Abstract
The practice of clinical medicine and the process of biomedical research have been transformed by the decoding of the human genome. The use of DNA microarrays to find gene expression patterns in disease and biological processes has already begun to have a significant impact on modern medicine. The study of hematological malignancies has particularly benefited from gene expression profiling, including discoveries about prognosis, mechanism and efficacious choice of therapeutic regimens. DNA microarrays have led to the discovery of better prognostic tools, including the use of Zap-70 in B-Cell Chronic Lymphocytic Leukemia (B-CLL) as an indicator of worse prognosis. Studies of Diffuse Large B-cell Lymphoma (DLBCL) have defined two molecular subgroups, with significantly different mortality rates and responses to conventional therapy. In Follicular Lymphoma (FL), the variable clinical course could be associated with molecular signatures reflecting a possible interaction between tumor cells and infiltrating immune cells. The molecular mechanisms of Mantle Cell Lymphoma (MCL) have also begun to be clarified, with a more detailed understanding of the roles of cell cycle and DNA damage pathways that are responsible for the varying degree of tumor cell proliferation and different clinical outcome in this lymphoma. While important discoveries have been made in leukemias, lymphomas and many other cancer subtypes using gene expression profiling, there are many questions left to study and the translation of these tools and their results into the clinic has just begun.
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References
In: Jaffe ES, HNL Stein H, Vardiman JW, eds. World health organization classification of tumours. Pathology and Genetics of Tumours of Haematopoietic and Lymphoid Tissues. Lyon: IARC Press, 2001.
Staudt LM. Gene expression profiling of lymphoid malignancies. Annu Rev Med 2002;53:303–318.
Alizadeh A, Eisen M, Davis RE et al. The lymphochip: A specialized cDNA microarray for the genomic-scale analysis of gene expression in normal and malignant lymphocytes. Cold Spring Harb Symp Quant Biol 1999;64:71–78.
Schena M, Shalon D, Davis RW et al. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 1995;270:467–470.
Staudt LM. Gene expression physiology and pathophysiology of the immune system. Trends Immunol 2001;22:35–40.
Eisen MB, Spellman PT, Brown PO et al. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 1998;95:14863–14868.
Rosenwald A, Alizadeh AA, Widhopf G et al. Relation of gene expression phenotype to immunoglobulin mutation genotype in B cell chronic lymphocytic leukemia. J Exp Med 2001;194:1639–1647.
Wright G, Tan B, Rosenwald A et al. A gene expression-based method to diagnose clinically distinct subgroups of diffuse large B cell lymphoma. Proc Natl Acad Sci USA 2003;100:9991–9996.
Braziel RM, Shipp MA, Feldman AL et al. Molecular diagnostics. Hematology (Am Soc Hematol Educ Program) 2003;279–293.
Alizadeh AA, Eisen MB, Davis RE et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 2000;403:503–511.
Rosenwald A, Wright G, Chan WC et al. The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N Engl J Med 2002;346:1937–1947.
Shaffer AL, Rosenwald A, Hurt EM et al. Signatures of the immune response. Immunity 2001;15:375–385.
Coiffier B. Diffuse large cell lymphoma. Curr Opin Oncol 2001;13:325–334.
Fisher RI, Gaynor ER, Dahlberg S et al. Comparison of a standard regimen (CHOP) with three intensive chemotherapy regimens for advanced nonHodgkin’s lymphoma. N Engl J Med 1993;328:1002–1006.
Coiffier B, Lepage E, Briere J et al. CHOP chemotherapy plus rituximab compared with CHOP alone in elderly patients with diffuse large-B-cell lymphoma. N Engl J Med 2002;346:235–242.
A predictive model for aggressive nonHodgkin’s lymphoma. The International NonHodgkin’s Lymphoma Prognostic Factors Project. N Engl J Med 1993;329:987–994.
Davis RE, Brown KD, Siebenlist U et al. Constitutive nuclear factor kappaB activity is required for survival of activated B cell-like diffuse large B cell lymphoma cells. J Exp Med 2001;194:1861–1874.
Karin M, Cao Y, Greten FR et al. NF-kappaB in cancer: From innocent bystander to major culprit. Nat Rev Cancer 2002;2:301–310.
Cheson BD. What is new in lymphoma? CA Cancer J Clin 2004;54:260–272.
Shipp MA, Ross KN, Tamayo P et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat Med 2002;8:68–74.
Smith PG, Wang F, Wilkinson KN et al. The phosphodiesterase PDE4B limits cAMP-associated PI3K/AKT-dependent apoptosis in diffuse large B-cell lymphoma. Blood 2005;105:308–316.
Monti S, Savage KJ, Kutok JL et al. Molecular profiling of diffuse large B-cell lymphoma identifies robust subtypes including one characterized by host inflammatory response. Blood 2005;105:1851–1861.
