Genomics & Informatics

Korea Genome Organization (한국유전체학회)
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Identification of Gene Expression Signatures in Korean Acute Leukemia Patients

  • Lee kyung-Hun (Department of Internal Medicine, Seoul National University, College of Medicine) ;
  • Park Se-Won (Department of Internal Medicine, Seoul National University, College of Medicine) ;
  • Kim In-Ho (Department of Internal Medicine, Seoul National University, College of Medicine) ;
  • Yoon Sung-Soo (Department of Internal Medicine, Seoul National University, College of Medicine) ;
  • Park Seon-Yang (Department of Internal Medicine, Seoul National University, College of Medicine) ;
  • Kim Byoung-Kook (Department of Internal Medicine, Seoul National University, College of Medicine)
  • Published : 2006.09.01
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Abstract

In acute leukemia patients, several successful methods of expression profiling have been used for various purposes, i.e., to identify new disease class, to select a therapeutic target, or to predict chemo-sensitivity and clinical outcome. In the present study, we tested the peripheral blood of 47 acute leukemia patients in an attempt to identify differentially expressed genes in AML and ALL using a Korean-made 10K oligo-nucleotide microarray. Methods: Total RNA was prepared from peripheral blood and amplified for microarray experimentation. SAM (significant analysis of microarray) and PAM (prediction analysis of microarray) were used to select significant genes. The selected genes were tested for in a test group, independently of the training group. Results: We identified 345 differentially expressed genes that differentiated AML and ALL patients (FWER<0.05). Genes were selected using the training group (n=35) and tested for in the test group (n=12). Both training group and test group discriminated AML and ALL patients accurately. Genes that showed relatively high expression in AML patients were deoxynucleotidyl transferase, pre-B lymphocyte gene 3, B-cell linker, CD9 antigen, lymphoid enhancer-binding factor 1, CD79B antigen, and early B-cell factor. Genes highly expressed in ALL patients were annexin A 1, amyloid beta (A4) precursor protein, amyloid beta (A4) precursor-like protein 2, cathepsin C, lysozyme (renal amyloidosis), myeloperoxidase, and hematopoietic prostaglandin D2 synthase. Conclusion: This study provided genome wide molecular signatures of Korean acute leukemia patients, which clearly identify AML and ALL. Given with other reported signatures, these molecular signatures provide a means of achieving a molecular diagnosis in Korean acute leukemia patents.

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References

  1. Baldus, C.D., Liyanarachchi, S., Mrozek, K., Auer, H., Tanner, S.M., Guimond, M., Ruppert, A.S., Mohamed, N., Davuluri, R.V., Caligiuri, M.A., Bloomfield, C.D., and de la Chapelle, A. (2004). Acute myeloid leukemia with complex karyotypes and abnormal chromosome 21: Amplification discloses overexpression of APP, ETS2, and ERG genes. Proc. Natl. Acad. Sci. USA 101, 3915-3920
  2. Bennett, J.M., Catovsky, D., Daniel, M.T., Flandrin, G., Galton, D.A., Gralnick, H.R., and Sultan, C. (1985). Proposed revised criteria for the classification of acute myeloid leukemia: a report of the French-American- British Cooperative Group. Ann. Intern. Med. 103, 620-625 https://doi.org/10.7326/0003-4819-103-4-620
  3. Bennett, J.M., Catovsky, D., Daniel, M.T., Flandrin, G., Galton, D.A., Gralnick, H.R., and Sultan, C. (1976). Proposals for the classification of the acute leukemias: French-American-British (FAB) Co-operative Group. Br J. Haematol. 33, 451-458 https://doi.org/10.1111/j.1365-2141.1976.tb03563.x
  4. Bullinger, L., Dohner, K., Bair, E., Frohling, S., Schlenk, R.F., Tibshirani, R, Dohner, H., and Pollack, J.R. (2004). Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia. N. Engl. J. Med. 350, 1605-1616 https://doi.org/10.1056/NEJMoa031046
  5. Debernardi, S., Lillington, D.M., Chaplin, T., Tomlinson, S., Amess, J., Rohatiner, A., Lister, T.A., and Young, B.D. (2003). Genome-wide analysis of acute myeloid leukemia with normal karyotype reveals a unique pattern of homeobox gene expression distinct from those with translocation-mediated fusion events. Genes chrormsomes Cancer 37, 149-158 https://doi.org/10.1002/gcc.10198
  6. Ebert, B.L. and Golub, T.R. (2004). Genomic approaches to hematologic malignancies. Blood 104, 923-932 https://doi.org/10.1182/blood-2004-01-0274
  7. Eisen, M.B., Spellman, P.T., Brown, P.O., and Botstein, D. (1998). Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14863-14868
  8. Falini, B., Tiacci, E., Liso, A., Basso, K., Sabattini, E., Pacini, R., Foa, R., Pulsoni, A., Dalla Favera, R., and Pileri, S. (2004). Simple diagnostic assay for hairy cell leukaemia by immunocytochemical detection of annexin A1 (ANXA1). Lancet. 363, 1869-1870 https://doi.org/10.1016/S0140-6736(04)16356-3
  9. Golub, T.R., Sionim, D.K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J.P., Coller, H., Loh, M.L., Downing, J.R., Caligiuri, M.A., Bloomfield, C.D., and Lander, E.S. (1999). Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531-537 https://doi.org/10.1126/science.286.5439.531
  10. Grimwade, D. (2001). The clinical significance of cytogenetic abnormalities in acute myeloid leukaemia. Best Parct. Res. Clin. Haematol. 14, 497-529 https://doi.org/10.1053/beha.2001.0152
  11. Jaffe, E.S., Harris, N.L., Stein, H., and Vardiman, J.W. (2001). World health organiztion classification of tumours: Pathology and genetics of tumours of haematopoietic and lymphoid tissues (Lyon, France: IARC Press)
  12. Kelly, L.M. and Gilliland, D.G. (2002). Genetics of myeloid leukemias. Annu. Rev. Genomics Hum. Genet. 3, 179-198 https://doi.org/10.1146/annurev.genom.3.032802.115046
  13. Kothapalli, R., Bailey, R.D., Kusmartseva, I., Mane, S., Epling-Burnette, P.K., and Loughran, T.P. Jr. (2003). Constitutive expression of cytotoxic proteases and down-regulation of protease inhibitors in LGL leukemia. Int. J. Oncol. 22, 33-39
  14. Margalit, O., Somech, R., Amariglio, N., and Rechavi, G. (2005). Microarray-based gene expression profiling of hematologic malignancies: basic concepts and clinical applications. Blood Rev. 19, 223-234 https://doi.org/10.1016/j.blre.2004.11.003
  15. Schoch, C., Kohlmann, A., Schnittger, S., Brors, B., Dugas, M., Mergenthaler, S., Kern, W., Hiddemann, W., Eils, R., and Haferlach, T. (2002). Acute myeloid leukemias with reciprocal rearrangements can be distinguished by specific gene expression profiles. Proc. Natl. Acad. Sci. USA 99, 10008-10013
  16. Valk P.J., Verhaak, R.G., Beijen, M.A., Erpelinck, C.A., Barjesteh van Waalwijk van Doorn-Khosrovani, S., Boer, J.M., Beverloo, H.B., Moorhouse, M.J., van der Spek, P.J., Lowenberg, B., and Delwel, R. (2004). Prognostically useful gene-expression profiles in acute myeloid leukemia. N. Engl. J. Med. 350, 1617-1628 https://doi.org/10.1056/NEJMoa040465