Personalized medicine uses genomic information for selecting therapy in patients with metastatic cancer. An issue is the optimal tissue source (primary tumor or metastasis) for testing. We compared the DNA copy number and mutational profiles of primary breast cancers and paired metastases from 23 patients using whole-genome array-comparative genomic hybridization and next-generation sequencing of 365 "cancer-associated" genes. Primary tumors and metastases harbored copy number alterations (CNAs) and mutations common in breast cancer and showed concordant profiles. The global concordance regarding CNAs was shown by clustering and correlation matrix, which showed that each metastasis correlated more strongly with its paired tumor than with other samples. Genes with recurrent amplifications in breast cancer showed 100% (ERBB2, FGFR1), 96% (CCND1), and 88% (MYC) concordance for the amplified/non-amplified status. Among all samples, 499 mutations were identified, including 39 recurrent (AKT1, ERBB2, PIK3CA, TP53) and 460 non-recurrent variants. The tumors/metastases concordance of variants was 75%, higher for recurrent (92%) than for non-recurrent (73%) variants. Further mutational discordance came from very different variant allele frequencies for some variants. We showed that the chosen targeted therapy in two clinical trials of personalized medicine would be concordant in all but one patient (96%) when based on the molecular profiling of tumor and paired metastasis. Our results suggest that the genotyping of primary tumor may be acceptable to guide systemic treatment if the metastatic sample is not obtainable. However, given the rare but potentially relevant divergences for some actionable driver genes, the profiling of metastatic sample is recommended.
Keywords: array-CGH; breast cancer; genomics; metastasis; sequencing.