Analysis of tumor suppressor genes based on gene ontology and the KEGG pathway

Area of Science:

• Genomics
• Cancer Biology
• Bioinformatics

Background:

• Cancer remains a leading cause of mortality worldwide, necessitating novel therapeutic strategies.
• Tumor suppressor genes (TSGs) play a critical role in preventing cellular transformation into cancer.
• Accurate identification of TSGs offers a promising avenue for developing effective cancer treatments.

Purpose of the Study:

• To identify key biological factors associated with tumor suppressor genes (TSGs).
• To explore the utility of gene ontology (GO) and pathway enrichment analysis for TSG identification.
• To apply feature selection methods for discovering significant markers of TSGs.

Main Methods:

• Gene ontology (GO) and KEGG pathway enrichment analysis were performed on known TSGs and non-TSGs.
• Feature selection techniques, including minimum redundancy maximum relevance (mRMR) and incremental feature selection (IFS), were utilized.
• Enrichment features were analyzed to identify significant biological processes and pathways.

Main Results:

• Several GO terms and KEGG pathways were identified as important for distinguishing TSGs.
• Key factors extracted include biological adhesion, cell cycle control, genomic stability maintenance, and cell death regulation.
• These identified features are significant indicators for predicting TSG status.

Conclusions:

• The findings highlight the importance of specific biological processes and pathways in tumor suppression.
• This study provides a foundation for developing robust prediction models for identifying TSGs.
• The results contribute to advancing the discovery of novel and effective cancer therapies.