Faculty Bibliography

Understanding haematological malignancies at the protein level is important as the development of targeted treatments must be based on knowledge regarding the molecular pathogenesis of the tumour, inherited genetic variation and the mode of action of drugs. 'Proteomics' describes the analysis of the entire proteome of a cell or tissue and incorporates multiple technologies including Western blotting, two-dimensional gel electrophoresis, mass spectrometry, and ProteinChip-based technology. Although there are a limited number of studies to date in haematology those performed highlight the potential future impact of these technologies in the discovery of novel markers, proteins associated with drug resistance and the identification of tumour biomarkers which may facilitate the development of a rapid diagnostic test easily applicable in the clinical setting. Rapid large-scale analysis of the proteome in normal pathways and disease offers the opportunity of identification of potential diagnostic/prognostic markers and proteins associated with the malignant phenotype. This review discusses the current situation regarding the use of these technologies and the potential opportunities their future use may offer in the field of haematology.

Genetic heterogeneity between individuals confounds the comparison of gene profiling of multiple myeloma (MM) cells versus normal plasma cells (PCs). To overcome this barrier, we compared the gene expression profile of CD138+ MM cells from a patient bone marrow (BM) sample with CD138+ PCs from a genetically identical twin BM sample using microarray profiling. Two hundred and ninety-six genes were up-regulated and 103 genes were down-regulated at least 2-fold in MM cells versus normal twin PCs. Highly expressed genes in MM cells included cell survival pathway genes such as mcl-1, dad-1, caspase 8, and FADD-like apoptosis regulator (FLIP); oncogenes/transcriptional factors such as Jun-D, Xbp-1, calmodulin, Calnexin, and FGFR-3; stress response and ubiquitin/proteasome pathway-related genes and various ribosomal genes reflecting increased metabolic and translational activity. Genes that were down-regulated in MM cells versus healthy twin PCs included RAD51, killer cell immunoglobulin-like receptor protein, and apoptotic protease activating factor. Microarray results were further confirmed by Western blot analyses, immunohistochemistry, fluorescent in situ hybridization (FISH), and functional assays of telomerase activity and bone marrow angiogenesis. This molecular profiling provides potential insights into mechanisms of malignant transformation in MM. For example, FGFR3, xbp-1, and both mcl-1 and dad-1 may mediate transformation, differentiation, and survival, respectively, and may have clinical implications. By identifying genes uniquely altered in MM cells compared with normal PCs in an identical genotypic background, the current study provides the framework to identify novel therapeutic targets.

Much has been learned regarding the biology and clinical implications of genetic abnormalities in multiple myeloma. Because of recent advances in the field, an International Workshop was held in Paris in february of 2003. This summary describes the consensus recommendations arising from that meeting with special emphasis on novel genetic observations. For instance, it is increasingly clear that translocations involving the immunoglobin heavy-chain locus are important for the pathogenesis of one-half of patients. As a corollary, it also clear that the remaining patients, lacking IgH translocations, have hyperdiploidy as the hallmark of their disease. Several important genetic markers are associated with a shortened survival such as chromosome 13 monosomy, hypodiploidy, and others. The events leading the transformation of the monoclonal gammopathy of undetermined significance (MGUS) to myeloma are still unclear. One of the few differential genetic lesions between myeloma and MGUS is the presence of ras mutations in the latter. Gene expression platforms are capable of detecting many of the genetic aberrations found in the clonal cells of myeloma. Areas in need of further study were identified. The study of the genetic aberrations will likely form the platform for targeted therapy for the disease.

The ability of donor lymphocyte infusions (DLIs) to induce complete responses (CRs) in patients with relapsed myeloma after allogeneic bone marrow transplantation (BMT) provides clear evidence of an effective graft-versus-myeloma (GVM) response. To identify target antigens of the GVM response, we screened a myeloma cDNA expression library with post-DLI serum from 4 patients with myeloma who achieved CR after DLI and 1 patient who was in CR before DLI. We identified a panel of 13 gene products reactive with post-DLI serum but negative with pre-DLI and pre-BMT serum. Antibodies to these proteins were not detected in the sera of 10 patients who underwent allogeneic BMT without DLI and 5 patients with acute graft-versus-host disease (GVHD). Minimal reactivity with these proteins was detected in the sera of 20 healthy donors and 20 patients with chronic GVHD. In contrast, 5 of these proteins were recognized by more than 1 myeloma DLI responder. Testing of serial serum samples showed an association between antibody response and time of best response after DLI. The expression of these genes was evaluated in primary myeloma cells and in normal plasma cells. This study demonstrates that the GVM response is associated with antibody responses to highly expressed myeloma-associated antigens.

To define specific pathways important in the multistep transformation process of normal plasma cells (PCs) to monoclonal gammopathy of uncertain significance (MGUS) and multiple myeloma (MM), we have applied microarray analysis to PCs from 5 healthy donors (N), 7 patients with MGUS, and 24 patients with newly diagnosed MM. Unsupervised hierarchical clustering using 125 genes with a large variation across all samples defined 2 groups: N and MGUS/MM. Supervised analysis identified 263 genes differentially expressed between N and MGUS and 380 genes differentially expressed between N and MM, 197 of which were also differentially regulated between N and MGUS. Only 74 genes were differentially expressed between MGUS and MM samples, indicating that the differences between MGUS and MM are smaller than those between N and MM or N and MGUS. Differentially expressed genes included oncogenes/tumor-suppressor genes (LAF4, RB1, and disabled homolog 2), cell-signaling genes (RAS family members, B-cell signaling and NF-kappaB genes), DNA-binding and transcription-factor genes (XBP1, zinc finger proteins, forkhead box, and ring finger proteins), and developmental genes (WNT and SHH pathways). Understanding the molecular pathogenesis of MM by gene expression profiling has demonstrated sequential genetic changes from N to malignant PCs and highlighted important pathways involved in the transformation of MGUS to MM.