Estimation of tumor heterogeneity using CGH array data

Background: Array-based comparative genomic hybridization (CGH) is a commonly-used approach to detect DNA copy number variation in whole genome-wide screens. Several statistical methods have been proposed to define genomic segments with different copy numbers in cancer tumors. However, most tumors are heterogeneous and show variation in DNA copy numbers across tumor cells. The challenge is to reveal the copy number profiles of the subpopulations in a tumor and to estimate the percentage of each subpopulation. Results: We describe a relation between experimental data and exact DNA copy number and develop a statistical method to reveal the heterogeneity of tumors containing a mixture of different-stage cells. Furthermore, we validate the method on simulated data and apply the method to 29 pairs of breast primary tumors and their matched lymph node metastases. Conclusion: We demonstrate a new method for CGH array analysis that allows a tumor sample to be classified according to its heterogeneity. The method gives an interpretable series of copy number profiles, one for each major subpopulation in a tumor. The profiles facilitate identification of copy number alterations in cancer development.