  This study presents an interdisciplinary approach to analyse the distribution
of cancer stem cell markers (CSCMs) across various cancer-affected organs using
hypergraphs. Cancer stem cells (CSCs) play a crucial role in cancer initiation,
progression, and metastasis. By employing hypergraphs, we model the
relationships between CSCM locations and cancerous organs, providing a
comprehensive representation of these interactions. Initially, we utilised an
unweighted incidence matrix and its Markov transition matrices to gain a
dynamic perspective on CSCM distributions. This method allows us to observe how
these markers spread and influence cancer progression in a dynamical context.
By calculating mutual information for each node and hyperedge, our analysis
uncovers complex interaction patterns between CSCMs and organs, highlighting
the critical roles of certain markers in cancer progression and metastasis. Our
approach offers a detailed representation of cancer stem cell networks,
enhancing our understanding of the mechanisms driving cancer heterogeneity and
metastasis. By integrating hypergraph theory with cancer biology, this study
provides valuable insights for developing targeted cancer therapies.
