ABSTRACT
Biological effects of proteasome inhibition 1483 Evidence for important clinical activity in the 1484
lymphoproliferative malignancies Future directions 1485 Targeting epigenetic pathways in the treatment of 1485
lymphoma: vorinostat Histone deacetylases and oncogenesis 1486 Histone deacetylase inhibitors 1486 Clinical activity of histone deacetylase inhibitors 1488 Future directions 1490 Targeting immunomodulatory pathways: thalidomide 1490
and lenalidomide (Revlimid®)
Preclinical evidence of antilymphoma activity for 1491 lenalidomide
Current clinical studies of lenalidomide in non-Hodgkin 1491 lymphoma
T cell lymphoma 1492 Adverse effects profile of the immunomodulatory agents 1493 Future directions 1493 Multifunctional alkylating agents: bendamustine 1493 Clinical activity – chronic lymphocytic leukemia 1494 Non-Hodgkin lymphomas 1494 Conclusion and future directions 1494 Novel antifol derivatives: pralatrexate 1494 Key points 1495 References 1495
The lymphoid neoplasms represent some of the most heterogeneous and diverse malignancies known to medicine. The spectrum of clinical diseases ranges from rapidly growing diseases like Burkitt and lymphoblastic lymphoma to some of the slowest and most indolent cancers known to science, like small lymphocytic lymphoma and follicular lymphoma. This diversity in clinical behavior reflects the molecular heterogeneity that often defines these complex neoplasms which, based on the World Health Organization (WHO) classification, can be subdivided into at least 40 different subtypes.1 Important advances in immunohistochemistry and cytogenetics, coupled with our historical skills in basic morphology, have now allowed the delineation of each non-Hodgkin lymphoma (NHL) subtype as a distinct clinical entity – each with its own unique clinical behavior and treatment paradigms. Recent advances in gene expression profiling (GEP) have led to an entirely new way to think about lymphoma classification based on individual gene clusters that correlate with prognosis and clinical behavior. These types of classification models offer an opportunity to think about designing rational and specific therapeutic regimens targeted against the unique biological basis of the disease. Chapter 84 pro-
For example, Alizadeh et al.2 reported the application of GEP on tissue from patients with diffuse large B cell lymphoma (DLBCL), and proposed a molecular classification that divided DLBCL into subtypes based on the cell of origin. These included categorizing DLBCL into a germinal center (GC) subtype and an activated B cell (ABC) or post-germinal center subtype, with a favorable outcome seen in lymphomas arising from the GC. Shipp et al.3
