Whole exome sequencing of 94 matched brain metastases and paired primary tumors reveals patterns of clonal evolution and selection of driver mutations. S. L. Carter1, P. K. Brastianos2,3, S. Santagata4, A. Taylor-Weiner1, P. Horowitz4, K. Ligon4, J. Seaone5, E. Martinez-Saez5, J. Tabernero5, D. Cahill3, S. Paek6, I. Dunn4, B. Johnson2, M. Rabin2, N. U. Lin2, R. Jones2, P. Hummelen2, A. Stemmer-Rachamimov3, D. L. Louis3, T. T. Batchelor3, J. Baselga7, R. Beroukhim2, G. Getz1,3, W. C. Hahn2 1) Cancer genome analysis, Broad institute, Cambridge, MA; 2) Dana-Farber Cancer Institute, Boston, MA; 3) Massachusetts General Hospital, Boston, MA; 4) Brigham and Women's Hospital; 5) Vall D'Hebron University Hospital; 6) Seoul National University College of Medicine; 7) Memorial Sloan-Kettering Cancer Center.

   Cancer metastasis to the brain is the most common malignancy of the brain, affecting approximately 200,000 patients per year. Brain metastases are associated with high morbidity and mortality, with a median survival time of 3-4 months. Despite the high incidence, relatively little is known about the molecular mechanisms driving brain metastasis. We subjected 94 trios consisting of primary tumor, brain metastasis, and normal reference tissue to whole exome sequencing (WES). To analyze the data, we developed novel computational tools to derive high quality allelic copy-number profiles directly from the WES data. These were used to perform an integrative analysis of somatic copy-number alterations (SCNAs) and somatic single nucleotide variants (SSNVs). This analysis allowed us to estimate the clonal architecture of the primary and metastatic samples from each patient, and to reconstruct a single phylogenetic tree relating all of the subclones in both samples. Every metastasis developed from a single clone, consistent with a single cell of origin. In some cases, we determined that the primary sample represented an ancestral population with respect to the metastases, based on the presence of subclones present in the primary that became fully clonal in the metastasis. In other cases, we observed fully clonal mutations in the primary sample that were not present in the metastasis, indicating a sibling relationship between the two samples. Subclonal mutations in the metastasis by definition occurred within the brain; these mutations displayed different mutational signatures than those acquired in the primary tumor. These contrasts were most pronounced in cases of lung cancer or melanoma, with tobacco and UV signatures prominent in these primaries and nearly absent from the mutations acquired after metastasis. In order to understand the molecular drivers of clonal evolution and metastasis in our data, we annotated each subclone with driver mutations identified using large numbers of cancer samples analyzed by the cancer genome atlas (TCGA) consortium. This produced a detailed portrait of each patients cancer, with nearly node in each phylogenetic tree associated with at least one driver mutation.

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