Cancer Gene Profiling pp 61-87

Part of the Methods in Molecular Biology book series (MIMB, volume 576)

A Decade of Cancer Gene Profiling: From Molecular Portraits to Molecular Function

  • Henri Sara
  • Olli Kallioniemi
  • Matthias Nees
Protocol

Summary

Cancer gene profiling has greatly profited from the progress in high-throughput technologies including microarray-, sequencing-, and bioinformatics-based methods. The flood of data generated during the last decade has provoked a panel of “-omics” fields that significantly changed our understanding of malignant diseases. However, while the terms “-omics” and “-ome” in principle refer to the completeness of a genetic approach, we are in fact far from a complete understanding of cancer progression. We may understand gene expression patterns better and successfully use gene signatures for outcome prediction and prognosis, but truly promising molecular targets still have to find their way into novel therapeutic concepts. In this chapter, we will show how more comprehensive strategies, integrating multiple layers of genetic information, might in the future provide a more profound functional understanding of cancer.

Key words

Microarray Expression CGH Comparative genomic hybridization Sequencing 

References

  1. 1.
    Bennett, S.T. et al. (2005) Toward the 1,000 dollars human genome. Pharmacogenomics 6, 373–382CrossRefPubMedGoogle Scholar
  2. 2.
    Church, G.M. (2006) Genomes for all. Sci. Am. 294, 46–54CrossRefPubMedGoogle Scholar
  3. 3.
    Collins, F.S. and Barker, A.D. (2007) Mapping the cancer genome. Pinpointing the genes involved in cancer will help chart a new course across the complex landscape of human malignancies. Sci. Am. 296, 50–57CrossRefPubMedGoogle Scholar
  4. 4.
    Schena, M. et al. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270, 467–470CrossRefPubMedGoogle Scholar
  5. 5.
    Shalon, D. et al. (1996) A DNA microarray system for analyzing complex DNA samples using two-color fluorescent probe hybridization. Genome Res. 6, 639–645CrossRefPubMedGoogle Scholar
  6. 6.
    Schena, M. et al. (1996) Parallel human genome analysis: microarray-based expression monitoring of 1000 genes. Proc. Natl. Acad. Sci. USA 93, 10614–10619CrossRefPubMedGoogle Scholar
  7. 7.
    DeRisi, J. et al. (1996) Use of a cDNA microarray to analyse gene expression patterns in human cancer. Nat. Genet. 14, 457–460CrossRefPubMedGoogle Scholar
  8. 8.
    Lipshutz, R.J. et al. (1995) Using oligonucleotide probe arrays to access genetic diversity. BioTechniques 19, 442–447PubMedGoogle Scholar
  9. 9.
    Brazma, A. et al. (2001) Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat. Genet. 29, 365–371CrossRefPubMedGoogle Scholar
  10. 10.
    Perou, C.M. et al. (1999) Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc. Natl. Acad. Sci. USA 96, 9212–9217CrossRefPubMedGoogle Scholar
  11. 11.
    Sorlie, T. et al. (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. USA 98, 10869–10874CrossRefPubMedGoogle Scholar
  12. 12.
    van ‘t Veer, L.J. et al. (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415, 530–536CrossRefPubMedGoogle Scholar
  13. 13.
    van de Vijver, M.J. et al. (2002) A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009CrossRefPubMedGoogle Scholar
  14. 14.
    Kallioniemi, A. et al. (1992) Comparative genomic hybridization for molecular cytogenetic analysis of solid tumors. Science 258, 818–821CrossRefPubMedGoogle Scholar
  15. 15.
    Pinkel, D. et al. (1998) High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat. Genet. 20, 207–211CrossRefPubMedGoogle Scholar
  16. 16.
    Pollack, J.R. et al. (1999) Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat. Genet. 23, 41–46CrossRefPubMedGoogle Scholar
  17. 17.
    Bergamaschi, A. et al. (2006) Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer. Genes Chromosomes Cancer 45, 1033–1040CrossRefPubMedGoogle Scholar
  18. 18.
    Chin, K. et al. (2006) Genomic and transcriptional aberrations linked to breast cancer pathophysiologies. Cancer Cell. 10, 529–541CrossRefPubMedGoogle Scholar
  19. 19.
    Neve, R.M. et al. (2006) A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes. Cancer Cell 10, 515–527CrossRefPubMedGoogle Scholar
  20. 20.
    Fridlyand, J. et al. (2006) Breast tumor copy number aberration phenotypes and genomic instability. BMC Cancer 6, 96CrossRefGoogle Scholar
  21. 21.
    Weir, B.A. et al. (2007) Characterizing the cancer genome in lung adenocarcinoma. Nature 450(7171), 893–898CrossRefPubMedGoogle Scholar
  22. 22.
    Garraway, L.A. et al. (2005) Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 436, 117–122CrossRefPubMedGoogle Scholar
