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Gene expression profiling data in lymphoma and leukemia: review of the literature and extrapolation of pertinent clinical applications.

作者信息

Dunphy Cherie H

机构信息

Department of Pathology and Laboratory Medicine, The University of North Carolina, Chapel Hill, NC 27599-7525, USA.

出版信息

Arch Pathol Lab Med. 2006 Apr;130(4):483-520. doi: 10.5858/2006-130-483-GEPDIL.

Abstract

CONTEXT

Gene expression (GE) analyses using microarrays have become an important part of biomedical and clinical research in hematolymphoid malignancies. However, the methods are time-consuming and costly for routine clinical practice.

OBJECTIVES

To review the literature regarding GE data that may provide important information regarding pathogenesis and that may be extrapolated for use in diagnosing and prognosticating lymphomas and leukemias; to present GE findings in Hodgkin and non-Hodgkin lymphomas, acute leukemias, and chronic myeloid leukemia in detail; and to summarize the practical clinical applications in tables that are referenced throughout the text.

DATA SOURCE

PubMed was searched for pertinent literature from 1993 to 2005.

CONCLUSIONS

Gene expression profiling of lymphomas and leukemias aids in the diagnosis and prognostication of these diseases. The extrapolation of these findings to more timely, efficient, and cost-effective methods, such as flow cytometry and immunohistochemistry, results in better diagnostic tools to manage the diseases. Flow cytometric and immunohistochemical applications of the information gained from GE profiling assist in the management of chronic lymphocytic leukemia, other low-grade B-cell non-Hodgkin lymphomas and leukemias, diffuse large B-cell lymphoma, nodular lymphocyte-predominant Hodgkin lymphoma, and classic Hodgkin lymphoma. For practical clinical use, GE profiling of precursor B acute lymphoblastic leukemia, precursor T acute lymphoblastic leukemia, and acute myeloid leukemia has supported most of the information that has been obtained by cytogenetic and molecular studies (except for the identification of FLT3 mutations for molecular analysis), but extrapolation of the analyses leaves much to be gained based on the GE profiling data.

摘要

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