Genome-wide allelic state analysis on flow-sorted tumor fractions provides an accurate measure of chromosomal aberrations.

Chromosomal aberrations are a common characteristic of cancer and are associated with copy number abnormalities and loss of heterozygosity (LOH). Tumor heterogeneity, low tumor cell percentage, and lack of knowledge of the DNA content impair the identification of these alterations especially in aneuploid tumors. To accurately detect allelic changes in carcinomas, we combined flow-sorting and single nucleotide polymorphism arrays. Cells derived from archival cervical and colon cancers were flow-sorted based on differential vimentin and keratin expression and DNA content and analyzed on single nucleotide polymorphism arrays. A new algorithm, the lesser allele intensity ratio, was used to generate a molecular measure of chromosomal aberrations for each case. Flow-sorting significantly improved the detection of copy number abnormalities; 31.8% showed an increase in amplitude and 23.2% were missed in the unsorted fraction, whereas 15.9% were detected but interpreted differently. Integration of the DNA index in the analysis enabled the identification of the allelic state of chromosomal aberrations, such as LOH ([A]), copy-neutral LOH ([AA]), balanced amplifications ([AABB]), and allelic imbalances ([AAB] or [AAAB], etc.). Chromosomal segments were sharply defined. Fluorescence in situ hybridization copy numbers, as well as the high similarity between the DNA index and the allelic state index, which is the average of the allelic states across the genome, validated the method. This new approach provides an individual molecular measure of chromosomal aberrations and will likely have repercussions for preoperative molecular staging, classification, and prognostic profiling of tumors, particularly for heterogeneous aneuploid tumors, and allows the study of the underlying molecular genetic mechanisms and clonal evolution of tumor subpopulations.