Detection of somatic mutations in tumors using unaligned clonal sequencing data.

Most cancers arise and evolve as a consequence of somatic mutations. These mutations influence tumor behavior and clinical outcome. Consequently, there is considerable interest in identifying somatic variants within specific genes (such as BRAF, KRAS and EGFR) so that chemotherapy can be tailored to the patient's tumor genotype rather than using a generic treatment based on histological diagnosis alone. Owing to the heterogeneous nature of tumors, a somatic mutation may be present in only a subset of cells, necessitating the use of quantitative techniques to detect rare variants. The highly quantitative nature of next-generation sequencing (NGS), together with the ability to multiplex numerous samples, makes NGS an attractive choice with which to screen for somatic variants. However, the large volumes of sequence data present significant difficulties when applying NGS for the detection of somatic mutations. To alleviate this, we have developed methodologies including a set of data analysis programs, which allow the rapid screening of multiple formalin-fixed, paraffin-embedded samples for the presence of specified somatic variants using unaligned Illumina NGS data.