Microarray expression technology in clinical research of non-Hodgkin lymphoma

Nowadays, in genomocentric era accelerated research of the human genome coupled with advances is enabling the comprehensive molecular profiling of human tissue. Particularly, DNA microarrays are powerful tools for obtaining global view of human non-Hodgkin lymphomas gene expression. Complex information from lymphomas "expression profiling" studies can, in turn, be used to create molecular markers that have diagnostic or prognostic implications. The gene "expression profiling" is not of routine clinical oncology practice, but is used in genomic classification of clinically relevant subgroups of non-Hodgkin lymphoma. The genomics biomarkers have been incorporated into current prognostic models which are based on IPI, R-IPI, and FLIPI. Molecular or pharmacogenomic profiling can be used as new therapeutic targets for patients who are refractory to current therapy. We discus the utility of DNA microarray-based lymphoma profiling in clinical oncology research, and identify future of research in lymphoma evolving fields.

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Targetable subsets of non-Hodgkin lymphoma in Malawi define therapeutic opportunities

Blood Advances ◽

10.1182/bloodadvances.2016000026 ◽

2016 ◽

Vol 1 (1) ◽

pp. 84-92 ◽

Cited By ~ 3

Author(s):

Elizabeth A. Morgan ◽

M. Patrick Sweeney ◽

Tamiwe Tomoka ◽

Nadja Kopp ◽

Daniel Gusenleitner ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profiling ◽

Hodgkin Lymphoma ◽

Expression Profiling ◽

Resource Constraints ◽

Objective Assessment ◽

Non Hodgkin Lymphoma ◽

Key Points ◽

Targeted Gene Expression

Key Points NHL subclassification is lacking in Malawi due to resource constraints yet is critical for directing therapy. Targeted gene expression profiling facilitates objective assessment and segregation of biologically defined subsets of NHL from Malawi.

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Combining gene expression profiling and machine learning to diagnose B-cell non-Hodgkin lymphoma

Blood Cancer Journal ◽

10.1038/s41408-020-0322-5 ◽

2020 ◽

Vol 10 (5) ◽

Author(s):

Victor Bobée ◽

Fanny Drieux ◽

Vinciane Marchand ◽

Vincent Sater ◽

Liana Veresezan ◽

...

Keyword(s):

Gene Expression ◽

Machine Learning ◽

B Cell ◽

Gene Expression Profiling ◽

Hodgkin Lymphoma ◽

Expression Profiling ◽

Non Hodgkin Lymphoma

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DNA Microarrays in Clinical Oncology

Journal of Clinical Oncology ◽

10.1200/jco.2002.20.7.1932 ◽

2002 ◽

Vol 20 (7) ◽

pp. 1932-1941 ◽

Cited By ~ 245

Author(s):

Sridhar Ramaswamy ◽

Todd R. Golub

Keyword(s):

Gene Expression ◽

Clinical Oncology ◽

Expression Profiling ◽

Dna Microarrays ◽

Human Cancer ◽

Clinical Applications ◽

Cancer Gene ◽

Comprehensive Understanding ◽

Aberrant Gene Expression ◽

Aberrant Gene

ABSTRACT: Aberrant gene expression is critical for tumor initiation and progression. However, we lack a comprehensive understanding of all genes that are aberrantly expressed in human cancer. Recently, DNA microarrays have been used to obtain global views of human cancer gene expression and to identify genetic markers that might be important for diagnosis and therapy. We review clinical applications of these novel tools, discuss some important recent studies, identify promising avenues of research in this emerging field of study, and discuss the likely impact that expression profiling will have on clinical oncology.

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Gene Expression Profiling and Outcome Prediction in Non-Hodgkin Lymphoma

Biology of Blood and Marrow Transplantation ◽

10.1016/j.bbmt.2005.10.017 ◽

2006 ◽

Vol 12 (1) ◽

pp. 50-52 ◽

Cited By ~ 3

Author(s):

Sandeep Dave

Keyword(s):

Gene Expression ◽

Gene Expression Profiling ◽

Hodgkin Lymphoma ◽

Expression Profiling ◽

Outcome Prediction ◽

Non Hodgkin Lymphoma

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Preparation of Salmonella enterica Serovar Typhi Genomic DNA Microarrays for Gene Expression Profiling Analysis*

PROGRESS IN BIOCHEMISTRY AND BIOPHYSICS ◽

10.3724/sp.j.1206.2008.00373 ◽

2009 ◽

Vol 2009 (2) ◽

pp. 206-212 ◽

Cited By ~ 5

Author(s):

Xiu-Mei SHENG ◽

Xin-Xiang HUANG ◽

Ling-Xiang MAO ◽

Chao-Wang ZHU ◽

Shun-Gao XU ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profiling ◽

Expression Profiling ◽

Salmonella Enterica ◽

Genomic Dna ◽

Dna Microarrays ◽

Profiling Analysis

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Gene expression profiling of wound healing in keratinocytes using DNA microarrays

Nature Genetics ◽

10.1038/14336 ◽

1999 ◽

Vol 23 (S3) ◽

pp. 54-54

Author(s):

Claire Johnson ◽

Frank Burslem ◽

Jerry Lanfear

Keyword(s):

Gene Expression ◽

Wound Healing ◽

Gene Expression Profiling ◽

Expression Profiling ◽

Dna Microarrays

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Gene Expression Profiling Data in Lymphoma and Leukemia: Review of the Literature and Extrapolation of Pertinent Clinical Applications

Archives of Pathology & Laboratory Medicine ◽

10.5858/2006-130-483-gepdil ◽

2006 ◽

Vol 130 (4) ◽

pp. 483-520 ◽

Cited By ~ 2

Author(s):

Cherie H. Dunphy

Keyword(s):

Gene Expression ◽

Acute Lymphoblastic Leukemia ◽

B Cell ◽

Gene Expression Profiling ◽

Hodgkin Lymphoma ◽

Expression Profiling ◽

Myeloid Leukemia ◽

Lymphoblastic Leukemia ◽

B Cell Lymphoma ◽

Clinical Applications

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.

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