Identifying gastric cancer related genes using the shortest path algorithm and protein-protein interaction network
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Published on: May 10, 2024
Yang Jiang1, Yang Shu2, Ying Shi3
1Colorectal Surgery Department, China-Japan Union Hospital of Jilin University, Changchun 130033, China.
Abstract:
Gastric cancer, as one of the leading causes of cancer related deaths worldwide, causes about 800,000 deaths per year. Up to now, the mechanism underlying this disease is still not totally uncovered. Identification of related genes of this disease is an important step which can help to understand the mechanism underlying this disease, thereby designing effective treatments. In this study, some novel gastric cancer related genes were discovered based on the knowledge of known gastric cancer related ones. These genes were searched by applying the shortest path algorithm in protein-protein interaction network. The analysis results suggest that some of them are indeed involved in the biological process of gastric cancer, which indicates that they are the actual gastric cancer related genes with high probability. It is hopeful that the findings in this study may help promote the study of this disease and the methods can provide new insights to study various diseases.
Insights
Researchers identified novel gastric cancer genes using a protein-protein interaction network and shortest path algorithm. These findings advance understanding of gastric cancer mechanisms and potential treatments.
Area of Science:
- Oncology
- Bioinformatics
- Genetics
Background:
- Gastric cancer is a leading cause of cancer deaths globally, with approximately 800,000 annual fatalities.
- The underlying mechanisms of gastric cancer remain incompletely understood.
- Identifying genes associated with gastric cancer is crucial for understanding its development and designing effective therapies.
Purpose of the Study:
- To discover novel genes implicated in gastric cancer.
- To leverage network-based approaches for gene identification in complex diseases.
Main Methods:
- Utilized a protein-protein interaction (PPI) network.
- Applied the shortest path algorithm to identify novel gastric cancer-related genes based on known ones.
Main Results:
- Discovered several novel genes potentially associated with gastric cancer.
- Analysis suggests these identified genes are likely involved in gastric cancer's biological processes.
Conclusions:
- The identified genes are highly probable candidates for novel gastric cancer-related genes.
- This study offers new insights into gastric cancer mechanisms and potential therapeutic targets.
- The network-based methodology may be applicable to studying other complex diseases.
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