Distinctive Genomic Signature Patterns Of Common Hematological Malignancies Uncovered By Chromosomal Microarray Analysis (Cma) Using A Cancer Specific Microarray

The application of chromosomal microarray analysis (CMA) in cancer research has produced a wealth of useful information about copy number alterations (CNAs) and their implications in cancer classification, disease progression, therapy response, and patient outcome. However, only a handful of clinical laboratories are offering CMA for cancer diagnosis. This is largely due to the lack of effective diagnostic standards and guidelines for cancer applications, and the absence of a cancer microarray database to aid in post-analytic interpretation. We have designed a combined targeted-/whole-genome array specific for cancer using the microarray CGH format. Approximately 20,000 high quality oligonucleotide probes were selected from the Agilent Tech. (Santa Clara, CA) eArray system to target all exons and exon/intron boundaries of more than 500 cancer genes, over 100 known cancer-associated genomic regions and all subtelomeric chromosome regions. Intervals between aforementioned genes or regions were filled relatively evenly with oligonucleotide probes to cover the whole genome. Using this custom designed array, we studied 250 cases of hematological malignancies and 30 normal bone marrow or blood controls. In addition to confirming and clarifying cytogenetic and FISH results, the array revealed many previously unknown CNAs, including intra-gene deletions and duplications in patients with normal or abnormal karyotype. Many apparently balanced translocations were found to harbor cryptic CNAs at or near the breakpoints. Many CNAs displayed strong association with specific category of malignancies. GeneSpring Hierarchical Clustering analysis showed distinctive genomic signature patterns for different types or sub-types of haematological cancers. Using BlueFuse Multi software, we were able to create a few disease classification/decision tracks, which are of great clinical significance in post-analytic interpretation and genotype-phenotype correlation for cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 314. doi:10.1158/1538-7445.AM2011-314