Advertisement

Identification of Tumor Antigens Using Subtraction and Microarrays

  • Jiangchun Xu
Chapter
Part of the Cancer Drug Discovery and Development book series (CDD&D)

Abstract

Recent advances in genomic discovery approaches have led to the identification of a new generation of tumor antigens. In this chapter, we discuss the application of nucleic acid subtraction methods combined with cDNA microarrays to identify potential tumor antigen candidates. Subtraction techniques form an effective means of enriching for tissue- and tumor-specific genes whereas microarray technology provides us with an efficient high-throughput screening approach that can simultaneously determine the gene expression of thousands of genes in a single experiment. The combination of these two powerful new discovery tools allows a systematic comparison of the cancer genome with the normal tissue genome to identify differentially expressed genes. This process has been optimized for rapid, thorough, and effective gene discovery and is not dependent on the availability of immunological reagents such as antibody and T cells from cancer patients. Genes identified via this integrated approach have the advantage of being tumoror tissue-specific and broadly expressed in cancers. Numerous tissue- and tumor-specific genes have been identified in prostate, breast, lung, and colon cancers using these approaches. Immunological validation strategies have been employed to determine the immunogenicity of these antigens and to identify naturally processed epitopes that can be used as immunogens or reagents for monitoring antigen-specific immune responses in subsequent vaccine strategies.

