Abstract LB-340: A novel method for estimating somatic mutations cellular prevalence in cancer using whole genome haplotype phasing

Abstract The process of malignant transformation results in the acquisition of complex chromosomal copy number alterations and somatic mutations. Moreover, cancer exhibits extensive intra-tumor heterogeneity with multiple sub-populations of tumor cells containing both common and private genomic alterations. Within- and between-patient tumor heterogeneity is now seen as one of the major obstacles for precision medicine and the development of effective treatment strategies. Revealing the proportion of cells affected by particular somatic changes is emerging as a key factor for designing targeted therapies, characterizing tumor evolution and understanding chemotherapy-resistance mechanisms. Determining the proportion of cells harboring a particular mutation (the so called cellular prevalence) is a difficult task as it is confounded by several variables. Normal cell contamination, local copy number profile and the temporal relationship between the mutation and the copy number alteration represent some of the key variables. In order to more effectively quantify the cellular prevalence of somatic mutations we developed a novel method, which uses a combination of side, and haplotype phase information obtained from long fragment read sequencing to more accurately compute mutational prevalence. The method utilizes three sources of information: the phasing information, the copy number variation and the allele counts for prevalence estimation using a simple equation in both a linear and a non-linear form. We present theoretical examples of known genomics alterations and show using simulation that our method was able to accurately estimate the cellular prevalence compared to standard methods. We also apply our method to a real data set obtained from dense long fragment read sequencing of a single ovarian cancer and demonstrate the highly accurate estimation of cellular prevalence. Finally we provide an implementation of the method in the statistical software. Citation Format: Donatien Chedom-Fotso, Ahmed Ahmed, Christopher Yau. A novel method for estimating somatic mutations cellular prevalence in cancer using whole genome haplotype phasing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-340.