Identifying Rarely Mutated Cancer Genes by Heterogeneous Network Embedding (CSIAM Transactions on Life Sciences, 2025)
Cancer is a multifaceted disease caused by dynamic interaction between genetic mutations and environmental factors. Understanding the genetic mutations underlying the development and progression of cancer is the stepstone for developingeffective treatments and therapies. However, these mutations occurred in only a smallfraction of cancer patients and it is extremely difficult to associate with cancer. Here,we propose MutNet, a heterogeneous network embedding method which integratebiomolecular network with cancer genomics data. Using pan cancer genomic datafrom The Cancer Genome Atlas program and public protein-protein interaction andpathway data, MutNet identifies rarely mutated cancer genes often overlooked by conventional genetic studies. In addition, the unified vector representation of biologicalentities allows us to reveal the tumor type specific cancer genes, cancer gene modules,and potential relationships among different tumor types. Our heterogeneous networkembedding method holds the promise for the underlying mechanisms of cancer andpotential therapeutic targets.
Keywords: Cancer genomics; cancer gene; network embedding.