TY - JOUR
T1 - Gene expression profiling in lymphoma diagnosis and management
AU - Iqbal, Javeed
AU - Liu, ZhongFeng
AU - Deffenbacher, Karen
AU - Chan, Wing C.
N1 - Funding Information:
This work was supported in part by an NCI grant (5U01/CA114778), Department of Health and Human Services.
PY - 2009/6
Y1 - 2009/6
N2 - The classification of lymphoid malignancies has evolved from a purely morphological scheme to the current WHO (World Health Organization) classification, which takes into consideration histological, immunophenotypic, genetic and clinical information. DNA microarray technology enables the simultaneous determination of the expression levels for thousands of genes (gene expression profile; GEP) and provides a powerful approach for investigating lymphoma biology and improving disease classification. Distinct molecular signatures for many lymphomas, as well as novel lymphoma subtypes have been identified. Molecular prognosticators have also been constructed. Many of the molecular subgroups of lymphoma also show distinct patterns of genetic abnormalities. We also briefly review the application of other genome-wide techniques to the study of lymphomas, such as high resolution array comparative genomic hybridization (aCGH) and next-generation sequencing, and how these technologies will complement each other in improving our understanding of the pathobiology of lymphoma. Specific therapeutic targets will likely emerge from the increased insight into the molecular pathogenesis of the different lymphomas, thus illustrating the utility of these global studies in advancing disease management strategies.
AB - The classification of lymphoid malignancies has evolved from a purely morphological scheme to the current WHO (World Health Organization) classification, which takes into consideration histological, immunophenotypic, genetic and clinical information. DNA microarray technology enables the simultaneous determination of the expression levels for thousands of genes (gene expression profile; GEP) and provides a powerful approach for investigating lymphoma biology and improving disease classification. Distinct molecular signatures for many lymphomas, as well as novel lymphoma subtypes have been identified. Molecular prognosticators have also been constructed. Many of the molecular subgroups of lymphoma also show distinct patterns of genetic abnormalities. We also briefly review the application of other genome-wide techniques to the study of lymphomas, such as high resolution array comparative genomic hybridization (aCGH) and next-generation sequencing, and how these technologies will complement each other in improving our understanding of the pathobiology of lymphoma. Specific therapeutic targets will likely emerge from the increased insight into the molecular pathogenesis of the different lymphomas, thus illustrating the utility of these global studies in advancing disease management strategies.
KW - diffuse large B-cell lymphomas
KW - gene expression profiling
KW - molecular classification
KW - molecular prognosis
KW - peripheral T-cell lymphoma
KW - targeted therapy
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U2 - 10.1016/j.beha.2009.05.001
DO - 10.1016/j.beha.2009.05.001
M3 - Review article
C2 - 19698928
AN - SCOPUS:68749087282
SN - 1521-6926
VL - 22
SP - 191
EP - 210
JO - Best Practice and Research: Clinical Haematology
JF - Best Practice and Research: Clinical Haematology
IS - 2
ER -