Literature DB >> 17591935

Analytical detection of immunoglobulin heavy chain gene rearrangements in gastric lymphoid infiltrates by peak area analysis of the melting curve in the LightCycler System.

Eduardo Retamales1, Luis Rodriguez, Leda Guzman, Francisco Aguayo, Mariana Palma, Claudia Backhouse, Jorge Argandona, Erick Riquelme, Alejandro Corvalan.   

Abstract

Because it is difficult to differentiate gastric mucosa-associated lymphoid tissue (MALT) lymphoma from chronic gastritis in gastric lymphoid infiltrates, molecular detection of monoclonality through immunoglobulin heavy chain (IgH) gene rearrangements is commonly performed. However, heterogeneity in the performance and results obtained from IgH gene rearrangements has been reported. To improve the accuracy in the diagnosis of gastric lymphoid infiltrates, we developed an analytical approach based on one-peak area analysis of the melting curve in the LightCycler System. Using a training-testing approach, the likelihood ratio method was selected to find a discriminative function of 4.64 in the training set (10 gastric MALT lymphomas and 10 chronic gastritis cases). This discriminative function was validated in the testing set (five gastric MALT lymphomas, six abnormal lymphocytic infiltrates with subsequently demonstrated gastric MALT lymphomas, and six cases of chronic gastritis). All but one case of gastric MALT lymphoma, as well as abnormal lymphocytic infiltrates, clustered under 4.64, and all chronic gastritis cases clustered above 4.64. These results were validated by conventional electrophoreses confirming one or two sharp bands in cases of gastric MALT lymphomas and a smear of multiple bands in cases of chronic gastritis. Analytical detection of IgH gene rearrangement in gastric lymphoid infiltrates by one-peak area analysis correctly distinguishes gastric MALT lymphomas from chronic gastritis, even in cases with diagnosis of abnormal lymphocytic infiltrates.

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Year:  2007        PMID: 17591935      PMCID: PMC1899425          DOI: 10.2353/jmoldx.2007.050129

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  29 in total

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