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DNA Microarrays in Lymphoid Malignancies

DNA Microarrays in Lymphoid Malignancies

Dr. Rosenwald presents a timely and highly lucid review of recent findings in molecular profiling-a powerful new tool that is helping to unravel the clinical and biologic heterogeneity of lymphomas. Although histologic classifications provide a framework for the organi- zation of lymphomas into distinct disease entities with shared pathogenesis and clinical behavior, many of these entities continue to display significant clinical and diagnostic variability. Molecular profiling represents the next step in the evolution of lymphoma classification that has advanced from exclusively morphologic to the current World Health Organization classification that incorporates immunophenotype and genetic end points.[1] This evolution is the direct result of insights into the molecular pathogenesis of lymphoma, including the identification of "hallmark" genetic abnormalities. Advances in molecular biology have helped identify the expression of individual gene products important in cellular proliferation, differentiation, and death, but insights into coordinated large-scale gene expression have not been possible until recently. The application of this technology to lymphoma is providing insights into unique molecular signatures of distinct types of B-cell malignancies. This technology can relate lymphoid neoplasms to normal stages in B-cell development and physiology, and is affording a new taxonomy of lymphomas and molecular indices of clinical outcome. Indeed, as the molecular analysis of tumors improves, the classification of human cancers will become more refined and informative. Standard Clinical Tool
Molecular profiling in lymphomas has numerous immediate clinical applications as well as an enormous potential to identify new therapeutic targets. The practical clinical application of this technology, however, is limited by the lack of appropriate "diagnostic" array chips, the routine collection and storage of fresh biopsy material, and most importantly, prospective clinical validation. Molecular profiling, or equivalent methods, will certainly become a standard clinical tool as this validation occurs, and will likely improve the accuracy of the current classification system by serving as a diagnostic check for both routine and borderline cases. Moreover, the evolving lymphoma taxonomy based on molecular profiling-as exemplified by germinal center B-cell, activated B-cell, and primary mediastinal B-cell diffuse large B-cell lymphoma (DLBCL) subtypes-may be identifying new lymphoma subtypes with unique biology and outcomes.[2,3] Clearly, in the absence of molecular profiling, clinical trials will be unable to accurately assess the efficacy of treatment approaches within such newly identified lymphoma subtypes. An excellent illustration of this issue comes from recent studies in DLBCL: Two recent reports found that the benefit of rituximab (Rituxan) in DLBCL is primarily restricted to tumors expressing bcl-2, suggesting rituximab may overcome the bcl-2-associated adverse effects seen in the activated B-cell subtype.[4,5] Another study suggests that the adverse prognostic effect of the tumor proliferation signature may be overcome by continuous-infusion chemotherapy schedules, as employed in the EPOCH regimen (etoposide, prednisone, vincristine [Oncovin], cyclophosphamide [Cytoxan, Neosar], doxorubicin HCl).[6] To prospectively assess findings such as these, molecular profiling should be incorporated into clinical trials and is a component of the soon-to-be-initiated Cancer and Leukemia Group B phase III randomized study comparing CHOP (cyclophosphamide, doxorubicin, vincristine, prednisone)/rituximab with doseadjusted EPOCH/rituximab. Mechanisms of Treatment Failure
Molecular profiling also serves as a biologically based predictor of outcome and, unlike clinical prognostic indices, is not a surrogate measure. As such, when applied to new therapeutic regimens, molecular profiling models can provide insight into the molecular mechanisms of treatment failure. By elucidating pertinent pathways of lymphomagenesis, molecular profiling can identify clinically useful targets, including those for therapeutic development. A finding from molecular profiling of chronic lymphocytic leukemia (CLL), for example, showed a high correlation between ZAP70 expression and the immunoglobulin (Ig)-unmutated CLL subtype; this discovery has led to its validation as a marker of Ig-unmutated CLL and the development of a diagnostic test.[7,8] Microarray profiling has also identified potential therapeutic targets. Shipp et al highlighted the potential importance of protein kinase C- beta as a therapeutic target in DLBCL, and molecular profiling revealed the high expression of nuclear factor- kappaB target genes in the activated B-cell (but not germinal B-cell) DLBCL subtypes (Figure 1).[2,9,10] Nuclear factor-kappaB signaling interferes with apoptotic cell death triggered by chemotherapy agents, and its inhibition was shown to be cytotoxic in activated B-cell (but not germinal B-cell) DLBCL cell lines. This finding has led to the testing of bortezomib (Velcade), a proteasome inhibitor that downregulates nuclear factor-kappaB in DLBCL. Conclusions
As a final point, clinical prognostic indices based on molecular profiling alone, or more likely in combination with clinical features, will provide a reliable measure of outcome and, hence, will lead to accurate treatment stratification and better outcomes. Indeed, molecular profiling has already significantly deepened our insight into the clinical and basic biology of lymphomas, and we are only beginning to reap the benefits of this technology.


The author(s) have no significant financial interest or other relationship with the manufacturers of any products or providers of any service mentioned in this article.


1. Jaffe ES, Harris NL, Stein H, et al (eds): Tumours of haematopoietic and lymphoid tissues. World Health Organization Classification of Tumours. Lyon, France, IARC Press, 2001.
2. 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 346:1937-1947, 2002.
3. Rosenwald A, Wright G, Leroy K, et al: Molecular diagnosis of primary mediastinal Bcell lymphoma identifies a clinically favorable subgroup of diffuse large B cell lymphoma related to Hodgkin lymphoma. J Exp Med 198:851-862, 2003.
4. Wilson W, O’Connor P, Hegde U, et al: Rituximab may overcome BCL-2-associated chemotherapy resistance in untreated diffuse large B-cell lymphomas. Proceedings of the American Society of Hematology, vol 99, 2001.
5. Mounier N, Briere J, Gisselbrecht C, et al: Rituximab plus CHOP (R-CHOP) overcomes bcl-2—associated resistance to chemotherapy in elderly patients with diffuse large B-cell lymphoma (DLBCL). Blood 101:4279- 4284, 2003.
6. Wilson WH, Grossbard ML, Pittaluga S, et al: Dose-adjusted EPOCH chemotherapy for untreated large B-cell lymphomas: A pharmacodynamic approach with high efficacy. Blood 99:2685-2693, 2002.
7. 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 194:1639-1647, 2001.
8. 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 101:4944-4951, 2003.
9. 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 8:68-74, 2002.
10. 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 194:1861-1874, 2001.
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