Esophageal adenocarcinoma (EAC) has one of the fastest increases in incidence of any cancer, along with poor five-year survival rates. Barrett's esophagus (BE) is the main risk factor for EAC; however, the mechanisms driving EAC development remain poorly understood. Here, transcriptomic profiling was performed using RNA-sequencing (RNA-seq) on premalignant and malignant Barrett's tissues to better understand this disease. Machine-learning and network analysis methods were applied to discover novel driver genes for EAC development. Identified gene expression signatures for the distinction of EAC from BE were validated in separate datasets. An extensive analysis of the noncoding RNA (ncRNA) landscape was performed to determine the involvement of novel transcriptomic elements in Barrett's disease and EAC. Finally, transcriptomic mutational investigation of genes that are recurrently mutated in EAC was performed. Through these approaches, novel driver genes were discovered for EAC, which involved key cell cycle and DNA repair genes, such as BRCA1 and PRKDC. A novel 4-gene signature (CTSL, COL17A1, KLF4, and E2F3) was identified, externally validated, and shown to provide excellent distinction of EAC from BE. Furthermore, expression changes were observed in 685 long noncoding RNAs (lncRNA) and a systematic dysregulation of repeat elements across different stages of Barrett's disease, with wide-ranging downregulation of Alu elements in EAC. Mutational investigation revealed distinct pathways activated between EAC tissues with or without TP53 mutations compared with Barrett's disease. In summary, transcriptome sequencing revealed altered expression of numerous novel elements, processes, and networks in EAC and premalignant BE. This study identified opportunities to improve early detection and treatment of patients with BE and esophageal adenocarcinoma. .