Current Hematologic Malignancy Reports

, Volume 1, Issue 2, pp 129–136 | Cite as

Gene arrays in lymphoma: Where will they fit in?

  • Javeed Iqbal
  • Francesco d’Amore
  • Qinglong Hu
  • Wing C. Chan
  • Kai Fu


Molecular diagnostics for lymphoid malignancies has undergone substantial technical evolution during the past two decades, moving from labor-intensive investigations of individual abnormalities to high-throughput genome-wide analyses. Accordingly, its role has expanded to new fields such as monitoring of minimal residual disease and, more recently, outcome prediction in specific lymphoma subtypes. One novel technology that has had a major impact on the molecular diagnosis of lymphoid malignancies is gene expression profiling by DNA microarrays. It has provided robust and distinct molecular signatures for the most common types of lymphomas and has identified novel subsets that would not be identified by conventional methods. It also has led to the construction of molecularly defined prognostic models in these lymphoma subtypes and to a better understanding of the molecular mechanisms of lymphomagenesis. This development will undoubtedly transform diagnostic medicine in the near future and lead us into an era when tumor diagnosis will incorporate the information of critical molecular abnormalities that will have significant impact on disease outcome in each individual tumor sample. Future treatments are likely to be founded on effective, individualized, and mechanism-based therapies with the least toxicity.


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References and Recommended Reading

