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Multiple myeloma shows no intra-disease clustering of immunoglobulin heavy chain genes.

AbstractBACKGROUND:
Characterization of the immunoglobulin gene repertoire has improved our understanding of the immunopathogenesis of lymphoid tumors. Early B-lymphocyte precursors of multiple myeloma are known to exist and might be susceptible to antigenic drive.
DESIGN AND METHODS:
To verify this hypothesis, we collected a database of 345 fully readable multiple myeloma immunoglobulin sequences. We characterized the immunoglobulin repertoire, analyzed the somatic hypermutation load, and investigated for stereotyped receptor clusters.
RESULTS:
Compared to the normal immunoglobulin repertoire, multiple myeloma displayed only modest differences involving only a few genes, showing that the myeloma immunoglobulin repertoire is the least skewed among mature B-cell tumors. Median somatic hypermutation load was 7.8%; median length of complementarity determining-region 3 was 15.5 amino acids. Clustering analysis showed the absence of myeloma specific clusters and no similarity with published chronic lymphocytic leukemia or lymphoma subsets.
CONCLUSIONS:
Analysis of multiple myeloma immunoglobulin repertoire does not support a pathogenetic role for antigen selection in this tumor.
AuthorsSimone Ferrero, Daniela Capello, Mirija Svaldi, Michela Boi, Daniela Gatti, Daniela Drandi, Davide Rossi, Sara Barbiero, Barbara Mantoan, Elisabetta Mantella, Manuela Zanni, Paola Ghione, Alessandra Larocca, Roberto Passera, Francesco Bertoni, Valter Gattei, Francesco Forconi, Luca Laurenti, Giovanni Del Poeta, Roberto Marasca, Sergio Cortelazzo, Gianluca Gaidano, Antonio Palumbo, Mario Boccadoro, Marco Ladetto
JournalHaematologica (Haematologica) Vol. 97 Issue 6 Pg. 849-53 (Jun 2012) ISSN: 1592-8721 [Electronic] Italy
PMID22207685 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
Chemical References
  • Complementarity Determining Regions
  • Myeloma Proteins
  • myeloma immunoglobulins
Topics
  • B-Lymphocytes (immunology, pathology)
  • Complementarity Determining Regions (chemistry, genetics, immunology)
  • Data Mining
  • Databases, Nucleic Acid
  • Genes, Immunoglobulin Heavy Chain (immunology)
  • Humans
  • Multigene Family (immunology)
  • Multiple Myeloma (genetics, immunology)
  • Myeloma Proteins (chemistry, genetics, immunology)
  • Sequence Analysis, DNA
  • Somatic Hypermutation, Immunoglobulin (immunology)

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