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.

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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

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article

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

Marcela V. Reale, Gustavo Paccosi, David H. Margarit, L. Romanelli
1 citations
Physical review. E
Bioinformatics and Genomic Networks
0.81
article

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

Marcela V. Reale, Gustavo Paccosi, David H. Margarit, L. Romanelli
article en
1 citations

Abstract

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.

Physical review. EVol. 111(5)
Consejo Nacional de Investigaciones Científicas y Técnicas (AR), National University of General Sarmiento (AR), Universidad Nacional de La Matanza (AR)
Consejo Nacional de Investigaciones Científicas y Técnicas
Openalex Percentile: Top 28%
Bioinformatics and Genomic Networks
0.81
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Decoding cancer dynamics: Hypergraph analysis of stem cell marker interactions through O-information and community detection — Marcela V. Reale, Gustavo Paccosi, et al. · Physical review. E (2025) | TGRS Research Map | TGRS