Acute lymphoblastic leukemia in children and SALL4 and BMI-1 gene expression

2021 ◽  
Author(s):  
Hossam Hodeib ◽  
Doaa El Amrousy ◽  
Amira Youssef ◽  
Rasha Khedr ◽  
Hassan Al-Asy ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
Lymphoblastic Leukemia ◽  
Leukemia In Children

Gene Expression Profiling of Acute Lymphoblastic Leukemia in Children with Very Early Relapse

2016 ◽  
Vol 47 (8) ◽  
pp. 644-655 ◽  
Author(s):  
Juan Carlos Núñez-Enríquez ◽  
Diego Alberto Bárcenas-López ◽  
Alfredo Hidalgo-Miranda ◽  
Elva Jiménez-Hernández ◽  
Vilma Carolina Bekker-Méndez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Lymphoblastic Leukemia ◽  
Early Relapse ◽  
Leukemia In Children

Physician compliance and relapse rates of acute lymphoblastic leukemia in children

1988 ◽  
Vol 43 (3) ◽  
pp. 228-232 ◽  
Author(s):  
Marie Peeters ◽  
Gideon Koren ◽  
Difat Jakubovicz ◽  
Alvin Zipursky
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
Lymphoblastic Leukemia ◽  
Physician Compliance ◽  
Relapse Rates ◽  
Leukemia In Children

High-Dose Cyclophosphamide for the Treatment of Refractory T-Cell Acute Lymphoblastic Leukemia in Children

2014 ◽  
Vol 36 (5) ◽  
pp. e265-e270 ◽  
Author(s):  
Rachel Kobos ◽  
Neerav Shukla ◽  
Thomas Renaud ◽  
Susan E. Prockop ◽  
Farid Boulad ◽  
...  
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
T Cell ◽  
Lymphoblastic Leukemia ◽  
High Dose ◽  
Cell Acute Lymphoblastic Leukemia ◽  
Leukemia In Children

scholarly journals CDX2 gene expression in acute lymphoblastic leukemia

2014 ◽  
Vol 26 (2) ◽  
pp. 55-59 ◽  
Author(s):  
Hanaa H. Arnaoaut ◽  
Doha A. Mokhtar ◽  
Rania M. Samy ◽  
Sahar A. Khames ◽  
Shereen A. Omar
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
Lymphoblastic Leukemia

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.

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