Understanding the mechanisms of cancers based on function sub-pathways

Area of Science:

• Bioinformatics
• Systems Biology
• Genomics

Background:

• Pathway analysis is crucial for understanding gene and protein expression.
• Existing sub-pathway methods often lack explicit functional interpretation.
• Identifying specific functional roles of sub-pathways remains a challenge.

Purpose of the Study:

• To introduce a novel Function Sub-Pathway Analysis (FSPA) method.
• To enable explicit analysis of sub-pathway functions in disease contexts.
• To quantify the impact of sub-pathways on specific biological functions.

Main Methods:

• Developed FSPA to include all downstream nodes leading to a specific function node.
• Defined a 'perturbation degree' based on the negative log p-value of sub-pathways.
• Applied FSPA to six cancer datasets (colorectal, lung, pancreatic).

Main Results:

• FSPA identified more cancer-associated pathways compared to existing methods.
• The method successfully pinpointed sub-pathways contributing to specific abnormal functions.
• Quantified the extent of functional impact and analyzed functional imbalances in biological processes.

Conclusions:

• FSPA provides explicit functional insights into sub-pathways.
• The method enhances understanding of cancer mechanisms.
• Results support the design of targeted therapeutic strategies.