Dave SS, Wright G, Tan B et al. Prediction of survival in follicular lymphoma based on molecular features of tumor-infiltrating immune cells. N Engl J Med 2004;351:2159–2169.
Damle RN, Wasil T, Fais F et al. Ig V gene mutation status and CD38 expression as novel prognostic indicators in chronic lymphocytic leukemia. Blood 1999;94:1840–1847.
Krober A, Seiler T, Benner A et al. V(H) mutation status, CD38 expression level, genomic aberrations, and survival in chronic lymphocytic leukemia. Blood 2002;100:1410–1416.
Dohner H, Stilgenbauer S, Benner A et al. Genomic aberrations and survival in chronic lymphocytic leukemia. N Engl J Med 2000;343:1910–1916.
Hamblin TJ, Davis Z, Gardiner A et al. Unmutated Ig V(H) genes are associated with a more aggressive form of chronic lymphocytic leukemia. Blood 1999;94:1848–1854.
Oscier DG, Gardiner AC, Mould SJ et al. Multivariate analysis of prognostic factors in CLL: Clinical stage, IGVH gene mutational status, and loss or mutation of the p53 gene are independent prognostic factors. Blood 2002;100:1177–1184.
Klein U, Tu Y, Stolovitzky GA et al. Gene expression profiling of B cell chronic lymphocytic leukemia reveals a homogeneous phenotype related to memory B cells. J Exp Med 2001;194:1625–1638.
Chen L, Apgar J, Huynh L et al. ZAP-70 directly enhances IgM signaling in chronic lymphocytic leukemia. Blood 2005;105:2036–2041.
Wiestner A, Rosenwald A, Barry TS et al. ZAP-70 expression identifies a chronic lymphocytic leukemia subtype with unmutated immunoglobulin genes, inferior clinical outcome, and distinct gene expression profile. Blood 2003;101:4944–4951.
Orchard JA, Ibbotson RE, Davis Z et al. ZAP-70 expression and prognosis in chronic lymphocytic leukaemia. Lancet 2004;363:105–111.
Crespo M, Bosch F, Villamor N et al. ZAP-70 expression as a surrogate for immunoglobulin-variable-region mutations in chronic lymphocytic leukemia. N Engl J Med 2003;348:1764–1775.
Rassenti LZ, Huynh L, Toy TL et al. ZAP-70 compared with immunoglobulin heavy-chain gene mutation status as a predictor of disease progression in chronic lymphocytic leukemia. N Engl J Med 2004;351:893–901.
Stankovic T, Weber P, Stewart G et al. Inactivation of ataxia telangiectasia mutated gene in B-cell chronic lymphocytic leukaemia. Lancet 1999;353:26–29.
Stankovic T, Stewart GS, Fegan C et al. Ataxia telangiectasia mutated-deficient B-cell chronic lymphocytic leukemia occurs in pregerminal center cells and results in defective damage response and unrepaired chromosome damage. Blood 2002;99:300–309.
Pettitt AR, Sherrington PD, Stewart G et al. p53 dysfunction in B-cell chronic lymphocytic leukemia: Inactivation of ATM as an alternative to TP53 mutation. Blood 2001;98:814–822.
Stankovic T, Hubank M, Cronin D et al. Microarray analysis reveals that TP53-and ATM-mutant B-CLLs share a defect in activating proapoptotic responses after DNA damage but are distinguished by major differences in activating prosurvival responses. Blood 2004;103:291–300.
Rosenwald A, Chuang EY, Davis RE et al. Fludarabine treatment of patients with chronic lymphocytic leukemia induces a p53-dependent gene expression response. Blood 2004;104:1428–1434.
Campo E, Raffeld M, Jaffe ES. Mantle-cell lymphoma. Semin Hematol 1999;36:115–127.
Rosenwald A, Wright G, Wiestner A et al. The proliferation gene expression signature is a quantitative integrator of oncogenic events that predicts survival in mantle cell lymphoma. Cancer Cell 2003;3:185–197.
Glas AM, Kersten MJ, Delahaye LJ et al. Gene expression profiling in follicular lymphoma to assess clinical aggressiveness and to guide the choice of treatment. Blood 2005;105:301–307.
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© 2007 Landes Bioscience and Springer Science+Business Media
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Henrickson, S.E., Hartmann, E.M., Ott, G., Rosenwald, A. (2007). Gene Expression Profiling in Malignant Lymphomas. In: Mocellin, S. (eds) Microarray Technology and Cancer Gene Profiling. Advances in Experimental Medicine and Biology, vol 593. Springer, New York, NY. https://doi.org/10.1007/978-0-387-39978-2_13
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DOI: https://doi.org/10.1007/978-0-387-39978-2_13
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