  23. 23.
    Easton, D.F. et al. (2007) Genome-wide association study idntifies novel breast cancer susceptibility loci. Nature 447, 1087–1093CrossRefPubMedGoogle Scholar
  24. 24.
    Futreal, P.A. et al. (2004) A census of human cancer genes. Nat. Rev. Cancer 4, 177–183CrossRefPubMedGoogle Scholar
  25. 25.
    Tomlins, S.A. et al. (2005) Recurrent fusion of TMPRSS2 and ETS transcription factor genes in prostate cancer. Science 310, 644–648CrossRefPubMedGoogle Scholar
  26. 26.
    Tomlins, S.A. et al. (2007) Distinct classes of chromosomal rearrangements create oncogenic ETS gene fusions in prostate cancer. Nature 448, 595–599CrossRefPubMedGoogle Scholar
  27. 27.
    Lipshutz, R.J. (1993) Likelihood DNA sequenc­ing by hybridization. J. Biomol. Struct. Dyn. 11, 637–653PubMedGoogle Scholar
  28. 28.
    Margulies, M. et al. (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437, 376–380PubMedGoogle Scholar
  29. 29.
    Emrich, S.J. et al. (2007) Gene discovery and annotation using LCM-454 transcriptome sequencing. Genome Res. 17, 69–73CrossRefPubMedGoogle Scholar
  30. 30.
    Davies, H. et al. (2002) Mutations of the BRAF gene in human cancer. Nature 417, 949–954CrossRefPubMedGoogle Scholar
  31. 31.
    Bardelli, A. et al. (2003) Mutational analysis of the tyrosine kinome in colorectal cancers. Science 300, 949CrossRefPubMedGoogle Scholar
  32. 32.
    Wang, Z. et al. (2004) Mutational analysis of the tyrosine phosphatome in colorectal cancers. Science 304, 1164–1166CrossRefPubMedGoogle Scholar
  33. 33.
    Samuels, Y. et al. (2004) High frequency of mutations of the PIK3CA gene in human cancers. Science 304, 554CrossRefPubMedGoogle Scholar
  34. 34.
    Ikediobi, O.N. et al. (2006) Mutation analysis of 24 known cancer genes in the NCI-60 cell line set. Mol. Cancer Ther. 5, 2606–2612CrossRefPubMedGoogle Scholar
  35. 35.
    Stephens, P. et al. (2005) A screen of the complete protein kinase gene family identifies diverse patterns of somatic mutations in human breast cancer. Nat. Genet. 37, 590–592CrossRefPubMedGoogle Scholar
  36. 36.
    Futreal, P.A. et al. (2005) Somatic mutations in human cancer: insights from resequencing the protein kinase gene family. Cold Spring Harb. Symp. Quant. Biol. 70, 43–49CrossRefPubMedGoogle Scholar
  37. 37.
    Davies, H. et al. (2005) Somatic mutations of the protein kinase gene family in human lung cancer. Cancer Res. 65, 7591–7595PubMedGoogle Scholar
  38. 38.
    Greenman, C. et al. (2007) Patterns of somatic mutation in human cancer genomes. Nature 446, 153–158CrossRefPubMedGoogle Scholar
  39. 39.
    Thomas, R.K. et al. (2007) High-throughput oncogene mutation profiling in human cancer. Nat. Genet. 39, 347–351CrossRefPubMedGoogle Scholar
  40. 40.
    Wang, T.L. et al. (2002) Prevalence of somatic alterations in the colorectal cancer cell genome. Proc. Natl. Acad. Sci. USA 99, 3076–3080CrossRefPubMedGoogle Scholar
  41. 41.
    Sjoblom, T. et al. (2006) The consensus coding sequences of human breast and colo­rectal cancers. Science 314, 268–274CrossRefPubMedGoogle Scholar
  42. 42.
    Wood, L.D. et al. (2007) The genomic landscapes of human breast and colorectal cancers. Science 318(5853), 1108–1113CrossRefPubMedGoogle Scholar
  43. 43.
    Calin, G.A. and Croce, C.M. (2006) MicroRNA signatures in human cancers. Nat. Rev. Cancer 6, 857–866CrossRefPubMedGoogle Scholar
  44. 44.
    Stransky, N. et al. (2006) Regional copy number-independent deregulation of transcription in cancer. Nat. Genet. 38, 1386–1396CrossRefPubMedGoogle Scholar
  45. 45.
    Barski, A. et al. (2007) High-resolution profiling of histone methylations in the human genome. Cell 129, 823–837CrossRefPubMedGoogle Scholar
  46. 46.
    Taylor, K.H. et al. (2007) Ultradeep bisulfite sequencing analysis of DNA methy­lation patterns in multiple gene promoters by 454 sequencing. Cancer Res. 67, 8511–8518CrossRefPubMedGoogle Scholar
  47. 47.
    Tomlins, S.A. et al. (2007) Integrative molecular concept modeling of prostate cancer progression. Nat. Genet. 39, 41–51CrossRefPubMedGoogle Scholar
  48. 48.
    Boehm, J.S. et al. (2007) Integrative genomic approaches identify IKBKE as a breast cancer oncogene. Cell 129, 1065–1079CrossRefPubMedGoogle Scholar
  49. 49.
    Vogelstein, B. and Kinzler, K.W. (2004) Cancer genes and the pathways they control. Nat. Med. 10, 789–799CrossRefPubMedGoogle Scholar

Copyright information

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

Authors and Affiliations

  • Henri Sara
    • 1
  • Olli Kallioniemi
    • 1
  • Matthias Nees
    • 1
  1. 1.VTT Medical BiotechnologyTurkuFinland

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