To screen proteins related to the progression of gastric carcinogenesis, we also compared non-neoplastic gastric tissues with GC samples of individuals with and without lymph node metastases. For the selection of differentially expressed proteins, we used a Mechlorethamine hydrochloride statistical parametrics test with bootstrapping resampling. We have undertaken a comprehensive computational analysis of tissue proteomic data to discover pathways and networks involved in gastric oncogenesis and progression. The possible associations among enolase 1 and heat shock 27 kDa protein 1 gene and protein expression, and clinicopathological characteristics were also evaluated in individuals from Northern Brazil. These two proteins have been reported frequently as deregulated molecules in previous GC proteomic studies in other populations. However, they were never evaluated in a Brazilian population. Although some proteomic-based studies were previously performed in human primary gastric tumors, to our knowledge, only three studies focus on noncardia GC. Most GC proteomic studies identified differentially expressed proteins based only on a fold change between two conditions. Other previous GC proteomic studies performed statistical analyses to compare the protein expression between groups, but without controlling the type I error. It is interesting to note that we compared the protein profiling of tumors and non-neoplastic samples using parametric tests with bootstrapping for differentially expressed protein identification. The resampling methods, commonly used in microarray studies, have been used to make p-value adjustments for multiple testing procedures which control the FWER and take into account the dependence structure between test statistics. The objective is to create many sets of bootstrap samples by resampling with the replacements from the original data. This supports the current data and indicates that the findings should be further investigated to identify or validate clinically relevant targets for the diagnosis and/ or the prognosis of GC. The identified proteins were grouped into different classes based on functional information available. Most of the identified proteins were intracellular organelle proteins and were part of the membrane-bound organelles, especially the mitochondria. These proteins are involved mainly in cellular metabolic processes and oxidation reduction. The comparison of tumors with lymph node metastases and control samples revealed the transport and the establishment of location as Butenafine hydrochloride enriched biological processes. This was not observed in the comparison of tumors without lymph node metastases and control samples. The oxidoreductase activity followed by coenzyme binding activity were the main molecular functions of the proteins involved in gastric carcinogenesis. Concerning the chromosomal location, most of the proteins were encoded by genes located at chromosome 1, chromosome 19, and chromosome 11. Complex karyotypes of gastric tumors preferentially involve these chromosomes, as well as chromosomes 3, 6, 7, 8, 13 and 17. Gain and loss of chromosome regions of 1, 19 and 11 were previously reported by our research group in GC samples. Thus, these chromosomes may contain several loci with dosage-sensitive genes. We have undertaken a comprehensive computational analysis of tissue proteomic data to discover pathways and networks involved in gastric oncogenesis and progression. Table 2 shows the principal canonical pathways using the Ingenuity Pathway Analysis database. The principal canonical pathways in the gastric carcinogenesis process were involved in the energy metabolism pathways including mitochondrial dysfunction, pyruvate metabolism, oxidative phosphorylation, citrate circle, and glycolysis/gluconeogenesis.