Decoding cancer dynamics: Hypergraph analysis of stem cell marker interactions through O-information and community...

Area of Science:

• Oncology
• Systems Biology
• Network Science

Background:

• Cancer stem cell markers (CSCMs) play a crucial role in tumor initiation, progression, and metastasis.
• Understanding the systemic interactions of CSCMs across different organs is vital for effective cancer treatment.
• Traditional analyses often overlook the complex, multi-organ relationships influenced by CSCMs.

Purpose of the Study:

• To explore the systemic interactions between CSCMs and cancer-affected organs.
• To develop a novel hypergraph-based framework for analyzing these complex relationships.
• To identify potential tumorigenic pathways and CSCMs with significant systemic influence.

Main Methods:

• Utilized a hypergraph model where organs are nodes and CSCMs are hyperedges to represent multiway relationships.
• Applied the Louvain algorithm for community detection to cluster organs based on shared CSCM profiles.
• Employed O-information to quantify information redundancy and synergy among CSCMs and organs.

Main Results:

• Identified distinct clusters of organs exhibiting similar CSCM profiles, suggesting coordinated tumorigenic processes.
• Revealed potential functional networks and pathways driven by CSCM interactions across organ systems.
• Quantified the systemic influence of specific CSCMs on tumor progression and metastasis using O-information.

Conclusions:

• The hypergraph approach provides a structured framework for understanding CSCM dynamics in a multiorgan context.
• Findings offer insights into how CSCMs orchestrate cancer progression and metastasis across the body.
• This research may inform the development of targeted, multiorgan therapeutic strategies for cancer.