Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review
  • Published:

An international database and integrated analysis tools for the study of cancer gene expression

Abstract

Researchers working collaboratively in Brazil and the United States have assembled an International Database of Cancer Gene Expression. Several strategies have been employed to generate gene expression data including expressed sequence tags (ESTs), serial analysis of gene expression (SAGE), and open reading-frame expressed sequence tags (ORESTES). The database contains six million gene tags that reflect the gene expression profiles in a wide variety of cancerous tissues and their normal counterparts. All sequences are deposited in the public databases, GenBank and SAGEmap. A suite of informatics tools was designed to facilitate in silico analysis of the gene expression datasets and are available through the NCI Cancer Genome Anatomy Project web site (http://cgap.nci.nih.gov).

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7

Similar content being viewed by others

References

  1. Garber ME et al . Diversity of gene expression in adenocarcinoma of the lung Proc Natl Acad Sci USA 2001 98: 13784–13789

    Article  CAS  Google Scholar 

  2. Perou CM et al . Molecular portraits of human breast tumours Nature 2000 406: 747–752

    Article  CAS  Google Scholar 

  3. Alizadeh AA et al . Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling Nature 2000 403: 503–511

    Article  CAS  Google Scholar 

  4. Bhattacharjee A et al . Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses Proc Natl Acad Sci USA 2001 98: 13790–13795

    Article  CAS  Google Scholar 

  5. Golub TR et al . Molecular classification of cancer: class discovery and class prediction by gene expression monitoring Science 1999 286: 531–537

    Article  CAS  Google Scholar 

  6. Shih LM et al . Top-down morphogenesis of colorectal tumors Proc Natl Acad Sci USA 2001 98: 2640–2645

    Article  CAS  Google Scholar 

  7. Polyak K, Riggins GJ . Gene discovery using the serial analysis of gene expression technique: implications for cancer research J Clin Oncol 2001 19: 2948–2958

    Article  CAS  Google Scholar 

  8. Riggins GJ . Using serial analysis of gene expression to identify tumor markers and antigens Disease Markers 2001 17: 41–48

    Article  CAS  Google Scholar 

  9. Khan J et al . Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks Nat Med 2001 7: 673–679

    Article  CAS  Google Scholar 

  10. Strausberg RL, Buetow KH, Emmert-Buck MR, Klausner RD . The cancer genome anatomy project: building an annotated gene index Trends Genet 2000 16: 103–106

    Article  CAS  Google Scholar 

  11. Strausberg RL, Dahl CA, Klausner RD . New opportunities for uncovering the molecular basis of cancer Nat Genet 1997 15: 415–416

    Article  CAS  Google Scholar 

  12. Strausberg RL . The Cancer Genome Anatomy Project: new resources for reading the molecular signatures of cancer J Pathol 2001 195: 31–40

    Article  CAS  Google Scholar 

  13. Strausberg RL, Greenhut SF, Grouse LH, Schaefer CF, Buetow KH . In silico analysis of cancer through the cancer genome anatomy project Trends Cell Biol 2001 11: S66–S71

    Article  CAS  Google Scholar 

  14. Buetow KH et al . High-throughput development and characterization of a genomewide collection of gene-based single nucleotidepolymorphism markers by chip-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry Proc Natl Acad Sci USA 2001 98: 581–584

    Article  CAS  Google Scholar 

  15. Buetow KH, Edmonson MN, Cassidy AB . Reliable identification of large numbers of candidate SNPs from public EST data Nat Genet 1999 21: 323–325

    Article  CAS  Google Scholar 

  16. Cheung VG et al . Integration of cytogenetic landmarks into the draft sequence of the human genome Nature 2001 409: 953–958

    Article  CAS  Google Scholar 

  17. Kirsch IR et al . A systematic, high-resolution linkage of the cytogenetic and physical maps of the human genome Nat Genet 2000 24: 339–340

    Article  CAS  Google Scholar 

  18. Mitelman F, Johansson B, Mertens F (eds) . Mitelman Database of Chromosome Aberrations in Cancer http://cgap.nci.nih.gov/Chromosomes/Mitelman 2002

  19. Dias-Neto E et al . Shotgun sequencing of the human transcriptome with ORF expressed sequence tags Proc Natl Acad Sci USA 2000 97: 3491–3496

