Signet ring cell carcinoma (SRCC) is a histological subtype of gastric tumors. It presents uniqueness in cellular morphology, epidemiology and clinicopathology as compared with other subtypes of gastric tumors, especially the adenocarcinomas (ACs). Rising in the incidence trend of gastric SRCC and lacking of practicable diagnosis for this disease prompt an urgent and valuable deed to globally portray gene expression patterns in gastric SRCC. In this project, the resected gastric tissues were collected and examined with inter-subtype matching in epidemiology and clinicopathology, resulting in 14 SRCC and 34 AC cases. Laser capture microdissection (LCM) was employed to reduce cellular heterogeneity of the tissues. Over 6,000 proteins were identified and quantified through mass spectrometry (MS) with data independent acquisition (DIA). Based on the quantitative proteomics, the differentially expressed proteins (DEPs) between tumor and adjacent tissues that were shared by SRCC and ACs were commonly enriched to extra cellular matrix and energy metabolism related pathways, while the DEPs baring the differences between SRCC and ACs were highlighted in some pathways, especially in complement cascade, which was more abundant in SRCC than ACs and its SRCC association was observed for the first time. Moreover, as an attempt to guide selection of appropriate cell models for gastric SRCC, proteomes of 15 gastric cell lines were probed and their subtype representativeness were clarified by machine learning-based classifier trained with the gastric tumor data. It turned out that all the cell lines including 3 originated from gastric SRCC, KATO-3, GCSR-1 and SNU-668, were more AC-like than SRCC-like, while MKN-7, a gastric adenocarcinoma cell line, exhibited the best representativeness for SRCC. In conclusion, this work revealed the proteomic landscape of gastric SRCC in an acceptable scale and depth in comparison with ACs and provided a suggestion on best representative cell lines for SRCC at proteomic level.