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ISSN: 2161-0681

Journal of Clinical & Experimental Pathology
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Chromosome microarray analysis - Changing the landscape of clinical cytogenetics

13th International conference on Pathology and Molecular Diagnosis

M Anwar Iqbal

University of Rochester Medical Center, USA

Posters & Accepted Abstracts: J Clin Exp Pathol

DOI:

Abstract
The conventional technique of G-banded chromosome analysis reliably detects large chromosomal abnormalities and rearrangements at a minimum size of about 3-10 Mb, and requires dividing cells. Its main limitation is that smaller chromosomal deletions or duplications may be overlooked. Fluorescence in situ hybridization (FISH) was developed to rapidly detect smaller chromosomal abnormalities with locus-specific probes, but one must clinically suspect a specific diagnosis associated with a particular chromosome or chromosomal region to request the appropriate probe. Array-based comparative genomic hybridization (aCGH) developed as a method to examine the entire genome for copy number changes caused by deletions, duplications, or whole chromosome aneuploidy. It improved resolution over conventional G-banded karyotype in detecting much smaller chromosomal abnormalities, as small as 50 to 100 kb, and does not require dividing cells. It has become a first-line diagnostic tool for the detection of chromosome abnormalities at both macro and micro level in postnatal, highrisk pregnancies and in products of conception samples. Application of these technologies in cancer research has produced a wealth of useful information about copy number alterations (CNAs), Loss of heterozygosity (LOH) and mutations of specific genes and their implications in cancer classification, disease progression, therapy response, and patient outcome. There is an increasing interest in the genetic diagnostic community in applying this new technology for cancer diagnosis. Our experience on more than 4000 cases performed using the aCGH, and aCGH and SNP arrays in postnatal, prenatal and cancer will be presented.
Biography

Email: anwar_iqbal@urmc.rochester.edu

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