Addition of chromosomal microarray and next generation sequencing to FISH and classical cytogenetics enhances genomic profiling of myeloid malignancies

Autor: Kristina J. Fasig, Patrick A. Lennon, Dana Tunnel, Terence Casey, Matthew Andreatta, Vladimir Kravtsov, Ian W. Flinn, Malini Sathanoori, James L. Prescott, Pranil Chandra, Scott R. Wheeler, David C. Spence, Zeq Ma, Randall Woodford, Sandeep Mukherjee, Hao Ho, Heather Rietz, Christopher D. Coldren, Mick Correll, Natalia Kozyr, Jesus G. Berdeja, William Donnelan, Mark Bouzyk, Taylor Hartley
Rok vydání: 2016
Předmět:
Zdroj: Cancer genetics.
ISSN: 2210-7762
Popis: Comprehensive genetic profiling is increasingly important for the clinical workup of hematologic tumors, as specific alterations are now linked to diagnostic characterization, prognostic stratification and therapy selection. To characterize relevant genetic and genomic alterations in myeloid malignancies maximally, we utilized a comprehensive strategy spanning fluorescence in situ hybridization (FISH), classical karyotyping, Chromosomal Microarray (CMA) for detection of copy number variants (CNVs) and Next generation Sequencing (NGS) analysis. In our cohort of 569 patients spanning the myeloid spectrum, NGS and CMA testing frequently identified mutations and copy number changes in the majority of genes with important clinical associations, such as TP53, TET2, RUNX1, SRSF2, APC and ATM. Most importantly, NGS and CMA uncovered medically actionable aberrations in 75.6% of cases normal by FISH/cytogenetics testing. NGS identified mutations in 65.5% of samples normal by CMA, cytogenetics and FISH, whereas CNVs were detected in 10.1% cases that were normal by all other methodologies. Finally, FISH or cytogenetics, or both, were abnormal in 14.1% of cases where NGS or CMA failed to detect any changes. Multiple mutations and CNVs were found to coexist, with potential implications for patient stratification. Thus, high throughput genomic tumor profiling through targeted DNA sequencing and CNV analysis complements conventional methods and leads to more frequent detection of actionable alterations.
Databáze: OpenAIRE