03O-101). We would like to thank Els Voorhoeve from the VU university medical center for collecting the samples.

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Correspondence to Bauke Ylstra.

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Supplementary_Figure 1

Chromosome 5 profile of BT474. aCGH profiles of a gain at the p-arm of chromosome 5 in BT474 with 100 %, 30 % and 20 % tumor DNA. (JPEG 95 kb)

High resolution image (TIFF 273 kb)

Supplementary_Figure 2

Dilution range of BT474 DNA on the NimbleGen platform. Profiles of all dilutions of BT474 DNA were performed on the NimbleGen platform. (PNG 203 kb)

Supplementary_Figure 3

aCGH profiles for CNVR3771/2 on chromosome 8 in a patient with ID. Panel A shows an overview of chromosome 8 in the undiluted sample. Panels BD show the detection of CNVR3771/2 (DNA loss) in dilutions to 35 %, 30 % and 25 % patient DNA. CNVR3771/2 (21 probes, ~1 Mb) could be detected with dilutions down to 35 % and 30 %, but not with 25 % patient DNA. The genomic locations of both CNVs are indicated in B. The X-axis represents the genomic locations (in Mb), and the Y-axis represents the log2 ratios for each probe. Grey lines represent the CBS segments [17]. (JPEG 94 kb)

High resolution image (TIFF 253 kb)

Supplementary_Figure 4

HER2/neu amplification in BT474. aCGH profiles of an amplification at 17q12 (30 probes, ~0.3 Mb), which includes HER2/neu. Hybrizations were performed with 100 %, 20 % and 10 % tumor DNA. The X-axis represents the chromosomal locations, and the Y-axis the log2 ratios. Grey lines represent the CBS segments [17]. (JPEG 120 kb)

High resolution image (TIFF 329 kb)

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Krijgsman, O., Israeli, D., van Essen, H.F. et al. Detection limits of DNA copy number alterations in heterogeneous cell populations. Cell Oncol. 36, 27–36 (2013). https://doi.org/10.1007/s13402-012-0108-2

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