Decoding cancer dynamics: Hypergraph analysis of stem cell marker interactions through O-information and community detection
This study explores the systemic interactions between cancer stem cell markers (CSCMs) and cancer-affected organs through a hypergraph-based approach. By modeling organs as nodes and CSCMs as hyperedges, we capture multiway relationships beyond conventional pairwise analyses. Using the Louvain algorithm, we identify clusters of organs with shared CSCM profiles, revealing potential tumorigenic pathways and functional networks. Additionally, O-information quantifies redundancy and synergy, highlighting CSCMs with systemic influence on tumor progression and metastasis. These findings provide a structured framework for understanding CSCM dynamics across organ systems, offering insights that may inform targeted, multiorgan therapeutic strategies.
Authors
- Marcela V. Reale (ORCID: https://orcid.org/0000-0002-9856-7501)
- Gustavo Paccosi (ORCID: https://orcid.org/0000-0002-0895-1957)
- David H. Margarit (ORCID: https://orcid.org/0000-0003-1946-0413)
- L. Romanelli (ORCID: https://orcid.org/0000-0002-9272-6575)
Institutions
- Consejo Nacional de Investigaciones Científicas y Técnicas (AR)
- National University of General Sarmiento (AR)
- Universidad Nacional de La Matanza (AR)
Publication Details
- Journal
- Physical review. E
- Published
- 2025-05-19
- DOI
- https://doi.org/10.1103/physreve.111.054410
- Citations
- 1
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- Consejo Nacional de Investigaciones Científicas y Técnicas