  1. 1.
    Jaffe ES, Harris NL, Stein H, Vardiman JW, eds: World Health Organization Classification of Tumours. Pathology and Genetics of Tumours of Haematopoietic and Lymphoid Tissues. Lyon, France: IARC Press; 2001.Google Scholar
  2. 2.
    Willis TG, Dyer MJ: The role of immunoglobulin translocations in the pathogenesis of B-cell malignancies. Blood 2000, 96:808–822.PubMedGoogle Scholar
  3. 3.
    Pasqualucci L, Migliazza A, Basso K, et al.: Mutations of the BCL6 proto-oncogene disrupt its negative autoregulation in diffuse large B-cell lymphoma. Blood 2003, 101:2914–2923.PubMedCrossRefGoogle Scholar
  4. 4.
    Pasqualucci L, Neumeister P, Goossens T, et al.: Hypermutation of multiple proto-oncogenes in B-cell diffuse large-cell lymphomas. Nature 2001, 412:341–346.PubMedCrossRefGoogle Scholar
  5. 5.
    Greiner TC, Moynihan MJ, Chan WC, et al.: p53 mutations in mantle cell lymphoma are associated with variant cytology and predict a poor prognosis. Blood 1996, 87:4302–4310.PubMedGoogle Scholar
  6. 6.
    Pinyol M, Hernandez L, Cazorla M, et al.: Deletions and loss of expression of p16INK4a and p21Waf1 genes are associated with aggressive variants of mantle cell lymphomas. Blood 1997, 89:272–280.PubMedGoogle Scholar
  7. 7.
    Pinyol M, Cobo F, Bea S, et al.: p16(INK4a) gene inactivation by deletions, mutations, and hypermethylation is associated with transformed and aggressive variants of non-Hodgkin’s lymphomas. Blood 1998, 91:2977–2984.PubMedGoogle Scholar
  8. 8.
    Gronbaek K, de Nully Brown P, Moller MB, et al.: Concurrent disruption of p16INK4a and the ARF-p53 pathway predicts poor prognosis in aggressive non-Hodgkin’s lymphoma. Leukemia 2000, 14:1727–1735.PubMedCrossRefGoogle Scholar
  9. 9.
    Dalla-Favera R, Migliazza A, Chang CC, et al.: Molecular pathogenesis of B cell malignancy: the role of BCL-6. Curr Top Microbiol Immunol 1999, 246:257–263; discussion 263–265.PubMedGoogle Scholar
  10. 10.
    National Cancer Institute sponsored study of classifications of non-Hodgkin’s lymphomas: summary and description of a working formulation for clinical usage. The Non-Hodgkin’s Lymphoma Pathologic Classification Project. Cancer 1982, 49:2112–2135.Google Scholar
  11. 11.
    Harris NL, Jaffe ES, Stein H, et al.: A revised European-American classification of lymphoid neoplasms: a proposal from the International Lymphoma Study Group. Blood 1994, 84:1361–1392.PubMedGoogle Scholar
  12. 12.
    A predictive model for aggressive non-Hodgkin’s lymphoma. The International Non-Hodgkin’s Lymphoma Prognostic Factors Project. N Engl J Med 1993, 329:987–994.Google Scholar
  13. 13.
    Salles G, Shipp MA, Coiffier B: Chemotherapy of non-Hodgkin’s aggressive lymphomas. Semin Hematol 1994, 31:46–69.PubMedGoogle Scholar
  14. 14.
    Shipp MA: Prognostic factors in aggressive non-Hodgkin’s lymphoma: Who has "high-risk" disease? Blood 1994, 83:1165–1173.PubMedGoogle Scholar
  15. 15.
    Armitage JO: Treatment of non-Hodgkin’s lymphoma. N Engl J Med 1993, 328:1023–1030.PubMedCrossRefGoogle Scholar
  16. 16.
    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. The first microarray study performed in lymphoid malignancies. This study identified two distinct subgroups of DLBCL using a supervised approach.PubMedCrossRefGoogle Scholar
  17. 17.
    Wright G, Tan B, Rosenwald A, et al.: A gene expressionbased method to diagnose clinically distinct subgroups of diffuse large B cell lymphoma. Proc Natl Acad Sci U S A 2003, 100:9991–9996.PubMedCrossRefGoogle Scholar
  18. 18.
    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. dy of 240 patients with diffuse large B-cell lymphoma, which confirmed the initial findings (reference 16••) and identified a model of 17 genes as molecular predictor of clinical outcome.PubMedCrossRefGoogle Scholar
  19. 19.
    Lossos IS, Alizadeh AA, Eisen MB, et al.: Ongoing immunoglobulin somatic mutation in germinal center B cell-like but not in activated B cell-like diffuse large cell lymphomas. Proc Natl Acad Sci U S A 2000, 97:10209–10213.PubMedCrossRefGoogle Scholar
  20. 20.
    Iqbal J, Sanger WG, Horsman DE, et al.: BCL2 translocation defines a unique tumor subset within the germinal center B-cell-like diffuse large B-cell lymphoma. Am J Pathol 2004, 165:159–166.PubMedGoogle Scholar
  21. 21.
    Huang JZ, Sanger WG, Greiner TC, et al.: The t(14;18) defines a unique subset of diffuse large B-cell lymphoma with a germinal center B-cell gene expression profile. Blood 2002, 99:2285–2290.PubMedCrossRefGoogle Scholar
  22. 22.
    Barth TF, Leithauser F, Joos S, et al.: Mediastinal (thymic) large B-cell lymphoma: Where do we stand? [review]. Lancet Oncol 2002, 3:229–234.PubMedCrossRefGoogle Scholar
  23. 23.
    Savage KJ, Monti S, Kutok JL, et al.: The molecular signature of mediastinal large B-cell lymphoma differs from that of other diffuse large B-cell lymphomas and shares features with classical Hodgkin lymphoma. Blood 2003, 102:3871–3879. of the two studies identifying a unique gene expression profile that can distinguish primary mediastinal large-B-cell lymphoma from other diffuse large-B-cell lymphomas, including those that happen to involve the anterior mediastinum.PubMedCrossRefGoogle Scholar
