Background: In advanced gastric cancer, most of clinical trials are designed based on IHC/in situ hybridization in tissue. However, NGS screening allowed us to comprehensively profile tumor gene status recently. Our goal is to profile both gene alterations and conventional biomarker in gastric cancer for potential molecular targeted therapy. Methods: Formalin-fixed, paraffin-embedded (FFPE) tumor samples from 121 patients with stage III/IV gastric cancer who underwent gastrectomy were examined for HER2, EGFR, c-MET and FGFR2 expression using IHC. In addition, genomic DNA was extracted from each FFPE sample and a total of 15,991 regions in 409 cancer-related genes were sequenced to detect mutations using the Ion AmpliSeq Library kit 2.0 and Comprehensive Cancer Panel. In addition, to evaluate copy number variation of a gene, relative reading depth to the reference (RRDR) of an individual gene was calculated. Amplification was defined as an RRDR greater than 2. Results: The most frequently mutated genes were TP53 (36.4%). In addition, mutations in oncogenes such as PIK3CA (7.4%), ROS1 (4.1%), HER2 (4.1%), MET (1.7%) and ALK (1.7%) were detected. The most frequently amplified gene was SRC (20.7%). Amplification was also detected for other genes such as HER2 (14.9%), CCNE1 (13.2%), CCND1 (9.1%), EGFR (7.4%), KRAS (7.4%), MET (6.6%), RET (3.3%) and FGFR2 (2.5%). The rate of over-expression (IHC 3+) was as follows: HER2 (16.5%), EGFR (23.1%), MET (9.9%) and FGFR2 (14.0%). Most of the cases with HER2 over-expression had HER2 amplification. On the other hand, in a few cases with EGFR/c-MET/FGFR2 over-expression, amplification of these genes was not detected. Over-expression cases with EGFR or FGFR2 had other various gene alterations such as PIK3CA mutations and/or KRAS alterations. In contrast, HER2 or c-MET over-expression cases were mutually exclusive with respect to PIK3CA mutations. Conclusions: We identified several possible candidate genes that could be targets for personalized therapy. Comprehensive analyses including IHC will be necessary to design the optimal therapy with which to treat the right population of patients in future clinical trials.