It is now well established that cell-free tumor DNA is released into the blood of cancer patients. In theory, this presents a potentially powerful opportunity to develop biomarkers for a variety of clinical applications including cancer detection, monitoring of response to therapy and detection of recurrent disease. To date however, this potential remains mostly unrealized. This is due to several factors. First, circulating, cell-free DNA is found at low concentrations (ng/ml) in plasma/serum and is mostly present as small fragments. This has historically made isolation of adequate DNA quantities for testing difficult. In addition, the majority of circulating, cell-free DNA is from normal cells not tumor cells, thus presenting a needle in a haystack problem. Finally, widely available and robust analytical tools capable of detecting rare, tumor-associated DNA alterations have for the most part been lacking. Furthermore, those tools that are available require a priori knowledge of the specific tumor-associated mutations to be detected in the plasma and therefore are not suitable for de novo cancer detection tests. In this application, we will use novel data and innovative technologies in order to overcome these issues and to determine the potential of circulating, cell-free tumor DNA as a biomarker for detection and treatment monitoring in patients with esophageal adenocarcinoma (EAC). Specifically, we will use a multiplex PCR- based pre-amplification technology (AmpliSeq(tm)) to generate next-generation sequencing libraries targeting >66Kb of DNA from the coding regions of 20 genes found to be frequently mutated in EAC. This technology is specifically designed to be compatible with nanogram inputs of highly fragmented DNA and we have successfully used it to sequence the 20 genes in tumor samples and in cell-free DNA from plasma. Average per-base read depth using Ion Torrent semi-conductor sequencing in these samples is >2000x and can easily be increased further. Thus we believe that we can detect mutations at any base in the target genes with detection sensitivity of 0.5% tumor DNA fraction or less. Complementing this novel sequencing approach, we will use another new technology, droplet digital PCR (ddPCR), to quantify tumor associated mutations in plasma with even lower sensitivity (<0.001%). In Specific Aim 1, these technologies combined will allow us to determine the feasibility of a next-generation, deep sequencing-based approach to cancer detection. Next, we will use these same technologies to address another important clinical issue in the management of patients with EAC: dynamic monitoring of response to neoadjuvant therapy. Up to 40% of patients do not respond to neoadjuvant therapy and are thus exposed to the associated toxicity and cost without benefit. Furthermore, potentially curative surgical therapy is delayed in these patients, some of whom progress to the point where surgery is no longer an option. In Specific Aim 2, we will use ddPCR to determine whether circulating tumor DNA load can be used to rapidly and dynamically identify response or resistance to neoadjuvant therapy.