Data Availability Sample metadata file are available from GitLab (https://gitlab.com/cruk-mi/tcell-immune-awakening). The data from all TCR sequencing performed for this study are deposited in ImmunoSEQ® Immune ACCESS repository (https://clients.adaptivebiotech.com/ immuneaccess). The RNA-Seq data for patient #12 can be downloaded from EGA (accession code EGAS00001004043). TCR sequencing data for matched pre-treatment and week 3 melanoma biopsy and PBMC samples of locally-advanced melanoma patients 18 re-analyzed here were downloaded from referenced accession EGAS00001003178 EGA study accession dataset EGAD00010001608. TCR sequencing data of matched pre-treatment and week 3 melanoma patient PBMC from AC Huang et al. 7 reanalyzed here were kindly made available by the Authors. TCR sequencing data of matched pre-treatment and week 3 PBMC for the cohort of locally-advanced treatment naive melanoma patients from referenced accession Amaria et al. 18 re-analyzed here were downloaded from EGAS00001003178 EGA study accession dataset EGAD00010001608, patient clinical history metadata file from EGAD00001004352. PBMC and biopsy CyTOF data from Krieg et al. 8 and Greenplate et al. 24 re-analyzed here were downloaded from referenced accession https://flowrepository.org/experiments/1124 and http://flowrepository.org/id/FR-FCM-ZZMC, respectively. PBMC REAP-Seq data from Peterson et al. 27 re-analyzed here were downloaded from referenced accession https:// www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100501. The authors confirm that, for approved reasons (UK Data Protection Act 2018), some access restrictions apply to data containing patient medical records (date of birth). Source data for Fig. 1-7 and Extended Data Fig. 3-6 are provided as Source Data files Fig. 1-7 and Extended Data Fig. 3-6. Additional data that support the findings of this study are available from the corresponding author on reasonable request.

Targeted therapies and immunotherapies have transformed melanoma care, extending median survival from ∼9 to over 25 months, but nevertheless most patients still die of their disease. The aim of precision medicine is to tailor care for individual patients and improve outcomes. To this end, we developed protocols to facilitate individualized treatment decisions for patients with advanced melanoma, analyzing 364 samples from 214 patients. Whole exome sequencing (WES) and targeted sequencing of circulating tumor DNA (ctDNA) allowed us to monitor responses to therapy and to identify and then follow mechanisms of resistance. WES of tumors revealed potential hypothesis-driven therapeutic strategies for BRAF wild-type and inhibitor-resistant BRAF-mutant tumors, which were then validated in patient-derived xenografts (PDX). We also developed circulating tumor cell–derived xenografts (CDX) as an alternative to PDXs when tumors were inaccessible or difficult to biopsy. Thus, we describe a powerful technology platform for precision medicine in patients with melanoma. Significance: Although recent developments have revolutionized melanoma care, most patients still die of their disease. To improve melanoma outcomes further, we developed a powerful precision medicine platform to monitor patient responses and to identify and validate hypothesis-driven therapies for patients who do not respond, or who develop resistance to current treatments. Cancer Discov; 6(3); 286–99. ©2015 AACR. This article is highlighted in the In This Issue feature, p. 217

IntroductionTumour burden is a prognostic biomarker in metastatic melanoma. However, tumour burden is difficult to measure and there are currently no reliable surrogate biomarkers to easily and reliably determine it. The aim of this study was to assess the potential of plasma total cell free DNA as biomarker of tumour burden and prognosis in metastatic melanoma patients.Materials and methodsA prospective biomarker cohort study for total plasma circulating cell-free DNA (cfDNA) concentration was performed in 43 metastatic melanoma patients. For 38 patients, paired blood collections and scan assessments were available before treatment and at first response evaluation. Tumour burden was calculated as the sum of volumes from three-dimensional radiological measurements of all metastatic lesions in individual patients.ResultsBaseline cfDNA concentration correlated with pre-treatment tumour burden (ρ = 0.52, P < 0.001). Baseline cfDNA levels correlated significantly with hazard of death and overall survival, and a cut off value of 89 pg/μl identified two distinct prognostic groups (HR = 2.22 for high cfDNA, P = 0.004). Patients with cfDNA ≥89 pg/μl had shorter OS (10.0 versus 22.7 months, P = 0.009; HR = 2.22 for high cfDNA, P = 0.004) and the significance was maintained when compared with lactic dehydrogenase (LDH) in a multivariate analysis. We also found a correlation between the changes of cfDNA and treatment-related changes in tumour burden (ρ = 0.49, P = 0.002). In addition, the ratio between baseline cfDNA and tumour burden was prognostic (HR = 2.7 for cfDNA/tumour volume ≥8 pg/(μl*cm3), P = 0.024).ConclusionsWe have demonstrated that cfDNA is a surrogate marker of tumour burden in metastatic melanoma patients, and that it is prognostic for overall survival.