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Hematology 2008

Investigative Tools for Diagnosis and Management

Nikhil C. Munshi1

Correspondence: Nikhil C. Munshi, MD, Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston VA Cancer Healthcare System, 44 Binney Street, M1B28, Boston, MA 02115; Phone: 617-632-5607; Fax: 617-582-7904; e-mail: nikhil_munshi{at}dfci.harvard.edu

Abstract

Recent advances in genomics and proteomics have advanced our understanding of myeloma pathogenesis, recognized novel mediators of disease process, and identified new therapeutic targets. These developments have provided newer diagnostic tools for myeloma, improved monitoring of the disease status and allowed for molecular classification of the disease. The recent advances in investigative techniques that have helped refine the diagnostic work up in myeloma includes use of serum free light chains, especially in oligosecretory myeloma, patients with renal disease and with amyloidosis; use of MRI and PET scan in diagnosis and managing bone disease; and use of cytogenetics and fluorescent in situ hybridization (FISH) technique to determine prognosis. Newer risk stratification protocols have included international staging systems as well as FISH-detected chromosomal changes, specifically t(4;14), t(14;16), and del 17p. These improved predictive risk stratification models are guiding treatment algorithms. As the novel therapies are able to attain complete responses in a significant number of patients, the response categories are also being redefined. Immunophenotypic identification of clonal plasma cells, inclusion of free light chain response and molecular markers of disease now allow us to define stringent complete responses. Recent studies show the increasing importance of attaining complete remission to extended overall survival. The ongoing oncogenomic studies including high-throughput expression profiling, high-density single nucleotide polymorphism (SNP)–arrays and array based comparative hybridization (aCGH) have been utilized to not only understand myeloma pathobiology, but for gene discovery, identification of biomarkers, and delineation of patient subgroups to incorporate them into therapeutic strategies and to eventually provide optimal individualized therapy.


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