Optimising diagnostic and prognostic investigations in myeloma

Abstract

In recent years an increasing number of investigations has been devised to improve diagnosis and prognostication in myeloma. Standard investigations range from the characterisation of paraprotein by serum and urine protein electrophoresis, immunofixation and bone marrow biopsy, with the definition of the ‘CRAB’ features of disease activity (hypercalcaemia, renal impairment, anaemia and bone lesions), to the International Staging System based on beta-2 microglobulin and albumin. Plasma cell labelling index measures proliferation by slide-based or flow cytometrical quantitation of replicating S-phase cells, with clear prognostic implications. More recently the quanitita-tion of serum free light chains was developed, based on antibody detection of light chain epitopes that are hidden when bound to heavy chains. The assay is useful, particularly in light chain myeloma, and in the assessment of responses including stringent complete response (sCR). Unique junctional epitopes between heavy and light chain constant regions can also be identified in the ‘heavy-light chain assay’. Response criteria based on para-protein levels correlate with survival and are crucial to the assessment of new therapies; in the detection of minimal residual disease, sCR was added to denote the absence of clonal cells by immunohistochemistry or flow cytometry, in conjunction with a normal free light chain ratio. Conventional and molecular cyto-genetics are some of the most important developments, ranging from the detection of IgH translocations, chromosomal deletions and ploidy changes. Myeloma can be divided into hyperdiploidy and non-hyperdiploidy groups, denoting standard and poor prognosis, respectively, the latter enriched for changes such as del13 and IgH translocations e.g., t(4;14). Basic panels comprise the detection of ploidy changes and del13 by conventional cytoge-netics, t(4;14), t(14;16) and del17p by FISH as high risk markers, and t(11;14) and t(6;14) as standard/good risk markers. Gene expression profiling has provided information on new pathogenic molecules and risk stratification, with specific patterns correlating with proliferation and responsiveness to novel therapies.