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
2006 ◽  
Vol 130 (4) ◽  
pp. 483-520 ◽  
Author(s):  
Cherie H. Dunphy

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.


Genes ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 376 ◽  
Author(s):  
Vanessa Villegas-Ruíz ◽  
Karina Olmos-Valdez ◽  
Kattia Alejandra Castro-López ◽  
Victoria Estefanía Saucedo-Tepanecatl ◽  
Josselen Carina Ramírez-Chiquito ◽  
...  

Droplet digital PCR is the most robust method for absolute nucleic acid quantification. However, RNA is a very versatile molecule and its abundance is tissue-dependent. RNA quantification is dependent on a reference control to estimate the abundance. Additionally, in cancer, many cellular processes are deregulated which consequently affects the gene expression profiles. In this work, we performed microarray data mining of different childhood cancers and healthy controls. We selected four genes that showed no gene expression variations (PSMB6, PGGT1B, UBQLN2 and UQCR2) and four classical reference genes (ACTB, GAPDH, RPL4 and RPS18). Gene expression was validated in 40 acute lymphoblastic leukemia samples by means of droplet digital PCR. We observed that PSMB6, PGGT1B, UBQLN2 and UQCR2 were expressed ~100 times less than ACTB, GAPDH, RPL4 and RPS18. However, we observed excellent correlations among the new reference genes (p < 0.0001). We propose that PSMB6, PGGT1B, UBQLN2 and UQCR2 are housekeeping genes with low expression in childhood cancer.


2006 ◽  
Vol 103 (21) ◽  
pp. 8167-8172 ◽  
Author(s):  
J. C. Strefford ◽  
F. W. van Delft ◽  
H. M. Robinson ◽  
H. Worley ◽  
O. Yiannikouris ◽  
...  

PLoS ONE ◽  
2019 ◽  
Vol 14 (12) ◽  
pp. e0224652
Author(s):  
Mingmin Wang ◽  
Jinquan Wen ◽  
Yuxia Guo ◽  
Yali Shen ◽  
Xizhou An ◽  
...  

2010 ◽  
Vol 59 (11) ◽  
pp. 1633-1644 ◽  
Author(s):  
Jessica C. Shand ◽  
Johan Jansson ◽  
Yu-Chiao Hsu ◽  
Andrew Campbell ◽  
Craig A. Mullen

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 1959-1959
Author(s):  
Meyling H. Cheok ◽  
Cong Ding ◽  
Wenjian Yang ◽  
Somas Das ◽  
Dario Campana ◽  
...  

Abstract Acute lymphoblastic leukemia (ALL) in children is a paradigm of disseminated cancer that is curable with chemotherapy, yet current treatment fails to cure about 20% of patients, for reasons that remain unknown. In a genome-wide assessment of in vivo treatment-induced changes in gene expression in ALL cells using the Affymetrix U95A and U133A oligonucleotide microarray, we found that patients who eventually relapsed did not up-regulate expression of the pro-apoptotic beta-2 adrenergic receptor gene (ADRB2) in their ALL cells after initial treatment with methotrexate and mercaptopurine. After treatment we observed a 5-fold lower level of ADRB2 gene expression in leukemia cells of patients who ultimately relapsed. We found a common genetic polymorphism in the ADRB2 promoter that was significantly linked to high-dose methotrexate induced up-regulation in ADRB2 gene expression in ALL cells. Moreover, the ADRB2 promoter haplotype was significantly linked to poor early treatment response in ALL cells from 242 children (i.e., probability of event-free survival at two years, p=0.0275 stratified by risk groups). These findings have revealed a germline polymorphism that is linked to the early antileukemic effects of ALL chemotherapy and provide new insights into genetic determinants of ALL treatment efficacy.


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