Gene expression profiling in malignant lymphomas

Adv Exp Med Biol. 2007:593:134-46. doi: 10.1007/978-0-387-39978-2_13.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Data Interpretation, Statistical
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation, Neoplastic*
  • Humans
  • Leukemia / genetics*
  • Lymphoma / genetics*
  • Lymphoma / immunology
  • Models, Theoretical
  • Oligonucleotide Array Sequence Analysis / methods*
  • Pattern Recognition, Automated
  • Prognosis
  • Treatment Outcome