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Immunoglobulin gene ‘fingerprinting’: an approach to analysis of B lymphoid clonality in lymphoproliferative disorders
Author(s) -
Deane Miriam,
Norton John D.
Publication year - 1991
Publication title -
british journal of haematology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.907
H-Index - 186
eISSN - 1365-2141
pISSN - 0007-1048
DOI - 10.1111/j.1365-2141.1991.tb08570.x
Subject(s) - gene rearrangement , biology , immunoglobulin heavy chain , lymphoproliferative disorders , minimal residual disease , polymerase chain reaction , b cell , immunoglobulin light chain , antibody , microbiology and biotechnology , immunology , gene , bone marrow , genetics , lymphoma
Summary Rearrangement of the immunoglobulin heavy chain (IgH) gene is widely exploited as a marker of B cell lineage and clonality in the pathology of lymphoproliferative disorders. We have developed a simple, polymerase chain reaction (PCR) based method for detecting IgH gene rearrangement which relies on the observation that by using a panel of PCR amplimers specific for each of the six heavy chain variable region families in conjunction with a common joining region amplimer, clonal rearrangement can be detected in over 90% of cases of B lymphoid malignancy. By using radiolabelled amplimers and exploiting the size heterogeneity resulting from independent IgH rearrangement events. we show that high resolution gel electrophoresis can be used to generate a‘fingerprint’representing the spectrum of B cell clonality in complex populations of B lymphocytes. The method effectively scans the entire IgH gene rearrangement repertoire and is capable of detecting rare clonal or oligoclonal B lymphoid cell populations. In normal bone marrow mononuclear cells. clonal IgH rearrangement could be readily detected at a sensitivity of 10 −3 . We illustrate the application of the method in assessing the spectrum of B cell clonality occurring in an autoimmune condition, Hashimoto's thyroiditis, and in a malignant B cell disorder, chronic lymphocytic leukaemia. In addition, we explore the potential application of the technique in tracking minimal residual disease and for monitoring clonal evolution in acute lymphoblastic leukaemia.