Fulltext:
98100.pdf
Embargo:
until further notice
Size:
675.2Kb
Format:
PDF
Description:
Publisher’s version
Publication year
2011Source
Genes, Chromosomes & Cancer, 50, 12, (2011), pp. 969-81ISSN
Publication type
Article / Letter to editor
Display more detailsDisplay less details
Organization
Human Genetics
Paediatrics - OUD tm 2017
Journal title
Genes, Chromosomes & Cancer
Volume
vol. 50
Issue
iss. 12
Page start
p. 969
Page end
p. 81
Subject
NCMLS 6: Genetics and epigenetic pathways of disease ONCOL 3: Translational researchAbstract
In acute lymphoblastic leukemia (ALL) specific genomic abnormalities provide important clinical information. In most routine clinical diagnostic laboratories conventional karyotyping, in conjunction with targeted screens using e.g., fluorescence in situ hybridization (FISH), is currently considered as the gold standard to detect such aberrations. Conventional karyotyping, however, is limited in its resolution and yield, thus hampering the genetic diagnosis of ALL. We explored whether microarray-based genomic profiling would be feasible as an alternative strategy in a routine clinical diagnostic setting. To this end, we compared conventional karyotypes with microarray-deduced copy number aberration (CNA) karyotypes in 60 ALL cases. Microarray-based genomic profiling resulted in a CNA detection rate of 90%, whereas for conventional karyotyping this was 61%. In addition, many small (< 5 Mb) genetic lesions were encountered, frequently harboring clinically relevant ALL-related genes such as CDKN2A/B, ETV6, PAX5, and IKZF1. From our data we conclude that microarray-based genomic profiling serves as a robust tool in the genetic diagnosis of ALL, outreaching conventional karyotyping in CNA detection both in terms of sensitivity and specificity. We also propose a practical workflow for a comprehensive and objective interpretation of CNAs obtained through microarray-based genomic profiling, thereby facilitating its application in a routine clinical diagnostic setting.
This item appears in the following Collection(s)
- Academic publications [243984]
- Electronic publications [130695]
- Faculty of Medical Sciences [92811]
Upload full text
Use your RU credentials (u/z-number and password) to log in with SURFconext to upload a file for processing by the repository team.