scholarly journals Digital gene expression profiling of primary acute lymphoblastic leukemia cells

Leukemia ◽  
2011 ◽  
Vol 26 (6) ◽  
pp. 1218-1227 ◽  
Author(s):  
J Nordlund ◽  
A Kiialainen ◽  
O Karlberg ◽  
E C Berglund ◽  
H Göransson-Kultima ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Lymphoblastic Leukemia ◽  
Digital Gene Expression ◽  
Leukemia Cells ◽  
Digital Gene Expression Profiling

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

2006 ◽  
Vol 130 (4) ◽  
pp. 483-520 ◽  
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.

scholarly journals Digital Gene Expression Profiling Analysis of Aged Mice under Moxibustion Treatment

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Nan Liu ◽  
Yunyao Jiang ◽  
Min Xing ◽  
Baixiao Zhao ◽  
Jincai Hou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Ontology ◽  
Gene Expression Profiling ◽  
Differentially Expressed Genes ◽  
Pathway Analysis ◽  
Expression Profiling ◽  
Digital Gene Expression ◽  
Differentially Expressed ◽  
Aged Mice ◽  
Digital Gene Expression Profiling

Aging is closely connected with death, progressive physiological decline, and increased risk of diseases, such as cancer, arteriosclerosis, heart disease, hypertension, and neurodegenerative diseases. It is reported that moxibustion can treat more than 300 kinds of diseases including aging related problems and can improve immune function and physiological functions. The digital gene expression profiling of aged mice with or without moxibustion treatment was investigated and the mechanisms of moxibustion in aged mice were speculated by gene ontology and pathway analysis in the study. Almost 145 million raw reads were obtained by digital gene expression analysis and about 140 million (96.55%) were clean reads. Five differentially expressed genes with an adjusted P value < 0.05 and |log⁡2(fold  change)| > 1 were identified between the control and moxibustion groups. They were Gm6563, Gm8116, Rps26-ps1, Nat8f4, and Igkv3-12. Gene ontology analysis was carried out by the GOseq R package and functional annotations of the differentially expressed genes related to translation, mRNA export from nucleus, mRNA transport, nuclear body, acetyltransferase activity, and so on. Kyoto Encyclopedia of Genes and Genomes database was used for pathway analysis and ribosome was the most significantly enriched pathway term.

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