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Developing Molecular Signatures for Chronic Lymphocytic Leukemia: e0128990
by
Debliquis, Agathe
, Docquier, Mylene
, Cornet, Edouard
, Drenou, Bernard
, Civic, Natacha
, Troussard, Xavier
, Rimelen, Valerie
, Matthes, Thomas
2015
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Developing Molecular Signatures for Chronic Lymphocytic Leukemia: e0128990
by
Debliquis, Agathe
, Docquier, Mylene
, Cornet, Edouard
, Drenou, Bernard
, Civic, Natacha
, Troussard, Xavier
, Rimelen, Valerie
, Matthes, Thomas
2015
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Developing Molecular Signatures for Chronic Lymphocytic Leukemia: e0128990
Journal Article
Developing Molecular Signatures for Chronic Lymphocytic Leukemia: e0128990
2015
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Overview
Chronic lymphocytic leukemia (CLL) is a clonal malignancy of mature B cells that displays a great clinical heterogeneity, with many patients having an indolent disease that will not require intervention for many years, while others present an aggressive and symptomatic leukemia requiring immediate treatment. Although there is no cure for CLL, the disease is treatable and current standard chemotherapy regimens have been shown to prolong survival. Recent advances in our understanding of the biology of CLL have led to the identification of numerous cellular and molecular markers with potential diagnostic, prognostic and therapeutic significance. We have used the recently developed digital multiplexed gene-expression technique (DMGE) to analyze a cohort of 30 CLL patients for the presence of specific genes with known diagnostic and prognostic potential. Starting from a set of 290 genes we were able to develop a molecular signature, based on the analysis of 13 genes, which allows distinguishing CLL from normal peripheral blood and from normal B cells, and a second signature based on 24 genes, which distinguishes mutated from unmutated cases (LymphCLL Mut). A third classifier (LymphCLL Diag), based on a 44-gene signature, distinguished CLL cases from a series of other B-cell chronic lymphoproliferative disorders (n = 51). While the methodology presented here has the potential to provide a \"ready to use\" classification tool in routine diagnostics and clinical trials, application to larger sample numbers are still needed and should provide further insights about its robustness and utility in clinical practice.
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