    Article  Google Scholar 

  20. Camargo AA et al . The contribution of 700 000 ORF sequence tags to the definition of the human transcriptome Proc Natl Acad Sci USA 2001 98: 12103–12108

    Article  Google Scholar 

  21. de Souza SJ et al . Identification of human chromosome 22 transcribed sequences with ORF expressed sequence tags Proc Natl Acad Sci USA 2000 97: 12690–12693

    Article  CAS  Google Scholar 

  22. Adams MD et al . Sequence identification of 2375 human brain genes Nature 1992 355: 632–634

    Article  CAS  Google Scholar 

  23. Velculescu VE, Zhang L, Vogelstein B, Kinzler KW . Serial analysis of gene expression Science 1995 270: 484–487

    Article  CAS  Google Scholar 

  24. Lal A et al . A public database for gene expression in human cancers Cancer Res 1999 59: 5403–5407

    CAS  PubMed  Google Scholar 

  25. Lash AE et al . SAGEmap: a public gene expression resource Genome Res 2000 10: 1051–1060

    Article  CAS  Google Scholar 

  26. Strausberg RL, Feingold EA, Klausner RD, Collins FS . The mammalian gene collection Science 1999 286: 455–457

    Article  CAS  Google Scholar 

  27. Wheeler DL et al . Database resources of the National Center for Biotechnology Information Nucl Acids Res 2001 29: 11–16

    Article  CAS  Google Scholar 

  28. Emmert-Buck MR et al . Laser capture microdissection Science 1996 274: 998–1001

    Article  CAS  Google Scholar 

  29. Emmert-Buck MR et al . Molecular profiling of clinical tissue specimens: feasibility and applications Am J Pathol 2000 156: 1109–1115

    Article  CAS  Google Scholar 

  30. Nakamura TM et al . Telomerase catalytic subunit homologs from fission yeast and human Science 1997 277: 955–959

    Article  CAS  Google Scholar 

  31. Argani P et al . Discovery of new markers of cancer through serial analysis of gene expression: prostate stem cell antigen is overexpressed in pancreatic adenocarcinoma Cancer Res 2001 61: 4320–4324

    CAS  PubMed  Google Scholar 

  32. Scheurle D et al . Cancer gene discovery using digital differential display Cancer Res 2000 60: 4037–4043

    CAS  PubMed  Google Scholar 

  33. Luo J et al . Human prostate cancer and benign prostatic hyperplasia: molecular dissection by gene expression profiling Cancer Res 2001 61: 4683–4688

    CAS  PubMed  Google Scholar 

  34. Ryu B, Jones J, Hollingsworth MA, Hruban RH, Kern SE . Invasion-specific genes in malignancy: serial analysis of gene expression comparisons of primary and passaged cancers Cancer Res 2001 61: 1833–1838

    CAS  PubMed  Google Scholar 

  35. Porter DA et al . A SAGE (serial analysis of gene expression) view of breast tumor progression Cancer Res 2001 61: 5697–5702

    CAS  PubMed  Google Scholar 

  36. Loging WT et al . Identifying potential tumor markers and antigens by database mining and rapid expression screening Genome Res 2000 10: 1393–1402

    Article  CAS  Google Scholar 

  37. Hough CD, Cho KR, Zonderman AB, Schwartz DR, Morin PJ . Coordinately up-regulated genes in ovarian cancer Cancer Res 2001 61: 3869–3876

    CAS  PubMed  Google Scholar 

  38. Lal A et al . Transcriptional response to hypoxia in human tumors J Natl Cancer Inst 2001 93: 1337–1343

    Article  CAS  Google Scholar 

  39. St Croix B et al . Genes expressed in human tumor endothelium Science 2000 289: 1197–1202

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The Human Cancer Genome Project was supported by the Ludwig Institute for Cancer Research (LICR) and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP). The ORESTES sequences were generated by a virtual network of 33 laboratories from the State of São Paulo, Brazil.

The NCI Cancer Genome Anatomy Project results from the effort of a multidisciplinary team of scientists from academic and industrial laboratories. A list of the CGAP team members can be found at URL:http://cgap.nci.nih.gov/Info/teams

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R L Strausberg.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Strausberg, R., Camargo, A., Riggins, G. et al. An international database and integrated analysis tools for the study of cancer gene expression. Pharmacogenomics J 2, 156–164 (2002). https://doi.org/10.1038/sj.tpj.6500103

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/sj.tpj.6500103

Keywords

This article is cited by

Search

Quick links