Keywords

Tumor Antigen Suppression Subtractive Hybridization Normal Pancreas Lung Squamous Cell Carcinoma Subtraction Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Coulie PG, Brichard V, Van Pel A, Wolfel T, Schneider J, Traversari C, et al. A new gene coding for a differentiation antigen recognized by autologous cytolytic T lymphocytes on HLA-A2 melanomas. J Exp Med 1994; 180:35–42.PubMedCrossRefGoogle Scholar
  2. 2.
    Kawakami Y, Eliyahu S, Delgado CH, Robbins PF, Sakaguchi K, Appella E, et al. Identification of a human melanoma antigen recognized by tumor-infiltrating lymphocytes associated with in vivo tumor rejection. Proc Natl Acad Sci USA 1994; 91:6458–6462.PubMedCrossRefGoogle Scholar
  3. 3.
    Kawakami Y, Eliyahu S, Delgado CH, Robbins PF, Rivoltini L, Topalian SL, et al. Cloning of the gene coding for a shared human melanoma antigen recognized by autologous T cells infiltrating into tumor. Proc Nat! Acad Sci USA 1994; 91:3515–3519.CrossRefGoogle Scholar
  4. 4.
    Robbins PF, El Gamil M, Kawakami Y, Stevens E, Yannelli JR, Rosenberg SA. Recognition of tyrosinase by tumor-infiltrating lymphocytes from a patient responding to immunotherapy. Cancer Res 1994; 54:3124–3126PubMedGoogle Scholar
  5. 5.
    Rosenberg SA, White DE. Vitiligo in patients with melanoma: normal tissue antigens can be targets for cancer immunotherapy. J Immunother Emphasis Tumor Immunol 1996; 19:81–84.PubMedCrossRefGoogle Scholar
  6. 6.
    Tureci O, Sahin U, Zwick C, Koslowski M, Seitz G, Pfreundschuh M. Identification of a meiosis-specific protein as a member of the class of cancer/testis antigens. Proc Natl Acad Sci USA 1998; 95:5211–5216.PubMedCrossRefGoogle Scholar
  7. 7.
    van der Bruggen P, Traversari C, Chomez P, Lurquin C, De Plaen E, Van den Eynde B, et al. A gene encoding an antigen recognized by cytolytic T lymphocytes on a human melanoma. Science 1991; 254:1643–1647.PubMedCrossRefGoogle Scholar
  8. 8.
    Cox AL, Skipper J, Chen Y, Henderson RA, Darrow TL, Shabanowitz J, et al. Identification of a peptide recognized by five melanoma-specific human cytotoxic T cell lines. Science 1994; 264:716–719.PubMedCrossRefGoogle Scholar
  9. 9.
    Pinkel D, Straume T, Gray JW. Cytogenetic analysis using quantitative, high-sensitivity, fluorescence hybridization. Proc Natl Acad Sci USA 1986: 83:2934–2938.PubMedCrossRefGoogle Scholar
  10. 10.
    Kallioniemi A, Kallioniemi OP, Sudar D, Rutovitz D, Gray JW, Waldman F, et al. Comparative genomic hybridization for molecular cytogenetic analysis of solid tumors. Science 1992; 258:818–821.PubMedCrossRefGoogle Scholar
  11. 11.
    Lisitsyn N, Lisitsyn N, Wigler M. Cloning the differences between two complex genomes. Science 1993; 259:946–951.PubMedCrossRefGoogle Scholar
  12. 12.
    Hatada I, Hayashizaki Y, Hirotsune S, Komatsubara H, Mukai T. A genomic scanning method for higher organisms using restriction sites as landmarks. Proc Natl Acad Sci USA 1991: 88:9523–9527.PubMedCrossRefGoogle Scholar
  13. 13.
    Canzian F, Salovaara R, Hemminki A, Kristo P, Chadwick RB, Aaltonen LA, et al. Semiautomated assessment of loss of heterozygosity and replication error in tumors. Cancer Res 1996; 56:3331–3337.PubMedGoogle Scholar
  14. 14.
    Pennisi E. A catalog of cancer genes at the click of a mouse [news]. Science 1997; 276:1023–1024.PubMedCrossRefGoogle Scholar
  15. 15.
    Vasmatzis G, Essand M, Brinkmann U, Lee B, Pastan I. Discovery of three genes specifically expressed in human prostate by expressed sequence tag database analysis. Proc Natl Acad Sci USA 1998; 95: 300–304.PubMedCrossRefGoogle Scholar
  16. 16.
    Velculescu VE, Zhang L, Vogelstein B, Kinzler KW. Serial analysis of gene expression [see comments]. Science 1995; 270:484–487.PubMedCrossRefGoogle Scholar
  17. 17.
    Zhang L, Zhou W, Velculescu VE, Kern SE, Hruban RH, Hamilton SR, et al. Gene expression profiles in normal and cancer cells. Science 1997; 276:1268–1272.PubMedCrossRefGoogle Scholar
  18. 18.
    Liang P, Pardee AB. Differential display of eukaryotic messenger RNA by means of the polymerase chain reaction [see comments]. Science 1992; 257:967–971.PubMedCrossRefGoogle Scholar
  19. 19.
    Hara T, Harada N, Mitsui H, Miura T, Ishizaka T, Miyajima A. Characterization of cell phenotype by a novel cDNA library subtraction system: expression of CD8 alpha in a mast cell-derived interleukin4-dependent cell line. Blood 1994; 84:189–199.PubMedGoogle Scholar
  20. 20.
    Diatchenko L, Lau YF, Campbell AP, Chenchik A, Moqadam F, Huang B, et al. Suppression subtractive hybridization: a method for generating differentially regulated or tissue-specific cDNA probes and libraries. Proc Natl Acad Sci USA 1996; 93:6025–6030PubMedCrossRefGoogle Scholar
  21. 21.
    Schena M, Shalon D, Davis RW, Brown PO. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 1995; 270:467–470.PubMedCrossRefGoogle Scholar
  22. 22.
    Zeng J, Gorski RA, Hamer D. Differential cDNA cloning by enzymatic degrading subtraction (EDS). Nucleic Acids Res 1994; 22:4381–4385.PubMedCrossRefGoogle Scholar
  23. 23.
    Lopez-Fernandez LA, del Mazo J. Construction of subtractive cDNA libraries from limited amounts of mRNA and multiple cycles of subtraction. Biotechniques 1993; 15:654–659.PubMedGoogle Scholar
  24. 24.
    Jiang Y, Harlocker SL, Molesh DA, Dillon DC, Stolk JA, Houghton RL, et al. Discovery of differentially expressed genes in human breast cancer using subtracted cDNA libraries and cDNA microarrays. Oncogene 2002; 21:2270–2282.PubMedCrossRefGoogle Scholar
  25. 25.
    Xu J, Stolk JA, Zhang X, Silva SJ, Houghton RL, Matsumura M, et al. Identification of differentially expressed genes in human prostate cancer using subtraction and microarray. Cancer Res 2000; 60:1677–1682.PubMedGoogle Scholar
  26. 26.
    Xu J, Kalos M, Stolk JA, Zasloff EJ, Zhang X, Houghton RL, et al. Identification and characterization of prostein, a novel prostate-specific protein. Cancer Res 2001; 61:1563–1568.PubMedGoogle Scholar
  27. 27.
    Fodor SP, Read JL, Pirrung MC, Stryer L, Lu AT, Solas D. Light-directed, spatially addressable parallel chemical synthesis. Science 1991; 251:767–773.PubMedCrossRefGoogle Scholar
  28. 28.
    Hughes TR, Mao M, Jones AR, Burchard J, Marton MJ, Shannon KW, et al. Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nat Biotechnol 2001; 19:342–347.PubMedCrossRefGoogle Scholar
  29. 29.
    Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 1998; 95:14863–14868.PubMedCrossRefGoogle Scholar
  30. 30.
    Tamayo P, Slonim D, Mesirov J, Zhu Q, Kitareewan S, Dmitrovsky E, et al. Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. Proc Natl Acad Sci USA 1999; 96:2907–2912.PubMedCrossRefGoogle Scholar
  31. 31.
    Khan J, Simon R, Bittner M, Chen Y, Leighton SB, Pohida T, et al. Gene expression profiling of alveolar rhabdomyosarcoma with cDNA microarrays. Cancer Res 1998; 58:5009–5013.PubMedGoogle Scholar
  32. 32.
    Wang T, Fan L, Watanabe Y, McNeill P, Fanger GR, Persing DH, et al. L552S, an alternatively spliced isoform of XAGE-1, is over-expressed in lung adenocarcinoma. Oncogene 2001; 20:7699–7709.PubMedCrossRefGoogle Scholar
  33. 33.
    Wang T, Hopkins DA, Fan L, Fanger GR, Houghton R, Vedvick TS, et al. A p53 homologue and a novel serine proteinase inhibitor are over-expressed in lung squamous cell carcinoma. Lung Cancer 2001; 34:363–374.PubMedCrossRefGoogle Scholar
  34. 34.
    Hural JA, Friedman RS, McNabb A, Steen SS, Henderson RA, Kalos M. Identification of naturally processed CD4 T cell epitopes from the prostate-specific antigen kallikrein 4 using peptide-based in vitro stimulation. J Immunol 2002; 169:557–565.PubMedGoogle Scholar

Copyright information

© Humana Press Inc. 2004

Authors and Affiliations

  • Jiangchun Xu

There are no affiliations available

Personalised recommendations