Affiliations: [a] Stem Cell Laboratory, Bone Marrow Transplantation Unit, Instituto Nacional de Câncer, Rio de Janeiro, RJ, Brazil | [b] Instituto Nacional de Ciência e Tecnologia Para o Controle do Câncer, Rio de Janeiro, RJ, Brazil | [c] Instituto Nacional de Câncer-Divisão de Patologia, Rio de Janeiro, RJ, Brazil | [d] Endoscopy Section, Instituto Nacional de Câncer, Rio de Janeiro, RJ, Brazil
Correspondence:
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Corresponding author: Everton Cruz dos Santos, Stem Cell Laboratory, Bone Marrow Transplantation Unit, Instituto Nacional de Câncer (INCA), Praça da Cruz Vermelha 23, 6o andar ALA C, Divisão de Laboratórios do CEMO, INCA, Rio de Janeiro-RJ, CEP 20.230-130, Brazil. Tel.: +55 21 3207 1874; Fax: +55 21 2509 2121; E-mail: [email protected].
Note: [1] These authors contributed equally to this work.
Abstract: BACKGROUND: Gastric cancer (GC) is the third leading cause of cancer worldwide. According to the Lauren classification, gastric adenocarcinoma is divided into two subtypes: diffuse and intestinal. The development of intestinal gastric cancer (IGC) can take years and involves multiple factors. OBJECTIVE: To investigate the protein profile of tumor samples from patients with IGC in comparison with adjacent nontumor tissue samples. METHODS: We used label-free nano-LC-MS/MS to identify proteins from the tissues samples. The results were analyzed using MetaCore™ software to access functional enrichment information. Protein-protein interactions (PPI) were predicted using STRING analysis. Hub proteins were determined using the Cytoscape plugin, CytoHubba. Survival analysis was performed using KM plotter. We identified 429 differentially expressed proteins whose pathways and processes were related to protein folding, apoptosis, and immune response. RESULTS: The PPI network of these proteins showed enrichment modules related to the regulation of cell death, immune system, neutrophil degranulation, metabolism of RNA and chromatin DNA binding. From the PPI network, we identified 20 differentially expressed hub proteins, and assessed the prognostic value of the expression of genes that encode them. Among them, the expression of four hub genes was significantly associated with the overall survival of IGC patients. CONCLUSIONS: This study reveals important findings that affect IGC development based on specific biological alterations in IGC patients. Bioinformatics analysis showed that the pathogenesis of IGC patients is complex and involves different interconnected biological processes. These findings may be useful in research on new targets to develop novel therapies to improve the overall survival of patients with IGC.
