Background: The tumor related gene profiling in esophageal cancer is further required to accelerate the development of novel molecular-targeting drugs. The aim of this study was to evaluate gene alteration profiles of in cancer-related genes in esophageal cancer patients and to correlate them with clinicopathological features, such as smoking status and survival outcomes. Methods: Surgically resected formalin-fixed, paraffin-embedded (FFPE) tissue was collected from 135 consecutive patients with esophageal cancer who underwent esophagectomy at the Shizuoka Cancer Center and University of Toyama between October 2002 and November 2011. Based on the assessment of DNA quality with a quantitative PCR (qPCR)-based assay, uracil DNA glycosylase pretreatment was performed to ensure quality and accuracy of amplicon-based massively parallel sequencing (MPS). Amplicon-based MPS was performed using the Illumina TruSeq Amplicon Cancer Panel. Gene amplification was detected by qPCR-based assay. Protein expression of HER2, MET, EGFR, ALK and HGF was determined by automated quantitative fluorescent immunohistochemistry. Prognostic factors associated with survival were identified by multivariate analyses using the Cox proportional hazards model. Results: Data on genetic alterations was available in 126 patients. Amplicon-based MPS identified frequent gene alterations in TP53 (66.7%), PIK3CA (13.5%), APC (10.3%), ERBB4 (7.9%), FBXW7 (7.9%). There was no association between clinicopathological features or prognosis with smoking status. Multivariate analyses revealed that the PIK3CA mutation and clinical T stage were independent favorable prognostic factors (hazard ratio 0.34, 95% confidence interval: 0.12-0.96, p = 0.042). PIK3CA mutations were significantly associated with APC alterations (p = 0.0007) and BRAF mutations (p = 0.0090). Conclusions: Our study provided profiles of cancer-related genes in Japanese patients with esophageal cancer by next-generation sequencing using surgically resected FFPE tissue, and identified the PIK3CA mutation as a favorable prognosis biomarker.