Proteomic and transcriptomic studies of BGC823 cells stimulated with Helicobacter pylori isolates from gastric MALT lymphoma

Zou, Qinghua, et al. “Proteomic and Transcriptomic Studies of BGC823 Cells Stimulated with Helicobacter Pylori Isolates from Gastric MALT Lymphoma.” PLOS ONE, edited by Roger Chammas, no. 9, Public Library of Science (PLoS), Sept. 2020, p. e0238379. Crossref, doi:10.1371/journal.pone.0238379.

Abstract

Background

The correlation between the infection of Hpylori and the occurrence of gastric MALT lymphoma (GML) has been well documented. However, the mechanism of how GML is caused by this bacterium is not well understood, although some immunologic mechanisms are thought to be involved.

Materials and methods

In this study, we performed both transcriptomic and proteomic analyses on gastric cancer cells infected by Hpylori isolates from GML patients and the gastric ulcer strain 26695 to investigate the differentially expressed molecular signatures that were induced by GML isolates.

Results

Transcriptomic analyses revealed that the differentially expressed genes (DEGs) were mainly related to binding, catalytic activity, signal transducer activity, molecular transducer activity, nucleic acid binding transcription factor activity, and molecular function regulator. Fifteen pathways, including the Wnt signaling pathway, the mTOR signaling pathway, the NOD-like receptor signaling pathway and the Hippo signaling pathway, were revealed to be related to GML isolates. Proteomic analyses results showed that there were 116 differentially expressed proteins (DEPs). Most of these DEPs were associated with cancer, and 29 have been used as biomarkers for cancer diagnosis. We also found 63 upstream regulators that can inhibit or activate the expression of the DEPs. Combining the proteomic and transcriptomic analyses revealed 12 common pathways. This study provides novel insights into Hpylori-associated GML. The DEPs we found may be good candidates for GML diagnosis and treatment.

Conclusions

This study revealed specific pathways related to GML and potential biomarkers for GML diagnosis.

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