Helicobacter pylori cagA and vacA proteins through affecting on PI۳K/AKT and Ras signaling pathways can induce gastric cancer: In silico study

BACKGROUND AND OBJECTIVESHelicobacter pylori infection is a critical risk factor for gastric cancer, contributing to approximately ۷۵% of all gastric cancer (GC) cases. Therefore, today intensive research is focusing on molecular mechanisms in which H. pylori infection cause GC. It has shown bacterial proteins by interacting with human proteins cause many diseases. This interaction can change the signaling, metabolic pathways and cellular processes of infected host. Therefore, we decided to use bioinformatics tools to find how H. pylori can induce cancer in human gastric cells.MATERIALS AND METHODSTo identify bacterial motifs that interact with human proteins, ImitateDB database was used. In this database, the H. pylori strain was selected and proteins that interact with human cells were recognized. Host interactor protein IDs were extracted from this database, and these codes were converted into gene symbols through BioDBnet database, and the function of these proteins was determined using string and EnrichR database.RESULTS AND DISCUSSIONImitateDB database showed H. pylori Cytotoxicity-associated immunodominant antigen (cagA) and Vacuolating cytotoxin A (vacA) can interact by human Tyrosine-protein phosphatase non-receptor type ۱۱ (PTPN۱۱) and NCK-interacting protein with SH۳ domain (NCKIPSD ) respectively. These two proteins also via different motifs relate to ۵۵ human proteins as figure ۱ shown. As you can see from figure ۲ functional analysis by EnrichR indicated these genes significantly regulated PI۵P, PP۲A and IER۳ Regulate PI۳K/AKT and Ras signaling pathway. Different studies have shown RAS and PI۳K/AKT signal transduction pathways dysfunctions have been involved in multiple cancer types including GC.CONCLUSIONToday finding the interaction between host proteins and bacterial proteins through different databases and software can be used as an effective way to investigate molecular mechanisms of bacterial pathogenies and find appropriate treatments.

کلیدواژه ها:

Helicobacter pylori ، Bioinformatics analysis ، Ras signaling ، ImitateDB database ، BioDBnet database ، EnrichR database