  24. 24.
    Rosenwald A, Wright G, Leroy K, et al.: Molecular diagnosis of primary mediastinal B cell lymphoma identifies a clinically favorable subgroup of diffuse large B cell lymphoma related to Hodgkin lymphoma. J Exp Med 2003, 198:851–862. of the two studies identifying a unique gene expression profile that can distinguish primary mediastinal large-B-cell lymphoma from other diffuse large-B-cell lymphomas, including those that happen to involve the anterior mediastinum.PubMedCrossRefGoogle Scholar
  25. 25.
    Campo E, Raffeld M, Jaffe ES: Mantle-cell lymphoma. Semin Hematol 1999, 36:115–127.PubMedGoogle Scholar
  26. 26.
    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. A study of 101 patients with mantle cell lymphoma (MCL), in which the authors identified a unique gene expression signature, illustrated the role of proliferative gene expression signature in predicting the survival of patients with MCL and identified several cases of cyclin D1-negative MCL.PubMedCrossRefGoogle Scholar
  27. 27.
    Fu K, Weisenburger DD, Greiner TC, et al.: Cyclin D1-negative mantle cell lymphoma: a clinicopathologic study based on gene expression profiling. Blood 2005, 106:4315–4321.PubMedCrossRefGoogle Scholar
  28. 28.
    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. A study of 58 cases of diffuse large-B-cell lymphoma using oligonucleotide microarrays, which identified a model of 13 genes as a molecular predictor of clinical outcome.PubMedCrossRefGoogle Scholar
  29. 29.
    Rimsza LM, Roberts RA, Miller TP, et al.: Loss of MHC class II gene and protein expression in diffuse large B-cell lymphoma is related to decreased tumor immunosurveillance and poor patient survival regardless of other prognostic factors: a follow-up study from the Leukemia and Lymphoma Molecular Profiling Project. Blood 2004, 103:4251–4258.PubMedCrossRefGoogle Scholar
  30. 30.
    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.PubMedCrossRefGoogle Scholar
  31. 31.
    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. A study of 192 patients with follicular lymphoma, which identified a model based on molecular features of tumor-infiltrating immune cells as molecular predictor of clinical outcome.PubMedCrossRefGoogle Scholar
  32. 32.
    Davis RE, Brown KD, Siebenlist U, Staudt LM: 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.PubMedCrossRefGoogle Scholar
  33. 33.
    Dave SS, Wright G, Tan B, et al.: LymphDx: a custom microarray for molecular diagnosis and prognosis in non-Hodgkin lymphoma. Blood 2004, 104:201a.Google Scholar
  34. 34.
    Lossos IS, Czerwinski DK, Alizadeh AA, et al.: Prediction of survival in diffuse large-B-cell lymphoma based on the expression of six genes. N Engl J Med 2004, 350:1828–1837.PubMedCrossRefGoogle Scholar
  35. 35.
    Hans CP, Weisenburger DD, Greiner TC, et al.: Confirmation of the molecular classification of diffuse large B-cell lymphoma by immunohistochemistry using a tissue microarray. Blood 2004, 103:275–282.PubMedCrossRefGoogle Scholar
  36. 36.
    Barrans SL, Fenton JA, Banham A, et al.: Strong expression of FOXP1 identifies a distinct subset of diffuse large B-cell lymphoma (DLBCL) patients with poor outcome. Blood 2004, 104:2933–2935.PubMedCrossRefGoogle Scholar
  37. 37.
    Elias L, Portlock CS, Rosenberg SA: Combination chemotherapy of diffuse histiocytic lymphoma with cyclophosphamide, adriamycin, vincristine and prednisone (CHOP). Cancer 1978, 42:1705–1710.PubMedCrossRefGoogle Scholar
  38. 38.
    Shipp MA, Yeap BY, Harrington DP, et al.: The m-BACOD combination chemotherapy regimen in large-cell lymphoma: analysis of the completed trial and comparison with the M-BACOD regimen. J Clin Oncol 1990, 8:84–93.PubMedGoogle Scholar
  39. 39.
    Klimo P, Connors JM: MOPP/ABV hybrid program: combination chemotherapy based on early introduction of seven effective drugs for advanced Hodgkin’s disease. J Clin Oncol 1985, 3:1174–1182.PubMedGoogle Scholar
  40. 40.
    Klimo P, Connors JM: MACOP-B chemotherapy for the treatment of diffuse large-cell lymphoma. Ann Intern Med 1985, 102:596–602.PubMedGoogle Scholar
  41. 41.
    Fisher RI, Gaynor ER, Dahlberg S, et al.: Comparison of a standard regimen (CHOP) with three intensive chemotherapy regimens for advanced non-Hodgkin’s lymphoma. N Engl J Med 1993, 328:1002–1006.PubMedCrossRefGoogle Scholar
  42. 42.
    A clinical evaluation of the International Lymphoma Study Group classification of non-Hodgkin’s lymphoma. The Non-Hodgkin’s Lymphoma Classification Project. Blood 1997, 89:3909–3918.Google Scholar
  43. 43.
    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.PubMedCrossRefGoogle Scholar

Copyright information

© Current Science Inc 2006

Authors and Affiliations

  • Javeed Iqbal
  • Francesco d’Amore
  • Qinglong Hu
  • Wing C. Chan
  • Kai Fu
    • 1
  1. 1.Department of Pathology and MicrobiologyUniversity of Nebraska Medical CenterOmahaUSA

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