ArticleMolecular systems biology2007
Network-based classification of breast cancer metastasis.
Article in Molecular systems biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 706 papers.
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Who cites it
706 citing papers in PubMed.
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- Integrated network propagation identifies prognostic metabolic signatures in acute myeloid leukemia.Journal of translational medicine · 2025Article
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- USP30 promotes the progression of breast cancer by stabilising Snail.Cancer gene therapy · 2024Article
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- Predicting immunotherapy response in melanoma using a novel tumor immunological phenotype-related gene index.Frontiers in immunology · 2024Article
646 more citing papers are in PubMed but not listed here.
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5 authors.
Funding
Abstract
Mapping the pathways that give rise to metastasis is one of the key challenges of breast cancer research. Recently, several large-scale studies have shed light on this problem through analysis of gene expression profiles to identify markers correlated with metastasis. Here, we apply a protein-network-based approach that identifies markers not as individual genes but as subnetworks extracted from protein interaction databases. The resulting subnetworks provide novel hypotheses for pathways involved in tumor progression. Although genes with known breast cancer mutations are typically not detected through analysis of differential expression, they play a central role in the protein network by interconnecting many differentially expressed genes. We find that the subnetwork markers are more reproducible than individual marker genes selected without network information, and that they achieve higher accuracy in the classification of metastatic versus non-metastatic tumors.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.