Analysis of the potential correlation between gastric cancer and gastrointestinal microbiota via in-silico data mining
Background
Emerging evidence shows the gastrointestinal microbiome might play an important role in the carcinogenesis of gastric cancer. While Helicobactor pylori has been reported to be a specific risk factor of gastric cancer, it is still controversial whether significant difference of non- H. pylori microbiota exists between gastric cancer patients and healthy control.
Results
In this study, we employed multiple bioinformatic databases to excavate the potential correlation between gastrointestinal microbiome and gastric cancer. The databases involved in this investigation include HMDB, STITCH, OMIM, GWAS Catalog, WebGestalt, Toppgene, GeneMANIA. In addition, the network diagrams were built by use of Cytoscape software. Notably, our results showed that 33 common genes participate in both gastrointestinal microbiome and gastric cancer. The further analysis of these common genes suggested that there was a wide array of interactions and pathways in which the correlation between gastrointestinal microbiome and gastric cancer is involved.
Conclusions
Our present study gives a bioinformatic insight into possible pathways in which the gastrointestinal microbiome play roles in gastric cancer. Future efforts are necessary to be paid to elicit the exact mechanisms as well as potential therapeutic targets of gastric cancer.
Figure 1
Figure 2
Figure 3
This is a list of supplementary files associated with this preprint. Click to download.
Posted 18 Dec, 2019
Analysis of the potential correlation between gastric cancer and gastrointestinal microbiota via in-silico data mining
Posted 18 Dec, 2019
Background
Emerging evidence shows the gastrointestinal microbiome might play an important role in the carcinogenesis of gastric cancer. While Helicobactor pylori has been reported to be a specific risk factor of gastric cancer, it is still controversial whether significant difference of non- H. pylori microbiota exists between gastric cancer patients and healthy control.
Results
In this study, we employed multiple bioinformatic databases to excavate the potential correlation between gastrointestinal microbiome and gastric cancer. The databases involved in this investigation include HMDB, STITCH, OMIM, GWAS Catalog, WebGestalt, Toppgene, GeneMANIA. In addition, the network diagrams were built by use of Cytoscape software. Notably, our results showed that 33 common genes participate in both gastrointestinal microbiome and gastric cancer. The further analysis of these common genes suggested that there was a wide array of interactions and pathways in which the correlation between gastrointestinal microbiome and gastric cancer is involved.
Conclusions
Our present study gives a bioinformatic insight into possible pathways in which the gastrointestinal microbiome play roles in gastric cancer. Future efforts are necessary to be paid to elicit the exact mechanisms as well as potential therapeutic targets of gastric cancer.
Figure 1
Figure 2
Figure 3