Abstract 167: Inferring subclonal relationships between multiple metastases from rapid autopsy of a single melanoma patient

Abstract Background: Despite recent advances in personalized cancer therapeutics, little impact has been made on curing advanced melanomas over the last several decades. Patients with metastatic melanoma generally have a poor prognosis; survival is limited and typically the 5-year survival rate is less than 15% in patients with metastatic disease. Dysregulation of BRAF signaling has been shown to be one of these key drivers of the pathogenesis of disease in a large subpopulation (∼40%) of patients. Although targeted therapy with BRAF and MEK inhibitors is the mainstay of therapy for recurrent/metastatic melanomas, this treatment modality provides a temporary respite. Often resistant tumor clones(carrying mutations in oncogenes) emerge, followed by a rapid progression, causing the patients to succumb to the disease. As such, in this study, we aim to understand inter- and intra- tumor heterogeneity that leads to resistance to therapy. Methods: We conducted deep exome sequence analysis (250X coverage) of a collection of 8 metastatic melanoma tumor samples collected by rapid autopsy from a patient who became resistant to Vemurafinib despite harboring sensitizing BRAF p. V600E mutations. We used whole exome sequence analysis to detect somatic mutations and copy number variants in every metastatic tumor. To infer subclonal populations present within each metastasis, we applied a combination of clonal inference tools to determine subclonal structures based on somatic point mutations (PyClone) and copy number alterations (TITAN). Subsequently, we applied clustering algorithms to the inferred populations to construct inter-tumor phylogenies. Results: We found that 89% of somatic point mutations were shared across all metastatic sites and were primarily clonal. Conversely, the cellular prevalence inferred from copy number alterations showed a greater degree of subclonal evolution. We found a clear relationship between the physical locations of tumors and shared subclonal patterns, whereby metastases from lung, brain and omentum metastases clustered distinctly from those in rectum, small intestine, peritoneum, diaphragm and mesentery. To look for shared patterns of subclonal variation underlying metastatic disease and resistance to therapy, we are currently extending our analysis to an additional six patients, each with tissues from 7-9 metastatic sites collected by rapid autopsy. Conclusion: Our analysis of multiple metastatic sites from a single patient by deep exome sequence analysis found most somatic mutations were shared across tumor sites and subclonal evolution appears to be driven primarily by acquisition of copy number alterations. Tumors in near proximity shared greater genomic similarity compare to distant sites. Ongoing analysis of additional patients is required to uncover recurrent mechanisms of resistance to targeted therapies in this disease. Citation Format: Soroush Samadian, Prashant Bavi, Dianne Chadwick, Arnavaz Danesh, Mark Dowar, Tiantian Li, Madura Siva, Michael Roehl, Anthony m. Joshua, Trevor J. Pugh. Inferring subclonal relationships between multiple metastases from rapid autopsy of a single melanoma patient. [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 167.

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